Calibration and Evaluation of Three CROPGRO Models under Different Water Regimes in a

Semi-Arid Tropical Environment

Kindie TesfayeHaramaya University, Ethiopia

16 Dec 2008

Outline of presentation

Introduction Ethiopia Subject

Methodology Results Conclusion

Introduction

The topic presented is result of research conducted in Ethiopia

Ethiopia is one of the ancient civilized countries

Has its own calendar (Julian) and Alphabets Federal administration (14 states)

Country profile Location: 8o 00 N, 38o 00 E Area: 1.13 million sq km (437,794 sq miles) Elevation: -125 to 4620 m Population: 75 million (UN, 2007) Capital: Addis Ababa Major languages: Amharic, Oromo, Tigrinya, Somali, English

(schools) Major religions: Christianity, Islam Main exports: Coffee, hides, cereals, oilseeds, grain legumes,

beeswax, sugar, cotton, cut flowers, livestock products Natural recourses: reserves of gold, platinum, copper, potash,

natural gas, petroleum, hydropower Tourist attractions: National game reserves (parks), historical

places, the oldest human fossils found (e.g. Lucy-3.18 m yrs old).

Endemic Animals and Plants

Chilada Baboon Walia Ibex23 endemic birds

Red fox

Mountain Nyala Colobus Monkey Oryx Spps.

Many plant genetic resources

Country profile-historical places

Axum Stelle- > 2000 yrs old

Blue Nile Water Falls

Sofamar Natural cave

Axum Zion- the oldest church Fasilede Palace –built in 16th C

Lalibela rock hewn churches-built in the 12th C.

Negash Mosque- 2000 yrs old

Challenges

Climate variability Recurrent drought Crop failures Deforestation Soil Degradation

Challenges… Almost half of the country is in the semi-arid climate belt Agricultural decision making is difficult

Climate variability Climate change Poor research and extension coverage lack of interdisciplinary approach

Grain legumes (drybean, chickpea, cowpea) are relegated to marginal areas

the majority of the production of these crops comes from the semi-arid parts of the country

Crop models could play an important role in managing agricultural production in the these areas because:

Involve integrated approach (climate, soil, crop, management) at once

fast results

Inexpensive

The CSM-CROPGRO model has been used to study and evaluate several production problems including:

climate change (e.g. Mera et al., 2006; Challinor and Wheeler, 2008)

spatial yield variability (Paz et al., 2001)

water related constraints (e.g. Ruiz-Noueira et al., 2001)

plating date and cultivar selection ( Cooper et al., 2006)

plant population and fertilizer interactions (Meirles et al., 2002)

optimum irrigation optimization (Faria et al., 1997; Heinemann et al., 2000).

Objective

To calibrate and evaluate CROPGRO-drybean, chickpea and cowpea under three water regimes in a semi-arid tropical environment

Methodology

Site: Dire Dawa latitude 9o6’N longitude 41o8’ E altitude 1197 m

Season: Three seaosns Dec, 2001-March, 2002 April-July, 2002 Oct, 2002-March, 2003

Treatments: Three water regimes Well-irrigated control (C) Mid-season water deficit (MS) Late-season water deficit (LS) Three crops (drybean, chickpea, cowpea)

Design: Split-plot in RCBD (WR: main plot; Water regimes: main-plot; Crops: sub-plot

Data collection Phenology Growth, Yield & YC Soil water Physiology (PS, SC, LWP) Canopy and soil temp. Radiation interception Weather Soil (initial, profile) Crop management

Methodology… Data organization for DSSAT format

data were organized and all the required files created (Soil.Soil, WTH files, Xfiles, A files, T files)

Calibration the 2001/2003 well-irrigated treatment of the respective spps. Stepwise calibration followed

First phenological parameters using Gencalc Growth and yield: sensitivity analysis using the data in the Tfiles

Evaluation Comparing simulated and measured phenology, growth and yield

parameters with using RMSE MAD CV (%) Willmot’s Index of agreement (d) Coefficient of determination (R2)

Results-Calibration

Genetic coefficients Drybean Chickpea Cowpea Critical short day length (h) 12.17 9.90 10.82 Slope of relative response to photoperiod (h-1) 0.00 -0.143 0.020 Time from emergence to flower appearance (pda) 33.10 33.00 32.40 Time from first flower to first pod (pda) 2.00 8.00 2.50 Time from first flower to first seed (pda) 8.21 8.64 4.25 Time from first seed to physiological maturity (pda) 26.40 46.00 27.60 Time from first flower and end of leaf expansion (pda) 15.10 32.21 16.50 Maximum leaf photosynthesis (mg CO2 m

-2 s-1) 1.44 1.19 1.19 Specific leaf area (cm2g-1) 183.00 138.10 150.00 Maximum leaf size (cm2) 133.00 10.00 240.00 Maximum fraction of partitioning to seeds and shell 0.90 0.60 0.95 Maximum weight per seed (g) 0.276 0.352 0.171 Seed filling duration (pda) 9.75 17.90 16.74 Seeds per pod (no. pod-1) 7.30 2.00 11.05 Pod addition duration (pda) 9.40 11.00 14.60 Shelling percentage 78.00 85.00 77.70 Fraction protein in seeds (g g-1) 0.235 0.216 0.300 Fraction oil in seeds (g g-1) 0.030 0.048 0.065

Table 1. Calibrated genetic coefficients of drybean, chickpea, cowpea using data from a well-irrigated experiment

Result-Calibration…

RMSE = 0.59; d = 0.95

0.0

1.0

2.0

3.0

4.0

5.0

6.0

0 20 40 60 80 100 120

LA

I

SimulatedMeasured

Drybean

RMSE = 0.26; d = 0.99

0.0

1.0

2.0

3.0

4.0

5.0

6.0

0 20 40 60 80 100 120

Days after planting

LA

I

Cowpea

RMSE = 0.35; d = 0.97

0.0

1.0

2.0

3.0

4.0

5.0

6.0

0 20 40 60 80 100 120

Days after planting

LA

I

Chickpea

Results-Calibration…

BM (RMSE = 1083; d = 0.99)PW (RMSE = 405; d = 0.99)

0

4000

8000

12000

16000

0 20 40 60 80 100 120

Dry

w

eig

t (

kg h

a-1

)

Simulated-BMMeasured-BMSimulated-PWmeasured-PW

Drybean

BM (RMSE = 513; d = 0.99)PW (RMSE = 341; d = 0.99)

0

4000

8000

12000

16000

0 20 40 60 80 100 120

Days after planting

Dry

wei

gt

(kg

ha

-1)

Cowpea

BM (RMSE = 375; d = 0.99)PW (RMSE = 391; d = 0.95)

0

4000

8000

12000

16000

0 20 40 60 80 100 120

Days after planting

Chickpea

Results-Calibration…

Parameter Drybean Chickpea Cowpea

S M S M S M

DTF (dap) 42 42 53 53 45 45

DTFP (dap) 51 NA 57 NA 47 48

DTFS (dap) 51 51 59 57 63 NA

DTPM (dap) 104 105 104 104 99 100

GY (kg/ha) 1767 1765 2553 2537 4177 4122

SN (m-2) 593 591 1191 NA 1820 1809

SW (g/unit) 0.30 0.30 0.21 0.23 0.23 0.24

SN per pod 2.01 2.00 11.10 11.00 7.40 7.40

ABM (kg/ha) 6296 6406 6230 6264 11240 11457

LAImax 2.94 2.98 3.65 3.65 4.1 4.1

HI 0.28 0.28 0.41 0.41 0.37 0.36

Shell perc. 86.1 86.0 78.7 NA 78.5 79.3

Results-Model Evaluation1. Soil water

Chickpea-MS

0.00

0.10

0.20

0.30

0.40

0.50

0 20 40 60 80

Days after planting

So

il w

ater

(cm

3 cm

-3)

DUL

DLLRMSE = 0.025; d = 0.93

Chickpea-LS

0.00

0.10

0.20

0.30

0.40

0.50

0 20 40 60 80 100

Days after planting

RMSE = 0.023; d = 0.94

Beans-MS

0.00

0.10

0.20

0.30

0.40

0.50

0 20 40 60 80 100

So

il w

ater

(cm

3 cm

-3)

MeasuredSimulated

DUL

DLL

RMSE = 0.029; d = 0.89

Beans-LS

0.00

0.10

0.20

0.30

0.40

0.50

0 20 40 60 80 100

RMSE = 0.034; d = 0.85

Results-Model Evaluation…

Cowpea-MS

0.00

0.10

0.20

0.30

0.40

0.50

0 20 40 60 80 100

Days after planting

So

il w

ater

(cm

3 cm

-3)

DUL

DLL

RMSE = 0.026; d = 0.92

Cowpea-LS

0.00

0.10

0.20

0.30

0.40

0.50

0 20 40 60 80 100

Days after planting

RMSE = 0.031; d = 0.90

Results-Model Evaluation…

Mean Evaluation statistics

S M MAD RMSE CV(%) d

Drybean 45.0 45.9 0.88 1.5 3.2 0.95

Chickpea 40.6 41.6 1.0 1.3 3.2 0.69

Cowpea 49.3 50.4 1.9 1.9 3.8 0.98

2. Days to flowering (dap)

Results-Model Evaluation…

Species WR Mean Comparison statistics

S M MAD RMSE CV (%) d

Drybean C 95 93 2.0 2.8 3.1 0.91

MS 94 91 7.0 7.1 7.8 0.75

LS 89 79 10.3 10.4 13.2 0.58

Pooled 92 87 7.0 7.8 9.0 0.77

Chickpea C 98 94 3.5 4.3 4.6 0.73

MS 87 78 9 11.7 14.9 0.66

LS 89 79 10.3 10.4 13.2 0.58

Pooled 90 82 8.0 10.0 12.1 0.71

Cowpea C 99 96 4.0 4.0 4.2 0.77

MS 95 88 7.7 7.9 9.0 0.68

LS 94 83 11.0 11.1 13.4 0.51

Pooled 96 88 8.0 8.6 9.8 0.66

3. Physiological maturity

Results-Model Evaluation…4. Growth-drybean

C (RMSE = 0.75; d = 0.92) MS (RMSE = 1.0; d = 0.83) LS (RMSE = 1.2; d = 0.85)

0.0

1.0

2.0

3.0

4.0

5.0

0 20 40 60 80 100 120

Days after planting

LA

I

Simulated-MS Measured-MSSimulated-LS Measured-LSSimulated-C Measured-C

LAI

C (RMSE = 1697; d = 0.96)MS (RMSE = 1113; d = 0.92)LS (RMSE = 1429; d = 0.95)

0

2000

4000

6000

8000

10000

12000

20 40 60 80 100 120

Bio

mas

s (k

g h

a-1)

Biomass

C (RMSE = 757; d = 0.93)MS (RMSE = 459; d = 0.82)LS (RMSE = 763; d = 0.87)

0

1000

2000

3000

4000

5000

6000

20 40 60 80 100 120Days after planting

Po

d w

eig

ht

(kg

ha

-1)

Pod growth

Results-Model Evaluation…4. Growth-chickpea

C (RMSE = 848; d = 0.99)MS (RMSE = 484; d = 0.99)LS (RMSE = 706; d = 0.98)

0

2000

4000

6000

8000

10000

12000

20 40 60 80 100 120

Bio

mas

s (k

g h

a-1)

Biomass

C (RMSE = 775; d = 0.94)MS (RMSE = 373; d = 0.93)LS (RMSE = 441; d = 0.90

0

1000

2000

3000

4000

5000

6000

20 40 60 80 100 120

Days after emergence

Po

d w

eig

ht

(kg

ha

-1)

Pod growth

C (RMSE = 0.28; d = 0.99)MS (RMSE = 0.91; d =0.78)LS (RMSE = 0.63; d = 0.94)0.0

1.0

2.0

3.0

4.0

20 40 60 80 100 120

Days after planting

LA

I

Simulated-C Simulated-MSSimulated-LS Measured-CMeasured-MS Measured-LS

LAI

Results-Model Evaluation…4. Growth-cowpea

C (RMSE = 0.60; d = 0.95)MS (RMSE = 0.57; d = 0.65)LS (RMSE = 0.98; d = 0.91)

0.0

1.0

2.0

3.0

4.0

5.0

6.0

20 40 60 80 100 120Days after planting

LA

I

LAIC (RMSE = 1343; d = 0.96)MS (RMSE = 1178; d = 0.98)LS (RMSE = 1306; d = 0.93)

0

2000

4000

6000

8000

10000

12000

20 40 60 80 100 120

Bio

mas

s (k

g h

a-1)

Biomass

C (RMSE = 542; d = 0.97)MS (RMSE = 847; d = 0.82)LS (RMSE = 458; d = 0.92)

0

1000

2000

3000

4000

5000

6000

20 40 60 80 100 120

Days after planting

Po

d

wei

gh

t (k

g h

a-1)

Simulated-CMeasured-CSimulated-MSMeasured-MSSimulated-LSMeasured-LS

Pod growth

Results-Model Evaluation…4. Grain yield (kg ha-1)

RMSE = 441 MAD = 367

CV = 23% d = 0.95

R2 = 0.940

1000

2000

3000

4000

0 1000 2000 3000 4000

Simulated

Mea

sure

d

CMSLS

Drybean 1:1 line

RMSE = 248 MAD = 207

CV = 23% d = 0.95

R2 = 0.940

1000

2000

3000

4000

0 1000 2000 3000 4000

Simulated

Mea

sure

d

Chickpea

RMSE = 292 MAD = 254 CV = 27% d = 0.87

R2 = 0.90

0

1000

2000

3000

4000

0 1000 2000 3000 4000

Simluated

Mea

sure

d

Cowpea

Results-Model Evaluation…

5. Relative yield reduction

0.00

0.20

0.40

0.60

0.80

MS LS C

Water regimes

Mea

n r

elat

ive

yiel

d r

edu

ctio

n

Measured

Simulated

Chickpea

0.00

0.20

0.40

0.60

0.80

1.00

MS LS C

Water regimes

Mea

n r

elat

rive

yie

ld r

edu

ctio

n

Measured

Simulated

Drybean

0.00

0.20

0.40

0.60

0.80

1.00

MS LS C

Water regimes

Mea

n r

elat

ive

yiel

d r

edu

ctio

n

Measured

Simulated

Cowpea

Results-Model Evaluation…5. Simulated WSF vs. Measured LWP

y = -0.84x - 0.85; R2 = 0.60

0.00

0.20

0.40

0.60

0.80

1.00

-4.0 -3.0 -2.0 -1.0 0.0

Measured leaf water potential (MPa)

Sim

ula

ted

wat

er s

tres

s fa

cto

r

Cowpea

y = -0.57x - 1.10, R2 = 0.88

0.00

0.20

0.40

0.60

0.80

1.00

-4.0 -3.0 -2.0 -1.0 0.0

Measured Leaf water potential (MPa)

Sim

ula

ted

wat

er s

tres

s fa

cto

r ChickpeaDryean

y = -1.71x - 2.19, R2 = 0.80

0.00

0.20

0.40

0.60

0.80

1.00

-4.0 -3.0 -2.0 -1.0 0.0

So

il w

ater

str

ess

fact

or 2002

2002/03

Conclusion The CSM-CROPGRO- drybean, chickpea and cowpea models

accurately simulated:

soil water dynamics in the root zone layer and the duration and intensity of water deficit occurrence during the growing seasons

the seasonal pattern of LAI, biomass accumulation and pod growth under different water regimes although accuracy is less in the MS treatment, and

grain yield variability with water supply.

The models overestimated the duration of physiological maturity under water deficit conditions suggesting the need for further improvement in this regard.

Conclusion…

If properly calibrated, the models have shown their ability to be used as decision support tools in:

irrigation water management, choice of cultivars to different water supply

environments, prescreening of genotypes for drought tolerance and determining the occurrence and severity of agricultural

drought in the semi-arid tropical environments.