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NATURAL RESOURCES SYSTEMS PROGRAMME PROJECT REPORT1

DFID Project Number

R8088A

Report Title

Using the PT model to determine appropriate management for maize production. A case study of Fulwe Village in Morogoro District for Morogoro District.

Annex B19[2] of the Final Technical Report of project R8088A.

Report Authors

Pangapanga, C.P., Marijani, B.J., Tumbo, S.D., Mapulila, T. and Rwehumbiza, F.B.

Organisation

SWMRG, Sokoine University of Agriculture, Tanzania

Date2005

NRSP Production System Semi Arid

1 This document is an output from projects funded by the UK Department for International Development (DFID) for the benefit of developing countries. The views expressed are not necessarily those of DFID.

Case Study Two

Morogoro District – Fulwe Village

Using the PT Model to Determine Appropriate WaterManagement for Maize Production: A Case Study of

Fulwe Village in Morogoro District

C. P. Pangapanga1, B. J. Marijani2, S. D. Tumbo3, T. Mpulila3, F. B. Rwehumbiza3

1Agricultural and Livestock Development Office, Morogoro District Council 2Agricultural and Livestock Development Office, Mvomero District Council

3Soil-Water Management Research Group, Sokoine University of Agriculture

Background

Fulwe village is located in Mikese ward, some 30 kilometres east of the Morogoro

Municipality, along the Morogoro - Dar es Salaam highway. It is located at longitude

37º53’60’’ East, and the latitude is 6º46’ south. The annual rainfall ranges from 700mm

to 1000 mm. The short rainy season (Vuli) starts in mid-October and ends in December

while the long rains (Masika) start in February and ends in mid May. The dry season

extends from June to October. The annual average maximum and minimum temperatures

are 26ºC and 21ºC respectively. Soils are acidic lithosols and ferralitic latosols with

deeper deposits of ferruginous sandy clay. Fulwe villagers depend mostly on rainfed

agriculture and maize is the main staple food and also one of the major sources of

income. Other crops cultivated include beans, soybeans and horticultural crops.

Farmers in the village have been facing a problem of good and poor maize yields even in

the same season. The reasons for the mixed results were not well known by the

agricultural extension officers serving the area. Some of the reasons that were being cited

include inadequate crop husbandry, non-use of certified maize seeds and improper

planting dates. The agricultural extension officers thought the problems were related to

improper planting dates. That is the variable yields among farmers were caused by some

farmers planting at the start of the rainy season and some in the middle and others very

late in the rain season. It was noted from the agricultural extension officers that they were

unable to successfully advise farmers on proper planting dates. In some cases they

advised farmers to plant once the rain started, but still farmers ended up with lower yields

PT Model Help Office 14

Sokoine University of Agriculture

Case Study Two


compared to those who planted a bit late. The main issue that confronted agricultural

extension officers, was therefore on finding tools or methods that will assist them in

identifying a proper planting window for farmers in Fulwe village.

It is against this background that the PT Model, which is an agro-hydrological software,

was therefore identified by the agricultural extension officers as a tool that could assist in

the identification of the proper planting window by simulating maize yields for different

planting dates in Fulwe village.

Description of the PT Model

PARCHED-THIRST stands for Predicting Arable Resource Capture in Hostile

Environments During the Harvesting of Incident Rainfall in the Semi-arid Tropics.

PARCHED-THIRST model is a user-friendly, process-based model, which combines the

simulation of hydrology with growth and yield of a crop on any number of distinct or

indistinct runoff producing areas (RPAs) and runoff receiving areas (RRAs). It is a

distributed model, which simulates the rainfall-runoff process, soil moisture movement

and the growth of sorghum, rice, maize and millet in response to daily climate data. The

model includes the simulation of rice and macro-catchment systems up to the hillside or

small catchment scale. The schematic diagram of its components is shown in Figure 1.

The model allows the user to enter dates for the start of the seasons (Vuli and/or Masika)

and for the sowing dates. Alternatively the software itself can determine the best planting

date. Furthermore, the software provides daily outputs of soil-moisture values for

different layers of soils, dry matter accumulation, grain filling and other variables.



Case Study Two


Figure 1: Interaction between the components making up the PARCHED-THIRST

model.

DATA PRE-PROCESSORS

USER

User

ClimateGenerator

RainfallDisaggregator

PedotransferFunctions

RunoffRouting

InfiltrationModel

RUNOFF MODEL

ModifiedORYZA_W

ModifiedPARCH

CROP MODEL

Daily weather

Rainfall intensity

Soil waterparameters Modified

LOWBAL

Piston Flow

Fl

SOIL WATER MODEL

FiniteDifference

Output crop and hydrological data

Input parametersand data

Objectives of the study

The main objective of the study was, to investigate the reasons for poor maize yield and

determine the appropriate management options that can improve maize production in

Fulwe village, Morogoro district.

The specific objectives included the following:

To investigate the effect of planting dates on maize yield in Fulwe village using the

PT Model.



Case Study Two


To simulate the effect of rainfall pattern on dry matter and on grain accumulation

using the PT Model.

Methodology

The main method employed in studying the problem was yield simulation using PT

model. This method was supplemented with field visit by agricultural extension workers

and PT Help office staff. The field visit assisted in understanding the problems faced by

farmers in the village.

Field visit

Before the visit, the agricultural extension officers organized a village meeting with

Fulwe village farmers. The meeting was attended by village leaders and village extension

workers in addition to agricultural extension officers from the Morogoro and Mvomero

Districts and staff from the PT Help office. Figure 2 below shows some of the farmers at

Fulwe village in addition to researchers from PT Help office – Sokoine University of

Agriculture, agricultural extension officers from Morogoro and Mvomero Districts and

village extension worker outside Fulwe village office.

Figure 2. Fulwe village farmers



Case Study Two


During the field visit, farmers were given opportunities to express the problems they are

facing with regard to maize production (Figure 3). The farmers reported that, agriculture

activities at Fulwe are seriously affected by poor rainfall, poor mechanization techniques,

lack of certified maize seeds and soil salinity.

Figure 3: One of Fulwe village farmers explaining problems facing their Agriculturalactivities

Input Data Collection

Weather data were obtained from Kingolwira Prison weather station and covered the

period from 1999 to 2004. The parameters collected were daily rainfall, maximum and

minimum temperature, humidity, radiation, wind speed and evaporation. Before running

simulations the data were formatted to the PT input standard. Soil profile data used was

also taken from Kingolwira (because of similarity to the soils found at Fulwe and

closeness to Fulwe village) and maize variety (TMV1) data was used.

Data Analysis

Simulations for different planting dates were run and summary and daily output files

were saved in the PT output folder. Output parameters analyzed were daily, seasonal and

cumulative rainfall, maize yield, soil moisture, dry matter accumulation and grain weight

gain.



Case Study Two


Results and Discussion

Rainfall Patterns

The important growing window for maize in Fulwe is between January and May. Figure

4 shows daily rainfall trend over the long rainy season for different years.

1999 2000

2002 2003

0

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rain

fall(

mm

)

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Dai

ly ra

infa

ll(m

m)

Figure 4: Daily rainfall patterns for the years 1999, 2000, 2002, and 2003.

These charts show a consistent pattern of dynamic two dry-spells between January and

first week of March. Dynamic here means the actual dates of occurrence of the dry spells

are not known. Farmers in Fulwe normally plant their maize between mid January and

mid February. The dynamic dry-spells also means the start of the season is highly

variable. It is therefore possible that some of the maize face moisture stress which affect

the final yield. Furthermore, the area gets good rains between mid March and April.



Case Study Two


There is poor rainfall in May in terms of low rainfall and frequent dry spells. These

characteristics have a significant effect on the final yield because most of the grain

weight accumulation occurs in May.

Effects of planting dates on maize grain yields at Fulwe village

Maize yield was simulated for different planting dates from 1999 to 2004. The results are

summarized in Figure 6. The best planting dates that resulted with higher yields were

between 20 January and 12 February. The average yields were between 0.45 and 0.49

t/ha and maximum yields ranged between 0.61 and 0.78 t/ha. However, the maximum

yields were not occurring only on dates with maximum yield (around February 5) instead

they occurred anywhere between 20 January and 12 February (a three-week window).

With regard to simulated yields, the simulated maize yields agreed with those reported by

farmers, which averaged between 0.5 and 0.7 t/ha. Therefore it was observed that

planting dates might not be the primary or the only reason for the low yields. It was

therefore necessary to carry out an analysis of dry matter accumulation.

0.00

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n-05

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Dates

Ave

rage

Yie

ld(t/

ha)

Figure 6: Average yields for different planting dates



Case Study Two


Dry matter accumulation

Results of dry matter accumulation are shown in Figure 7 and Figure 8. The results

indicate that dry matter accumulations at different planting dates were not significantly

different for both 1999 and 2000. The same was observed on the other two years.

Variation in dry matter accumulation from one year to another, which is normal, was

observed in years 1999 and 2000. This was attributed mainly to the little amount of

rainfall received in the year 1999. However, dry matter accumulation for 1999 was lower

than that for year 2000 due to the following reasons:

The year 1999 had both little annual and seasonal rainfall compared to year 2000. For

example, the seasonal rainfall, as computed using the PT model, for 1999 was 441mm

versus 514mm in 2000, while total annual rainfall was 761mm for 1999 versus

1011mm for 2000.

The year 1999 had longer dry spells during the growing period as compared to that of

2000. For example, the year 1999-experienced dry spells of 16 days from February 18

to 5 March; while for the year 2000 there were only 5 days of dry spells within the

same period.

0

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Date

Dry

Mat

ter A

ccum

ulat

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(t/ha

)

1-Feb 6-Feb 11-Feb

Figure 7: Dry matter accumulation in 1999



Case Study Two


Since our interest was to assess if the different planting dates could affect the dry matter

accumulation, the difference was not apparent or clear as shown in Figures 7 and 8. The

science of crop development shows that a crop such as maize is not affected significantly

by water stress, during its early days of growth. The most critical stage is at flowering

and grain filling stages. This called for further investigations into the grain filling stage.

0

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ccum

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(t/ha

)

26-Jan 1-Feb 6-Feb

Figure 8: Dry matter accumulation 2000

Grain weight accumulation

For maize, and many other crops, grain filling stage is one of the critical periods for water

requirements. Therefore availability of water at this period would increase partitioning of

dry matter to grain leading to good crop yield. Since dry matter accumulation could not

show the significant difference observed in the maize yield, analysis of grain weight

accumulation was necessary.

Figure 9 and 10 show four maize grain filling charts for years 1999, 2000, 2002 and 2003

on a daily time step. Each chart has three lines representing three different planting dates.

It is clear from the charts that each date responded differently. All charts have zero values

up to late March or early April when the lines start to increase (grain filling start). The

earlier the start of grain filling the earlier was the planting/sowing date. Therefore, the

start of grain filling is fixed for a particular variety of maize. However, the start of the



Case Study Two


grain filling stage and subsequent days are very important to the final yield. For example,

the comparison of grain filling rate for maize planted on 1st February and those planted

on 6th February show that at the first few days of grain accumulation the maize planted on

1st February was being affected by very short dry spells compared to maize planted on 6th

February. The grain filling was severely affected from 10th February because of a much

longer dry-spell. The same dry-spell period showed that the rate of filling affected most

the older plants than the younger ones since the growth rate of the maize planted on the

11th February was higher than that planted either on 1st or 6th February.

The second chart (year 2000) in Figure 9 shows a steady increase in grain weight

compared to the 1999 chart, where the increase is step-wise. The steeper slopes for maize

planted on 26th January and 6th February indicates a good supply of water during the start

of grain filling. There was a dry-spell during the start of the grain filling stage for maize

planted on the 1st February.

The 2002 chart in Figure 10 shows that all the lines are steadily increasing without any

cross-over and the first line (21-Jan) having a steeper slope and therefore higher yield

than the other two lines. Under normal circumstances, when the rainfall distribution is

good even during grain filling stage, this is supposed to happen. The reason for the lower

yields for the maize crop planted on 28th January and 1st February is the decrease in the

rainfall amount toward the end of the rainfall season. This is contrary to the 2003 chart in

Figure 10 because there is a cross-over between the 1st February and 11th February lines.

The maize planted on the 1st February (1-Feb) suffered severe water stress at the start of

grain filling stage. Maize planted on the 11th February (11-Feb) did not suffer water stress

because the rainfall came on time such that the rate of grain filling was very high. The

intersection of the grain filling lines was caused by the fact that the younger plants tend to

have the highest growth rate compared to the older ones under the same and good

environmental conditions (no water stress in this case). Therefore, when the water stress

came, already the 11-Feb maize had achieved good yield and the 1-Feb grain

accumulation had already been limited because of the previous dry-spell.



Case Study Two


0

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Gra

in W

eigh

t (t/h

a)

6-Feb 1-Feb 11-Feb

Figure 9: Maize grain filling for 1999 & 2000 season

0

0.1

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2-Ja

n-02

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21-Jan 26-Jan 1-Feb

0

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n-03

Date

Gra

in w

eigh

t (t/h

a)

1-Feb 11-Feb 21-Feb

Figure10 Maize Grain filling for 2002 and 2003 seasons

Therefore, the low and variable maize yields that farmers were experiencing in the village

were due to water stress during grain filling stage. Late planting also can result into lower

yields if a normal rainfall pattern occurs, which means decrease in the amount of rainfall

towards the end of the season.

Conclusions and Recommendations

Conclusions

Given soil characteristics and weather data of Kingolwira prison weather station, it

was possible to use the PT Model to determine appropriate management practices that

could increase maize yields. The practices include among others, conservation

agriculture and rainwater harvestingPT Model Help Office 24


Case Study Two




Dry matter accumulations for maize planted on different planting dates was not

significantly different for any particular year.

It was observed that grain weight (t/ha) differed for maize planted on different

planting dates. The main reason leading to the differences were due to dry-spells

during the grain filling stage.

Recommendations

Farmers at Fulwe village should practice conservation agriculture that will assist to

conserve soil moisture.

Also farmers should practice rainwater-harvesting (RWH) with storage techniques.

The stored water can later be used at the grain filling stage, which is the critical stage

of moisture requirements for maize crop.

Further testing/ using the PT Model to investigate the cause of poor maize crop yields

in other locations.

References

http://www.mapsofworld.com/lat_long/tanzania-lat-long.html

Mzirai, O.B.,T. Bwana, S.D. Tumbo, F.B. Rwehumbiza and H.F. Mahoo (2004), PARCHED THIRST Model Handbook, SWMRG – PT Help Office.

Robin M., S. William (2002), Crop-Soil Simulation Models Applications in Developing Countries, CABI Publishing, UK

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