HYDROLOGY OF FOREST ECOSYSTEMS IN THE HONOULIULI WATERSHED

HYDROLOGY OF FOREST ECOSYSTEMS IN THE HONOULIULI

PRESERVE: IMPLICATIONS FOR GROUNDWATER RECHARGE AND

WATERSHED RESTORATION.

A DISSERTATION SUBMITTED TO THE GRADUATE DIVISION OF THEUNIVERSITY OF HAWAI'I IN PARTIAL FULFILLMENT OF THE

REQUIREMENTS FOR THE DEGREE OF

DOCTOR OF PHILOSOPHY

IN

BOTANICAL SCIENCES(BOTANY - ECOLOGY, EVOLUTION AND CONSERVATION BIOLOGY)

DECEMBER 2004

ByTeresa G. Restom Gaskill

Dissertation Committee:

Guillermo Goldstein, ChairpersonK. W. Bridges

John EwelFrederick Meinzer

Thomas Giambelluca

111

To Doug and Sofiafor their love and support

Acknowledgements

This project was supported by the USDA Forest Service through Agreement No.

PSW-97-0017CA to G. Goldstein, by the Ecology, Evolution and Conservation

Biology Program (EECB), the College ofNatural Sciences of the University of

Hawaii at Manoa, and the Dai Ho Chun Dissertation Completion Scholarship. I also

received support from the Postl Endowed Scholarship and the Mildred Towle

Scholarship for International Students.

I would like to thank the US Forest Service, the UH Agricultural Engineering

Department, Rick Meinzer, Tom Giambelluca and Michael Constantinides for

lending several pieces of equipment, and the Botany Department at the University of

Hawaii and the US Forest Service for letting me use their four-wheel drive vehicles. I

would also like to thank Robin Harrington, Jack Ewel, Jennifer Garrison, and The

Nature Conservancy of Hawaii - Oahu for their help in choosing sites and during

several stages of the research.

Randy Amiscaray contributed greatly in the design and application of the rainfall,

stemflow and throughfall collectors. David Fujii, Ted Schmidt, Heidi Masuko, Doug

Restom Gaskill and others gave valuable contributions in collecting data. Thanks also

to Shannon Peters for the soil identification, to Michael Clearwater and Shelley James

for their help and training in the construction of the sapflow probes, and to Leone!

Sternberg and Doug Restom Gaskill for their help in data analyses.

IV

Abstract

The main objectives of this study were (1) to quantify and explain differences

in the components of the water cycle among forest stands dominated by non-native

tree species and (2) to estimate the potential of these stands to recharge groundwater.

These forest stands were planted in the 1900s to repair the hydrological impacts that

deforestation had caused on the watersheds in Hawaii in the 1800s. Rainfall

interception and leaf area index (LAI) were measured in stands dominated by each of

four species (Casuarina glauca, Fraxinus uhdei, Eucalyptus robusta and Grevillea

robusta). Transpiration, patterns of water uptake and soil moisture dynamics were

measured in one stand each dominated by the first three species. The data collected

were used to assess the potential of some of the stands to recharge groundwater from

May 2001 to April 2002.

A long period of drought was observed between January 2000 and October

200 I. The Fraxinus stand exhibited deep water uptake and recovered LAI promptly

after the end of the drought. The Eucalyptus stand had relatively deep water uptake

but had a very slow recovery of LAI in relation to the other stands. The Casuarina

stand had shallow water uptake but it was still able to recover LAI relatively quickly.

Transpiration, relative to tree basal area, was similar among the three species after the

end of the drought.

Interception ranged from 4 to 29% of rainfall for the year of 1999 and there

were no significant differences in interception among stands dominated by different

species. Evapotranspiration (ET) rates were 90, 94 and 65% of rainfall for Fraxinus,

v

Eucalyptus and Casuarina, respectively. Thirty two percent of rainfall was lost as

surface runoff in the Casuarina stand.

No groundwater recharge was observed in these stands during the period

studied. The results suggest that the species chosen for reforestation in Honouliuli

were not ideal for restoring and protecting the groundwater resource. It would have

been more desirable to use species that are conservative water users instead of fast

growing trees which are able to reduce erosion in a short term but which exhibit

relatively high ET rates even after 80 years.

VI

Table of Contents

Acknowledgements iv

Abstract v

List of Figures xi

List of Abbreviations and Symbols xiii

1. Introduction 1

1.1. Overview 1

1.2. Restoration of ecosystem processes by tree plantations 1

1.3. Hydrological cycle in forest ecosystems 4

1.4. Groundwater use and recharge on Oahu 8

1.5. Objectives and hypotheses 9

1.6. Dissertation outline 11

1.7. Methods 12

1.7.1. The study site 12

1.7.2. Species studied 13

1.7.3. Field measurements 17

1.8. Summary 22

1.9. References 22

2. Patterns of water uptake and transpiration in Eucalyptus robusta,Fraxinus uhdei and Casuarina glauca growing in plantations in Honouliuli,Hawaii 34

2.1. Abstract 34

2.2. Introduction 35

2.3. Methods 37



2.4. Results 41

2.4.1. Rainfall pattern and soil moisture dynamics 41

2.4.2. Vertical pattern of water uptake by roots 42

2.4.3. Leaf area dynamics 43

2.4.4. Transpiration 44

VB

2.5. Discussion 46

2.6. Conclusions 52

2.7. References 53

3. Effects of Species Composition on the Rainfall Interception, Stemflow andThroughfall of Mesic Forest Plantations of Hawai'i 72

3.1. Abstract 72


3.3. Methods 75


3.3.2. Species studied 75


3.3.4. Statistical Analyses 78

3.4. Results 79

3.4.1. Rainfall 79

3.4.2. Leaf area index 80

3.4.3. Throughfall 80

3.4.4. Stemflow 82

3.4.5. Interception 82

3.5. Discussion 83

3.5.1. Throughfall 83

3.5.2. Stemflow 85

3.5.3. Interception 87

3.5.4. Effect of forest structure on throughfall and stemflow 88

3.6. Conclusion 89

3.7. References 90

4. Evapotranspiration and Groundwater Recharge by Tree Plantations in theHonouliuli Preserve, Hawaii 108

4.1. Abstract 108


4.3. Methods 111



Vlll

4.3.3. Micrometeorological data 112

4.3.4. Potential evapotranspiration 113

4.3.5. Water balance method 114

4.3.6. Temperature variance method (TVAR) 118

4.3.7. Sap flow method 120

4.4. Results 121

4.4.1. Potential evapotranspiration (PE) 121

4.4.2. Water balance method 122

4.4.3. Temperature variance method (TVAR) 123

4.4.4. Sap flow method 123

4.4.5. Interception vs. evapotranspiration 124

4.5. Discussion 124

4.5.1. Effect of species composition on evapotranspiration 124

4.5.2. Evapotranspiration vs. potential evapotranspiration 127

4.5.3. Groundwater recharge and runoff 128

4.5.4. The methods 129

4.5.5. Implications of reforestation on groundwater 131

4.6. Conclusion 133

4.7. References 134

5. Conclusions and implications for groundwater recharge and watershedrestoration projects in Hawaii. 153

5.1. Are there differences in the components of the water cycle of forests dominated

by different species? 153

5.2. How do direct measurements of evapotranspiration compare to previous

estimates? 156

5.3. Do forests dominated by different species differ in their potential to recharge

groundwater? 157

5.4. Implications of this research for groundwater recharge and watershed

restoration in Hawai'i 159

5.5. References 161

6. Literature cited 163

IX

List of Tables

Table 1.1 - Characteristics of the stands studied at the Honouliuli Preserve, Oahu,Hawaii 31Table 2.1 - Characteristics of the stands studied at the southern section of theHonouliuli Preserve, Oahu, Hawaii, as of 1998 57Table 2.2 - Number of water samples collected from trees and from the soil pits 57Table 2.3 - Depth of sapwood and of the sap flow sensors installed in trees inHonouliuli 58Table 2.4 - Sap flow for the trees studied 58Table 2.5 - Equations obtained from multiple regression comparing transpiration withair saturation deficit and volumetric water content in different cumulative depths ofthe soil for F. uhdei trees 59Table 2.6 - Equations obtained from multiple regression comparing transpiration withair saturation deficit and volumetric water content in different cumulative depths ofthe soil for C. glauca trees 60Table 2.7 - Equations obtained from multiple regression comparing transpiration withair saturation deficit and volumetric water content in different cumulative depths ofthe soil for Eucalyptus trees 61Table 3.1 - Comparison of manually collected throughfall among stands dominatedby different species 95Table 3.2 - Results from the one-way analyses of variance comparing throughfall as aproportion of rainfall in an event basis 96Table 3.3 - Throughfall as a proportion of rainfall during periods of high and low leafarea index in the stands of the southern section of the Honouliuli Preserve 96Table 3.4 - Regression equations between rainfall and stemflow obtained for treesthroughout the stands studied 97Table 3.5 - Throughfall, stemflow, and interception based on manual measurementson stands dominated by different species 98Table 3.6 - Rainfall, throughfall, stemflow, and interception on stands dominated bydifferent species in the Honouliuli Preserve from January to December 1999 98Table 4.1 - Terms in the water balance model. 141Table 4.2 - Final curve numbers used to estimate runoff in the forest stands studied inthe Honouliuli Preserve between May 2001 and April 2002 141Table 4.3 - Precipitation and estimated values of runoff, evapotranspiration andgroundwater recharge in the forest stands from May 5, 2001, to April 27, 2002..... 142

x

List of Figures

Figure 1.1 - Location ofthe Honouliuli Preserve on the Island of Oahu, Hawaii ...... 32Figure 1.2 - Location of the stands studied, weather stations and additional rainfallcollectors in the Honouliuli Preserve on the island of Oahu, Hawaii 33Figure 2.1 - Monthly rainfall from August 1998 to March 2002 near the standsstudied 62Figure 2.2 - Soil moisture of the three stands studied between May 19,2001 and April7, 2002 63Figure 2.3 - Soil volumetric water content in the dry season and in the wet season forstands dominated by Fraxinus uhdei, Eucalyptus robusta and Casuarina glauca in theHonouliuli Preserve 64Figure 2.4 - Patterns of water uptake by roots of Fraxinus uhdei, Eucalyptus robustaand Casuarina glauca as indicated by the hydrogen isotope ratio (8D) 65Figure 2.5 - Rainfall, leaf area index, volumetric water content of the top 15 cm ofthesoil profile, and sap flux density of trees in stands dominated by Casuarina glauca,Fraxinus uhdei or Eucalyptus robusta in Honouliuli 66Figure 2.6 - Sapwood area in trees of different DBH of the three species studied inHonouliuli 67Figure 2.7 - Diurnal patterns of air saturation deficit and sap flow in different depthsof the sapwood for 15 January 2002 68Figure 2.8 - Sap flux density in the sapwood profile for one tree each of Casuarinaglauca, Fraxinus uhdei, and Eucalyptus robusta for February and March 2002........ 69Figure 2.9 - Daily total sap flow plotted against basal area for Casuarina glauca,Fraxinus uhdei, and Eucalyptus robusta for the period between January and March2002 70Figure 2.10 - Total daily sap flow as a function of mean daily air saturation deficit atthe beginning and at the peak of the drought for representative trees of Casuarinaglauca, Fraxinus uhdei, and Eucalyptus robusta 71Figure 3.2 - Rainfall distribution in three sections of the Honouliuli Preserve 100Figure 3.3 - Monthly rainfall in the three sections of the Honouliuli Preserve betweenMarch 1998 and February 2002 101Figure 3.4 - Leaf area index on stands dominated by Casuarina glauca, Eucalyptusrobusta, Fraxinus uhdei, and Grevillea robusta from June 1999 to July 2000 102Figure 3.5 - Leaf area index in the forest stands of the southern section of theHonouliuli Preserve between June 2001 and March 2002 103Figure 3.6 - Throughfall, as a proportion of rainfall, for events < 3 mm, as a functionof leaf area index for the three stands in the southern section of the HonouliuliPreserve 104Figure 3.7 - Stemflow as a function of rainfall in stands dominated by Eucalyptusrobusta, Fraxinus uhdei, Casuarina glauca, or Grevillea robusta in the northern,middle and southern sections of the Honouliuli Preserve 105Figure 3.8 - Throughfall as a function of various stand characteristics and of rainfallfor the period between January and December 1999 106

Xl

Figure 3.9 - Stemflow as a function of various stand characteristics and of rainfall forthe period between January and December 1999 107Figure 4.1 - Relationship between half-hourly measurements of soil heat flux and netradiation in the Brazilian Cerrado from August 29 to October 16, 2001.. 143Figure 4.2 - Comparison of mean daily potential evapotranspiration per monthestimated with the Penman equation from May 2001 to April 2002, above the canopyof three forest plantations, and the estimated by Giambelluca (1983) for the years1946 through 1975, adjusted for dry forest cover. 144Figure 4.3 - Water balance model calibration curves comparing estimated andmeasured soil volumetric water content for the forest stands, before includingestimates of runoff 145Figure 4.4 - Water balance model calibration curves comparing estimated andmeasured soil volumetric water content, including runoff estimates, for the foreststands 146Figure 4.5 - Evapotranspiration estimated by the water balance method in standsdominated by Casuarina glauca, Eucalyptus robusta and Fraxinus uhdei betweenMay 5, 2001 and April 28, 2002 147Figure 4.6 - Comparison of half-hourly estimates between potentialevapotranspiration and canopy evaporation during daytime periods with no rain forstands dominated by Casuarina glauca and Fraxinus uhdei, between June andNovember 2001 148Figure 4.7 - Daily evapotranspiration estimated by the sap flow method in standsdominated by Casuarina glauca, Eucalyptus robusta, or Fraxinus uhdei in March2002 149Figure 4.8 - Comparison of evapotranspiration estimated by the water balance and bythe sap flow methods, in three forest stands in the Honouliuli Preserve dominated byCasuarina glauca, Eucalyptus robusta or Fraxinus uhdei 150Figure 4.9 - Daily evapotranspiration in the Eucalyptus robusta stand estimated bythe water balance and the sap flow methods in May 2001 151Figure 4.10 - Precipitation and estimated potential evapotranspiration,evapotranspiration, and interception in the forest sites studied from May 5,2001 toApril 28, 2002 152

Xll

List of Abbreviations and Symbols

A - downward longwave radiation, in W m-2

As - sapwood area, in m2

ASD - air saturation deficit, in kPa

Cp - heat of air at constant pressure, in J kg-l K-1

d - zero-plane displacement, in m

~D - relative abundance of deuterium, in %0

DBH - diameter at 1.3 m, in cm

11SM - soil moisture variation in the root zone, in mm

E: - emissivity of the surface

Ei - interception evaporation, in mm

Et - dry canopy evaporation, in mm

ET - evapotranspiration, in rom

g - acceleration due to gravity, in m S-2

G - soil heat flux, in W m-2

H - sensible heat flux, in W m-2

HOF - Horton overland flow, in mm

k - von Kannan constant (0.4)

Kd - downward shortwave radiation, in W m-2

Ku - reflected shortwave radiation, in W m-2

A- latent heat of vaporization

LAI- Leaf area index, in m2 m-2

Xlll

p - air density, in kg m-3

P - precipitation, in mm

PE - potential evapotranspiration, in mm

R - groundwater recharge, in mm

r a - aerodynamic resistance, in s m-1

Rnet - net radiation, in W m-2

(J - Stephan-Boltzmann constant (5.67 x 10-8 W m-2 K 4)

(JT - standard deviation of the temperature

SFD - sap flux density, in g m2S-l

To - surface temperature, in K

Ta - air temperature, in K

U - wind speed, in m S-l

VWC - soil volumetric water content, in %

Zo - roughness height for momentum transfer, in m

zo' - roughness height for heat transfer, in m

XIV

1. Introduction

1.1. Overview

The planting of alien trees has been used as a tool to repair deforestation

impacts both in temperate and tropical areas. In Hawaii, alien tree plantations were

introduced in the first half of the 20th century to ameliorate the hydrological impacts

that intensive sandalwood extraction and cattle ranching had caused on the

watersheds in the 1800s. Since their introduction, the impact of these tree plantations

on the hydrological cycle, including groundwater recharge, has not been evaluated.

The present study has the objectives of quantifying, for the first time in

Hawaii, the components of the water cycle in forest plantations dominated by

different alien tree species thereby estimating the potential of these stands to recharge

groundwater. These objectives were achieved through a four-year field study in the

Honouliuli Preserve, on the Waianae Mountains of the Island of Oahu, Hawaii.

Native tree plantations or remnants of native vegetation are not included in this study

due to their absence in mid-elevation sites on the Waianae Mountains, but the data

obtained on the alien tree plantations may provide grounds for future watershed

restoration projects and management decisions in Hawaii.

1.2. Restoration of ecosystem processes by tree plantations

Tree plantations have been widely established to rehabilitate degraded lands.

In Hawaii, both primary and secondary successions operate at a very slow rate (e.g.,

Drake 1993). When native forest species have very low growth rates the recovery of

1

degraded or denuded land by fast-growing introduced plants can be done

alternatively. In continental tropical regions, growth of secondary vegetation can be

very fast after slash and bum practices because of the high species diversity and the

proximity to the seed source, and therefore rehabilitation of deforested areas may not

require introduction of fast-growing species. In isolated islands, such as Hawaii,

intervention on the secondary succession may be required to speed the rate of

restoration. Studies in Puerto Rico (Lugo 1988, Parrota 1992, 1993, 1995) have

shown that forest plantations established on degraded sites long devoid of native

forests can act as facilitators of the recovery of ecosystem functions, providing better

climatic conditions and safe sites for the establishment of seedlings of native species.

The ability of forest plantations to provide conditions for colonization by native

Hawaiian plants has been observed in forest plantations in Hawaii (Harrington and

Ewe11997, Woodcock et al. 1999). The invasion of native as well as non-native

plants in forest plantations can be explained by the inability of some planted species

to efficiently utilize the resources available for growth (Haggar and Ewel 1997).

Ecosystem structure and function is expected to differ among plantations of

different species. For example, Eucalyptus robusta plantations in Puerto Rico

(Parrota 1995) and Hawaii (Garrison 2003) exhibit higher density and richness of

seedlings in the understory than Casuarina plantations. These differences can be

attributed to structural differences between the plantations such as litter depth

(Parrota 1995). The choice of species for reforestation thus appears to be a very

important step towards the recovery of forest ecosystems.

2

In the Honouliuli Preserve in Hawaii (Fig. 1.1), non-native trees were planted

to restore and protect watersheds (Asner et al. 1993). In 1815, sandalwood extraction

initiated large changes in the vegetation of the Waianae Mountains and was followed

by cattle ranching until 1877. By 1855, over 20,000 animals could be found grazing

throughout the preserve including cattle, horses and sheep (Asner et al. 1993). There

were no fences to limit animal movement and the remnant forests were severely

damaged during this period. During the sugarcane production, several non-native tree

species were planted on Oahu in an effort to reduce erosion and to restore the

watersheds (Asner et al. 1993). By 1960, 4,200 ha ofplantations of species such as

Eucalyptus spp., Casuarina spp., Fraxinus uhdei, Grevillea robusta, and Melaleuca

quinquenervia covered nearly half of the 9,120-hectare Honouliuli Preserve (Nelson

et al. 1968).

The species planted in Honouliuli are representative of the trees used for

reforestation throughout the tropics. Some Eucalyptus and Casuarina species, for

example, are used for reforestation to regulate the depth of water table and salinity in

wetlands of Australia (e.g., Morris et al. 1998, Cramer et al. 1999). Eucalyptus spp

are by far the most studied of the trees used for reforestation in the tropics. Studies

on this genus have shown its importance in the water cycle of forests (e.g., Vertessy

et al. 1997, Calder 1998). Observations that some forest plantations exhibit high

transpiration rates have changed the traditional notion that forests increase the water

yield when compared to short crops (Calder 1998, 2000).

Alien tree plantations in Honouliuli exhibit very low density and richness of

native plants and very high density and richness of invasive plants in their understory

3

(Garrison 2003). Ares and Fownes (1999) found evidence that F uhdei might be

competing with the native Acacia koa for water, and J. B. Friday and colleagues

(pers. comm.) have measured a decrease in the basal area of native species in stands

mixed with F uhdei. However, native plants do grow in the understory of F uhdei

plantations (Harrington and Ewel1997). Nonetheless, the ability of tree plantations

to foster seed recruitment also favors the establishment of invasive plants. As some

invasive plants grow faster than native Hawaiian plants (e.g., Walker and Vitousek

1991, Pattison et al. 1998), their influence and spread threatens the rehabilitation of

Hawaiian forests. Because they have characteristics that may result in higher rates of

water utilization (Pattison et al. 1998, Stratton et al. 2000, Baruch and Goldstein

1999), these invasive non-native plants may change the hydrological functioning of

forests considerably.

1.3. Hydrological cycle in forest ecosystems

Forests are responsible for recycling most of the fresh water available in the

continents. When forests are cut down, increased soil compaction and reduced

transpiration cause more water to flow faster to rivers and oceans (Salati and Nobre

1991, Nepstad et a11994, Jipp et al. 1998). Forests affect the water cycle mainly by

returning the precipitated water back to the atmosphere through evapotranspiration,

and by providing high infiltration (Dunne and Leopold 1978). Changes in land use in

continental regions with extensive forested areas can affect hydrological processes,

such as evapotranspiration, and, consequently, affect regional or even global climate

(Shukla and Mintz 1982, Lean and Warrilow 1989, Shukla et al. 1990, Salati and

Nobre 1991). Development of secondary vegetation reduces the impact of

4

deforestation on the hydrological cycle (Giambelluca et al. 1996, HOlscher et al.

1997, Jipp et al. 1998); however, in some cases, natural regeneration ofthe forest is

very slow. As a result, a faster process of reforestation of watersheds is needed in

order to decrease the impacts of changes in land cover. Although reforestation can

reduce erosion and runoff, it does not always restore the hydrological processes to the

levels found before deforestation (see reviews by Bruijnzeel1996, 1997). In Hawaii,

the main concern in relation to deforestation is the possible reduction in groundwater

recharge, and reforestation with alien trees was done in order to increase this

component of the water cycle. Understanding the water cycle in reforested areas may

provide tools to improve land management programs that affect water resources in

Hawaii and other tropical islands.

The main input of water in a tropical forest is usually through rainfall. Fog

interception may be an important source of water and nutrients in certain high

elevation forests in Hawaii (e.g., Heath and Huebert 1999), but it is not an important

input of water in the mid-elevation forests ofHonouliuli (personal observation).

After reaching the forest canopy, the water follows three main pathways: interception

by the canopy and eventual evaporation, dripping from the leaves and branches or

falling directly to the ground (throughfall), or reaching the ground by flowing down

tree stems (stemflow). Before reaching the mineral soil, some of the water is

intercepted by the litter and eventually evaporated. Part of the water that enters the

soil returns to the atmosphere through the plant by transpiration, and another part

seeps to the water table. Evaporation directly from the soil is usually negligible in

forests (e.g., Jordan and Heuveldop 1981). The water that is not transpired or held by

5

the soil may move by surface runoff to the streams, or vertically to recharge

groundwater. Although the effects of different cover types (e.g., grasses and forests)

on the hydrological cycle have been well studied (e.g., Bultot et al. 1990, Hodnett et

al. 1996, Calder 1998, Jipp et al. 1998), the effects of different forest types on the

magnitude of the water cycle components are still unclear.

Stand structure and tree species may affect forest hydrology by influencing

each of the components of the water cycle cited above, changing the rate and amount

of groundwater recharge. Interception and throughfall, for example, are directly

related to the stand basal area, cover and tree density (Rogerson 1967); the higher the

level of each of these characteristics, the higher the amount of water intercepted by

the canopy (Rogerson 1967). In continental areas, interception amounts to 11 to 39%

of rainfall in hardwood forests (Raich 1983, Pandit et al. 1991, Bruijnzeel1997) and

7 to 28% in softwood plantations (Bruijnzeel 1997), and represent 10 to 34% of

evapotranspiration (Jordan and Heuveldop 1981; Leopoldo et al. 1982, 1995; Moreira

et al. 1997). However, Aboal et al. (1999) found interception loss rates between 30

and 41 % of rainfall on a laurel forest in the Canary Islands, and attributed these rates

partly to the high storage capacity of the canopy. Interception values between 14%

and 22% of gross precipitation found for lower montane rainforests in Jamaica

(Hafkenscheid 2000) and Puerto Rico (Schellekens 2000) were similar to continental

sites but interception was estimated to comprise between 41 and 74% of

evapotranspiration. These observations have led to an increased interest in expanding

direct measurements of interception on tropical island ecosystems (Schllekens et al.

6

1999, Bruijnzeel 2000), but there is still very little information on island forests ofdry

to mesic climate (Bruijnzeel 2000, Schllekens et al. 2000).

Helvey and Patrie (1965) proposed general equations to calculate throughfall

and stemflow that can be applied to hardwood forests of the eastern United States.

However, later studies showed differences among species in relation to these two

hydrological components (e.g., Cape et al. 1991, Sood et al. 1993, Bruiijnzeel1997,

HOlscher et al. 1998), indicating that species composition may influence the forest

water cycle. Canopy density and deciduousness (Cape et al. 1991), bark texture

(Sood et al. 1993), and leaf and branch angles (van Elewijck 1989, Holscher et al.

1998) are species characteristics that may influence throughfall and stemflow.

Throughfall and stemflow in young stands (::=; 12 years old) of different Eucalyptus

species were found to vary from 81 to 94% and 1 to 8% of precipitation, respectively

(reviews by Poore and Fries 1985, and BruijnzeeI1997). Waterloo (1994) found

stemflow to be 1.4% ofprecipitation in a Pinus caribaea plantation in Fiji, but high

values of stemflow, 13 to 18% of precipitation, were reported for lower montane rain

forests in Jamaica (Hafkenscheid 2000) and the extreme value of 41 % was observed

in a secondary forest of eastern Amazonia dominated by Phenakospermum

guyannense (Holscher et al. 1998).

Transpiration rates depend on net radiation, air saturation deficit, wind

conditions, soil moisture availability, leaf area, and stomatal and boundary layer

conductances. Differences in transpiration among species have been widely observed

(Granier et al. 1996, Goldstein et al. 1998, Hunt and Beadle 1998, Restom and

Nepstad 2001), but comparisons among studies are difficult due to the strong effect

7

that climatic factors have on transpiration (Granier et al. 1996). In a stand or

ecosystem level, transpiration rates have been estimated to be similar among forests

dominated by different species. Roberts and Rosier (1994) estimated annual

transpiration rates from one stand ofFraxinus excelsior and one of Fagus sylvatica of

407 and 393 mm, respectively.

Evapotranspiration rates in tropical forests located at continental edges or

islands may be higher than in continental forests. In forests ofPuerto Rico

(Schellekens 2000) and Fiji (Waterloo et aI1999), rainfall interception was greater

than the values predicted by energy balance equations, indicating that other sources of

energy, besides solar radiation, are controlling interception (BruijnzeeI2000). If this

occurs on Oahu, it is possible that previous studies underestimated evapotranspiration

on the island and, consequently, overestimated groundwater recharge.

1.4. Groundwater use and recharge on Oahu

Many problems in maintaining good water quality and a sufficient amount of

water for domestic and industrial consumption arise on islands. Human consumption

is the largest pressure on this resource. For example, human populations on islands

that rely on surface water suffer during periods of extended drought (Shade et al.

1992). Demand on groundwater then increases as an alternative to the less

dependable surface water resource. An extremely serious impact of groundwater

exploitation in oceanic islands is salinization of the water. Groundwater in Hawaii

occurs mainly as basal water, a lens of freshwater floating on and displacing saltwater

at or below sea level (Robins and Lawrence 2000). High levels of pumping from

8

coastal wells, lowering the water levels, cause a rise in the level of the freshwater

saltwater boundary below the well.

The Island of Oahu relies on groundwater, which provided 86% of the

freshwater consumed on the island in 1995 (DLNR 1995). The groundwater in the

Pearl Harbor area, which is part of the southern Oahu groundwater flow system, is the

most developed of the island. The water table in this area have lowered at a rate of

about 30 cm i l from 1910 to 1977, when pumpage increased from 4.5 m3S·l to 10.5

m3S·l (Anthony 1997), and is estimated to have lowered from 10m above sea level

(asl) near Honouliuli before development to lower than 6 m asl in 1984 (Nichols et al.

1996). In 1980, over 60% of groundwater used on the island was pumped from the

southern Oahu area alone (Nakahara 1980).

Estimates of groundwater recharge for the Island of Oahu were based on

estimates of evapotranspiration based on an uncalibrated water balance model

(Giambelluca 1983, Shade and Nichols 1996), and thus might have been

overestimated (see section 1.3). Direct measurements of evapotranspiration are

necessary to improve these estimates.

1.5. Objectives and hypotheses

The main objectives of this study were (1) to quantify and explain differences

in the components of the water cycle among stands dominated by different species

and (2) to estimate the potential of these stands to recharge groundwater.

In this research, stands of Eucalyptus robusta, Fraxinus uhdei, Casuarina

glauca and Grevillea robusta, planted in the Honouliuli Preserve between 1930 and

9

1950, were studied to observe their patterns of water utilization. The species differ in

several aspects, such as size, leaf shape and size, phenology and rooting depth.

Differences in depth of water uptake, and canopy cover and phenology were

considered as stand characteristics that directly affect water use. The data collected

were used to assess the potential of each stand to recharge groundwater.

The questions and hypotheses of this study are summarized below:

1. Are there differences in the components ofthe water cycle offorestplantations

dominated by different species?

HI. There are differences in the components of the water cycle among forests

dominated by different species.

Prediction: The water cycle components will vary according to stand's

characteristics that are a result of species composition such as leaf area index, tree

density, canopy phenology, and rooting depth. I expect that stands dominated by

evergreen species, and with high leaf area index, high tree density and deep water

uptake to have low throughfall and high rates of stemflow, interception, transpiration

and evapotranspiration. On the other end of the spectrum, stands dominated by

deciduous species, and with low leaf area index, low tree density and shallow water

uptake will have high throughfall and low rates of stemflow, interception,

transpiration and evapotranspiration.

10

2. How do measurements ofevapotranspiration compare to values obtained

previously?

H2: Evapotranspiration rates in the forests of Honouliuli, estimated by direct

measurements of sensible heat flux, are higher than previously estimated values based

on an uncalibrated water balance model (Giambelluca 1983).

3. Do forests dominated by different species differ in their potential to recharge

groundwater?

H3: The potential to recharge groundwater will differ among stands


Prediction: Based on the prediction of hypothesis 1 (HI) and considering

surface runoff negligible, the stands with higher evapotranspiration rates will have

lower potential to recharge groundwater and the stands with low evapotranspiration

rates will have higher potential to recharge groundwater.

1.6. Dissertation outline

The hypotheses above are addressed in this dissertation as outlined below:

In Chapter 2, I discuss the patterns of water utilization, particularly

transpiration and soil water uptake, of three stands each dominated by a different tree

species, addressing part of hypothesis HI.

In Chapter 3, I discuss the differences in rainfall interception among stands

dominated by different species, addressing another part of hypothesis HI.

11

In Chapter 4, I discuss the differences in evapotranspiration among three of

the stands studied and their potential to recharge groundwater, addressing part of

hypothesis HI, and hypotheses H2 and H3.

Finally, in Chapter 5 I conclude this dissertation by discussing the

implications of the data obtained in this study for watershed restoration.

1.7. Methods

The study was conducted from April 1998 to April 2002 in the Honouliuli

Preserve. Interception was measured in twelve forest stands, three stands dominated

by each of four species: Casuarina glauca, Eucalyptus robusta, Fraxinus uhdei and

Grevillea robusta. The other components of the water cycle were measured or

estimated in one stand each dominated by the first three species.

1. 7.1. The study site

A reserve was established in Honouliuli (59°46'42" E, 23°68'634" N) at the

end of the 1920s by Campbell Estate and was adopted by The Nature Conservancy as

a preserve in 1990. Honouliuli Preserve contains a high occurrence of rare native

Hawaiian plant and animal species. It is located in the Honouliuli land division of

Oahu, on the eastern slope of the southern Waianae Mountain Range, on the Southern

Oahu groundwater flow-system (Nichols et al. 1996). Mean annual rainfall in this

area ranges from 540 to 750 mm (Giambelluca et al. 1986). The native forest was

largely devastated by sandalwood extraction and ranching. Native forest remnants

are now concentrated on the summit areas where cattle could not access them, but

12

representatives of the native vegetation, individually or in small patches, are found at

lower elevations.

The soils at Honouliuli are an association of Tropohumults-Dystrandepts. The

northern part of the preserve is dominated by Ultisol Tropohumults soils while the

southern part of the preserve is dominated by Inceptisol Dystrandepts soils (S. Peters,

Soil Sciences Department, University of Hawaii). However, the Eucalyptus robusta

stand in the northern part of the preserve is on the soil series mahana, an Inceptisol,

and the Eucalyptus and Fraxinus stands in the middle part of the preserve are on the

soil series kemoo, an Alfisol (Nagel 2003). Soil depth varies between approximately

20 and 130 cm in the southern part of the preserve (personal observation).

1. 7.2. Species studied

Out of almost 17,000 ha of forest trees planted before 1950 on the island of

Oahu, Eucalyptus robusta, Casuarina spp., Fraxinus uhdei and Grevillea robusta

account for 48% (Nelson et al. 1968).

Eucalyptus robusta Sm. - Myrtaceae. Eucalyptus robusta (swamp-mahogany

eucalypt), the most common Eucalyptus planted in Hawaii, is originally from swamp

areas of coastal southeastern Australia. Over 4,000 ha of E. robusta were planted on

Oahu before 1950 (Nelson et al. 1968). These trees can attain heights of over 30 m

and diameters of over 1 m. The trunk is usually straight with a red-brown, thick,

rough and very fibrous bark. Other species ofEucalyptus were found to have

maximum rooting depths from 2.7 m (E. regnans) to 40 m (E. marginata) (review by

Canadell et al. 1996). Eucalyptus regnans has been shown to have high transpiration

13

rates, from 75 to 285 kg dai l in trees of 56 to 89 cm DBH (Vertessy et al. 1997).

However, significant differences in leaf water use efficiency among some species of

Eucalyptus have not been detected (Hatton et al. 1998). In Honouliuli, stands ofE.

robusta usually exhibit a thick layer of coarse litter and little developed understory.

The trees in the stands studied reached 30 to 43 m heights and their basal area was

relatively high when compared to stands dominated by the other species of this study

(Table 1.1).

Casuarina glauca Sieber ex Spreng - Casuarinaceae. Casuarina spp.

(ironwood) were some ofthe most planted trees on Oahu with almost 3,000 ha

planted before 1950 (Nelson et al. 1968). Originally from Australia, Casuarina

glauca is now the most common species of Casuarina in the forest reserves ofHawaii

(Little and Skolmen 1989). Shrubs from this genus were observed to have maximum

rooting depths from 2.0 m (c. muelleriana) to 2.4 m (c. pusilla) (review by Canadell

et al. 1996). Species of Casuarina may produce allelopathic chemicals in low levels

(Suresh and Rai 1988, Barritt and Facelli 2001), which, together with the high

accumulation of litter mass (Suresh and Rai 1988), decreases understory colonization

(Parrota 1995, Barritt and Facelli 2001). Although Casuarina spp. fix nitrogen, the

characteristics cited above make these species unsuitable for catalyzing the

restoration of native flora. In Honouliuli, stands dominated by Casuarina are

remarkable by the lack of understory plants and the presence of a very thick layer of

litter and roots at the soil surface. The trees found in these stands are smaller in

height and diameter than in the stands dominated by the other species of this study.

14

Fraxinus uhdei (Wenzig) Lingelsh. - Oleaceae. Fraxinus uhdei (tropical ash)

is originally from Mexico. Since 1920, over 700,000 trees have been planted on all

islands in Hawaii for watershed cover (Little and Skomen 1989), but until 1950 less

than 40 ha were planted on Oahu (Nelson et al. 1968). Of these, at least 20 ha were

planted in Honouliuli. Fraxinus uhdei is deciduous, losing all of its foliage for one

month between November and January in Hawaii (Harrington and EweI1997). In

temperate deciduous forests, another species of this genus, Fjaponica, may have

roots down to 2 m depth (review by Canadell 1996), but, in this study, the roots of F

uhdei as well as the roots of the other species, are probably limited by the shallow soil

(personal observation). Fraxinus stands in Honouliuli usually exhibit a dense

understory, with 94% of seedlings and saplings being of the same dominant canopy

species (Garrison 2003). The litter layer is very thin suggesting that decomposition of

the leaves is relatively fast in these stands.

Grevillea robusta A. Cunn. (Proteaceae) is a large tree, reaching 12 to 30 m in

height, with rough, thick bark. This species is the second most commonly planted

tree in Hawaii (Little and Skolmen 1989). In Honouliuli, Grevillea forms stands with

tall sparse trees and higher percent ground cover than stands dominated by Casuarina

glauca or Eucalyptus robusta (Garrison 2003). The stands of Grevillea in Honouliuli

are starting to show signs of senescence and the ones located in the drier areas have

their understory dominated by the invasive shrub Schinus terebinthifolius. Due to the

physiological constraints that the trees in these dying stands may be experiencing, this

species was only included in part of the study.

15

The stands used in this study are still dominated by the original planted

species but most of them have been invaded by several other trees and shrubs. When

the density of these other species was high, they were also included in the

measurements. The species included were Psidium cattleianum and Schinus

terebinthifolius.

Psidium cattleianum Sabine - Myrtaceae. Originally from southern Brazil, P.

cattleianum (strawberry guava) is a small evergreen tree that can reach heights of 6 to

15 m. It was introduced into Hawaii in 1825 for its edible fruit (Little and Skolmen

1989) and now occurs up to 1,300-m elevation across a broad range ofprecipitation

(Jacobi and Warshauer 1992). A high density ofthis species can be found invading

forest plantations such as Eucalyptus saligna (Harrington and Ewel 1997). The bark

ofP. cattleianum trees is smooth resulting in large amounts of stemflow (personal

observation). The edible fruits attract animals that help to disperse the seeds. This

characteristic, associated with their clonal growth, turns this species into one of the

most aggressive invasive species in Hawaii (Huenneke and Vitousek 1990).

Schinus terebinthifolius Raddi - Anacardiaceae. Schinus terebinthifolius

(Christmas berry, Brazilian pepper, wilelaiki) is an evergreen shrub or small tree that

can reach a height of 8 m. It is originally from South America and was introduced

into Hawaii before 1911 as an ornamental due to its attractive red berries (Little and

Skolmen 1989). The bark of mature plants is furrowed and slightly scaly (Lemke

1992). Schinus terebinthifolius shows a very high plasticity in water utilization when

compared to native Hawaiian plants in dry forest (Stratton et al. 2000), giving it a

competitive advantage in dry environments.

16

1. 7.3. Field measurements

For the purpose ofthis study, the Honouliuli Preserve was subdivided in three

sections: south, middle, and north. This subdivision was done to account for

topographic and climatic differences in the study area. In each of these sections, one

stand dominated by each ofthe planted species was studied (Fig. 1.2). A summary of

the characteristics of each stand can be found in Table 1.1.

Interception and leaf area index were measured in all 12 stands. Complete

sets of measurements were obtained in three stands (Casuarina, Eucalyptus and

Fraxinus) in the southern section, each dominated by a different species, including

rainfall above the canopy, interception, soil moisture, and transpiration. The data of

these three stands were applied to a water balance equation to estimate the water

available to recharge groundwater. Meteorological data and rainfall were collected

for each section of the preserve from three weather stations (Fig. 1.2).

All the data were collected for eight months (July 2001 to March 2002) in the

three stands of the southern section. Interception was measured for three years (from

April 1998 to March 2001) in the northern section and for two years (from April 1999

to March 2001) in the middle and southern sections. Leaf area index was measured in

all stands for one year (from August 1999 to July 2000) and in the three southern

stands for an additional eight months (from July 2001 to April 2002).

Stand characterization

Depth of water uptake was estimated for one stand of each forest type using

the natural abundance of the stable isotopes hydrogen and deuterium in the soil and

tree sapwood water (White et al. 1985). Water was collected at different depths in the

17

soil down to 90 cm in three soil profiles per stand and analyzed for the relative

abundance of these isotopes in each layer. Water was also obtained from sapwood

samples of four to five plants near where the soil samples were taken. Both the soil

and xylem samples were vacuum-distilled. The extracted water was analyzed for

stable isotope ratios of hydrogen/deuterium using mass-spectrometry (Mountain Mass

Spectrometry, Evergreen, CO, USA). The depth of water uptake was determined by

comparison between the plant sample and the soil profile.

Leaf area index (LAl) was estimated with a LAl-2000 Plant Canopy Analyzer

(LiCor, Lincoln, NE, USA) at 12 to 20 points along two or more transects in each

stand every two months for one year, and additionally every month for eight months

in the stands of the southern section. The points were at 10m intervals along

transects set 15 m apart. The number of points varied in each stand in order to get a

standard error:S 5%. This method bases on the light extinction through the canopy to

estimate cover and compares the measurements done under the canopy with

measurements done in an open area. Simultaneous measurements below the canopy

and in the open were done with the use of two LAl-2000 units. LAl estimated with

the LAl-2000 was tested by Lopez-Serrano et al. (2000) and was shown to give

similar results as other methods.

Components ofthe water cycle

Rainfall was measured above the canopy and in open areas close to the stands

with tipping bucket rain gauges (Texas Electronics, Dallas, TX). The gauges were

connected to dataloggers (21 X or CRI0, Campbell Sci., Logan, UT; or Hobo Event,

Onset, Pocasset, MA) to measure intensity and duration of each event.

18

Interception was estimated by subtracting the sum of throughfall and stemflow

from the rainfall value for a certain period.

Throughfall collectors were composed of a set of three troughs attached to a

bucket. Each set had a collection area of 0.2 m2. Three to nine sets (depending on

data variation) were installed under the canopy in each stand. The water collected in

the buckets was measured every other week in each stand for the first three years of

the study (1998 - 2000) and additionally every week for six months in 2001 in the

stands on the southern section. For the 2001 measurements, approximately half ofthe

collectors were automated with tipping buckets connected to dataloggers (Hobo

Event, Onset, Pocasset, MA), collecting data for a total of eight months.

Stemflow was measured with spiral collars fitted to tree stems channeling

water into 4- to 30-liter collection bottles, or to a tipping bucket connected to a

datalogger (Hobo Event, Onset, Pocasset, MA). These collectors were installed in

four to eight trees in each stand. The water collected in the bottles was measured

every two weeks in each stand for the first three years of the study and additionally

every week for six months, or eight months for the automated collectors, in the stands

on the southern section. Regressions were done between rainfall and stemflow

amount for trees in different diameter classes to permit scaling up tree measurements

to the stand in units of water depth, based on a vegetation survey.

Soil moisture, in terms of volumetric water content, was measured weekly

from May 2001 to April 2002 in three stands on the southern section with time

domain reflectometry (TDR, MP-917, E.S.!. Environmental Sensors, Inc., BC,

Canada). Three electrically segmented profiling probes (Type F, E.S.I.

19

Environmental Sensors, Inc., BC, Canada) were installed vertically in the soil at three

random locations in each stand for measuring soil moisture at five depths: 0-15, 15

30,30-45,45-60, and 60-90 em. Measurements were obtained manually with a

viewing instrument (MP-917, Environmental Sensors, Inc.) specially designed to

interrogate the probes.

Transpiration was measured with the heat dissipation technique (Granier

1985). One to six pairs (depending on tree size) of thermocouple probes of variable

lengths were inserted in each tree 1.5 m above the ground, in different depths of the

sapwood to measure sap flow. Measurements are based on the heat dissipation

method (Granier 1985, 1987) with probes made in our laboratory following the

procedure of James et al. (2002), and data were collected by a datalogger (21X or

CRlO plus a AM416 multiplexer, Campbell Sci., Logan, UT, USA). Total tree

transpiration was calculated based on sapwood area, which was determined by

injecting dye into the sapwood. Sap flow measurements were taken simultaneously

when possible in the three stands of the southern section between July 2001 and

March 2002.

Potential evapotranspiration (PE) was estimated based on the equation

proposed by Penman (1948) as described in Chapters 3 and 4.

Dry canopy evapotranspiration (the evapotranspiration occurring between

rainfall events) was estimated based on the temperature variance (TVAR) method

(Vugts et al. 1993). The TVAR method is based on the variation of temperature

measured with fast-response thermocouples above the canopy during dry canopy

conditions (Schellekens 2000). Chapter 4 gives more details on this method.

20

Data analysis of the components of the water cycle was done using Analysis

of Variance (ANOVA), Repeated Measures ANOVA or Analysis of Covariance to

determine differences among the species.

Micrometeorology

Micrometeorological data were collected from three weather stations installed

throughout the preserve, one in each section, and from infrared transducers

(4000AZL, Everest Interscience, Inc., Tucson, AZ, USA) measuring the canopy

temperature of three stands in the southern section. The stations measured solar

radiation (LI-200SZ, LiCor, Lincoln, Nebraska, USA), air temperature and relative

humidity (HMP45C, Vaisala, Inc., Sunnyvale, CA, USA), wind speed (OI4A,

MetOne Instruments, Rowlett, TX, USA), and precipitation. Upon completion ofthe

first three years of data collection, the weather station on the southern section was

moved to a new location to collect data above the canopy of short Schinus

terebinthifolius vegetation. This station was used as a reference, and was equipped

additionally with one net radiometer (Q7.1_L50, Radiation Energy Balance Systems/

Campbell Scientific, Logan, UT, USA), one infrared transducer measuring canopy

temperature, and one pyranometer positioned upside down to measure reflected

shortwave radiation.

Groundwater recharge

Evapotranspiration and groundwater recharge were estimated using a water

balance model calibrated for the study sites based on field measurements of soil

moisture. The water balance method used was the bookkeeping procedure

(Thornthwaite 1948, Thornthwaite and Mather 1955) modified by Giambelluca

21

(1983, 1986) and is described in more detail in Chapter 4. Groundwater recharge was

estimated from May 2001 to April 2002 in three stands on the southern section each

dominated by Casuarina, Eucalyptus or Fraxinus.

1.8. Summary

By measuring directly the components of the water cycle in non-native forest

plantations in the Honouliuli Preserve, this project aims to increase the understanding

of the hydrology of forests on oceanic islands and to contribute with data on

groundwater recharge, providing important tools to improve watershed management

and conservation. These direct measurements may be used to calibrate estimates of

evapotranspiration based on models created for continental areas, thus providing a

more accurate estimate of groundwater recharge for part of the Island of Oahu.

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30

Table 1.1 - Characteristics of the stands studied at the Honouliuli Preserve, Oahu, Hawaii. Stand elevation, area, basal area, tree

density and height, and density of volunteer trees were measured between April and October 1998 (except for F uhdei North, which

was done in April 1999). Values of leaf area index (LAI) shown here are the values measured in June 1999 (for Grevillea stands) or

the range between June 1999 and July 2000.

Basal areab Tree densitlVolunteer

Dominant Elevation Area Mean/Maxtreesb,e

LAILocation Code"

(m2ha'l) (trees ha'l) (m2m'2)species (m) (ha) heights (m)(trees ha'l)

South 3091 540 0.80 28.8d 9.2 / 30.5 1,094d 363 d 1.5-3.1Eucalyptus

Middle 3109 390 3.60 53.0 21.0/42.9 487 51 1.6 - 3.0robusta

27.7d 1,381 d 567 dNorth 3128 460 1.25 9.0/29.0 1.6-2.1

South 540 25.7 5.9 13.5 3,238 III 2.2 - 3.0Casuarina

Middle 3405 490 0.37 22.2 5.2 / 9.0 2,211 191 1.4-2.4glauca

North 530 0.13 22.2 6.3/17.5 2,778 85 2.0-2.8

South 3095 460 0.52 36.0 6.7/ 19.0 1,044 560 2.1-4.8Fraxinus

Middle 3088 430 0.96 25.4 7.7/19.5 1,644 465 2.6 -4.6uhdei

North 530 0.45 32.7 7.2 /20.3 1,912 223 2.2 -4.2

3004 490 40.7 13.8/32.4 719 216 2.5Grevillea

49.7 d 707 d 414 dMiddle 3118 460 0.55 17.5/45.9 1.8robusta

31.1 d 649 d 318 dNorth 3125 520 0.50 13.0/30.1 3.7

a Code corresponds to the identification of the stand given by the State ofHawaii at the time of planting (Nelson et al. 1968). The stands with no

code were not identified through the plantation maps.

b Basal area and tree density were estimated based on trees with DBH:;::: 5 em.

e Volunteer trees are the trees that do not belong to the same species as the original planted trees.

d Data from Garrison (2003).

31

,- ,..

I

·....

• -.>':fa

.."

..

.'

nONOUUUUPRJ!SERVE

, <J Kaql OAHU

Nil..... ~ ~MoIoItIi

La.. 0 bMIUJ..THE "-01

HAWAIIANISVJIIDS

Figun 1:

Honouliuli Preserve(3,692 acres)

D..., ...L-__~'~ 1- H

ca-.; _ \000 Fe,,'

Figure 1.1 - Location of the Honouliuli Preserve on the Island ofOahu, Hawaii (map

from The Nature Conservancy of Hawaii).

32

Figure 1.2 - Location of the stands studied, weather stations and additional rainfall

collectors in the Honouliuli Preserve on the island of Oahu, Hawaii. Map was

modified from original map created by The Nature Conservancy of Hawaii - Oahu.

33

2. Patterns of water uptake and transpiration in Eucalyptus

robusta, Fraxinus uhdei and Casuarina glauca growing in plantations

in Honouliuli, Hawaii.

2.1. Abstract

This study focuses on the patterns of water uptake, and on transpiration, leaf

area and soil moisture dynamics of three non-native tree species widely planted in

Hawaii: Eucalyptus robusta, Fraxinus uhdei, and Casuarina glauca. The objective

was to assess differences in water uptake and transpiration among these species and

stands dominated by them. Data were collected in one stand dominated by each

species from August 1998 to March 2002. The vertical pattern of water uptake by

roots was determined using the natural abundance of stable hydrogen isotopes; leaf

area index (LAI) was measured monthly with a plant canopy analyzer; volumetric

water content was measured weekly using time domain reflectometry; and tree sap

flow was measured with heat dissipation probes. A long drought occurred from

January 2000 to October 2001. Three months after the end of the drought,

transpiration in Eucalyptus and Fraxinus trees was two to five times higher than in

Casuarina trees of similar diameter. However, the relationship between transpiration

and basal area was not significantly different among the three species, possibly due to

a lack of large Casuarina trees in the stand studied. It is suggested that species

composition and thus stand structural characteristics influence the speed and

magnitude of decline and recovery of tree transpiration. The stand dominated by

Fraxinus possibly takes water from at least 75 cm deep, has high soil moisture, and

34

recovered LAI promptly after the end of the drought. The Eucalyptus stand takes

water from approximately 45 cm deep soil and had high soil moisture, but had a very

slow recovery of LAI in relation to the other stands. The Casuarina stand takes water

from soil shallower than 40 cm, has very low soil moisture, but it was still able to

recover LAI relatively fast.

2.2. Introduction

Forest plantations on Oahu, Hawaii, occupy an area of 17,000 ha, which is

more than 11% of the island's area. These plantations were established during the

first half of the 1900s in order to increase groundwater recharge, which was thought

to have been reduced after a large part of the island's mountains were deforested by

sandalwood extraction and cattle grazing in the 1800s. Since their establishment, no

studies have been done to directly measure the water utilization of these forests and

their importance in the water yield of the watersheds. In this chapter I present results

from part of a larger study that aims to estimate the potential of these plantations to

recharge groundwater in the mesic watershed of Honouliuli, Island of Oahu, Hawaii.

This study focuses on the rates and patterns of transpiration, patterns of water uptake

by roots, and leaf area and soil moisture dynamics of forests dominated by three non

native tree species.

Forest stands dominated by one or very few species usually exhibit a certain

structure determined by the dominant species' characteristics (Wolf 1998, Galindo

Jaimes et al. 2002). The structure of the stand can be quantified by measuring

variables such as leaf area index, basal area, tree density, ground cover and species

35

richness. These variables may influence transpiration of individual trees in different

ways (e.g., Meinzer et al. 1996 for tree density, Calder 1998 for tree size, Oren et al.

1999 for leaf area index) resulting in differences in whole-stand transpiration when

comparing stands dominated by different species.

For accurate comparisons of water use among stands dominated by different

species, simultaneous measurements are required, or transpiration rates must be

normalized by relevant climatic driving variables, such as the air saturation deficit or

potential evapotranspiration. This is not always possible due to the high cost of

acquiring climatological equipment or the large number of sap flow sensors necessary

for adequate scaling of measurements on individual trees to the stand level. Recent

improvements in techniques for measuring sap flow have tried to address the problem

of scaling up the measurements from the probes to the tree (Clearwater et al. 1999,

James et al. 2002, Nadezhdina et a12002, Ford et al. 2004) and from the tree to the

stand (e.g., Hatton et al. 1995, Hunt and Beadle 1998) by reducing the errors in

estimating whole-tree transpiration rates. These improvements involve measuring sap

flow in different depths of the sapwood and increasing the number of probes per tree

to account for a larger part of the radial and axial sap flow variation within a tree. By

measuring sap flow in different depths of the sapwood, some authors have observed

radial differences in sap flow patterns among different species (James et al. 2002,

Nadezhdina et al. 2002, Ford et al. 2004).

I report data collected on stands of Eucalyptus robusta, Fraxinus uhdei, and

C;asuarina glauca that were planted in the Honouliuli Preserve between 1930 and

1950. I studied these stands to assess differences in water uptake and transpiration of

36

different species and their possible effect on whole-stand water use. I hypothesize

that water uptake and transpiration will differ among stands dominated by different

species due to differences in rooting depth, sapwood area, and leaf area dynamics.

This chapter focuses on transpiration at the tree level. Stand transpiration is analyzed

in Chapter 4.

2.3. Methods

2.3.1. The study site

The Nature Conservancy's Honouliuli Preserve is located on the eastern slope

of the southern Waianae Mountain Range, on the Island of Oahu, Hawaii. Mean

annual rainfall in this area ranges from 540 to 750 mm (Giambelluca et al. 1986).

The southern part of Honouliuli, where this study was conducted, is dominated by 20

to 130-cm-deep Dystrandepts (identification by S. Peters, Soil Sciences Department,

University of Hawaii at Manoa).

The native forest in Honouliuli was largely devastated by sandalwood

extraction and grazing during the 1800s. Native forest remnants are now

concentrated on the summit areas where cattle could not access them, but small

patches ofnative vegetation are still found at lower elevations. Between the 1920s

and late 1940s, several non-native fast-growing tree species were planted in this area,

in mono-specific stands, in order to reduce erosion and to facilitate groundwater

recharge.

37

2.3.2. Field measurements

From June 2000 to March 2002, sap flow, soil moisture, patterns of water

uptake, and leaf area index were measured in three forest stands dominated by each of

three species: Eucalyptus robusta, Casuarina glauca and Fraxinus uhdei (Section

1.7.2, Table 2.1). One micrometeorological station measuring rainfall, net and

incoming solar radiation, albedo, wind speed, air temperature, and relative humidity

was placed near the stands.

Vertical patterns of water uptake by roots were observed in July 2001, after at

least 36 days with no rainfall event larger than 1 mm, using the natural abundance of

the stable isotopes hydrogen and deuterium in the soil and xylem water (White et al.

1985). Water was collected at different depths in the soil down to 90 cm, where

possible, in three soil profiles per stand (Table 2.2) and analyzed for the relative

abundance of deuterium (oD) in each layer. Water was also obtained from sapwood

samples of five to fourteen plants near where the soil samples were taken. Samples

were collected on July 12,2001, in the Fraxinus and Eucalyptus stands, and on July

25,2001, in the Casuarina stand. There were three rainfall events smaller than 0.5

mm each between these dates, the last on July 18. Both the soil and xylem samples

were vacuum-distilled, and the extracted water was analyzed for stable isotope ratios

ofhydrogenldeuterium using mass-spectrometry (Mountain Mass Spectrometry,

Evergreen, CO, USA). Analysis of variance and Tukey's pairwise comparisons

between the plant samples and the samples taken at different layers ofthe soil profile

were used to determine the depth of water uptake in each stand.

38

Leaf area index (LAI) was estimated with a LAI-2000 Plant Canopy Analyzer

(LiCor, Lincoln, NE) in 15 to 20 points along two or more transects in each stand

every month from June 2001 to March 2002. The points were at 10 m intervals along

transects set 15 m apart. The number of points varied in each stand in order to get a

standard error :S 5%. This method bases on the light extinction through the canopy to

estimate cover and compares the measurements done under the canopy with

measurements done in an open area. Simultaneous measurements below the canopy

and in the open were done in this study with the use of two LAI-2000 units. LAI

measured with the LAI-2000 was tested by Lopez-Serrano et al. (2000) and was

shown to give similar results as other methods.

Rainfall was measured at a weather station located between the Fraxinus and

Eucalyptus stands, and in an open area close to the Casuarina stand. Rainfall was

measured at 1 min intervals using tipping bucket rain gauges (Texas Electronics,

Dallas, TX) connected to a datalogger (21 X, Campbell Sci., Logan, UT; or Hobo

Event, Onset Computer Corp., Pocasset, MA).

Soil volumetric water content (VWC) was measured weekly from May 2001

to April 2002 in the three stands using time-domain reflectometry (Topp et al. 1980,

Topp and Davis 1985). Three electrically segmented profiling probes (Type F, E.S.!.

Environmental Sensors, Inc., BC, Canada) were installed vertically in the soil at three

random locations in each stand for measuring soil moisture at five depths: 0-15, 15

30,30-45,45-60, and 60-90 cm. Measurements were obtained manually with a

viewing instrument (MP-917, Environmental Sensors, Inc.) specially designed to

interrogate the probes.

39

Sap flow was measured with the heat dissipation technique (Granier 1985,

1987). One to six pairs (depending on tree size) of thermocouple probes of variable

lengths, each with a I-em measuring tip, were inserted in each tree in different depths

of the sapwood. The probes were made in our laboratory, following the procedure of

James et al. (2002), and the data were recorded by a datalogger (21X or CR10 plus

AM416 multiplexer, Campbell Sci., Logan, UT, USA) every ten minutes. The

sensors were inserted in pairs at approximately 1.5 m above the ground, forming a

spiral with the probes at successive depths, in four to six trees per stand. Each sensor

was separated vertically from its pair by 10 em, and circumferentially from the next

pair of probes by 5 em. Ideally, each tree was to be measured in at least two depths in

two sides of the trunk. However, the sensors were very delicate and several of them

broke either during installation or shortly after. This reduced the number oftrees

measured, the number of probes per tree, and the number of replicates per depth. The

probes that worked for a considerable number of days and were used for the analyses

are listed in Table 2.3.

Sap flow measurements were taken in June 2000 in the Casuarina stand, in

September 2000 in the E. robusta stand, and in the three stands between July 2001

and March 2002. Commercially available heat-dissipation probes (TDP 30 mm,

Dynamax, Houston, Texas, USA) were used in a few trees (Table 2.3). Total tree

transpiration was calculated based on sapwood area, determined at the end of the

study by inserting a 1% Safranin solution into a hole in the sapwood and collecting a

core above the hole two to three hours later. Sap flow was scaled up from the probe

to the tree by assigning each probe's measurement to the sapwood ring surrounding

40

the probe beginning halfway from the shallower probe tip and ending halfway to the

next, deeper, probe tip (James et al. 2002).

To test the null hypothesis that sap flow is similar in the three species, a

comparison of the regression curves between basal area and sap flow from January to

March 2002 for each species was made using analysis of covariance, having basal

area as the covariate.

An additional method to determine the preferential depth of water uptake

involved comparing the sap flow data to the soil moisture at different cumulative

depths. The VWC for each layer of the soil was averaged to obtain mean VWC in

cumulative depths of 0-15, 0-30, 0-45, 0-60, and 0-90 cm and to compare the

moisture at these layers to the sap flow of each tree measured. Mean daily tree

transpiration was used as the independent variable, and air saturation deficit (ASD)

and VWC in each layer were used as independent variables in a multiple regression

analysis to estimate depth of water uptake. Each depth was analyzed separately with

ASD against transpiration and the relationships that yielded the p values :S 0.05 were

considered to indicate the preferential depth of water uptake.

2.4. Results

2.4.1. Rainfallpattern and soil moisture dynamics

A long drought occurred in the study area between January 2000 and

November 2001, during which rainfall did not exceed 60 mm in any month (Fig. 2.1).

The normal winter rainfall pattern (based on Giambelluca et al. 1986) resumed in

November 2001, but February 2002 was drier than usual for February. Consequently,

41

soil moisture was very low until mid-November 2001 in all stands (Fig. 2.2), with an

average of 14.5% for the Fraxinus and Eucalyptus stands and of 12% for the

Casuarina stand. On average, the Fraxinus stand exhibited higher soil moisture

recharge after the rain restarted than the other stands, whereas soil at the Casuarina

stand was drier than at the other two sites (Fig. 2.2). The difference in soil water

content between the dry and wet seasons within the stands dominated by Fraxinus or

Eucalyptus is large, whereas within the Casuarina stand the difference is not as

dramatic (Fig. 2.3). Soil volumetric water content in the Casuarina stand remained

low even four months after the start of heavier rains (Fig. 2.2).

2.4.2. Vertical pattern ofwater uptake by roots

The soil 3D profile was very similar in the Casuarina and Eucalyptus stands,

with the most superficial layer (5-20 cm and 5-10 cm, respectively) having 3D values

around -30%0 and decreasing steadily with depth (Fig. 2.4). There were no significant

differences in 3D among the three layers of the soil sampled in the Fraxinus stand,

but most samples taken in the deepest layer exhibited more negative 3D values than

the shallower ones. The 3D measurements of the xylem water indicated that water

uptake might be deeper in stands dominated by Fraxinus than in the other two stands.

The 3D value in the sapwood water in Eucalyptus trees was similar to the values of

all soil layers sampled between 5 and 40 cm, but different from the 45-90 cm depth (F

= 6.25, p = 0.001). The 3D value in the sapwood water in Casuarina trees was

similar to the values in the 5-40 cm layers and different from the values in the layers

below that (F = 13.6, P < 0.001). In the Fraxinus stand, the water 3D value of the

42

sapwood was similar to the values of all layers, but barely significant for the two

more superficial layers (F = 3.49, p = 0.037). These results suggest that whereas

Eucalyptus and Casuarina might be drawing water from the profile down to 40 cm,

Fraxinus trees might be drawing water from as deep as 75 cm (Fig. 2.4). A more

accurate estimate of the depth of water uptake for the Fraxinus stand was not possible

because only one out of three soil pits had soil deeper than 30 cm. It is possible that

this species might be drawing water from the weathered basaltic substrate as indicated

by the more negative 8D values found in Fraxinus trees when compared to the soil

8D values. No correlation between plant size and xylem water 8D was detected for

the Casuarina trees. With the exception of one tree (DBH = 9.5 cm), the Casuarina

trees measured seem to consistently tap water from shallow soil. Diameter of the

sampled trees was not measured in the other stands.

2.4.3. Leafarea dynamics

Fraxinus stands had higher LAI than Eucalyptus or Casuarina stands before

the drought (Chapter 3). The LAI of the stands reached their lowest values from

September to December 2001 (Fig. 2.5, second panel). Eucalyptus appeared to have

been affected the most by the drought, dropping to LAI values < I, and recovering

very slowly after the rainfall increased, from November 2001 on (Fig. 2.5, second

panel). On the other hand, Fraxinus exhibited a relatively fast recovery of LAI after

the rain restarted.

43

2.4.4. Transpiration

The entire radial profile of Fraxinus and Casuarina trees consisted of active

sapwood but this was not the case in the Eucalyptus trees (Fig. 2.6). A similar

relationship between DBH and sapwood area was observed for Fraxinus and

Casuarina, which fit the same relationship observed by Meinzer et al. (2001). In

contrast, the DBH (in cm) and sapwood area (As, in m2) relationship for Eucalyptus is

described (r2 = 0.89, p = 0.005, n = 6) by the following equation (Fig. 2.6):

AsE.robusta = 0.0263 In(DBHE.robusta) - 0.0532 (eq.2.1)

Differences in sap flow were observed in the measurements made with probes

at the same depth within a tree. In some instances sap flow differed by 100%

between different sides of the same tree (Fig. 2.7). Radial differences within trees

were also observed among probes installed at different depths. Sap flux density

(SFD) was highest near the bark and decreased towards the center of the trunk in

Fraxinus and Eucalyptus. The decrease in SFD was steeper in Eucalyptus than in

Fraxinus as Eucalyptus tends to have shallower hydro-active xylem than Fraxinus.

In contrast, SFD remained the same throughout the Casuarina sapwood profile in

February and March 2002 (Fig. 2.8). These SFD profiles were used to estimate tree

transpiration in the trees that had no shallow probes (Table 2.3). The hypothesis that

sap flow as a function of basal area was the same in all three species tested with the

analysis of covariance could not be rejected (F = 0.59, p> 0.25). Some sampling bias

may have contributed to this result. The trees in the Casuarina stand are much

smaller in diameter than the trees in the other stands, and only three trees were

44

measured in the Fraxinus stand. A regression curve combining all three species

indicates that basal area explained 50% of the variation in the sap flow (Fig. 2.9).

The daily average SFD of all trees measured in each stand was very low

during the drought (Fig. 2.5, bottom panel). An increase in SFD after the drought

was observed in Eucalyptus and Fraxinus trees, but not in Casuarina trees, with the

exception of one Casuarina tree in November 2001 (Fig. 2.5, bottom panel). Sap

flow in Casuarina trees four months after the beginning of the drought was relatively

high, at an average of 100 kg d-1• Sap flow in the largest Casuarina tree decreased

drastically from 99 kg d-1 in June 2000 to 7 kg d-1 by the end ofthe drought. Even

after the end of the drought, sap flow in Casuarina trees continued to decrease to an

average ofless than 2 kg d-1 (Table 2.4). The earliest sap flow measurements in

Eucalyptus trees were done on September 2000, seven months after the beginning of

the drought. By this time, the mean sap flow of the trees measured was less than 10

kg d-1 (Table 2.4). In September 2000, two of the Eucalyptus trees had mean sap flow

of 7 kg d-1• By the end of the drought, sap flow on these same trees averaged 1 kg d-1

and increased to an average of4.3 kg d-1 after the end of the drought. Sap flow

measurements in Fraxinus trees began 18 months after the beginning of the drought.

Sap flow remained low in one Fraxinus tree from July to December 2001, at around 3

kg d- 1, then increased to around 17 kg d-1 after the end ofthe drought (Table 2.4).

Eucalyptus trees responded to the first rains after the drought faster than Fraxinus or

Casuarina trees, exhibiting an increase in sap flow as early as November and

December 2001 (Table 2.4).

45

The influence of the atmospheric demand on transpiration in dry and wet

periods for each stand is shown in Figure 2.10. There was an atmospheric regulation

of transpiration during the dry months (Fig. 2.10) and practically no relationship

between air saturation deficit (ASD) and sap flow during the wet months for all

stands (not shown).

The sap flow in the 45 cm DBH Fraxinus tree was significantly correlated to

VWC in the 0-30, 0-45, 0-60, and 0-90 cm soil depths, indicating that this tree may be

drawing water from at least 90 cm deep (Table 2.5). Sap flow was not significantly

correlated to VWC over any depth in the other two Fraxinus trees (Table 2.5). No

significant relationship was found between the sap flow in the Casuarina trees

examined and ASD and VWC at any depth (Table 2.6). Ofthe five Eucalyptus trees

examined, only one exhibited significant relationships, with soil moisture from 0-30

cm (Table 2.7).

2.5. Discussion

The differences in water use among the trees studied became apparent as the

drought ended. Sap flow was equally low in all three species by the end of the

drought, and it was not significantly different, as a function of basal area, after the

drought ended. However, the three species differed in the way they responded to the

return of the rain with Eucalyptus and Fraxinus showing faster responses than

Casuarina.

Although Eucalyptus had the fastest response of the three species in terms of

sap flow, its LAI took long to respond. This implies that Eucalyptus was able to

sustain high transpiration rates at low leaf area, caused possibly by increased stomatal

46

opening in response to increased leaf-specific hydraulic conductivity (Gt) following

increases in soil moisture. If Gt is inversely proportional to the leaf area:sapwood

area ratio (LA/SA) in Eucalyptus, as observed for several species by Andrade et al.

(1998), then assuming that sapwood area does not vary much, the loss in leaf area in

this species would result in higher Gt • The weak relationship found between sap flow

and ASD in the peak of the drought could be a consequence of both reduced leaf area

and stomatal responses to humidity. Bucci et al. (in press) observed that species with

larger decreases in LA/SA from the wet to the dry season in the Brazilian Cerrado

tended to exhibit smaller declines in stomatal conductance during the dry season.

Leaf-specific hydraulic conductivity in these species seems to be particularly

sensitive to fluctuations in leaf area (Bucci et aI., in press). Morris et ai. (1998) found

no relationship between stomatal conductance and vapor pressure deficit in

Eucalyptus grandis and E. camaldulensis. However, strong stomatal control was

found in E. globulus in a plantation in Portugal (David et ai. 1997). Hatton et ai.

(1998) provided evidence that different Eucalyptus species balance stomatal

conductance and LAI in order to maintain similar leaf efficiencies when growing in a

similar environment.

In Fraxinus, recovery of LAI and sap flow was relatively rapid shortly after

the end of the drought. This suggests that this species is well adapted to dry periods

and, like Eucalyptus, it controls transpiration by losing leaves, and, to a lesser extent,

by closing its stomata. However, unlike Eucalyptus, Fraxinus trees may have access

to soil moisture at greater depths and thus be able to restore leaf area faster. Even

though Fraxinus might have access to deeper water sources than the other two

47

species, as shown by the hydrogen isotope analyses, on average, SFD in Fraxinus was

not higher than in Eucalyptus or Casuarina. These results contrast with those of

Jackson et al. (1999), who found that plants with access to deeper, more dependable,

water sources tended to have higher rates of water use in the Brazilian Cerrado.

However, similar to this study, they found that deciduous species tended to tap deeper

water from the soil profile than evergreen species.

The response of Casuarina to the drought was unexpected. Even though

VWC and SFD were low, LAI increased relatively quickly in the Casuarina stand

after the end of the drought. There is a chance that the long-term monitoring of sap

flow in Casuarina could have resulted in a wound around the probe, damaging the

xylem. However, sap flow probes installed in January 2002, after the end of the

drought, measured low sap flow, consistent with the probes inserted earlier. It is also

possible that tree sap flow was drastically reduced during the drought through the

formation of embolisms in the xylem vessels. The combination of wound, embolism,

and the small number of probes used likely underestimated tree transpiration in

Casuarina. After the drought, soil moisture was much lower in the Casuarina stand

than in the other two stands. This may be an indication that the soil under the

Casuarina canopy is hydrophobic and/or that surface runoff occurs during a large

percentage of the rainfall events, as was shown to happen in stands dominated by

Eucalyptus robusta and Acacia confusa in Honouliuli, and in an area dominated by

the grass Tricachne insularis bordering the preserve (Nagel 2003). In support of this

hypothesis, high runoff was estimated in the Casuarina stand using a water balance

model (Chapter 4). Another possibility is that interception of throughfall by the litter

48

layer is significant, but ET estimates for this stand (Chapter 4) were very low,

suggesting that runoff is a stronger factor influencing soil moisture than ET. Poor

water penetration in soils under Casuarina could explain the preferential use by this

species of shallow water for transpiration as indicated by the isotope and VWC data.

The advantages of detecting the vertical patterns of water uptake using the

natural abundance of isotopes in xylem and soil water during a dry period are that in

this extreme situation (1) it is more likely to show a difference in oD values between

surface and deeper layers of the soil, and (2) plants are likely to be taking water from

the deepest moist layers of soil that their roots reach. During a long dry period,

preferential evaporation oflighter hydrogen causes an enrichment of deuterium at the

soil surface (Barnes and Allison 1984, Jackson et al. 1995), resulting in a steep

gradient between shallower and deeper soil layers such as the isotopic profiles

obtained for the Eucalyptus and Casuarina stands. In contrast, the profile of oD in

the soil of the Fraxinus stand did not follow this pattern. The lack of a steep isotopic

gradient in the soil of the Fraxinus stand may be explained by low evaporation at the

soil surface due to the dense understory and high LAI, or by a possible redistribution

of water between shallow and deep soil layers by the plants. The redistribution of

water among soil layers with different water potentials (Caldwell and Richards 1989,

Burgess et al. 2001) may create a mixing of the isotopic signature of the water in the

soil (Burgess et al. 2000).

Based on the natural abundance of hydrogen isotopes in the xylem and soil

water, depth of water uptake in the Eucalyptus and Casuarina stands was estimated as

between 0 and 40 cm, whereas in the Fraxinus stand it was estimated as deeper than

49

75 cm. Actually, VWC was lowest at a depth of 30-45 cm in the Eucalyptus stand

both in the wet and in the dry seasons (Fig. 2.3), and the comparison with moisture in

different soil depths did not yield very clear information, with one tree probably

drawing water from 0-30 cm and the others possibly from soil deeper than 90 cm

(Table 2.7). As the sapwood in Eucalyptus tends to be narrow, it is possible that the

samples taken for the isotope analyses included part of the heartwood. If heartwood

oD values were similar to sapwood values (as found by Thombum et al. 1993), the

mixture would not affect the estimate of depth of water uptake. However, if

heartwood oD values were less negative than sapwood values, as observed by White

et al. (1985) in a dry site in New York, USA, then the mixture of the two would cause

an underestimation of the depth of water uptake. So, it is possible that Eucalyptus

was drawing water from deeper layers of the soil (down to 60 cm) than the isotope

measurements indicated.

It is important to note that soil water potential was not measured in the sites

studied, thus soil water content may not be the same as soil water availability.

Because of the lack of these data, comparisons across sites and across depths within a

site should be done with caution. In the Fraxinus stand, VWC was apparently highest

in the deepest soil layer measured (60-90 cm). Trees that can tap water from that

layer have access to more moisture than is available at the surface during the dry

season (Fig. 2.3). By accessing a deeper soil profile, Fraxinus may have more access

to water during the dry season than the other two species. The deciduousness of

Fraxinus is probably not related to drought as this species usually loses its leaves

during wet months (November - January) in Hawaii (Chapter 3, Harrington and Ewel

50

1997). However, Fraxinus trees lost their leaves by the end of the long dry period

observed and started recovering LAI when rainfall resumed. Valentini et al. (1992)

found that deciduous species in Mediterranean climate tended to access deeper water

and be less water-use efficient than evergreen species. In contrast, Jackson et al.

(1995) found that deciduous species had shallower roots than evergreen species in a

lowland tropical forest of seasonal rainfall regime, and that water use efficiency was

not correlated to root depth. Fraxinus was shown to draw water from deep soil but

did not exhibit higher water use than the other species in this study. Because the soil

in Honouliuli is generally shallow, it may be possible that Fraxinus trees were

drawing water from the regolith. This happens especially in forests lying over thin

soils (e.g., Rose et al. 2003). It is likely that the soil moisture probes penetrated into

the regolith during installation, as the basaltic substrate consists of very porous, easily

penetrated rocks.

The isotope data indicated that Casuarina trees could be drawing water from

between 0 and 40 cm. However, the moisture gradient in the soil profile (Fig. 2.2)

and the lack of correlation between sap flow and VWC suggest that most trees might

be drawing water from very close to the surface. This agrees with field observations

that Casuarina trees form a thick root mat on top of the soil. In contrast with the

findings ofMeinzer et al. (1999), the variation found in the 8D values among

Casuarina trees was not due to plant size. The trees measured for xylem water 8D

ranged from 6 to 23 cm DBH, which are smaller than the trees studied by Meinzer et

al. (1999), but reflects the range of most of Casuarina trees in the stand (up to 36 cm

51

DBH). With the exception of one tree (DBH = 9.5 cm), the Casuarina trees

measured seem to consistently tap water from shallow soil.

2.6. Conclusions

The long drought resulted in a large reduction in soil moisture and LAI in all

three forest stands studied. These reductions caused a drastic decrease in

transpiration, approaching zero, in all three species. After rainfall resumed, Fraxinus

and Eucalyptus trees increased transpiration levels, but Casuarina did not. Sap flow

after the end of the drought, as a function of basal area, was not significantly different

among the species studied. However, the small diameter of Casuarina trees resulted

in very low transpiration rates of this species, and probably of the stand. Specific

stand characteristics contributed to the speed and magnitude of the decline and

recovery of transpiration. The Fraxinus stand had deep roots and high soil moisture,

and recovered LAI promptly after the end of the drought. The Eucalyptus stand had

relatively deep roots and high soil moisture, but had a very slow recovery of LAI in

relation to the other stands. The Casuarina stand, on the other hand, exhibited

shallow roots and very low soil moisture, but its LAI recovered relatively fast. High

radial sap flow variation was observed and might have resulted in a large error of the

transpiration estimates due to the small number of probes per tree and of trees

measured.

52

2.7. References

Andrade, J.L., F.C. Meinzer, G. Goldstein, N.M. Holbrook, J. Cavelier, P. Jackson,

and K. Silvera. 1998. Regulation of water flux through trunks, branches, and

leaves in trees of a lowland tropical forest. Oecologia. 115: 463-471.

Barnes, C.J. and G.B. Allison. 1984. The distribution of deuterium and 180 in dry

soils. 3. Theory for non-isothermal water movement. Journal ofHydrology 74:

119-135.

Bucci, S.1., G. Goldstein, F.C. Meinzer, A. Franco, P. Campanello, and F. Scholz. In

press. Mechanisms contributing to seasonal homeostasis of minimum leaf water

potential and predawn disequilibrium between soil and plant water potential in

Neotropical savanna trees. Trees.

Burgess, S.S.O., M.A. Adams, N.C. Turner, and B. Ward. 2000. Characterisation of

hydrogen isotope profiles in an agroforestry system: implications for tracing water

sources of trees. Agricultural Water Management 45(3):229-241.

Burgess, S.S.O., Adams M.A., Turner N.C., White, D.A., and Ong, C.K. 2001. Tree

roots: conduits for deep recharge of soil. Oecologia 126, 158-165.

Calder, LR. 1998. Water use by forests, limits and controls. Tree Physiology 18: 625

631.

Caldwell, M.M., and Richards, IH. 1989. Hydraulic lift: water efflux from upper

roots improves effectiveness of water uptake by deep roots. Oecologia 79: 1-5.

Clearwater, M.J., F.C. Meinzer, J.L. Andrade, G. Goldstein, and N. M. Holbrook.

1999. Potential errors in measurement of non-uniform sap flow using heat

dissipation probes. Tree Physiology 19(10): 681.

David, T.S., M.L Ferreira, 1.S. David, and 1.S. Pereira. 1997. Transpiration from a

mature Eucalyptus globules plantation in Portugal during a spring-summer period

of progressively higher water deficit. Oecologia 110: 153-159.

Ford, C.R., M.A. McGuire, R.J. Mitchell, and R.O. Teskey. 2004. Assessing variation

in the radial profile of sap flux density in Pinus species and its effect on daily

water use. Tree Physiology 24: 241-249.

53

Galindo-Jaimes, L., M. Gonzalez-Espinosa, P. Quintana-Ascencio, and L. Garcia

Barrios. 2002. Tree composition and structure in disturbed stands with varying

dominance by Pinus spp. in the highlands ofChiapas, Mexico. Plant Ecology 162:

259-272.

Giambelluca, T.W., M.A. Nullet, and T.A. Schroeder. 1986. Rainfall Atlas of Hawaii.


Granier, A. 1985. Dne nouvell methode pour la mesure du flus de seve brute dans Ie




Harrington, R.A., and JJ. Ewel. 1997. Invasibility of tree plantations by native and


153-162.

Hatton, TJ., SJ. Moore, and P. H. Reece. 1995. Estimating stand transpiration in a

Eucalyptus polpunea woodland with the heat pulse method: measurement errors

and sampling strategies. Tree Physiology 15: 219-227.

Hatton, T., P. Reece, P. Taylor, and K. McEwan. 1998. Does leaf water efficiency


536.

Hunt, M.A. and C.L. Beadle. 1998. Whole-tree transpiration and water-use



Jackson, P.C., J. Cavelier, G. Goldstein, F.C. Meinzer, and N.M. Holbrook. 1995.

Partitioning of water resources among plants of a lowland tropical forest.

Oecologia 101: 197-203.

Jackson, P.C., F.C. Meinzer, M. Bustamante, G. Goldstein, A. Franco, P.W. Rundel,

L. Caldas, E. Igler, and F. Causin. 1999. Partitioning of soil water among tree

species in a Brazilian Cerrado ecosystem. Tree Physiology 19: 717-724.

54

James, S. A., M. J. Clearwater, F.C. Meinzer, and G. Goldstein. 2002. Heat

dissipation sensors of variable length for the measurement of sap flow in tree with

deep sapwood. Tree Physiology 22: 277-283.

Lopez-Serrano, F. R., T. Landete-Castillejos, J. Martinez-Millan, and A. del Cerro



Meinzer, F. c., J. H. Fownes, and R. A. Harrington. 1996. Growth indices and

stomatal control of transpiration in Acacia koa stands planted at different

densities. Tree Physiology 16: 607-615.

Meinzer, F.C., J.L. Andrade, G. Goldstein, N.M. Holbrook, J. Cavelier, and S.J.

Wright. 1999. Partitioning of soil water among canopy trees in a seasonally dry

tropical forest. Oecologia 121: 293-301.

Meinzer, F.C., G. Goldstein, and J.L. Andrade. 2001. Regulation of water flux

through tropical forest canopy trees: Do universal rules apply? Tree Physiology

21: 19-26.

Morris, J., L. Mann, and J. Collopy. 1998. Transpiration and canopy conductance in a


555.

Nadezhdina, N., J. Cermak, and R. Ceulemans. 2002. Radial patterns of sap flow in

woody stems of dominant and understory species: scaling errors associated with

positioning of sensors. Tree Physiology 22: 907-918.


hydrologic properties within the Honouliuli Preserve, Oahu, Hawaii. Master's


Oren, R., N. Phillips, B. E. Ewers, D. E. Pataki, and J. P. Megonigal. 1999. Sap flux

scaled transpiration responses to light, vapor pressure deficit, and leaf area

reduction in a flooded Taxodium distichum forest. Tree Physiology 19(6): 337

347.

55

Rose, K. L., R C. Graham, and D. R Parker. 2003. Water source utilization by Pinus

jeffreyi and Arctostaphylos patula on thin soils over bedrock. Oecologia 134: 46

54.

Thombum, PJ., G.R. Walker, and J.P. BruneI. 1993. Extraction of water from

Eucalyptus trees for analysis of deuterium and oxygen-I 8: laboratory and field

techniques. Plant, Cell and Environment 16: 269-277.

Topp, G.C., J.L. Davis, and A.P. Annan. 1980. Electromagnetic determination of soil

water content: measurement in coaxial transmission lines. Water Resources

Research 16(3): 574-582.

Topp, G. C., and J. L. Davis. 1985. Measurement of soil water content using Time

Domain Reflectometry (TDR): A field evaluation. Soil Science Society of

America Journal 49: 19-24.

Valentini, R, G.E. Scarascia Mugnozza, and J.R Ehleringer. 1992. Hydrogen and

carbon isotope ratios of selected species of a Mediterranean macchia ecosystem.

Functional Ecology 6: 627-631.

White, J.W.c., E.R Cook, J.R Lawrence and W.S. Broecker. 1985. The D/H ratios

of sap in trees: implications for water sources and tree ring D/H ratios.


Wolf, J. 1998. Species composition and structure of the woody vegetation of the

Middle Casamance region (Senegal). Forest Ecology and Management 111: 249

264.

56

Table 2.1 - Characteristics of the stands studied at the southern section of the

Honouliuli Preserve, Oahu, Hawaii, as of 1998.

Dominant species

Eucalyptus robusta

Code"

3091

Elevation Area

(m) (ha)

540 0.80

Basal areab

(m2 ha-I)

Tree densityb

(trees ha-I)

Volunteer treesb,c

(trees ha- I)

363

Casuarina glauca

Fraxinus uhdei

540 25.7 3,238 III........................................................... . ~ . .

3095 460 0.52 36.0 1,044 560

corresponds to the identification of the stand given by the State of Hawaii at the time of

planting. The C. glauca stand was not identified through the plantation maps.

b Basal area and tree density were estimated based on trees with diameter at 1.3 m (DBH) z 5 cm (all

species combined).

C Volunteer trees are the trees that do not belong to the same species as the original planted trees.

d Data from Garrison (2003).

Table 2.2 - Number of water samples collected from trees and from each of three soil

pits (SI, S2, S3) in stands dominated by Casuarina glauca, Eucalyptus robusta or

Fraxinus uhdei.

Soil depth (cm) SI 82 S3

5-20 4 3 4

C. glauca stand 21-40 2 3 2

14 trees 55-81 2 2 1

100-125 3

5-10 2 2 2

E. robusta stand 15-20 2 1 2

11 trees 21-40 2 3 2

45-90 1 5 1

5-10 2 2 2F. uhdei stand

15-30 2 3 25 trees

40-75 4

57

Table 2.3 - Depth of sapwood and of the sap flow sensors installed in trees in

Honouliuli.

SpeciesOBH Sapwood depth Sensor depth in sapwood(em) (em) (em)8.4 4.2 0.5-1.514.7 7.3 1_2a 3_4a,b 5_6a

C. glauca17.3 8.5 6-718.1 8.6 4-529.2 13.9 9-1033.1 15.2 1-2 4-57.5 2.3 0.5-1.512.3 5.5 1-2 3-4

E. robusta21.4 5.5 1-227 5.5 0_3*a,b 1_2b 4_5b 7_8a,b

40.1 3.9 1_2a,b 4_5a,b

89.5 2.5 0_3*a,b 1_2b 2_3a

9.9 4.9 0_3*a,b

F. uhdei 15.1 6.7 0_3*a,b 0.5-1.5a 1_2a 4_5a,b

45.1 21.5 4_5a,b 9_10a

a, b different sides of the trunk* Dynamax probes

Table 2.4 - Sap flow (kg d-1) for the trees studied. The lower panel indicates the dry

and wet periods.

Species

C. glauca

E. robusta

F uhdei

OBH(em)

8.414.717.318.129.2

33.17.512.321.427

40.189.59.915.1

45.1

June2000

33.9 ± 13.5

125±24.1

98.6 ± 25.8

Sept2000

0.9 ± 0.55.6± 2.07.6 ± 0.15.9± 3.0

27.8 ± 4.8

Mean sap flow ± SO (kg d- I)

May-June July-Oct2001 2001

7.0 ± 3.1

0.5 ± 0.21.1 ± 0.40.9 ± 0.4

5.4 ± 3.1

3.5 ± 1.8

Nov-Dec2001

1.0 ± 0.3

5.8 ± 1.30.2 ± 0.18.0 ± 3.5

5.5 ± 3.010.8±9.5

3.9 ± 1.639.8 ± 22.6

2.8 ± 0.8

Jan-Mar2002

0.4 ± 0.2

1.1±0.5

2.9± 0.7

2.7 ± 1.2

5.3 ± 2.93.3 ± 2.214.4 ± 8.3

7.3 ± 2.963.8 ± 29.6

2.6 ± 0.45.3 ± 2.2

17.3 ± 8.2

-------------------------------Ory-----------------------------

58

Table 2.5 - Equations obtained from multiple regression comparing transpiration (T,

in kg d-1) with air saturation deficit (ASD, in kPa) and volumetric water content

(VWC, in %) in different cumulative depths of the soil for F. uhdei trees. The star (*)

identifies the relationships significant at a = 0.05.

DBH (em) Soil depth (em) equation r2 p

0-15 TI = -0.22 + 3.69 ASD + 0.0298 VWCO_15 0.72 0.146

0-30 T I = -0.498 + 3.62 ASD + 0.0352 VWCO_30 0.81 0.083

9.9 0-45 TI = -0.184 + 3.41 ASD + 0.0292 VWCO-45 0.81 0.085

0-60 TI = -0.152 + 3.37 ASD + 0.0295 VWCO_60 0.78 0.104

0-90 TI = -0.47 + 3.42 ASD + 0.0351 VWCO-90 0.77 0.113

0-15 T2 = 152 - 236 ASD + 0.17 SF2 VWCO_15 0.21 0.558

0-30 T2 = 201 - 217 ASD - 1.76 VWCO-30 0.24 0.498

15.1 0-45 T2 = 187 - 214 ASD - 1.39 VWCO_45 0.24 0.508

0-60 T2 = 188 - 214 ASD - 1.46 VWCO_60 0.23 0.511

0-90 T2 = 232 - 197 ASD - 2.92 VWCO_90 0.29 0.431

0-15 T3 = -41.0 + 48.4 ASD + 0.927 VWCO_15 0.54 0.068

0-30 * T3 = -47.3 + 51.3 ASD + 0.955 VWCO_30 0.71 0.013

45.1 0-45 * T3 = -47.8 + 51.5 ASD + 0.972 VWCO_45 0.79 0.004

0-60 * T3 = -49.7 + 53.6 ASD + 1.01 VWCO_60 0.78 0.005

0-90 * T3 = -50.5 + 53.9 ASD + 0.940 VWCO_90 0.74 0.008

59


in kg d- l) with air saturation deficit (ASD, in kPa) and volumetric water content

(VWC, in %) in different cumulative depths ofthe soil for C. glauca trees.

DBH(em) Soil depth (em) equation [2 p

0-15 T1 = 1.45 + 6.16 ASD - 0.041 VWCO_J5 0.33 0.366

0-30 TJ = 1.81 + 5.90 ASD - 0.046 VWCO-30 0.34 0.359

33.1 0-45 T1 = 2.14 + 5.62 ASD - 0.058 VWCO-45 0.34 0.348

0-60 T1 = 2.19 + 5.58 ASD - 0.056 VWCO-60 0.35 0.342

0-90 T1 = 2.66 + 5.19 ASD - 0.066 VWCO_90 0.37 0.319

0-15 T2 = -0.81 + 4.41 ASD - 0.055 VWCO_15 0.44 0.748

0-30 T2 = -l.l5 + 4.13 ASD - 0.010 VWCO_30 0.41 0.765

14.7 0-45 T2 = -1.06 + 4.17 ASD - 0.017 VWCO_45 0.42 0.762

0-60 T2 = -1.00 + 4.34 ASD - 0.023 VWCO_60 0.43 0.755

0-90 T2 = -0.94 + 4.34 ASD - 0.023 VWCO_90 0.43 0.755

60


in kg dol) with air saturation deficit (ASD, in kPa) and volumetric water content

(VWC, in %) in different cumulative depths of the soil for Eucalyptus trees. The star

(*) identifies the relationships significant at a = 0.05.

DBH(cm) Soil depth (em) equation r2 p

0-15 T2 = 29.9 - 26.5 ASD - 0.347 VWCO-15 0.42 0.253

0-30 T2 = 29.9 - 25.8 ASD - 0.350 VWCO-30 0.3 0.409

12.3 0-45 T2 = 31.9 - 28.6 ASD - 0.395 VWCO-45 0.28 0.441

0-60 T2 = 30.2 - 26.6 ASD - 0.370 VWCO_60 0.22 0.530

0-90 T2 = 29.9 - 26.4 ASD - 0.362 VWCO-90 0.2 0.566

0-15 * T3 = 12.0 - 3.25 ASD - 0.253 VWCO_15 0.82 0.014

0-30 * T3 = 11.5 - 2.2 ASD - 0.249 VWCO-30 0.71 0.04421.4

0-45 T3 = 11.5 - 2.3 ASD - 0.264 VWCO-45 0.69 0.055

0-60 T3 = 10.5 - 1.1 ASD - 0.250 VWCO-60 0.65 0.073

0-90 T3 = 10.4 - 1.0 ASD - 0.246 VWCO-90 0.63 0.083

0-15 T4 = 9.8 + 3.6 ASD - 0.027 VWCO_15 0 0.987

0-30 T4 = 2.2 + 13.0 ASD + 0.073 VWCO-30 0 0.97827

0-45 T4 = -7.5 + 25.2 ASD + 0.211 VWCO-45 0.02 0.916

0-60 T4 = -14.5 + 34.0 ASD + 0.308 VWCO-60 0.05 0.839

0-90 T4 = -16.7 + 36.8 ASD + 0.335 VWCO_90 0.06 0.818

0-15 Ts = 10.7 - 13.3 ASD + 0.085 VWCO_15 0.42 0.255

0-30 Ts = 5.3 - 6.7 ASD + 0.155 VWCO-30 0.51 0.16440.1

0-45 Ts = 3.6 - 4.6 ASD + 0.186 VWCO_45 0.54 0.140

0-60 Ts = 2.4 - 3.0 ASD + 0.204 VWCO_60 0.58 0.117

0-90 T5 = 1.3 - 1.5 ASD + 0.216 VWCO-90 0.6 0.103

0-15 T6 = 134 - 123 ASD - 0.68 VWCO_1S 0.07 0.837

0-30 T6 = 78 - 52 ASD + 0.03 VWCO_30 0.03 0.935

89.5 0-45 T6 = 59 - 29 ASD + 0.28 VWCO_45 0.03 0.924

0-60 T6 = 40 - 4 ASD + 0.55 VWCO_60 0.04 0.893

0-90 T6 = 27 + 12 ASD + 0.71 VWCO_90 0.06 0.867

61

20012000

- .. - near C. glauca,-----r--------.,.---1 near F. uhdei and E. robusta !----r----;180

160 1999

140

-120E5100

~ 80com

60....

40

20

0

A 0 0 F A J A 0 0 F A J A 0 0 F A J A 0 0 F

Figure 2.1 - Monthly rainfall from August 1998 to March 2002 near the stands

studied.

62

Casuarina glauca

·15

E-3G-00

~

.c 45-a.Gl ~o0

-75

-905956

Eucalyptus robusta 53504744

413835

a. 32Gl0 29

26232017

Fraxinus uhdei 141185

30-May-01 7-Sep-01 16-Dec-01 26-Mar-01

Figure 2.2 - Soil moisture of the three stands studied between May 19,2001 and April

7,2002. The volumetric moisture content ranged from 5% (white) to 60% (black).

63

0

F. uhdei10

20

30

40

50

60

70

0

E. robusta10

,..... 20E~ 30.c:......a. 40 -0-- dry season(])

-- wet season"050

'0(/) 60

70

0

C. glauca10

20

30

40

50

60

70

800 10 20 30 40 50 60

VWC (%)

Figure 2.3 - Soil volumetric water content (VWC, in %) in the dry season (Mean

VWC of August to October 2001) and in the wet season (mean VWC of January and

February 2002) for stands dominated by Fraxinus uhdei (top), Eucalyptus robusta

(middle) and Casuarina glauca (bottom) in the Honouliuli Preserve. Bars represent

standard errors. Error bars are smaller than the symbols in the dry season.

64

0

- -20E(.) -40.......-

..c...... -60a.(J)

"'0 -80

-100

& && && & ~& && & ~AU.'"

I • :I • If---e--I

~f---e--j

~ I-e-I

•~ ~

• soil water • soil water • soil water& F. uhdei & E. robusta & C. glauca

•-120-70 -60 -50 -40 -30 -20 -10 o -60 -50 -40 -30 -20 -10

80 (%0)

o -60 -50 -40 -30 -20 -1 0 o

Figure 2.4 - Patterns of water uptake by roots of Fraxinus uhdei (left), Eucalyptus robusta (center) and Casuarina glauca (right) as

indicated by the hydrogen isotope ratio (oD). The triangles above the line of the surface are the values found in trees (n = 5 to 14 per

stand). Bars represent standard errors of the mean of up to three soil profiles.

65

160

140

120

E 100.s]! 80

c 60.~

40

20

0

3

NE

N 2.s«...J

• near C. gJauca stand- --A- - near F. uhdei and E. robusta stands

/'

/

0 ->-- C. gJauca stand---{}- F. uhdei stand

40---.- E. robusta stand

;R 30~

0

~ 20

10

0

h, 10N

E..9

~ 5(f)

->-- C. gJauca---{}- F. uhdei---.- E. robusta

O-'------~-'---..-----==='---,---=~----'-~--"---~-~---'

01-Apr-01 01-Jun-01 01-Aug-01 01-0ct-01 01-Dec-01 01-Feb-02 01-Apr-02

Figure 2.5 - Rainfall, leaf area index (LAI), volumetric water content (VWC) ofthe

top 15 cm of the soil profile, and sap flux density (SFD) of trees in stands dominated

by Casuarina glauca, Fraxinus uhdei or Eucalyptus robusta in Honouliuli.

66

<> C. glaucao F. uhdei... E. robusta-- Meinzer et al. 2001

0.16

0.14

0.12

0.10.--..

N

E 0.08'-"'

<{til

0.06

0.04

0.02

0.00

0 20 40 60 80 100 120 140

DBH (em)

Figure 2.6 - Sapwood area (As) in trees of different DBH ofthe three species studied

in Honouliuli. The curve shows the relationship obtained by Meinzer et al. (2001) for

forest canopy tree species in Panama.

67

1.5 r.============::;-------~

me..~......;g 1.0Q)

"0Co~

~ 0.5~

ml/)

- January 15, 2002- March 22, 2002

-1-2em........ 3-4em

---5-6em

0.0

E. robusta -- 1 - 2 em (a)25 1- 2 em (b)

--- 4 - 5 em (b)

20

15

-~'l/) 10

'i"E 5-9:;: 00

'+= F. uhdei - 0.5-1.5em0- 25m .... 1-2eml/)

---4-5em20

15

10-~'l/)

5N

E-9 0

:;: 25C. glauca

0'+=0-m 20l/)

15

10

5

o 300 600 900 1200 1500 1800 2100 2400

time

Figure 2.7 - Diurnal patterns of air saturation deficit (ASD) and sap flow in different

depths of the sapwood for 15 January 2002 (Eucalyptus Tobusta, DBH = 40.1 em)

and 22 March 2002 (Fraxinus uhdei and Casuarina glauca, DBH = 15.1 and 14.7 em,

respectively). Letters a and b represent different sides of the trunk.

68

4,------------------------,

February 2002

3

5 6

--<>- C. glauca--0-- F. uhdei~ E. robusta

......------§

2

..-...-

I(/)

N

fI 1E0>---->-.......'00C 0a.>

7 March 2002"'0x::J

i:i= 60-m(/)

5

4

3

2

} -10

0 2 3 4

sapwood depth (em)

Figure 2.8 - Sap flux density in the sapwood profile for one tree each of Casuarina

glauca (DBH = 14.7 cm), Fraxinus uhdei (DBH = 15.1 cm), and Eucalyptus robusta

(DBH = 40.1 cm) for February (top) and March (bottom) 2002. Each symbol

represents the mean sap flux density at each depth (each symbol is plotted in the

middle ofa l-cm length measurement area), estimated based on the measurement of

one probe per depth on the same side of each tree.

69

30

0 C. glauca 1= 2.03 + 73.1x2

25 ... E. robusta =0.5 P < 0.016

0 F. uhdei

20...--

~0> 15~.......,3:0

ti= 100..co(/)

5

<> ~0

0.00 0.05 0.10 0.15

basal area (m2)

Figure 2.9 - Daily total sap flow plotted against basal area for Casuarina glauca,

Fraxinus uhdei, and Eucalyptus robusta for the period between January and March

2002. The large E. robusta tree (DBH = 89.5 cm) was much larger than the largest

tree plotted in this graph (DBH = 45.1 cm) and thus excluded from this analysis in

order not to bias the regression curve (done for all trees together).

70

16 180

June 00 R2 =0.75C. glauca

0 160I>. July-Sep 01 R2 =0.34 I>.

b 0 140 bOJ

12 OJ

6 1206

N 00 00 100 0

";l 0 N8 0 3:~ 0

0 80 00 I>. 0::

N 0 a.60 III

3: en0 4 I>.0:: 40a. I>. 0III I>.en 20

0 0F. uhdei

I July-Aug 01 R2 =0.65 II>.

12

8I>.

I>.

..--.. I>...... 4 I>.

I

"0 I>.

0> IYP~'-"

5 00 E. robusta

ii= 0 Sep 00 R2 =0.930- I>. I>. May 01 R2 =0.21<U(/) 12

0I>.

8 0/"Dol>.0

01>.1>. I>.4 0

I>. I>.

0 I>.

1.21.00.80.60.40.2

0+---,-----,------,------,------,---------10.0

ASD (kPa)

Figure 2.10 - Total daily sap flow as a function of mean daily air saturation deficit

(ASD) at the beginning (circles) and at the peak (triangles) of the drought for

representative trees of Casuarina glauca (DBH = 33.1 cm), Fraxinus uhdei (DBH =

45.1 cm), and Eucalyptus robusta (DBH = 27.0 cm).

71

3. Effects of Species Composition on the Rainfall Interception,

Stemflow and Throughfall of Mesic Forest Plantations of Hawai'i.

3.1. Abstract

Throughfall (TF) and stemflow (SF) were measured in three stands each of

four species (Eucalyptus robusta, Fraxinus uhdei, Casuarina glauca and Grevillea

robusta) for estimates of rainfall interception (E j) in the Honouliuli Preserve in

Hawaii. The objectives of this study were to quantify Ej, and to analyze the effect of

species composition on E j , TF, and SF in forest plantations. The data collected were

compared to variables describing forest structure to identify characteristics that might

be most useful in predicting changes in TF and SF, and, consequently, E j • Data on

rainfall, SF, TF, and leaf area index (LAI) were collected between August 1998 and

April 2002. Forest structure, characterized by tree density and basal area, was also

studied. Throughfall ranged between 70 and 91 %, SF between 0.6 and 4%, and Ej

between 4 and 29% of rainfall for the year of 1999. In general, TF and E j did not

differ among stands of different species composition. However, different TF patterns

were found between manual (7- to 14-day intervals) and automated (per event) data

collection. Stemflow was significantly higher in Fraxinus stands (mean of 3% of

rainfall) than in stands dominated by Grevillea (mean of 0.8% of rainfall). No single

forest characteristic seemed to regulate TF and SF variation. The characteristic that

most influenced TF and SF was tree density. With the exception of two Fraxinus

stands, the interaction between rainfall and tree density significantly influenced

stemflow variation across stands. Contrary to expectations, variation in LAI did not

72

result in direct responses of TF or SF across the forest stands. The results indicate

that SF is affected by forest composition and tree density. However, E j is not affected

by forest composition in the Honouliuli Preserve.

3.2. Introduction

The water cycle is a relatively well-studied ecosystem process in forests.

However, the underlying mechanisms that control water movement within

ecosystems are still understudied. Studies of rainfall interception (Ej), for example,

have moved from simple quantification to more process-based analyses (e.g., Rutter

et al. 1975), but later studies suggest that Ej models generated in temperate forests are

not always applicable to tropical forests (Shuttleworth 1988, Bruijnzeel 2000).

Variations in Ej - the component of the water cycle that, together with rainfall,

determines the amount of water reaching the soil - have been explained by differences

in forest structural characteristics such as basal area, cover, tree density (Rogerson

1967), and leaf area index (Zimmermann et al. 1999, van Dijk and Bruijnzeel 2001).

The higher the level of each of these characteristics, the higher the amount of water

intercepted by the canopy (Rogerson 1967), and consequently, the lower the amount

of water that reaches the ground.

Interception is calculated indirectly as rainfall minus the sum of throughfall

(rainfall under the canopy) and stemflow (water that flows down the stems).

Interception in continental areas has been reported to range between 11 and 39% of

rainfall in hardwood forests (Raich 1983, Pandit et al. 1991, Bruijnzeell997) and

from 7 to 28% in softwood plantations (Bruijnzeel 1997). Aboal et al. (1999) found

73

higher E j rates (30 to 41 % of rainfall) in a laurel forest on the Canary Islands.

Similarly, Ej in continental sites ranges from 10 to 34% of evapotranspiration (Jordan

and Heuveldop 1981; Leopoldo et al. 1982, 1995; Moreira et al. 1997), while

Hatkenscheid (2000) estimated that Ej contributes between 41 and 57% of the

evapotranspiration rates in forests in Jamaica, and Schellekens (2000) estimated

between 62 and 74% for forests in Puerto Rico. These observations have led to an

increased interest in expanding direct measurements of E j on tropical island

ecosystems (Schllekens et al. 1999, BruijnzeeI2000), but there is still very little

information on island forests with dry to mesic climate (Bruijnzeel 2000, Schllekens

et al. 2000).

The influence of species composition on Ej in forests has been assumed to be

minimal or non-significant (Helvey and Patrick 1965). However, more recent studies

indicate that throughfall and stemflow differ among species (e.g., Cape et al. 1991,

Sood et al. 1993, Crockford et al. 1996a, Bruiijnzeel1997, Holscher et al. 1998).

Canopy density and deciduousness (Cape et al. 1991), bark texture (Sood et al. 1993),

and leaf and branch slopes (van Elewijck 1989, Holscher et al. 1998) are species

characteristics that may influence throughfall and stemflow. Nonetheless, very few

studies (e.g., Cape et al. 1991) have compared E j among forests dominated by

different species in a replicated design.

In this chapter I quantify Ej in twelve tree plantations in Hawaii, analyze the

effect of species composition on E j , throughfall, and stemflow, and give evidence that

structural characteristics of the stands may not cause a direct response on throughfall

or stemflow in plantations of different species composition.

74

3.3. Methods


The Honouliuli Preserve (Fig. 1.1) is located on the eastern slope of the

southern Waianae Mountain Range on the island of Oahu, Hawaii. Mean annual

rainfall in this area ranges from 540 to 750 mm (Giambelluca et al. 1986). The native

forest was largely devastated by sandalwood extraction, fire, and grazing during the

19th century. During the first half of the 20th century, several non-native tree species

were planted in an effort to reduce erosion and to restore the watersheds to supply

water for agriculture (Asner et al. 1993). By 1960,4,200 ha of tree plantations

composed of stands of different species such as Eucalyptus spp., Casuarina spp.,

Fraxinus uhdei, Grevillea robusta, and Melaleuca quinquenervia covered nearly half

of the 9,120-hectare preserve (Nelson et al. 1968).

3.3.2. Species studied

I investigated the stemflow, throughfall, and interception in plantations

dominated by each of four species: Eucalyptus robusta, Casuarina glauca, Fraxinus

uhdei, and Grevillea robusta. The area planted with these species, plus other species

ofEucalyptus and Casuarina, account for 48% of the total area planted for

reforestation on Oahu before 1950. A description of these species plus of the

common volunteer species in these stands, Schinus terebinthifolius and Psidium

cattleianum, is in Section 1.7.2.

75


For the purpose of this research, the Honouliuli Preserve was subdivided into

three study sections, south, middle, and north, due to a North-South gradient in

rainfall. In each of these sections, one stand dominated by each of the planted species

was studied (Fig. 3.1). These stands were planted between 1927 and 1945. Data

were collected between August 1998 and April 2002. The stands dominated by

Grevillea were excluded from the study in September 1999 because several Grevillea

individuals in one of them showed symptoms of senescence. Table 1.1 summarizes

the characteristics of each stand.

Rainfall, stemflow, throughfall, and leaf area index (LAI) were measured in

each stand. Stemflow and throughfall were measured during 19 months in the

northern section (October 1998 to May 2000), 17 months in the middle section

(December 1998 to May 2000) and for almost three years in the southern section

(August 1998 to April 2000, and May 2001 to April 2002). Leaf area index was

measured in all stands for one year (June 1999 to July 2000) and in the three southern

stands for an additional ten months (June 2001 to March 2002).

Leaf area index (the ratio of leaf area per unit of ground area) was measured

with a LAI-2000 Plant Canopy Analyzer (LiCor, Lincoln, NE, USA) at 15 to 20

points along two or more transects every two months for one year in all stands, and

additionally every month for ten months in the stands of the southern section. The

points were 10m apart along transects set 15 m apart. The number of sample points

varied in each stand in order to get a standard error :s 5%. Measurements were taken

at approximately 50 cm from the ground (just above the height of the throughfall

76

collectors). Different methods to measure LAI were tested by Lopez-Serrano et al.

(2000), and the LAI-2000 was shown to give results similar to other methods.

Rainfall data were collected from three weather stations, one in each section,

and from two automated rainfall collectors near stands located further than 800 m

from a weather station (Fig. 3.1). The distance between the rainfall collectors and

each stemflow or throughfall collector within the forest canopies was approximately

between 100 and 500 m. Rainfall was measured with tipping bucket rain gauges

(Texas Electronics, Dallas, TX, USA) connected to dataloggers (21 X or CRlO,

Campbell Sci., Logan, UT, USA; or Hobo Event, Onset, MA, USA) recording data

each minute or whenever there was a tip. Events were arbitrarily separated by 3-hour

periods with no rain to allow for complete drying of the canopy.

Throughfall collectors consisted of a set of three troughs (each with projected

dimensions of 129.2 x 5.5 cm), which directed the water into a covered bucket. Each

set had a collection area of 0.2 m2 and stood 50 cm above the ground. Depending on

variation of preliminary data, three to nine collectors were placed randomly under the

canopy in each stand. The water collected in the buckets was measured every other

week for the first two years of the study (1998 - 2000) and additionally every week

for six months in 2001 in the stands on the southern section. For the 2001

measurements, approximately half of the collectors were automated with tipping

bucket gauges connected to dataloggers (Hobo Event, Onset, Pocasset, MA, USA),

collecting data for a total of eight months.

Stemflow was measured with spiral collars tightly fitted to the tree trunk that

channel water into a 4- to 30-liter collection bottle, or to a tipping bucket connected to

77

a datalogger (Hobo Event, Onset, Pocasset, MA, USA). Each collar was assembled

in the field by attaching one piece of Trimtex plastic archway L-bead to the tree trunk

with one nail at each extremity of the spiral and forming a canal by overlapping

another archway L-bead with the first one. The two L-beads were secured to each

other with metal twist ties. The archway L-bead is very flexible and can be adjusted

to make very good contact with the tree; caulking was also used to ensure complete

contact between the collar and the tree trunk. The canal was then covered with

aluminum tape (Shurtape #AF973, Hickory, NC, USA) to provide a smooth surface

for the water to flow down. These collectors were installed in four to eight trees in

each stand spanning the range of diameters found in a vegetation survey of trees ~ 5

cm DBH (diameter at 1.3 m height). The water collected in the bottles was measured

every two weeks in each stand for the first two years of the study and additionally

every week for six months. Sixteen stemflow collectors were automated for the last

eight months of the study in the stands of Eucalyptus, Casuarina and Fraxinus in the

southern section.

Interception was derived from measurements of rainfall, throughfall and

stemflow by subtracting the sum of throughfall and stemflow from rainfall for a given

period.

3.3.4. Statistical Analyses

Repeated measures ANOVA was used to assess differences in the throughfall

collected manually among stands within each section. As stands dominated by

Grevillea did not have data collected throughout the entire study period, the analyses

78

were divided in periods when all four species were measured and periods when data

were available for only three species. Automated data were analyzed using a one

way ANOVA, based on the average of the water collected in the buckets per stand for

each event. Missing automated data were replaced by estimates based on regression

curves relating existing data to rainfall for each bucket.

Regressions were done between rainfall and stemflow amount for trees in

different diameter classes. The regression per size classes permitted the scaling up of

the stemflow measured in each tree size class to the stand, and the conversion of

volume units to depth units for stemflow, based on the total area occupied by each

stand. All curves were forced through the origin.

A one-way ANOVA test was applied to the total throughfall, stemflow depth,

or interception of each stand in a one-year period for comparison among stands


Multiple regressions were used to identify the effect of stand basal area, tree

density, LAI, and rainfall (independent variables) on throughfall, stemflow, or

interception (dependent variables).

3.4. Results

3.4.1. Rainfall

In 1999, total rainfall was 690, 768, and 673 mm in the northern, middle, and

southern sections of the preserve, respectively. The distribution of the rainfall events,

both in terms of frequency and amount, was very similar among the three sections.

79

Events smaller than 0.6 mm constituted over 50% of all events within a year but

contributed less than 8% of the total volume of water, whereas the three largest events

alone contributed almost 30% ofthe total amount of rainfall (Fig. 3.2). A long

drought occurred in the southern section ofthe preserve between January 2000 and

November 2001, during which rainfall did not exceed 60 mm in any month (Fig.3.3).

3.4.2. Leafarea index

Fraxinus stands had higher LAI and larger seasonal changes than Eucalyptus or

Casuarina stands during the period between June 1999 and July 2000 (Fig. 3.4). Leaf

area index measurements were resumed in June 2001 for the stands on the southern

section of the preserve and continued until March 2002 (Fig. 3.5). In these stands,

pre-drought LAI values ranged from 2.4 to 3 for Casuarina, 3.1 to 4.8 for Fraxinus,

and 1.5 to 3.1 for Eucalyptus. Leaf area index reached its lowest values between

September and December 2001 (Fig. 3.5), the end of the long drought (Fig. 3.3).

Eucalyptus appears to have been affected the most by the drought, reaching LAI

values lower than 1, and having a slow recovery after rainfall increased, in November

2001. The LAI of the Fraxinus stands exhibited the fastest LAI increase after rainfall

restarted by increasing from 1 in October 2001 to 3.5 in March 2002 (Fig. 3.5).

3.4.3. Throughfall

Results for manually collected throughfall were compared using repeated

measures ANOVA to detect potential differences among stands dominated by

different species within each section of the preserve (Table 3.1). It was expected that

Fraxinus stands would have lower throughfall values due to higher LAI than the other

80

stands. However, the stand of Fraxinus had higher throughfall values than

Eucalyptus and Casuarina stands in the North section of the preserve and was not

significantly different in the other sections (Table 3.1). Throughfall was not different

between stands of Fraxinus and Grevillea in any instance.

The automated, or per-event, throughfall data were compared using one-way

ANOVA for the stands on the southern section (Table 3.2). Data from all buckets

were averaged per event in each stand. The stand dominated by Fraxinus exhibited

lower throughfall than the other stands for rainfall events :s 3 mm and for all events

analyzed together (Table 3.2). In these per-event analyses, Fraxinus had lower

throughfall than the other two stands in periods of high LAI and lower throughfall

than Eucalyptus in periods oflow LAI (Table 3.3). Throughfall was negatively

correlated with LAI within the stand dominated by Fraxinus, but not in the other

stands (Table 3.3). However, the relationship between LAI and throughfall was very

weak for the stands of the southern section, even for Fraxinus (Fig. 3.6).

Storage capacity (S) was calculated for each stand by plotting throughfall

collected in each bucket against rainfall for events 2: 2 mm, similar to the method

employed by Aboal et al. (1999). The estimated S was 0.7, 0.6, and 0 mm for stands

dominated by Eucalyptus, Fraxinus, and Casuarina, respectively. The S of the stand

dominated by Eucalyptus was significantly larger than the S of the stand dominated

by Casuarina (F = 5.69, P = 0.034).

81

3.4.4. Stemjlow

Stemflow was regressed against rainfall for each species, independent of the

stand where they were located, per class of diameter (5-10, 10-30, 30-50, and 50-80

cm DBH). The equations obtained from these regressions (Table 3.4) were applied to

all trees on the stand based on rainfall measured in the same period as throughfall.

Stemflow, as a function of rainfall, was higher for Fraxinus and Psidium cattleianum

(small tree present in the understory of Grevillea and Fraxinus plantations) trees than

for Eucalyptus, Casuarina, or Grevillea in any diameter class. Fraxinus stands had

higher stemflow than Grevillea stands in all sections (Fig. 3.7).

3.4.5. Interception

Interception derived from the throughfall and stemflow measurements ranged

from 4% of rainfall in the northern stand of Fraxinus to 32% in the southern stand of

Grevillea (Table 3.5). In 1999, throughfall ranged between 70 and 91% ofrainfall,

stemflow ranged between 0.7 and 3.9% of rainfall, and interception ranged between

32 and 197 mm, or 4 and 29% of rainfall (Table 3.6). No differences among stands

dominated by different species were detected in throughfall or interception. Stands

dominated by Fraxinus generated significantly more stemflow than stands dominated

by Grevillea (means of3.0 and 0.8% of rainfall, respectively, F = 4.39, p = 0.042).

No single variable, nor the interaction among them, explained throughfall

(Fig. 3.8) or interception in all stands. Trends can be observed within species, but no

conclusions can be drawn, as there are data for only three stands per species.

However, throughfall in Eucalyptus appears to be negatively correlated with tree

82

density and rainfall (Fig. 3.8a and 3.8d), and in Fraxinus positively correlated with

tree density (Fig. 3.9a).

Similarly, no single variable explained stemflow in all stands together (Fig.

3.9). When the Fraxinus stands in the middle and northern sections are excluded

from a multiple regression analysis, the interaction between rainfall and tree density

explains variations in stemflow across all other stands (stemflow = - 0.30 + 0.0006

density + 0.0012 rainfall, F = 10.34, P = 0.008).

3.5. Discussion

3.5.1. Through/all

Throughfall varied between 70 and 91 % of rainfall in the stands studied, in

the upper end of the range of results from other hardwood plantations in the tropics

and subtropics (57 to 90%; Bruijnzeel 1997). The values ofthroughfall for the

Eucalyptus robusta stands (76 to 86% of rainfall) were a little lower than those

reported for other Eucalyptus stands:s 12 years old (Lima 1976, Poore and Fries

1985, Bruijnzeel 1997), which ranged from 81 to 94% ofprecipitation.

Holscher et al. (1998) found that a 10-year old secondary forest dominated by

Phenakospermum guyanensis (an understory herb) had significantly lower throughfall

than a younger, more diverse secondary forest. Stemflow, on the other hand, was

substantial in both forests (38 and 23% of rainfall, respectively). In this study,

species composition did not account for among-stand differences in throughfall,

similar to the findings of Huber and Iroume (2001) for 29 research plots in Chile.

However, Fraxinus had significantly higher throughfall than the other stands in the

83

northern section of the preserve during manual data collection and lower throughfall

in the southern section during the automated measurements. These differences

between the manual and the automated data may be explained either by problems

involved in the manual collection or by the different scales of observation. Whereas

manual collections provide a reliable total amount of throughfall generated over

intervals, the mixing of events of different amounts and intensities in the same sample

collection may mask the relationship between throughfall and rainfall in each event.

Differences among stands are more obvious during small rainfall events, which

represent most of the events in a year. However, the large amount of water falling

during larger events may hide these differences. Annual variation in rainfall

distribution could also cause a change in the throughfall responses of stands

dominated by different species. Cape et al. (1991) found differences in throughfall

among stands ofPinus sylvestris and stands ofLarix decidua, Quercus petrea or

Alnus glutinosa in Britain, but some of these differences did not persist in multiple

years.

The differences between the manual and the automated data may have been

caused by the reduction in LAI following the drought that occurred in the southern

section of the Honouliuli Preserve. After the drought, when the stand dominated by

Eucalyptus had the lowest LAI values, throughfall was higher than in the other

stands. However, LAI did not explain throughfall variation within this stand (Table

3.3). The expected lower throughfall in Fraxinus stands, due to their higher LAI, was

only found in the data collected on an event basis. This might have also been caused

by a proportional increase in the number of small events during the drought, when

84

Fraxinus shows significantly lower throughfall than Eucalyptus or Casuarina (Table

3.2). Leaf area index was also shown to be an important factor in the throughfall

generated within stands of Fraxinus (Table 3.3).

The storage capacity (S) values obtained in the Eucalyptus and Fraxinus

stands are within the range of S values for other tree plantations (0.2 - 2 mm, Lima

1993). The differences found in the S values between the Eucalyptus and Casuarina

stands did not result in significant differences in throughfall. The low S found in

Casuarina may be explained by the shape and angle of its leaves. This species has

needle-like twigs, vertically oriented, which do not offer a large horizontal surface

area for water storage.

3.5.2. Stemjlow

With the exception of two stands ofFraxinus, my stemflow data were similar to

those found for lowland tropical forests where stemflow is commonly under 2% of

rainfall (Levia, Jr. and Frost 2003). However, stemflow in the Eucalyptus robusta

stands of Honouliuli (0.6 to 2.3% of rainfall) was lower than the values found for

other Eucalyptus plantations (4.2 to 8% ofrainfall, Lima 1976, Bruijnzeel 1997) or

for natural Eucalyptus forests (3.4 to 5.9% of rainfall, Crockford et al. 1996b). The

bark of Eucalyptus robusta is thicker and more absorbent than that of most other

species of Eucalyptus, probably contributing to the low stemflow found in this study.

Even though stemflow variability is usually higher than throughfall variability

(Zamoch et al. 2002), I was able to detect differences in stemflow among stands

dominated by different species more clearly than differences in throughfall. Stands

85

dominated by Fraxinus generated at least twice as much stemflow as stands

dominated by Grevillea. This could be explained not only by lower stemflow

generated by trees of similar diameter but also by the very low tree density in the

Grevillea stands compared to the Fraxinus stands. Huber and Iroume (2001) found

significant differences in stemflow between conifer and broadleaved forests in Chile,

however, they found lower stemflow in stands oflower tree density. In contrast with

their findings, neither throughfall nor stemflow in this study were positively

correlated with rainfall across stands, with the exception of stemflow in stands

dominated by Eucalyptus.

Even though stemflow does not seem to contribute much to the hydrological

cycle in most forests (Lima 1976, Crockford et al. 1996b, Bruijnzeel 1997, Levia, Jr.

and Frost 2003), in dry forests such as the ones in Honouliuli, this 1 to 5% of rainfall

water added to the system in a non-random fashion may allow species to compete

differently for water. Since the concentration of nutrients is higher in stemflow water

than in throughfall (Crockford et al. 1996a, 1996b), trees that produce higher

stemflow may be at an advantage both in terms of water and of nutrients. Stemflow

not only causes a spatial redistribution of water to the soil but also a heterogeneous

distribution of nutrients and pH, which may affect understory species composition

and distribution (Falkengren-Grerup 1989, Andersson 1990). Forest species

composition seems to affect the level at which this heterogeneity occurs due to the

differences in stemflow volume produced by different species (Mahendrappa 1990).

The high stemflow generated by P. cattleianum in Honouliuli, for example, may

86

cause a change in the hydrological and nutrient cycles of forests invaded by this

specIes.

3.5.3. Interception

The 1999 values for interception found in this study represent less than 10%

of the PE estimated by Giambelluca (1983) for the same area. With the exception of

the extremely low interception value found for the Fraxinus stand in the northern

section of the preserve, the interception rates found in this study are comparable to

the rates found in other plantations in the tropics and subtropics (Bruijnzeel 1997).

The interception rates between 13 and 22% in 1999 obtained for the Eucalyptus

stands are within the rates found for mature natural forests dominated by other

Eucalyptus species (10-24%, Lima 1993). There were no significant differences in

interception among stands dominated by different species. In this study, forest

diversity (based on the density of volunteer trees, Table 1.1) did not seem to affect

interception, in contrast with observations of Zhou et al. (2002) and Dunisch et al.

(2003). The low interception found for Fraxinus in the northern section of the

preserve seems to be explained by its high tree density, although the reason is not

clear. Interception in other Eucalyptus plantations has been reported to change with

age, varying from 12% of rainfall at six-year old plantations in India and Brazil

(BruijnzeeI1997) to a peak of between 23 and 38% of rainfall at 30 years old,

declining to between 21 to 35% at age of80, to between 15 and 27% at age of240

years old in natural forests (Haydon et al. 1996). The interception values found in

this study for Eucalyptus stands, approximately 70 years old, ranged from 13 to 22%

87

of rainfall, a little lower than modeled by Haydon et al. (1996) for natural eucalypt

forests.

Possible errors involved in the measurements may account for the patterns

seen in throughfall, stemflow, and, consequently, interception. Rainfall, for example,

was measured outside the stands. Even though the rainfall collectors were not at

large distances from the throughfall and stemflow collectors, the differences in the

topographic exposure between the stands and the rainfall collectors have probably an

effect on the rainfall catch by the canopy.

3.5.4. Effect offorest structure on throughfall and stemjlow

Even though no significant differences were found in throughfall and

interception among stands dominated by different species, Figures 3.8 and 3.9 show

that stands dominated by the same species showed consistent relationships between

throughfall or stemflow and some of their structural characteristics. Tree density, for

example, is the variable that best explained variations in throughfall and stemflow

among stands dominated by Eucalyptus and by Fraxinus. However, in Eucalyptus

throughfall decreased with increasing tree density, whereas it increased with

increasing tree density in Fraxinus. The differences in the aspect of the terrain of the

stands may have caused these contrasting responses. Rainfall was an important

variable in explaining variation in throughfall only in stands dominated by

Eucalyptus. Variations in stemflow also showed distinct relationships with structural

characteristics in the different stands studied. Stemflow was positively associated

with the interaction of rainfall and tree density for most stands (except for Fraxinus in

88

the middle and northern sections). Similarly, Huber and Iroume (2001) found a

strong influence of rainfall and tree density on stemflow; however, they found that

stemflow was negatively associated with tree density.

The comparison among stands dominated by the same species in this study

provides a different perspective on the previous evidence that certain forest structural

characteristics have universal effects on the components of rainfall interception (e.g.,

Hanchi and Rapp 1997, Park and Hattori 2002). Whereas throughfall and stemflow

in some species are related to structural characteristics of the stands, I found no single

variable that explained either throughfall or stemflow across all species. The variable

that best explained variation in stemflow among stands in almost all species was tree

density and this should be investigated further with a larger number of broad-leaved

species.

Leaf area index is one stand characteristic that has been suggested to influence

interception positively (e.g., Zimmermann et al. 1999, van Dijk and Bruijnzeel2001).

In this study, LAI influenced throughfall within a stand ofFraxinus, but it did not

explain the variations in throughfall among stands. LAI was not a good predictor of

interception for forests dominated by any of the species studied.

3.6. Conclusion

Based on the data collected in this study, throughfall and interception do not

seem to be affected consistently by forest species composition. However, stemflow

was significantly higher in forests dominated by Fraxinus than in forests dominated

by Grevillea, suggesting that changes in forest composition may have an effect on

this small but important input of water.

89

Throughfall and stemflow data from Honouliuli strongly indicate that no

forest characteristic alone governs these components of the water cycle. The

characteristic that most influenced throughfall and stemflow was tree density but only

for stemflow did it cause a significant response across almost all stands. On the other

hand, leaf area index, which is generally considered to influence throughfall and

stemflow positively, did not produce consistent responses from the stands. It was

also observed that the throughfall patterns in the stands studied varied according to

the temporal scale of measurements. Analysis of throughfall collected weekly- to 15

day intervals showed no differences among stands dominated by different species in

the southern section of the preserve. On the other hand, analyses on the data

collected in an event basis showed that throughfall was significantly lower in a stand

dominated by Fraxinus than in stands dominated by Casuarina or Eucalyptus. These

discrepancies suggest that the temporal scale of measurements is an important factor

to take into consideration in studies of rainfall partitioning in forests.

3.7. References



Meteorology 97: 73-86.

Andersson, T. 1990. Influence of stemflow and throughfall from common oak

(Quercus robur) on soil chemistry and vegetation patterns. Canadian Journal of

Forest Research 21: 917-924.


Honouliuli Preserve, The Nature Conservancy of Hawaii, Honolulu, HI, USA.

Bruijnzeel, L.A. 1997. Hydrology of forest plantations in the tropics. In:

Management of Soil, Nutrients and Water in Tropical Plantation Forests (E. K. S.

90

Nambiar, A. G. Brown, eds), ACIAR, CSIRO (Australia) and CIFOR

(Indonesia): 125-167.



Cape, J.N., A.H.F. Brown, S.M.C. Robertson, G. Howson, and 1.S. Paterson. 1991.



Crockford, R.H., D.P. Richardson, and R. Sageman. 1996a. Chemistry of rainfall,

throughfall and stemflow in a eucalypt forest and a pine plantation in south

eastern Australia: 2. Throughfall. Hydrological Processes 10: 13-24.

Crockford, R.ll., D.P. Richardson, and R. Sageman. 1996b. Chemistry of rainfall,


eastern Australia: 3. Stemflow and total inputs. Hydrological Processes 10: 25

42.

van Dijk, A.I.J.M., and L.A. Bruijnzeel. 2001. Modelling rainfall interception by

vegetation of variable density using an adapted analytical model. Part 1. Model

description. Journal of Hydrology 247: 230-238.

Diinisch, 0., M. Erbreich, and T. Eilers. 2003. Water balance and water potentials of

a monoculture and an enrichment plantation of Carapa guianensis Aubl. In the

Central Amazon. Forest Ecology and Management 172: 355-367.

van Elewijck, L. 1989. Influence ofleaf and branch slope on stemflow amount.

Catena 16:525-533.

Falkengren-Grerup, U. 1989. Effect of stemflow on beech fores soils and vegetation

in southern Sweden. Journal of Applied Ecology 26: 341-352.

Giambelluca, T.W. 1983. Water balance of the Pearl Harbor-Honolulu basin,

Hawai'i, 1946-1975. Water Resources Research Center, Technical Report No.

151, University of Hawaii at Manoa, Honolulu. HI, USA.



91

Hafkenscheid, R 2000. Hydrology and biogeochemistry of tropical montane rain

forests of contrasting stature in the Blue Mountains, Jamaica. Ph. D. dissertation,

Vrije Universiteit, The Netherlands, 302 pp.

Hanchi, A and M. Rapp. 1997. Stemflow determination in forest stands. Forest

Ecology and Management 97: 231-235.

Haydon, S.R, R.G. Benyon, and R. Lewis. 1996. Variation in sapwood area and

throughfall with forest age in mountain ash (Eucalyptus regnans F.Muell.).

Journal of Hydrology 187: 351-366.

Helvey, J.D., and J.H. Patric. 1965. Canopy and litter interception of rainfall by


Holscher, D., T.D. Sa, RF. Moller, M. Denich, and H. FoIster. 1998. Rainfall



Oecologia 114: 251-257.

Huber, A, and A Iroume. 2001. Variability of annual rainfall partitioning for

different sites and forest covers in Chile. Journal of Hydrology 248: 78-92.




evapotranspirac;ao de floresta amazonica de terra firme. Sup!. Acta Amazonica

12: 23-28.

Leopoldo, P.R, W.K. Franken, and N.A Villa Nova. 1995. Real evapotranspiration



Levia, Jr., D.F., and E.E. Frost. 2003. A review and evaluation of stemflow literature

in the hydrologic and biogeochemical cycles of forested and agricultural

ecosystems. Journal of Hydrology 274: 1-29.

Lima, W.P. 1976. Interceptac;ao da chuva em povoamentos de eucalipto e de pinheiro.

IPEF, Piracicaba 13:75-90.

92

Lima, W.P. 1993. Impacto Ambiental do Eucalipto. Editora da Universidade de Sao

Paulo, 301 pp.

Lopez-Serrano, F.R., T. Landete-Castillejos, J. Martinez-Millan, and A. del Cerro



Mahendrappa, M.K. 1990. Partitioning of rainwater and chemicals into throughfall

and stemflow in different forest stands. Forest Ecology and Management 30:65

72.

Moreira, M.Z., L. Sternberg, L. Martinelly, R. Victoria, E. Barbosa, L. Bonates, and



Nelson, R.E., W.H.C. Wong, Jr., H.L. Wick. 1968. Plantation timber on the Island of


Bulletin PSW-lO, 52 pp.


throughfall and stemflow in teak forest. Indian Journal ofForestry 14(4): 287

289.

Park, H-T. and S. Hattori. 2002. Applicability of stand structural characteristics to

stemflow modeling. Journal of Forest Research 7: 91-98.

Poore, M.E.D., and C. Fries. 1985. The Ecological Effects of Eucalyptus. Food and




Rogerson, T.L. 1967. Throughfall in pOle-sized loblolly pine as affected by stand



Rutter A.J., A.J. Morton, and P.C. Robins. 1975. A predictive model of rainfall

interception in forests. II. Generalization of the model and comparison with

observations in some coniferous and hardwood stands. Journal of Applied

Ecology 12: 367-380.

93

Schellekens, J. 2000. Hydrological processes in a humid tropical rain forest: A

combined experimental and modeling approach. PhD. Dissertation, Vrije

Universiteit, The Netherlands, 158 pp.



Puerto Rico. Water Resources Research 36(8):2183-2196.

Shuttleworth, W.1. 1988. Evaporation from Amazonian rain forest. Proceedings of the

Royal Society of London, Series B 233: 321-346.

Sood, V.K., R. Singh, and M. Bhatia. 1993. Throughfall, stemflow and canopy



Zarnoch, S.1., D.A. Abrahamson, and P.M. Dougherty. 2002. Sampling throughfall

and stemflow in young loblolly pine plantations. US Department of Agriculture

Forest Service, Research Paper SRS-27.

Zhou, G.Y., J.D. Morris, J.H. Yan, Z.Y. Yu, and S.L. Pengo 2002. Hydrological

impacts of reafforestation with eucalypts and indigenous species: a case study in

southern China. Forest Ecology and Management 167:209-222.

Zimmermann, L., C. Frtihauf, and Ch. Bernhofer. 1999. The role of interception in

the water budget of spruce stands in the Eastern Ore Mountains/Germany. Phys.

Chern. Earth (B) 24 (7): 809-812.

94

Table 3.1 - Comparison of manually collected throughfall among stands dominated

by different species between November 1998 and May 2000 for the North and South

sections, and between January 1999 and May 2000 for the Middle section. Repeated

measures ANOVA was used to compare throughfall among the stands in two

different analyses: one including all four species (4 spp) and another excluding

Grevillea (3 spp), which did not have any throughfall data after September 1999.

Median throughfall (in ml) of each stand is shown for comparison. Different letters

identify significantly different values (p < 0.05) in throughfall among columns of the

same row. (N = number of collection days, F = ratio of the variance in the sample,

and p = probability of F being larger than estimated)

Throughfall (ml)

Casuarina Eucalyptus Fraxinus Grevillea N F P

3 spp 1280a 1377a 2052b 44 9.36 0.014North

4 spp 1424a 1820a 2633b 2802b 25 6.11 0.018

3 spp 977 709 1250 32 4.54 0.063Middle

4spp 1803 1578 2243 2124 15 1.97 0.197

3 spp 815 934 848 40 1.90 0.230South

4 spp 935 1168 1038 1319 11 1.80 0.243

95

Table 3.2 - Results from the one-way analyses of variance comparing throughfall as a

proportion of rainfall in an event basis. Different letters (by row) indicate significant

differences among stands; no letter indicates that the values in the row are similar.

Data from all buckets were averaged per event in each stand. Storage capacity (S)

was estimated as 0.7,0.6, and 0 mm for the Eucalyptus, Fraxinus and Casuarina

stands, respectively.

Rainfall size Throughfall / Rainfall

(mm) Eucalyptus Fraxinus Casuarina F p

S-3 0.51 a 00406 0.52a 5.94 0.003

3.1 - 6 0.58 0.50 0.56 0.66 0.525

>6 0.62 0.56 0.65 1.61 0.208

all events 0.55a OA8b 0.56a,b 3.65 0.027

Table 3.3 - Throughfall as a proportion of rainfall during periods of high and low leaf

area index (LAI) in the stands of the southern section of the Honouliuli Preserve.

Values were compared using Student's two-sample t-test. Different letters in same

row indicate significant differences (p < 0.05) within stand.

High LAI LowLAI T p

Eucalyptus 0.53 0.59 -1.39 0.083

Fraxinus 0.34 a OA6 b -3.01 0.002

Casuarina 0.50 0.56 -0.84 0.200

96

Table 3.4 - Regression equations between rainfall (P, in mm) and stemflow (sf, in ml)

obtained for trees throughout the stands studied. Psidium cattleianum and Schinus

terebinthifolius are invasive trees in the understory of the tree plantations (N =

number of sampled intervals).

Species# Diameter

Regression equation N r2trees (cm)

p

2 5 -10 sf= -63 P + 3.4 p2 41 0.71 < 0.0001

Eucalyptus6 10-30 sf= 14.376 P + 6.4793 p2 _0.046 p3 123 0.62 < 0.0001

5 30- 50 sf= 101.2 P 74 0.32 < 0.0001

4 50- 80 sf= - 109.2 P + 10.532 p2 _0.0728 p3 87 0.49 < 0.0001

4 5 -10 sf= 191.9 P 88 0.58 < 0.0001

Fraxinus6 10 -30 sf= 255.4 P 135 0.44 < 0.0001

3 30-50 sf= 357.4 P 58 0.57 < 0.0001

2 50- 80 sf = - 46 P + 13.1 p2 23 0.59 0.0001

Casuarina6 5 -10 sf= 38.1 P 168 0.37 < 0.0001

11 10-30 sf= 183.8 P 312 0.67 < 0.0001

7 10 -30 sf= 81.522 P - 3.2996 p2 + 0.0456 p3 99 0.56 < 0.0001

Grevillea 6 30-50 sf= 0.2103 P + 2.6242 p2 _0.0147 p3 85 0.43 < 0.0001

2 50- 80 sf= 33.103 P - 2.1256 p2 + 0.0755 p3 28 0.99 < 0.0001

4 5 -10 sf= 129.9 P 82 0.73 < 0.0001Psidium

2 10 -30 sf= 236.1 P 24 0.45 0.0003

Schinus 3 10-30 sf= 69.6 P - 0.3 p2 57 0.57 < 0.0001

97

Table 3.5 - Throughfall (TF), stemflow (SF), and interception (ED, all shown as

percentage of rainfall, based on manual measurements on stands dominated by

different species.

measurement Rainfall Eucalyptus Casuarina Fraxinus Grevillea

period (mm)TF SF E; TF SF E; TF SF E; TF SF Ej

Aug 98 to Apr 00 879 78.1 1.2 20.7 79.4 2.4 18.2 75.6 1.5 22.9 70.0 0.7 29.3South

May to Dec 01 217 71.4 1.1 27.5 78.3 2.4 19.3 69.7 1.2 29.1 67.0 0.7 32.3

Middle Dec 98 to May 00 841 83.6 0.5 15.9 82.2 2.0 15.8 80.6 3.5 15.9 76.2 0.9 22.9

North Oct 98 to May 00 1047 77.5 2.1 20.4 76.5 1.9 21.6 92.2 3.9 3.9 88.1 0.7 11.2

Table 3.6 - Rainfall (P), throughfall (TF), stemflow (SF), and interception (Ej) on

stands dominated by different species in the Honouliuli Preserve from January to

December 1999. Mean standard error (SE) found for throughfall events in 1999 are

shown as percentage of throughfall for each stand.

TFP(mm) SF (% P) Ej (% P)

(%P) SE (% TF)

South 680 78.4 9.0 1.3 20.3

Eucalyptus Middle 628 85.6 9.0 0.6 13.8

North 753 76.1 7.7 2.2 21.7

South 583 82.5 10.6 2.4 15.2

Casuarina Middle 770 80.1 8.0 2.0 17.9

North 753 76.5 17.4 1.9 21.6

South 680 77.5 13.0 1.5 21.0

Fraxinus Middle 770 82.0 17.5 3.5 14.5

North 753 91.4 12.0 4.0 4.3

South 680 70.3 14.6 0.7 29.0

Grevillea Middle 770 77.4 12.8 0.9 21.7

North 753 87.6 15.0 0.8 11.6

98

E. robustaG. robusta

• F. uhdei

,t;~~~~':. c. elauca~ Weather station

Rainfall

7------

Figure 3.1 - Location of the Honouliuli Preserve on the island of Oahu, Hawaii, showing the

stands studied weather stations and additional rainfall collectors. Map was modified from

original map created by The Nature Conservancy of Hawaii - Oahu.

99

14 ~

12 :::::c

10 58 E

al

North268 events

616mm

South235 events

549mm

Middle247 events

652mm

-,-------------------.--------------------,- 20

18

16

6

4

2

f--ULLI.l..LLIJll.LlllL1lll;.u:LC-eo..=.J::l.=- -f...ILl..Ll..Lll..ud.J..Ll.lllLLUJ..l.Lll..1.L1lll-l.-_-----l.l.tl_.-ll{o

18

16

14 ~

12 :::::c

10 ::l

~8 al

6

4

2

Ll,-u.,u,J.I,.LJ.,.U!,'LY-'-r'-'fl-'i'-Ye....,.u;i"-'T'-~""T_1,_,_...........""'i"_'II"_T_.,....J.--y..yL..t,J-!,r'-'fIJY-'r'..r,.u.,r'-'flJy..y..r,.u.,.u,.uL,L,-...,.......,--.-.,...y_¥..,-,---LO

14 _

12 ~10 C

::l

8 ~6 al

4

2

+-'"'UA.L.1.LJ..I.iLLJ..Llll..l..U'-'--.......c:u::L ~-l-LJ.J.JU_ll_'_L..IJLil.J_'....l.L_'_L..IJLLUJ...!.L.LLIJLl..Ll_ __U..____I.I___'_J.......+O

18

16

60

50

- 40

*'-I/)30-C

~Q) 20

10

0

50

- 40~0-I/)

30-CQ)

a; 20

10

0

SO

~40

0-I/)30-CQ)

>Q) 20

10

0

event size (mm)

Figure 3.2 - Rainfall distribution in three sections of the Honouliuli Preserve: north

(top two graphs), middle (middle graphs), and south (lower graphs). The data are

presented in terms ofoccurrence ofevents in each category and proportional amount

over the total rainfall in the period between Mar h 19 1999 and Mar h 18 2000.

100

2001

--South

,······Middle

- - North200019991998

40

20

0+-r--,--,-r-,-r::~---r-4-,-,--,-.,.--r_r_T"-,--,r-r.,__+_r_T"-,-,r_r_.,......,....,......,._,__,_l_.,_,_..,.....,._,_r_r_.,......,.....,__,__+_,._i

180.--------r------..-;------I

160

140

_ 120E.§. 100

~ 80c'f! 60

MMJSNJMMJSNJMMJSNJMMJSNJ

Figure 3.3 - Monthly rainfall in the three sections of the Honouliuli Preserve between

March 1998 and February 2002.

101

5-.-------------------------------.

4

3

2

--- C. glauca-0-- E. robusta-T- F. uhdei----'\1- G. robusta

O..L-------r---,--------,---,-----,---r----,-----'

Jun-99 Aug-99 Nov-99 Jan-OO Mar-OO May-OO Jul-OO

Figure 3.4 - Leaf area index (LAI, m2 of leaf area per m2 of ground) on stands

dominated by Casuarina glauca, Eucalyptus robusta, Fraxinus uhdei, and Grevillea

robusta from June 1999 to July 2000. Bars represent standard errors of three stands

per species. LAI in F. uhdei was significantly higher than Casuarina glauca and

Eucalyptus robusta for the period measured (Repeated Measures ANOVA F = 8.95, P

< 0.0001).

102

5

--<>- C. glauca

4 -0-- F. uhdei

---.- E. robusta

3

«...J

2

O-\---r------,,.----,.----,..---,---...,...---,----,---.,....----j

Figure 3.5 - Leaf area index (LAI, in m2 m-2) in the forest stands of the southern

section of the Honouliuli Preserve between June 2001 and March 2002. Bars

represent standard errors.

103

2-.----------------------------,

•

• Casuarina glaucao Eucalyptus robusta.., Fraxinus uhdei

-- R2 =0.11, P < 0.0001

..,

..,

,..,..,

••

•..,o

o

o

oo

o

o

J§c.~-ocoto0..

2 10..rotJ)

-e

432

O+------,-------,-------,-----------jo

LAI

Figure 3.6 - Throughfall, as a proportion of rainfall, for events < 3 mm, as a function

of leaf area index (LAI, m2 m-2) for the three stands in the southern section of the


104

5~-------------------~

North

4

E 3

-S~ 2

E2V>

o

o E. robusta• C. glauca.., F. uhdei

v G. robusta

o

o ••

oo

• •

o

•

3.5.,----------------------,

Middle3.0

2.5

E 2.0-S~ 1.5""E* 1.0

0.5

0.0

•

3.0,--------------------,

2.5

2.0

E-S 1.5

~E 1.0

"*0.5

0.0

South

•••

...o

~..,

••

00o ..,.., ..,

o 20 40 60 80 100 120

rainfall (mm)

Figure 3.7 - Stemflow as a function of rainfall in stands dominated by Eucalyptus

robusta, Fraxinus uhdei, Casuarina glauca, or Grevillea robusta in the northern,

middle and southern sections of the Honouliuli Preserve.

105

A B... ...v v

0 0

... • ~

• •0 0v ... • ... v0 • 0

0 E. robustaV V • c. glauca... F. uhdei

V G. robusta

95

90

85

80

75

70

~<:.~ 65-o 0

~~ 95

-§, C6 90

:5

500 1000 1500 2000 2500

tree density (stems ha-1)

3000 3500 20

o

25 30 35 40basal area (m2 ha-1

)

45 50 55

85 0 0

• ... • ...80 • •

0 0V • ... ... e V

075

70 V

651.5 2.0 2.5 3.0 3.5 4.0 550 600 650 700 750 800

LAI(m2 m-2) rainfall (mm)

Figure 3.8 - Throughfall as a function of various stand characteristics (A-C) and of

rainfall (D) for the period between January and December 1999.

106

A B0 E. robusta

• C. glaucaT T T F. uhde;

v G. robustaT T

• •0 0

• • •T T

0 0

'Iv VV

0 V V 0

5

4

3

2

~c 0.~

'0 0 500 1000 1500 2000 2500 3000 3500 20 25 30 35 40 45 50 55

';R0

?:50

E c.illIn

4

tree density (stems ha-')

T

D

basal area (m2 ha-')

T

T

T

•

3

•02 • •

0

V

0'1

01.5 2.0 2.5 3.0

LAI (m2 m-2)

3.5 4.0 550

•

600

•

650

rainfall (mm)

700

•• •

V V

750 800

Figure 3.9 - Stemflow as a function of various stand characteristics (A-C) and of

rainfall (D) for the period between January and December 1999.

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4. Evapotranspiration and Groundwater Recharge by Tree

Plantations in the Honouliuli Preserve, Hawaii.

4.1. Abstract

Evapotranspiration (ET) is one of the main components of the hydrological

cycle affecting groundwater recharge by forests. In Hawaii, estimates ofET, and thus

recharge, have usually relied on water balance models developed for continental areas

with no field calibration in Hawaii. This study aimed to compare three methods for

estimating ET based on (1) water balance calibrated with field measurements of soil

moisture, (2) temperature variation above the canopy (TVAR), and (3) sap flow data

in three planted forests of different species composition. The plantations, dominated

by Fraxinus uhdei, Casuarina glauca or Eucalyptus robusta, were located in the

Honouliuli Preserve, which is part of the southern Oahu groundwater flow system. I

hypothesized that (l) the actual ET rates estimated by the TVAR method are higher

than previously estimated based on an uncalibrated water balance model and (2) that

ET rates differ among forests of different species composition. Evapotranspiration

estimates were based on soil moisture, sap flow, and microclimate data collected from

May 5, 2001, to April 27, 2002. Evapotranspiration estimates from the TVAR

method gave erroneous results and were not reliable for testing the hypothesis 1.

Evapotranspiration estimated from both the water balance and the sap flow methods

was higher in the Eucalyptus stand than in the other stands. The water balance

method indicated that ET was 65%, 94% and 91 % of annual rainfall, and runoff 32%,

3% and 11 % of annual rainfall in stands of Casuarina, Eucalyptus, and Fraxinus,

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respectively. Evaporation of rainfall intercepted by the canopy was substantial,

representing 41 %,29% and 35% ofET, respectively. The only stand that produced

recharge was Fraxinus with 12 mm i l• I concluded that, due to no or very little

recharge, the species chosen for reforestation in Honouliuli, after 50 to 70 years after

planting, have not achieved the desired effect of restoring and protecting the

groundwater resource due to their relatively high ET rates.

4.2. Introduction

One of the greatest concerns related to deforestation is its impact on the

hydrology. Changes in land use in regions with extensive forest cover can affect

hydrological processes such as evapotranspiration (ET) and, consequently, regional or

even global climate (Shukla and Mintz 1982, Lean and Warrilow 1989, Shukla et al.

1990, Salati and Nobre 1991). The development of secondary vegetation in these

areas reduces the impact of deforestation on the hydrological cycle by raising ET and

infiltration rates to levels closer to the primary forest's levels (Giambelluca et al.

1996a, Holscher et al. 1997, Jipp et al. 1998). However, in some cases, natural forest

regeneration is very slow. As a result, a faster process of reforestation of watersheds

may be needed in order to decrease the impacts of deforestation. In Hawaii, the main

concern related to deforestation is the possible reduction of the groundwater level due

to the low infiltration rates generated by denuded land. Thus, fast growing non-native

trees were planted on many deforested Hawaiian watersheds in order to restore

groundwater recharge. Oahu, as many other oceanic islands, depends mostly on

groundwater for domestic consumption and for the development and maintenance of

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economic activities. In 1995, 86% of the freshwater consumed on the Island of Oahu

was obtained from groundwater (DLNR 1995). The abundance and distribution of

groundwater on the island is limited, and it is a priority to understand the dynamics of

this resource, especially in relation to its recharge.

Although the effects of different cover types (e.g., grasses versus forests) on

the hydrological cycle have been well studied (e.g., Bultot et al. 1990, Hodnett et al.

1996, Calder 1998, Jipp et al. 1998), research on the effects of different forest types

on the magnitude of the water cycle components is still scant (e.g., Bigelow 2001

Cape et al. 1991). Understanding the water cycle in reforested areas may provide

tools to improve land management programs that affect water resources in Hawaii

and other tropical islands.

I use the term evapotranspiration (ET) in this chapter to define the total

evaporation from the forest including interception, transpiration, and litter and soil

evaporation. Estimates on ET in some tropical forests located at continental edges or

islands have shown higher values than in continental forests. In forests of Puerto

Rico (Schellekens 2000) and Fiji (Waterloo et al. 1999), for example, evaporation

from intercepted water was greater than the values predicted by energy balance

equations developed for continental areas, indicating that other sources of energy,

besides solar radiation, are affecting interception (Bruijnzeel 2000). In Hawaii, ET

has been estimated using water balance models developed for continental areas and

based mostly on data on precipitation, stream flow and some pan evaporation in

agricultural sites. Because of the limited amount of available data on soil moisture,

transpiration, interception, ET and infiltration, the models usually estimate these

110

components based on empirical equations, and do not incorporate calibrations

obtained from field measurements (e.g., Giambelluca 1983).

In this study I used soil moisture data collected in forests dominated by

different species to obtain more direct estimates of ET and I hypothesized that ET is

higher, thus groundwater recharge is lower, than previous estimates for Oahu and that

ET is different in forests of different species composition.

4.3. Methods


The Nature Conservancy's Honouliuli Preserve is located on the eastern slope

of the southern Waianae Mountain Range, on the Island of Oahu, Hawaii, and is part

of the southern Oahu groundwater flow system. Mean annual rainfall in this area

ranges from 540 to 750 mm (Giambelluca et al. 1986). Total rainfall in 1999 was 630

mm, but in 2000 and 2001 it was below usual at 386 and 450 mm, respectively, in the

southern part of the preserve (Chapter 3), where this study was conducted. Normal

rainfall level resumed after November 2001 (Fig. 3.3). This part of Honouliuli is

dominated by 20 to 130 em deep Dystrandepts soils. Between the 1920s and the

1940s, several non-native fast-growing tree species were planted in this area, in

mono-specific stands, in order to reduce erosion and to protect and recharge

groundwater.

111


Stand-level ET was estimated independently by three methods: water balance,

temperature variance, and direct measurements of tree sap flow combined with

rainfall interception (hereafter called the sap flow method). The sap flow and water

balance methods were applied to the data collected in one plantation dominated by

each of three species: Fraxinus uhdei, Casuarina glauca, and Eucalyptus robusta

(hereafter referred to as the forest sites). These stands were located in the southern

part of the preserve and their characteristics are described in Section 1.7.2 and in

Table 1.1. The temperature variance method was not used to estimate ET in the

Eucalyptus stand because of the absence of temperature measurements above the

canopy.

4.3.3. Micrometeorological data

Due to the difficulties in measuring the microclimate directly above the

canopy of the forests stands, micrometeorological data were collected from a weather

station installed above a short-canopy forest, approximately 5 m tall, dominated by

Schinus terebinthifolius (hereafter referred to as the reference site). This site was

located between the Fraxinus and Eucalyptus stands and was used as reference to

allow for the estimate of potential evapotranspiration on the forest sites. The

instruments were placed 2 m above the canopy in the reference site and collected data

on rainfall (tipping bucket rain gauge, Texas Electronics, Dallas, TX, USA), net

radiation (Q7.1_L50, Radiation Energy Balance Systems! Campbell Scientific,

Logan, UT, USA), wind velocity (OI4A, MetOne Instruments, Grants Pass, OR,

112

USA), relative humidity and air temperature (HMP45C, Vaisala, Inc., Sunnyvale,

CA, USA), canopy temperature (infrared transducer 4000AZL, Everest Interscience,

Inc., Tucson, AZ, USA), and incoming and reflected shortwave radiation

(pyranometers, LI-200SZ, LiCor, Lincoln, Nebraska, USA). An additional rain gauge

(Texas Electronics, Dallas, TX, connected to a Hobo Event datalogger, Onset,

Pocasset, MA, USA) was placed near the Casuarina stand. Data were collected from

January 2001 to April 2002.

4.3.4. Potential evapotranspiration

Potential evapotranspiration (PE, in W m-2), the maximum evapotranspiration

by a vegetated surface with unlimited water supply, was estimated at the reference

site based on the equation proposed by Penman (1948) for open water surfaces:

PE = !J.(Rnet - G) + r[(0.263 + 0.138U)(e, - e)]

!J.+r(4.1)

where Rnet (W m-2) is the net radiation, G (W m-2

) the soil heat flux, r (mb K 1) the

psychrometric constant, U (m S-I) the wind velocity, es the saturation vapor pressure

(mb), and e the ambient vapor pressure (mb). The same equation was used to

estimate PE in the forest sites. The values of vapor pressure and wind velocity used

were those obtained at the reference site, but Rnet was calculated with equation 4.2

(Giambelluca et al. 2003), by adjusting the reference site Rnet to an albedo (u) of 0.13.

Rnet =Kd - (uKct) + EA - EoTo4 (4.2)

where Kd (W m-2) is the incoming shortwave radiation, E:: is the emissivity of the

surface, A (W m-2) the downward longwave radiation from the atmosphere, (J the

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Stephan-Boltzmann constant (5.67 x 10-8 J K 4 m-2S-I), and To (K) the surface

temperature. Measured canopy infrared temperature at the reference site was

substituted for To (Choudhury et al. 1986).

Soil heat flux (G) was estimated on the basis of Rnet according to data from

Giambelluca et al. (unpublished, Fig. 4.1) from the Brazilian Cerrado from August

2001 to October 2002. Differences in G between the Cerrado and Honouliuli should

not affect the estimates of daily PE in Honouliuli because mean G is negligible over a

daily interval.

4.3.5. Water balance method

The water balance method used in this study is a bookkeeping procedure

(Thomthwaite 1948, Thomthwaite and Mather 1955) modified by Giambelluca

(1983, 1986) to estimate the influence of land use on the water balance of southem

Oahu. The original model proposed by Thomthwaite used monthly means of

precipitation (P) and PE as inputs, and assumed that P evaporated at the PE rate.

Giambelluca (1983,1986) and Giambelluca and Oki (1987) improved the accuracy of

the model by having measurements ofP and PE at shorter intervals (hourly or daily)

as inputs, and by considering soil moisture and depth of water uptake in the ET

calculation. The model keeps account of the exchange of moisture between the soil

and the vegetation that occurs in each interval considered. In this study, the interval

of inputs to the model was daily. A starting value of available water (AWi-I)

describes the initial state of the system, and available water for each day is calculated

based on the state variable Xi:

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(4.3)

where AW is the difference between the moisture content and the zero extraction

point (ZEP) in the root zone, and Pi, RO j and ET j are the precipitation, surface runoff

and evapotranspiration during day i. All variables are expressed in the same unit of

water depth (mm, in this study). The ZEP is the lowest soil moisture limit available

for evaporation and was considered in this study to be the lowest level of soil

moisture at the end of the 21-month long drought. Available water at the end of each

interval is assumed to be zero when X j ::; 0, or a function ofXj or depth of water

uptake when Xi > °(Table 4.1). The model estimates ET for each day as a function

of PE adjusted for the vegetation cover and the available soil water content in the root

zone (Giambelluca et al. 1996b):

ET=PE for

for

Sc.N

S<N

(4.4)

(4.5)

where S is the instantaneous available moisture content in the root zone, and N is a

function of depth of water uptake and PE, and it could be interpreted as the amount of

available moisture in the root zone below which ET is depressed below PE.

Groundwater recharge in the model is considered to occur only when AW exceeds the

field capacity. Detailed description of the model can be found in Giambelluca et al.

(l996b).

Runoffwas calculated separately, as a function ofP, using the empirical u.s.

Soil Conservation Service Curve Number model (Dunne and Leopold 1978). The

Curve Number model calculates surface runoff based on precipitation, antecedent soil

115

moisture condition (AMC) and the curve number parameter, which represents the

hydrologic characteristics of the site. Antecedent moisture condition is obtained by

adding the rainfall in the 5 days prior to the beginning of each period considered

(AMC I < 12.7 mm, AMC II is between 12.7 and 27.9 mm, and AMC III > 27.9 mm).

The initial curve numbers were estimated in this study based on the soil hydrologic

characteristics and land cover as published by Dunne and Leopold (1978), and were

adjusted based on the measured soil moisture data. The initial curve numbers used

for all sites were 40,60 and 78, for antecedent moisture conditions (AMC) classes I,

II, and III, respectively. These curve numbers represent a forest cover with moderate

levels of grazing in soils with moderate infiltration rates (Dunne and Leopold 1978).

Model calibration andparameters

The water balance model was calibrated by comparing estimated AW against

the field soil moisture measurements done using time domain reflectometry, as

described in Chapter 2. The model parameters were adjusted to improve the fit of the

estimates to the measured soil moisture data points. The accuracy of the model was

assessed by estimating the root mean square error (RMSE) of the relationship

between measured and estimated soil moisture. The RMSE is determined by taking

the square root of the sum of the deviations of the estimated (s) from the measured (0)

values:

(4.6)

The bias of the simulated soil moisture values was determined by the relative

difference between mean simulated values and mean observed values:

116

BIAS = s=oo

The parameters adjusted in the model (Table 4.1) were the field capacity,

(4.7)

depth of water uptake and crop factor. While all other parameters were held constant,

different values were assigned to the parameter being adjusted in order to obtain the

lowest RMSE of the fit between the estimated and the measured AW. The

adjustment of the parameters was done first assuming that no runoff occurred in the

forest sites. After all parameters were adjusted, runoff was added to the model to

increase the fit of the estimated and measured data. The curve numbers used to

estimate runoff were adjusted also in order to get the lowest RMSE.

Available water capacity. Available water capacity (AWC) is the difference between

the field capacity and the zero extraction point (ZEP), i.e., it is the maximum moisture

available for evaporation within the root zone. The ZEP was considered to be the

lowest soil moisture value during the end of the dry period (when soil moisture was

nearly constant).

Depth ofwater uptake. Depth of water uptake is an important parameter for

determining the AW for transpiration. The starting value for depth of water uptake

was based on the estimated values obtained from the measurements in Chapter 2, then

adjusted to reduce the RMSE of the calibration curve.

Crop factor (or adjusted PE). Because Giambelluca's modifications were made to

estimate ET on a surface covered by pineapple and sugar cane, adjustments need to

be made on the PE for vegetation cover based on the proportion of the area covered

with vegetation. The crop factor (CF), adjusted for each forest site in order to reduce

117

the RMSE of the calibration curve, ranges from 0 to 1 and is defined as the ratio of

the forest PE (PEfar) to sugarcane PE (PEsc) (Giambelluca 1983, Giambelluca et al.

1996b):

PEror = CF* PE,c (4.8)

Several sources of uncertainty are associated with this method. The main

sources of errors are from the measured variables and from the estimation of the

parameters. Errors may come from the spatial variation of precipitation and PE, for

example, and also from the measurement errors associated with the sensors or their

installation. Errors in the PE estimates also may have incurred from the difference in

the canopy characteristics between the forest sites and the reference site. Other errors

may come from the estimation of the parameters of the model, which are directly

affected by the soil moisture measurement errors and variability. Giambelluca et al.

(1996b) estimated the errors in the estimation of groundwater recharge caused by the

parameters estimates of the same model but without calibration with field

measurements of 16% for sugar cane and 51 % for pineapple. My calibration of the

model with field measurements of soil moisture should result in lower errors

associated with the parameters estimation than those found by Giambelluca et al.

(1996b).

4.3.6. Temperature variance method (TVAR)

The temperature variance method (TVAR, Tillman 1972, Vugts et al. 1993,

Schellekens et al. 2000) estimates ET based on the standard deviation of temperature

fluctuations, following the general energy balance equation:

118

J...ET = Rnet - G - H

(4.9)

where Ais the latent heat of vaporization (28.36 W m-2 mm-1 d-1) and H is the sensible

heat flux (W m-2). This method was chosen because it requires the measurement of

only one variable (temperature) at a single height above the canopy. In addition, the

TVAR method is not sensitive to irregularities in the terrain, an advantage for

measuring ET in the steep slopes of Honouliuli. Sensible heat flux is estimated in this

method by the following equation (Vugts et al. 1993):

H = 1.075 p Cp crll2[( k g (z- d)/ T ]1/2 (4.10)

where p (kg m-3) is the air density, Cp (J kg-1 K 1

) is the heat capacity of air at constant

pressure, crT is the standard deviation of the temperature, k is the von Karman

constant (0.4), g is the acceleration due to gravity (9.8 m S-2), d is the height of the

zero-plane displacement (m), and T (K) is the temperature measured with fast

response copper-constantan thermocouples at height z (m), which was approximately

2 m above the canopy. Net radiation was estimated based on the measurements at the

reference site as described in Section 4.3.4.

A limitation of the TVAR method is that ET estimates can only be done

during daytime periods (Rnet > 30 W m-2) with no rain. During rainy periods,

transpiration was assumed to be zero for one hour after rainfall events smaller than 1

mm, and for three hours following rainfall events equal or larger than 1 mm. During

these periods, evaporation from interception (E j) was assumed to be the only form of

evaporation occurring. Interception in each forest stand was derived from automated

measurements of rainfall and throughfall, and estimates of stemflow based on the

119

equations proposed in Table 3.4, as described in Section 3.3.3. Other uncertainties

associated with this method come from the placement of the thermocouples above the

canopy. As it can be seen from equation 4.10, H is proportional to the square root of

(z-d). The sensitivity ofthis method to d (zero-plane displacement height) is

considerable, so best results can be obtained if the temperature measurements are

done at a height which is large compared to d (Lloyd et al 1991, Holwerda 1997).

4.3.7. Sap flow method

The sap flow method combines direct measurements of tree sap flow, scaled

to the stand level, and rainfall interception. Sap flow was measured with the heat

dissipation technique (Granier 1985, 1987), as described in Section 2.3.2. Stand

transpiration (Es, in mm) for the dominant tree species in each stand was obtained by

scaling up transpiration from the tree to the stand using the measured trees as

representatives of size classes, based on their DBH, as described by the following

equation (Granier et al. 1996):

E =A *"(SFD *~Js TL-J fAT

(4.11 )

where AT is the stand sapwood area per unit of ground area (m2 ha-l) calculated as the

sum of the sapwood area of all trees divided by the total ground area of the stand,

SFDi is the mean sap flux density (g m-2S-I) of trees in the class of diameter i, and Ai

is the sapwood area (m2) ofthe trees in the class of diameter i. Mean SFD of each

tree was obtained by dividing each tree's sap flow by its sapwood area, which was

determined by inserting a 1% Safranin solution into a hole in the sapwood and

120

collecting a core above the hole two to three hours later. The sapwood area for all

trees in each stand was determined based on the relationships between sapwood area

and basal area described in Section 2.4.4.

The errors associated with estimating stand transpiration based on the sap

flow of individual trees are mostly associated with the scaling from the probe to the

tree (Hatton et al. 1995), which involves errors in the sap flux density measurements,

in the estimation of active xylem area, and in the sampling variance. These errors can

be on the order of 38% of the estimates (Hatton et al. 1995). The use of variable

length probes in this study (Chapter 2) should reduce the errors associated with radial

variation in sap flow within trees. In addition to the sap flow estimates errors,

understory transpiration, and litter and soil evaporation were considered negligible in

the analyses based on this method, which may result in underestimates ofET.

4.4. Results

4.4.1. Potential evapotranspiration (PE)

Potential evapotranspiration was estimated using the Penman (1948) equation

and was adjusted for each plantation type during the calibration of the water balance

model for the period from May 4,2001, to April 28, 2002, based on data collected on

283 days. There were two large gaps in data collection, one from September 3 to

November 2,2001, and the other from November 25 to December 9,2001. The

missing data were replaced by estimated values based on the results of the 10 days

before and 10 days after the missing period. The total estimated PE from May 4,

2001, to April 28, 2002, was 1201, 1472, and 1338 mm for the Casuarina, Eucalyptus

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and Fraxinus stands, respectively. Mean daily PE for the Casuarina stand was

similar to the estimates made by Giambelluca (1983) for the same area from 1946 to

1975 (Fig. 4.2). The estimates for the Fraxinus and Eucalyptus stands were in

average 14% and 25% higher than Giambelluca's estimates, respectively (Fig. 4.2).

4.4.2. Water balance method

The calibration of the water balance model resulted in a very good fit

between the estimated and measured soil moisture, and yielded different values for

the parameters adjusted in each forest stand (Fig. 4.3). After runoff was added to the

model (Fig. 4.4), the RMSE between the estimates and the measured soil moisture

decreased from 3.01 to 1.34%,2.37 to 2.20%, and 2.64 to 2.62% for the Casuarina,

Eucalyptus and Fraxinus stands, respectively. The estimated biases of the soil

moisture estimates were very low at -0.009,0.001, and 0.096% of AW, respectively.

The final curve numbers used to estimate runoff are listed in Table 4.2.

Estimated runoff for the whole period was 186, 19, and 11 mm for the Casuarina,

Eucalyptus and Fraxinus stands, respectively (Table 4.3). Estimated daily ET ranged

from 0.1 to 3.6 mm in the Casuarina stand, 0.1 to 6.2 mm in the Eucalyptus stand,

and 0.2 to 5.6 mm in the Fraxinus stand. Mean daily ET was lowest from July to

September, 2001, and highest in February and March, 2002 (Fig. 4.5). From the dry

season (May to October) to the wet season (November to March), ET increased from

an average of 0.45 to 1.7 mm d-1 in the Casuarina stand, from 0.6 to 2.8 mm d-1 in the

Eucalyptus stand, and from 0.6 to 2.6 mm d-1 in the Fraxinus stand. Total ET in the

whole period was highest in the Eucalyptus stand and lowest in the Casuarina stand

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(Table 4.3). The high value of runoff in the Casuarina stand and the high ET in the

Eucalyptus stand resulted in no groundwater recharge by these stands in the period

studied (Table 4.3). The groundwater recharge by the Fraxinus stand, which

exhibited relatively high ET and very low runoff, was only 12 mm for the period

measured, an average of 0.03 mm dol.

4.4.3. Temperature variance method (TVAR)

The TVAR method yielded extremely variable data, with several

exceptionally negative or exceptionally positive values ofET (Fig. 4.6). These values

were probably a result of the low height where the thermocouples were placed above

the canopy (approximately 2 m above the canopy of each stand). For this reason, this

method was not considered reliable for further estimates.

4.4.4. Sap flow method

Estimates of ET using the sap flow method were only done for days when

there were sap flow data for at least three trees and interception data in each stand.

Based on the sap flow data of the dominant species, all stands exhibited low

transpiration rates, with values lower than 1 mm dol, In February and March 2002,

the Eucalyptus stand exhibited the highest transpiration rates of the three stands, with

rates of 0.14 to 0.76 mm dol, and the Casuarina stand the lowest, with rates of 0.1 to

0.23 mm dol. Total evaporation from intercepted rain (Ej) in the dry season (May to

August) was 29 mm for the Casuarina stand, 34 mm for the Eucalyptus stand, and 40

mm for the Fraxinus stand, and in the wet season (November to February) was 75,

89, and 103 mm, respectively. The Eucalyptus stand exhibited higher daily ET rates

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on practically all days with no rain. However, this was not true for rainy days, when

E j dominated ET (Fig. 4.7). This method tended to underestimate mean daily ET

when compared to the water balance method (Fig. 4.8), and the results exhibited

larger fluctuation than those obtained by the latter (Fig. 4.9).

4.4.5. Interception vs. evapotranspiration

A comparison between the measured interception with the estimated ET rates

by the water balance method describes the patterns of evaporation in the forest sites.

Evapotranspiration was largely determined by interception in wet months following

dry months (when soil moisture was low). This was more evident in the Casuarina

and Fraxinus stands than in the Eucalyptus stand (Fig. 4.10). As expected, in dry

months with high soil moisture, transpiration dominates ET. Total interception in the

period measured was 154, 180 and 209 mm, representing 41 %,29% and 35% ofET

for the stands dominated by Casuarina, Eucalyptus and Fraxinus, respectively.

4.5. Discussion

4.5.1. Effect ofspecies composition on evapotranspiration

The water balance method estimated ET in the Eucalyptus stand to be

slightly higher than in the Fraxinus stand, and almost twice as high as ET in the

Casuarina stand. Similarly, the results from the sap flow method indicated that ET

was higher in the Eucalyptus stand, followed by Fraxinus and, finally, by the

Casuarina stand. In general, the differences in ET among the stands were more

obvious during the wet season as soil moisture during the dry season reached the zero

124

extraction point, causing transpiration in all stands to be at its lowest. This low soil

moisture was a result of a long period of drought that started in February 2000 in the

study area (Fig. 3.3). In addition, evaporation from interception represented a

considerable fraction of total ET, between 29% and 41%. Some of these values are

higher than values of 10 to 34% estimated for continental sites (Jordan and

Heuveldop 1981; Leopoldo et al. 1982, 1995; Moreira et al. 1997), but lower than the

values of 41 to 74% observed in lower montane forests in Jamaica (Hafkensheid

2000) and Puerto Rico (Schellekens 2000).

The low ET found by the two methods in the Casuarina stand can be

explained by this stand's inability to recover transpiration rates after the end of the

drought (Chapter 2), and by the high runoff it generates. This stand, similar to other

stands of Casuarina throughout the preserve, has a very thick layer of litter and a very

dense root mat at the top of the soil, which probably results in a barrier for water

infiltration. Stands of other species of Casuarina were also found to transpire at low

rates (1 mm d- l in C. cunnighamiana, Morris and Collopy 1999), lower than those

estimated in areas with shallow saline water table, between 1.5 and 3 mm d- l, in

Australia (Cramer et al. 1999).

The Eucalyptus stand exhibited the highest levels ofET, mostly due to

relatively high transpiration rates. The sap flow measurements, however, suggest that

the stand-level transpiration in the Eucalyptus stand was lower than measurements on

the same genus made elsewhere. Robert and Rosier (1993) estimated transpiration of

young plantations ofE. camaldulensis or E. tereticornis in southern India from 1 mm

d- l during the dry season up to 6 mm d- l when soil moisture was high. Hunt and

125

Beadle (1998) estimated transpiration of 8-year-old E. nitens plantations to be

between 1.6 and 2.8 mm d-1. The relatively high transpiration rates (in comparison to

the available water) in the Eucalyptus stand may be explained by this stand's

relatively deep water uptake (Chapter 2), large basal area, and possible tree-level high

leaf-specific hydraulic conductivity, which allows high transpiration rates at low leaf

area (as discussed in Chapter 2).

The relatively high stand ET rates found in the Fraxinus stand were probably

a result of the combination of relatively deep water uptake, high leaf area index, and

the relatively high transpiration rates of Fraxinus trees (Chapter 2). Even though the

Fraxinus stand had higher leaf area index (LAI) than the Eucalyptus stand (Fig. 3.4),

its ET was slightly lower. Because the end ofthe 2001 dry season coincided with the

end of a 2l-month long dry period, Fraxinus, which usually loses leaves between

November and January in Hawaii, exhibited its lowest LAI in October 2001. In

normal years, when the difference in LAI between the Fraxinus and the Eucalyptus

stands is larger, ET may reach similar values.

The estimated 40 cm depth of water uptake in the Casuarina stand made

during the calibration procedure of the water balance model was similar to the

estimates based on the hydrogen isotope data (Chapter 2). On the other hand, while

the isotope method suggested that water uptake in the Eucalyptus and in the Fraxinus

stands occurred in the soil profile down to 40 and at least 75 cm, respectively, the

calibration of the water balance model suggested these depths to be 55 and 50 cm,

respectively. The water balance model estimates for depth of water uptake seem to

agree better with the depth of water uptake indicated by the soil moisture profiles in

126

Fig. 2.2. As discussed in section 2.5, the depth of water uptake in Eucalyptus could

have been underestimated due to the possible collection of non-sapwood water for the

isotope measurement.

4.5.2. Evapotranspiration vs. potential evapotranspiration

The TVAR method was the most appropriate of the three methods used to

test the hypothesis that ET is higher than the energy available through radiation, as

found in other oceanic islands (Waterloo et al. 1999, Schellekens 2000). However,

the lack of measurements high above the canopy resulted in ET estimates that did not

seem reliable as it resulted in several days with extremely negative or extremely

positive ET values. Consequently, I was unable to test the hypothesis that ET

measured directly was higher than previously estimated ET.

However, my PE data give some indication that ET underestimation might

have happened in previous studies. Potential evapotranspiration estimated from

measurements at our site was up to 25% higher than that estimated by Giambelluca

(1983), using data from few stations throughout the Pearl Harbor-Honolulu basin.

This could be due to the fact that my study period was dominated by a long drought,

maybe resulting in estimated values not representative of the long-term average.

Also, Giambelluca (1983) used average data for a large zone in contrast to localized

measurements done in my study. The hydrological gradients as elevation increases

are significant, and that could account for much of the difference.

127

As ET estimates are directly related to PE in the model used by Giambelluca

(1983), his study could have underestimated ET by up to 20%, and, consequently,

overestimated groundwater recharge.

4.5.3. Groundwater recharge and runoff

Groundwater recharge was estimated by the water balance method to be 12

mm i 1 for the Fraxinus stand and 0 mm i 1 for the Eucalyptus and Casuarina stands.

Due to the calibration of the model with field measurements of soil moisture, I expect

these estimates to have an associated error lower than 51 %, which was the estimated

error in groundwater recharge estimates by Giambelluca et al. (1996b) using the same

model on Oahu, for pineapple fields. These estimates were much lower than the

average annual recharge estimated by Giambelluca (1983), at 500 mm y-l, for the

same area. The difference between the estimates of the two studies is due to the lack

of available data for this area in Giambelluca's study, and due to the long drought that

my study period encompassed. However, the total rainfall in the year that this study

was conducted (591 to 665 mm) was within the long term annual rainfall range (540

to 750 mm, Giambelluca et al. 1986).

The lack of recharge by the Eucalyptus stand was due to the relatively high

ET rates estimated for this stand, mainly due to its transpiration rates. On the other

hand, the lack of recharge by the Casuarina stand was likely due to the high runoff

this stand generates. Runoff there was generated by rainfall events> 3.8 mm. This is

consistent with personal observations in the field that water does not infiltrate easily

in the soil of this stand. This low infiltration, and thus low soil moisture, may explain

128

the shallow depth of water uptake and low transpiration rates estimated for trees in

the Casuarina stand (Chapter 2). In contrast with Casuarina, runoff in the Fraxinus

and in the Eucalyptus stands was generated only by rainfall events 2: 50 mm, when

antecedent moisture conditions were high. A previous study in another Fraxinus

stand in Honouliuli (in the middle section, code 3088 from Table 1.1) estimated that

no runoff would be generated even with one-hour rainfall of 51 mm h-1 and return

interval of 10 years (Nagel 2003). In the same study, two stands of Eucalyptus

(middle and north, codes 3109 and 3128, respectively, Table 1.1) were found to

exhibit a water-repellency characteristic in over 50% of the soil sampled in the field.

This repellency caused runoff to be generated more frequently than for the Fraxinus

stand (Nagel 2003). The Eucalyptus stand ofthis study did not show obvious

evidence of being water repellent judging by the relatively low runoff it generated.

Based on the data from this study, it is more likely that the Casuarina stand may have

hydrophobic soil than the Eucalyptus stand.

4.5.4. The methods

The water balance method is a valuable tool to estimate ET and groundwater

recharge and requires very little information as input. The only information needed is

PE, rainfall, and a starting value of soil moisture. In this study, the validity of this

method was increased by having frequent soil moisture measurements that allowed

for a good model calibration. However, the uncertainties associated with the model

were not estimated in this study. The sources of uncertainties on the estimates of

groundwater recharge can derive from measurement errors of the input data

129

(precipitation, PE and soil moisture) and errors in estimating the model parameters

(Awe, depth of water uptake, crop factor). The measurement errors include

instrumentation precision, and spatial and temporal variability, while the estimated

parameters would be affected mostly by errors related to the soil moisture

measurements. The coefficient of variation of soil moisture in each stand of in

average between 27% and 40%, plus the lack of continuity in the data (because were

collected manually), missing measurements during the peak of rainfall events,

contributed to the errors involved in estimating the parameters of the model.

The main advantage of the TVAR method is that, besides net radiation, it

needs only data on temperature as input. Even though there is no need to level the

thermocouples above the canopy of the forest, which makes their installation

relatively convenient, it is difficult to place them high above the forest canopy. In the

Fraxinus stand, for example, the thermocouples were initially placed on a cable

running over the canopy of the forest, from a higher location on a ridge to a tall tree.

The cable was tightened as much as possible after installation, but the wind and the

tall-tree movement constantly lowered the height ofthe thermocouples. Later, the

thermocouples were moved to a 7.6-m pole, installed near the top of the ridge. The

canopy below this new position was probably not representative of the parts with

taller trees. A similar pole was installed in the Casuarina stand and the same kinds of

problems might have resulted in the high fluctuation of the data.

Several reasons might have contributed to the underestimation of ET by the

sap flow method. The small number of probes and trees probably caused high

cumulative errors in the scaling up process from the probe to the tree and from the

130

tree to the stand. Hatton et al. (1995) estimated these errors as higher than 38% of the

estimated stand transpiration, mostly due to the scaling from the probe to the tree.

Radial (James et al. 2002, Nadezhdina et al. 2002, Ford et al. 2004) and axial (Fig.

2.7, Hatton et al. 1995) variations of the sap flow within trees are the major source of

errors in estimating tree transpiration from sap flow measurements. Jimenez et al.

(1996) found radial variation in sap flow ranging from 3% to 31 % in Laurus trees. In

addition, sap flow in this study was measured in 3 to 6 trees per stand, or 5 to 7

sampling trees ha-1• Cermak et al. (1995) estimated scaling errors oftranspiration to

the stand of 15% and 22% for pine and spruce, respectively, using 12 sampling trees

ha-1. However, Hatton et al. (1995) estimated that a sample size of 8 trees would be

enough to reduce considerably the errors associated with the scaling from the tree to

the stand. The stand transpiration estimates in Honouliuli were based on

representative trees of the dominant canopy species, neglecting transpiration from

other canopy species and from the understory, which have contributed to the

underestimation ofET by this method. Roberts and Rosier (1994) estimated that 45%

of the annual transpiration of a Fraxinus excelsior stand came from the understory.

4.5.5. Implications ofreforestation on groundwater

Some planted forests do increase soil infiltration in relation to pastures (e.g.,

Wood 1977, Nagel 2003). However, forests are known to have higher ET rates than

pasture or short vegetation (e.g., Waterloo 1994, Jipp et al. 1998) probably due to

lower surface albedo, higher leaf area, higher aerodynamic roughness and deeper

water uptake in the forests versus shorter vegetation. In reforestation efforts in a dry

131

place like Honouliuli, preference should be given to species that have characteristics

that would contribute to more conservative water use and to increase infiltration. It is

very likely that the original forests in Honouliuli were a lot more adapted to the

weather conditions and water availability than the planted forests presently there.

Studies on the comparative physiology of native versus non-native plants in Hawaii

suggest that the former have lower growth and photosynthetic rates (Pattison et al

1998, Baruch and Goldstein 1999, Durand and Goldstein 2001), which would result

in more conservative water use. Moreover, the dominant native tree in some of the

remaining vegetation communities in the mesic forests of Honouliuli, Acacia koa,

was found to be able to adjust its water use efficiency according to water availability

in a gradient of rainfall and elevation on the island of Hawaii (Ares and Fownes

1999).

Fraxinus seemed to be the least negative species of the three, allowing some

water for groundwater recharge and generating very little runoff. This happens

probably because this species is has deep water uptake (Chapter 2), allows the

development of a dense understory, and is deciduous. Fraxinus loses leaves during

one month in the wet season in Hawaii, when ET rates are high. This may

compensate for the relatively high rates of transpiration and interception found in this

stand. Although Eucalyptus are often reported as high water consumers and as

having a detrimental ecological effect (e.g., Shiva and Bandyopadhyay 1983), this

study shows Casuarina to have a more negative effect in the watershed. Besides not

allowing water for groundwater recharge, the stand dominated by Casuarina

produced much higher surface runoff than the other stands. This may not only reduce

132

groundwater recharge in the basin but also increase the amount of nutrients

transported to the streams.

The relative contribution of the different hydrological components to the

water balance of forests is likely to change with time. Vertessy et al. (1998, as cited

by Bruijnzeel 2000), for example, observed that as the understory develops with the

aging of Eucalyptus regnans plantations, its transpiration forms a greater portion of

ET. This occurs concomitantly with a reduction in overstory transpiration and total

ET. At 50 to 70 years of age, the stands studied in Honouliuli still exhibit relatively

high ET rates and very little groundwater recharge. As these stands age it is likely

that ET rates will decrease and more water would be available for recharge, but the

time frame is unknown.

4.6. Conclusion

The stand dominated by Eucalyptus exhibited the highest ET rates followed

by the stand dominated by Fraxinus and by the stand dominated by Casuarina.

Evapotranspiration alone would not give accurate estimates of groundwater recharge

as runoff proved to be a considerable part of the water balance in the Casuarina

stand. The high runoff generated by this stand, at 190 mm it, not only resulted in no

groundwater recharge but may also cause erosion and an increase in the transport of

soil and nutrients to the streams. Of the three stands, the one dominated by Fraxinus

was considered to have the least negative effect on the watershed because it allowed

some water for recharge (12 mm y-t) and generated very little runoff (11 mm it).

The errors associated with these estimates can be up to 50% of the recharge estimates.

133

As recharge was so low, it is difficult to estimate the margin of error involved in the

estimates. In addition, the period measured in this study encompassed the end of a

long drought, which may explain the lack of groundwater recharge. Even though

groundwater recharge during years with normal rainfall is probably higher than the

estimated during my study period, during periods similar to the one study recharge is

probably close to zero, suggesting that these planted forests have not achieved the

desired goal of restoring and protecting groundwater recharge anticipated by

reforestation in the Waianae Mountains.

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Bigelow, S. 2001. Evapotranspiration modeled from stands of three broad-leaved

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140

Table 4.1 - Terms (in mm) in the water balance model for day i.

Terms

Precipitation

Potential Evapotranspiration

Wilting PointField Capacity

Available Water Capacity

Depth of water uptakeSoil Moisture

Runoff

Actual Evapotranspiration

Groundwater Recharge

Abbreviation

PE j

WPFC

AWC

ZAWi

Definition

Measured directly

Estimated based on eq. 4.1 (Penman 1948)

Equals AW at the end of the dry seasonEstimated based on model calibration

AWC=FC - WP

Estimated based on model calibrationBased on Xj = AWj_1 + (Pi - ROj- ETDAWi-1 measured in each forest site;If Xi :s 0, AWi = 0If 0 < Xi :s A Wz , A W j = XiIf Xi > AWz, AW i =AWz

AWz is the AW in the root zoneSCS Curve Number method (see text)

If AW 2': Cj, ETi = PEi;If AW < C, ETi = AWi X Cj-I x PEi ;

C j =f(Z, PE)Occurs when AWi > FC

Table 4.2 - Final curve numbers used to estimate runoff in the forest stands studied in

the Honouliuli Preserve between May 2001 and April 2002. See text for explanations

of how the antecedent moisture condition (AMC) class was determined for each

period.

Casuarina glauca

Eucalyptus robusta

Fraxinus uhdei

AMCI

70

22

18

141

AMCII

85

40

35

AMC III

94

60

55

Table 4.3 - Precipitation and estimated values of runoff, evapotranspiration and

groundwater recharge (all in mm) in the forest stands from May 5, 2001, to April 27,

2002. Runoff was estimated using the u.s. Soil Conservation Service curve number

method (Dunne and Leopold 1978). Evapotranspiration and groundwater recharge

were estimated using the bookkeeping water balance method.

Casuarina

Eucalyptus

Fraxinus

Precipitation

581.5

655.7

651.2

Runoff

186.5

19.4

11.2

142

Evapotranspiration

375.0

619.7

592.9

Recharge

o

o

11.9

••

800

G =-10.9 + 0.088Rnet

( =0.75 P < 0.0001

1000

••

600400

Rnet

(W m-2)

• •

200

••

•••

•

• •• ••••

o

••

80

60

40

20..--.~

ES 0"-"

(?-20

-40

-60

-80

Figure 4.1 - Relationship between half-hourly measurements of soil heat flux (G) and

net radiation (Rnet) in the Brazilian Cerrado from August 29 to October 16,2001

(Giambelluca et aI., unpublished).

143

61------------;:===========:::;----~

5

, 4"0

E5g: 3

2

--<>--~-

--0-

1946-1975CasuarinaEucalyptusFraxinus

May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr

Figure 4.2 - Comparison of mean daily potential evapotranspiration (PE) per month

estimated with Penman (1948) equation from May 2001 to April 2002, above the

canopy of three forest plantations, and the estimated by Giambelluca (1983) for the

years 1946 through 1975, adjusted for dry forest cover.

144

35

30zero extraction point 9%

field capacity 30%root depth 40 em

25 crop factor 0.9

;? 20~

~ 15

10

5

0

50

zero extraction point 13%

40 field capacity 41 %root depth 55 cm

crop factor 1.1

;? 30~

~ •20

•10 •

C. glauca

E. robusta

O...L-__'--_--'-__--'-__-'--_----'__---'--__-'--__l.....-_--'-__--'----__.L-_--'

50.,------------------------------------,

40

;? 30~

~ 20

10

zero extraction point 12%field capacity 46%root depth 50 cmcrop factor 1.0

••

F. uhdei

01-May-0201-Mar-0201-Jan-0201-Nov-0101-Sep-0101-Jul-01

O+--~--_r_--..---__._--...,--____,--~--.__---,.--.__-----,---1

01-May-01

Figure 4.3 - Water balance model calibration curves comparing estimated (line) and

measured (symbols) soil volumetric water content (VWC) for the forest stands, before

including estimates of runoff. The parameters adjusted to obtain the best fit between

the two are listed on the left upper part of each graph.

145

30

zero extraction point 9% C. glauca25 field capacity 30%

root depth 40 cm

20crop factor 0.9

~e-.

~15

10

5

0

50

zero extraction point 13% E. robusta

40 field capacity 41 %root depth 55 cmcrop factor 1.1

.--. 30~.....--0

~ 20 •

10 •0

50

zero extraction point 12% F. uhdei40 field capacity 46%

root depth 50 cmcrop factor 1

.--. 30~e-.0

~ 20 •10 •

0

01-May-01 01-Jul-01 01-Sep-01 01-Nov-01 01-Jan-02 01-Mar-02 01-May-02

Figure 4.4 - Water balance model calibration curves comparing estimated (line) and

measured (symbols) soil volumetric water content (VWC), including runoff

estimates, for the forest stands.

146

5-r--------------------------------,

4

o

-¢--- C. glauca~ E. robusta--D- F. uhdei

MayOl JunOl JulOl AugOl SepOl OctO1 NovOl DecOl Jan02 Feb02 Mar02 Apr02 May02

Figure 4.5 - Evapotranspiration estimated by the water balance method (ETWB) in

stands dominated by Casuarina glauca, Eucalyptus robusta and Fraxinus uhdei

between May 5, 2001 and April 28, 2002.

147

25

20 C. glauca stand

15

10

5

0

-5

-10

-15.--..,...~ -20EE-

o:: 20 F. uhdei stand~

I- 15W

10

5

0

-5

-10

-15

-20

0 5 10 15 20 25

PE (mm d-1)

Figure 4.6 - Comparison of half-hourly estimates between potential

evapotranspiration (PE) and canopy evaporation during daytime periods with no rain

(ETTVAR) for stands dominated by Casuarina glauca and Fraxinus uhdei, between

June and November 2001. The lines indicate equality ofETrvAR and PE.

148

3.5 ~-------------------------------,

3.0

2.5

~

'c 2.0

E.s 1.5u..(/)

~

w 1.0

0.5

0.0

--<>- C. glauca~ E. robusta-0- F. uhdei

09-Mar-02 12-Mar-02 15-Mar-02 18-Mar-02 21-Mar-02 24-Mar-02

Figure 4.7 - Daily evapotranspiration estimated by the sap flow method (ETSF) in

stands dominated by Casuarina glauca, Eucalyptus robusta, or Fraxinus uhdei in

March 2002. There were two rainfall events of 10 to 15 mm each on March 13 and

16.

149

3.0

2.5C. glauca -e- water balance

-0- sap flow

~ 2.0

'0E 1.5.s-f-w 1.0

0.5

0.0

5

E. robusta4

~ 3'0E

2.s-f-w

Q:0

5

4F. uhdei

3

'02

E.s-f-w

0

-1

May-01 Jul-01 Sep-01 Nov-01 Jan-02 Mar-02 May-02

Figure 4.8 - Comparison of evapotranspiration (ET) estimated by the water balance

(WB) and by the sap flow (SF) methods, in three forest stands in the Honouliuli

Preserve dominated by Casuarina glauca, Eucalyptus robusta or Fraxinus uhdei.

Symbols represent mean daily ET in each month and bars represent standard errors.

150

1.4

§1.2 -0- SF

1.0

~

!o 0.8ESI- 0.6UJ

0.4

0.2

0.0

13-May-01 16-May-01 19-May-01 22-May-O1 25-May-01 28-May-01

Figure 4.9 - Daily evapotranspiration (ET) in the Eucalyptus robusta stand estimated

by the water balance (WB) and the sap flow (SF) methods in May 2001.

151

C. glauca

F M ASON 0 JJM J

20

140

160 -.--------------ll~ET -Eil _c:::::J El-P-PE

~ 120E5 100..ci5.. 80Q)

"tJ

.m 60ro:5: 40

E. robusta200 -,-------------------------,

180

160

E 140

5120..ci5..100Q)

~ 802ro:5:

20

o .j-L--L.,f-'--'---t--L-.4-.L.....J.+-Jc:l..+-'----J-r-J----'--f-'-.L+...I.-J4--L.....l--+--l~-f-L_L..j

M J J A SON 0 J F M A

160 r----------------------.

140

~ 120E5 100..ci5.. 80Q)

"tJ... 60~:5: 40

20

F. uhdei

M J J A SON D J F M A

Figure 4.10 - Precipitation (P) and estimated potential evapotranspiration (PE),

evapotranspiration (ET), and interception (Ei) in the forest sites studied from May 5,

2001 to April 28, 2002. ET was estimated by the water balance method and is

represented in the graph by the whole length of the bars.

152

5. Conclusions and implications for groundwater recharge and

watershed restoration projects in Hawaii

This research aimed to primarily answer three important questions regarding

the hydrology of mesic tropical forests dominated by non-native tree species in

Hawaii: (1) Are there differences in the components of the water cycle of forests

characterized by different species? (2) How do measurements of evapotranspiration

compare to values obtained previously? and (3) Do forests dominated by different

species differ in their potential to recharge groundwater? In this chapter, I will revisit

these questions posed in Chapter 1 and will also discuss the implications of this

research for groundwater and watershed management in Hawaii.

5.1. Are there differences in the components of the water cycle of forests

dominated by different species?

The main components of the water cycle studied in this project were rainfall,

throughfall, stemflow, interception, tree transpiration, evapotranspiration, and soil

moisture. Rainfall was measured in five locations, near the forest stands studied. The

most systematic comparison among stands dominated by different species was done

for throughfall, stemflow and interception, in a study using three replicates of stands

dominated by each of four species: Eucalyptus robusta, Fraxinus uhdei, Casuarina

glauca and Grevillea robusta. The remaining components were measured in one

stand dominated by each of the first three species.

153

Throughfall represented over 95% of the water that reached the forest floor in

the Honouliuli tree plantations. On an annual basis, interception and throughfall did

not differ among stands of different species composition. However, within sections

of the preserve, throughfall, and consequently interception, was significantly different

in stands dominated by Fraxinus than in the other stands. In the northern section of

the Honouliuli Preserve, throughfall measured in two-week intervals was higher in

the Fraxinus stand than in the other stands, and, in the southern section, throughfall

measured during each rainfall event was lower in the Fraxinus than in the other

stands. Interestingly, the detection ofthis difference depended on the temporal scale

of the measurements. In the southern section, no differences among the stands were

observed in the accumulated throughfall measured in two-week intervals. This

suggests that the observed differences in throughfall among stands dominated by

different species on an event basis, although biologically relevant, are rather

insignificant when estimating the forest annual water budget or groundwater

recharge.

Stemflow was 1 to 4% ofannual rainfall in the stands studied in Honou1iuli,

and was significantly different between stands dominated by Fraxinus and Grevillea.

Stands dominated by Fraxinus generated approximately twice as much stemflow as

stands dominated by Grevillea, probably due in large part to the very low tree density

found in the Grevillea stands compared to the Fraxinus stands. Even though

stemflow usually constitutes a small part of the water cycle, in dry forests such as the

ones in Honouliuli, this water added to the system in a non-random fashion may

allow species to compete differently for water and for the nutrients in this water.

154

Tree transpiration and depth of water uptake were determined in one stand

each dominated by Eucalyptus, Fraxinus and Casuarina. There were no differences

in the transpiration of trees of same basal area among the three species. However,

stand-level evapotranspiration (ET) was almost two times higher in the stands

dominated by Eucalyptus and Fraxinus than in the stand dominated by Casuarina.

Evapotranspiration in the Casuarina stand increased by a factor of four from the

middle of the dry season until two to three months after the wet season started,

whereas in Fraxinus and Eucalyptus stands, ET showed a six-fold increase in the

same period. The high ET rates detected in Fraxinus can be attributed to the high leaf

area index of stands dominated by this species (0.5 to 2 m2m'2 higher than in stands

dominated by the other species) and to its deep pattern of water uptake. Based on the

natural abundance of stable isotopes of hydrogen, water uptake by Fraxinus trees

occurred in the soil profile deeper than 75 cm, whereas for Casuarina and

Eucalyptus, it was shallower than 40 and 60 cm, respectively. However, ET rates

were equally high in the Eucalyptus stand, when compared to the Fraxinus stand,

even though the stand dominated by Eucalyptus exhibited lower leaf area index and

shallower water uptake. This suggests that Eucalyptus probably exhibits higher leaf

specific hydraulic conductivity than Fraxinus, being able to maintain high

transpiration rates at low leaf area levels.

Soil moisture in the wet season in the stand dominated by Casuarina was

half of that in the stands dominated by Eucalyptus or Fraxinus, possibly a result of

high surface runoff. The soil moisture in the stand dominated by Fraxinus exhibited

155

the largest difference between seasons of the three stands, especially in the deeper

layers, reflecting the deeper pattern of water uptake of this species.

In sum, stands dominated by Fraxinus and by Eucalyptus exhibited higher

interception, higher leaf area index, deeper water uptake, and larger changes in soil

moisture between seasons in the root zone than stands dominated by Casuarina.

These characteristics resulted in higher ET rates in the two stands than in the

Casuarina stand, observed as the rains resumed after a long period of drought in

Honouliuli.

5.2. How do direct measurements of evapotranspiration compare to

previous estimates?

This question could not be answered by this study. The temperature variance

method chosen to measure ET failed to give reliable results. Due to the difficulty in

placing the thermocouples high above the canopy of the forests in Honouliuli, the

temperature data showed high fluctuations, resulting in extremely negative or

extremely positive estimated ET values.

Potential evapotranspiration (PE) estimated from data collected in Honouliuli

was up to 25% higher than estimated by Giambelluca (1983), indicating that ET could

have been underestimated in his study, which calculated ET based on PE.

Giambelluca's study was the most detailed study of the water balance of the Pearl

Harbor-Honolulu basin, where the Honouliuli Preserve is located, and was the basis

for subsequent groundwater recharge estimates for the southern Oahu area (Shade and

Nichols 1996).

156

Even though the few dry areas like Honouliuli do not substantially affect the

water balance of the basin, it is possible that ET higher than predicted occurs in

wetter areas that receive additional non-solar energy. Ekern (1983), for example,

found ET to be at least 19% higher than predicted through net radiation in high

rainfall areas of the Manoa Valley, and attributed that to the positive advection from

the urban areas nearby. A precise estimate ofET in southern Oahu is needed because

it is the main input in models estimating groundwater recharge to replenish the water

supply for greater Honolulu.

5.3. Do forests dominated by different species differ in their potential to

recharge groundwater?

The estimated values of groundwater recharge for stands dominated by

Casuarina, Eucalyptus and Fraxinus for the period between May 5, 2001, and April

27,2002, were 0, 0, and 11 mm, respectively. The spatial variation in the soil

moisture measurements and the calibration of the model may have resulted in an error

of30 to 40% in the groundwater estimates. The short duration of this project during

the end of a very dry period must have yielded values lower than usual, even though

the total annual rainfall was within the long-term annual rainfall range for the area

(Giambelluca et al. 1986). However, these values are much lower than the mean

annual recharge of 500 mm estimated by Giambdluca (1983) for the same area. The

low values of groundwater recharge found in this study deviate from the original

expectation that the reforestation efforts in the early 1900s in the Waianae Mountains

would increase groundwater recharge.

157

The low rate of groundwater recharge found in the forest stands studied

resulted from different aspects of each stand. In the Eucalyptus stand, the nil

groundwater recharge was due to high ET rates, whereas in the Casuarina stand, it

was due to high surface runoff. The Fraxinus stand showed slightly higher

groundwater recharge, with very low runoff values and high ET rates. Even though

there was only one replicate of the stands dominated by each species, the differences

in groundwater recharge among the stands can be attributed to a certain point to their

different species composition. The dominant species confers a particular structure to

the forest, such as leaf area, depth of water uptake, understory development, etc, that

may result in different ET or runoff rates. These two components of the water

balance have to be taken equally into account when managing groundwater recharge.

The Casuarina stand, for example, showed very little interception or transpiration,

resulting in a very low annual ET rate. However, the high runoff generated by this

stand left no water remaining for groundwater recharge. The structure of the stands

studied is very similar to other stands dominated by each of these species throughout

the Honouliuli Preserve (personal observation, Garrison 2003). The most striking

characteristics of the stands dominated by Casuarina, for example, are the extremely

low species diversity, lack of understory, and very thick layers oflitter and roots on

the top of the soil. The concentration of roots at the top of the soil and the lack of

understory could even be a consequence, and not a cause, of high runoff, but still

suggest that high runoff may be produced by these other stands. Similarly, stands of

Fraxinus throughout the preserve exhibit high leaf area index, high density of trees,

well developed understory and deep water uptake, which resulted in high ET and low

158

runoff rates. The Eucalyptus stands commonly exhibit high basal area, some

understory development, and moderately deep water uptake, which, together with

relatively high tree transpiration rates, result in relatively high ET rates.

The indication that forest species composition may have an effect on

groundwater recharge should be tested in a larger scale. The water balance method

appeared to yield reasonable results for the water balance of each stand, using simple

measurements such as micrometeorology in a reference site, and soil moisture within

the forest. These measurements would be relatively easy to take in forests throughout

the southern Oahu watersheds, and could yield more reliable estimates of

groundwater recharge, and useful information for reforestation plans and watershed

management.

5.4. Implications of this research for groundwater recharge and watershed

restoration in Hawai'i

Fresh water is the most important natural resource on oceanic islands,

especially those such as Oahu that have a high population density. Having an

accurate estimate of groundwater recharge is crucial to the economic and social

development of the island. The recharge estimates obtained in this dissertation

suggest that the forests widely planted in the Waianae Mountains to protect and

restore the watersheds actually facilitate very little or no groundwater recharge. Even

though the year when this study was conducted included the end of a long drought,

the total rainfall (591 to 665 mm) was within the long term annual rainfall range (540

to 750 mm, Giambelluca et al. 1986).

159

In addition to a possible overestimation of groundwater recharge by previous

studies (Giambelluca 1983, Shade and Nichols 1996), a disproportionate increase in

water consumption in relation to population growth on Oahu may result in an earlier

than projected shortage of groundwater for the island. Giambelluca (1983), for

example, estimated that the groundwater in the principal source of water supply for

the greater Honolulu area was sufficient to support a population increase of

approximately 450,000 from its number in 1983. The Honolulu County resident

population was 789,000 then, and is projected to be 1,030,000 by the year 2025

(DBEDT 2004), an increase of241,000 people. These projections generate an

optimistic scenario, where groundwater withdrawal would still be below its maximum

capacity for decades to come. However, water use on Oahu has increased at a much

higher rate than population increase. The Honolulu County population grew from

804,294 in 1985 to 876,156 in 2000, an increase of9% (DBEDT 2004). In the same

period, total fresh groundwater use in the Honolulu County increased from 358

million gallons per day (mgd) to 433 mgd, or 21 % (USGS 2004, Hutson et al. 2004).

In view of this, watershed and groundwater management projects on Oahu

need to be seriously reviewed. While reducing water consumption requires a lot of

political and economic motivation, increasing groundwater recharge by managing the

vegetation in the natural areas is a more viable alternative. The planting of fast

growing introduced species in the early 1900s was a decision based on the belief that

these species would reduce the high erosion rates and increase groundwater recharge.

Seventy years later, these forests maintain relatively high ET rates, some of them high

runoff, and most likely did not improve groundwater recharge. Before it was

160

deforested, the mesic Honouliuli area was probably dominated by shrubs and short

trees, which were likely more conservative water users than the fast-growing trees

planted in the reforestation efforts. When choosing species for reforestation, it is

necessary to take into account their effect on the water cycle, preferably by selecting

species that will impart a combination of low ET and low surface runoff rates to the

forest. These species, when planted in monospecific stands, probably provide a well

developed understory, average levels of leaf area index, average depth of water

uptake, and low transpiration rates.

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