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Evaluation of Crop Models for Simulating and Optimizing Deficit Irrigation Systems in Arid and Semi-arid Countries Under Climate Variability

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  • Sebastian Kloss
  • Raji Pushpalatha
  • Kefasi Kamoyo
  • Niels Schütze

Abstract

The variability of fresh water availability in arid and semi-arid countries poses a serious challenge to farmers to cope with when depending on irrigation for crop growing. This has shifted the focus onto improving irrigation management and water productivity (WP) through controlled deficit irrigation (DI). DI can be conceived as a strategy to deal with these challenges but more knowledge on risks and chances of this strategy is urgently needed. The availability of simulation models that can reliably predict crop yield under the influence of soil, atmosphere, irrigation, and agricultural management practices is a prerequisite for deriving reliable and effective deficit irrigation strategies. In this context, this article discusses the performance of the crop models CropWat, PILOTE, Daisy, and APSIM when being part of a stochastic simulation-based approach to improve WP by focusing primarily on the impact of climate variability. The stochastic framework consists of: (i) a weather generator for simulating regional impacts of climate variability; (ii) a tailor-made evolutionary optimization algorithm for optimal irrigation scheduling with limited water supply; and (iii) the above mentioned models for simulating water transport and crop growth in a sound manner. The results present stochastic crop water production functions (SCWPFs) that can be used as basic tools for assessing the impact on the risk for the potential yield due to water stress and climate variability. Example simulations from India, Malawi, France and Oman are presented and the suitability of these crop models to be employed in a framework for optimizing WP is evaluated. Copyright Springer Science+Business Media B.V. 2012

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  • Sebastian Kloss & Raji Pushpalatha & Kefasi Kamoyo & Niels Schütze, 2012. "Evaluation of Crop Models for Simulating and Optimizing Deficit Irrigation Systems in Arid and Semi-arid Countries Under Climate Variability," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(4), pages 997-1014, March.
    • Handle: RePEc:spr:waterr:v:26:y:2012:i:4:p:997-1014
    DOI: 10.1007/s11269-011-9906-y
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    3. Kögler, F. & Söffker, D., 2017. "Water (stress) models and deficit irrigation: System-theoretical description and causality mapping," Ecological Modelling, Elsevier, vol. 361(C), pages 135-156.
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    8. Yenesew Yihun & Abraham Haile & Bart Schultz & Teklu Erkossa, 2013. "Crop Water Productivity of Irrigated Teff in a Water Stressed Region," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(8), pages 3115-3125, June.
    9. Kögler, Friederike & Söffker, Dirk, 2020. "State-based open-loop control of plant growth by means of water stress training," Agricultural Water Management, Elsevier, vol. 230(C).
    10. Lalehzari, Reza & Kerachian, Reza, 2020. "Developing a framework for daily common pool groundwater allocation to demands in agricultural regions," Agricultural Water Management, Elsevier, vol. 241(C).
    11. Wouter Buytaert & Jan Friesen & Jens Liebe & Ralf Ludwig, 2012. "Assessment and Management of Water Resources in Developing, Semi-arid and Arid Regions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(4), pages 841-844, March.
    12. Daniela D’Agostino & Alessandra Scardigno & Nicola Lamaddalena & Daniel Chami, 2014. "Sensitivity Analysis of Coupled Hydro-Economic Models: Quantifying Climate Change Uncertainty for Decision-Making," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 4303-4318, September.
    13. Mehran Homayounfar & Sai Lai & Mehdi Zomorodian & Ali Sepaskhah & Arman Ganji, 2014. "Optimal Crop Water Allocation in Case of Drought Occurrence, Imposing Deficit Irrigation with Proportional Cutback Constraint," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 3207-3225, August.
    14. He, Liuyue & Xue, Jingyuan & Wang, Sufen, 2023. "WHCrop: A novel water-heat driven crop model for estimating the spatiotemporal dynamics of crop growth for arid region," Agricultural Water Management, Elsevier, vol. 287(C).
    15. Arman Ganji & Sara Kaviani, 2013. "Probability Analysis of Crop Water Stress Index: An Application of Double Bounded Density Function (DB-CDF)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(10), pages 3791-3802, August.
    16. Martínez-Romero, A. & López-Urrea, R. & Montoya, F. & Pardo, J.J. & Domínguez, A., 2021. "Optimization of irrigation scheduling for barley crop, combining AquaCrop and MOPECO models to simulate various water-deficit regimes," Agricultural Water Management, Elsevier, vol. 258(C).
    17. López-Mata, E. & Tarjuelo, J.M. & Orengo-Valverde, J.J. & Pardo, J.J. & Domínguez, A., 2019. "Irrigation scheduling to maximize crop gross margin under limited water availability," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.

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