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Estimation of Spatial Actual Estimation of Spatial Actual Evapotranspiration to Close Water Evapotranspiration to Close Water

Balance in Irrigation SystemsBalance in Irrigation Systems

1- Key Research Issues2- Evapotranspiration through Remote Sensing3- SEBAL Applications4- Data Requirements and Way Forward

Mohsin Hafeez and Shahbaz Khan

CSIRO Land and Water, Wagga Wagga

CSIRO LAND and WATER

Water losses and gains are part of Water losses and gains are part of the water cyclethe water cycle

gain

loss

ET is important at all scales

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5125

14

17

3924

15

1096

7

1217

2536

22

194

1181

21

466

2038

-99590

164282386

#

Wagga Wagga

#

Narrandera

#

Darlington Pt

#

D/S Hay W eir

#

D/S Balranald Weir

Inflow / Outflow (GL)

Diversions (Gl)

Evaporation (GL)

Net Change (GL)

1880

1945

1830

2216

#

Burrinjuck Dam

#

Blowering Dam

Murrumbidgee System Water Account Murrumbidgee System Water Account (1991)(1991)

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Key Research IssuesKey Research Issues

ET is coupled mass/energy process, linking the energy and water cycles

Estimation of ET is critical for on-farm and regional models in irrigation systems

ET is the largest water balance component after rainfall and irrigation input

Water quantification (i.e. productive and non-productive use) is important for irrigated agriculture.

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Why determine spatial ET?Why determine spatial ET?

Classical methods will measure ET at the field scale.– Penman - Monteith (PM) method

Need to have accurate estimates of spatially distributed ET at multi-scales.

• Remote sensing provide spatially distributed actual evapotranspiration– Accurate and cheap for large landscape systems

– Many RS algorithms developed in last decades

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In-situ measurement (Bowen ratio tower, Lysimeters, etc.)

Air-borne measurement (fluxes)

Satellite measurement

– High Spatial Resolution (ASTER and Landsat)

– High Temporal Resolution (MODIS and NOAA-AVHRR)

Modelling Approaches (plant to catchment)

Current state-of-the-art Approaches for Current state-of-the-art Approaches for measuring ETmeasuring ET

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1. Empirical direct methods

- Characterizing crop water status through the cumulative temperature difference (Ts-Ta)

2. Residual methods of the energy budget

– Combination of empirical relationship and physical modules (SEBAL, & SEBS)

3. Deterministic methods

– Soil-Vegetation-Atmosphere Transfer models (SVAT)

4. Vegetation Index methods

Methods for Quantification of ET Methods for Quantification of ET through RSthrough RS

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Methods Advantage DisadvantageSimplified Relationship

Operational from local to regional scale

Spatial variation of coefficients

Inference models (Kc f(NDVI))

Operational if combined with ground measurements

Requires calibration for each crop type; Kc varies according to water stress

Empirical-physical (SEBAL,….)

Operational, low cost, need no additional climatic data.

Requires presence of wet and dry pixels. Some empirical relationship

Deterministic (SVAT,….)

Estimation of intermediate variables (LAI), links with climate, hydrological models, assimilation to find some parameters

Requires more parameters ± easy to estimate. Requires accurate remote sensing data

models (PBL, …)

Estimation of climatic data, lateral exchange accounted, possible to stimulate landuse modification

Complex and high cost for CPU, only short simulation for high spatial resolution

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Surface Energy Balance Algorithm for Land (SEBAL); thermodynamically based model, which partitions between sensible heat flux and latent heat of vaporization flux.

The core of SEBAL is based on the assumption that at hot/dry pixels, all energy flux into the atmosphere is sensible heat and at cool/wet pixels all is latent heat.

SEBAL robustly interpolates values at intermediate pixels but is very sensitive to the right choice and flux values at the extremes.

SEBAL

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Surface Energy BalanceSurface Energy Balance

ET is calculated as a “residual” of the energy balance

ET = R - G - Hn

Rn

G (heat to ground)

H (heat to air) ET

The energy balance includes all major sources (Rn) and consumers (ET, G, H) of energy

Basic Truth: Evaporation consumes Energy

(radiation from sun and sky)

Adapted from IDAHAO

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The energy balance components

Energy Balance Equation

Rn = Go + H+ λE

Evaporative Fraction

Daily ETa

Seasonal ETa

SEBAL Derived Actual Evapotranspiration

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ALBEDO NDVI

Surface Temperature

Emissivity

Albedo

Pre-processing of satellite image

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Study Area (Lower Murrumbidgee)Study Area (Lower Murrumbidgee)

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24 October 1990

Land use Classification for Lower Land use Classification for Lower MurrumbidgeeMurrumbidgee

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Actual ET Distribution for Lower Murrumbidgee

24 October 1990

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0

10000

20000

30000

40000

50000

60000

Water Bodies RedgumForest

Wetland AgricultureCrops

Lignum Fallow Land Soil Others

Land Use Classes

Are

a (H

a)

0

100

200

300

400

500

600

ET (M

L/d)

Area ET24 October 1990

ET from different land use classes ET from different land use classes using Landsat 5 TM sensorusing Landsat 5 TM sensor

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Ground based – temporal variation:– Micro-meteorology and fluxes

– Calibration data (soil temperature, LAI, NDVI, LST, albedo, and net radiation)

– Vegetation description and surface roughness

Airborne based – spatial variation:– Surface conditions - soil moisture, LST, NDVI, LAI, albedo,

– Surface fluxes

– Low flying over irrigation supply channels

Satellite based - model requirements:– NDVI, LAI, LST, albedo, emissivity, net radiation, surface roughness

– Other data (rainfall, soil moisture, fluxes….)

Data RequirementsData Requirements

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Uncertainty analysis of different input parameters for remote sensing based ET models

Validation of remote sensing derived ET by ground and airborne fluxes.

Customization of remote sensing based algorithms for ET estimation for Australian landscape.

Integration of spatial estimation of seasonal ET for water balance studies using system level approach

Flexible for any irrigation system

Way ForwardWay Forward

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Working across different scales with universities and other partners as

one CSIRO

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Seasonal Evapotranspiration (ETSeasonal Evapotranspiration (ETseasonalseasonal))

Step 1: Decide the length of the season Step 2: Determine period represented by each satellite image Step 3: Compute the cumulative ETr for period represented by

image. Step 4: Compute the cumulative ET for each period

(n = length of period in days) Step 5: Compute the seasonal ET.

ETseasonal = ETperiod

n

irperiodrperiod i

ETFETET1

24