Calibration and Evaluation of Three CROPGRO Models under Different Water Regimes in a Semi-Arid Tropical Environment - PowerPoint PPT Presentation

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Calibration and Evaluation of Three CROPGRO Models under Different Water Regimes in a Semi-Arid Tropical Environment. Kindie Tesfaye Haramaya University, Ethiopia 16 Dec 2008. Outline of presentation. Introduction Ethiopia Subject Methodology Results Conclusion. Introduction.

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Calibration and Evaluation of Three CROPGRO Models under Different Water Regimes in a Semi-Arid Tropical Environment

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Calibration and Evaluation of Three CROPGRO Models under Different Water Regimes in a Semi-Arid Tropical Environment

Kindie Tesfaye

Haramaya University, Ethiopia

16 Dec 2008

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Outline of presentation

  • Introduction

    • Ethiopia

    • Subject

  • Methodology

  • Results

  • Conclusion

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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)

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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).

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Endemic Animals and Plants

23 endemic birds

Chilada Baboon

Walia Ibex

Red fox

Mountain Nyala

Colobus Monkey

Oryx Spps.

Many plant genetic resources

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Country profile-historical places

Blue Nile Water Falls

Negash Mosque- 2000 yrs old

Sofamar Natural cave

Axum Stelle- > 2000 yrs old

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

Axum Zion- the oldest church

Fasilede Palace –built in 16th C

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Climate variability

Recurrent drought

Crop failures


Soil Degradation

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  • 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

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  • 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

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  • 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).

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

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  • 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

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    Data collection

    • Phenology

    • Growth, Yield & YC

    • Soil water

    • Physiology (PS, SC, LWP)

    • Canopy and soil temp.

    • Radiation interception

    • Weather

    • Soil (initial, profile)

    • Crop management

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    • 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)

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

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    Results-Model Evaluation

    1. Soil water

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    Results-Model Evaluation…

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    Results-Model Evaluation…

    2. Days to flowering (dap)

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    Results-Model Evaluation…

    3. Physiological maturity

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    Results-Model Evaluation…

    4. Growth-drybean

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    Results-Model Evaluation…

    4. Growth-chickpea

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    Results-Model Evaluation…

    4. Growth-cowpea

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    Results-Model Evaluation…

    4. Grain yield (kg ha-1)

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    Results-Model Evaluation…

    5. Relative yield reduction

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    Results-Model Evaluation…

    5. Simulated WSF vs. Measured LWP

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    • 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.

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    • 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.

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    THANK YOU for Your Attention!

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