IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v228y2020ics0378377419311229.html
   My bibliography  Save this article

Unified framework for model-based optimal allocation of crop areas and water

Author

Listed:
  • Linker, Raphael

Abstract

The paper presents a model-based optimization scheme for allocation of cropping areas and water. The novelty of the scheme is that rather than using highly simplified models of crop response to deficit irrigation, detailed dynamic models of crop/soil/atmosphere interactions are used to determine the crop water productivity function. While the use of such models has traditionally been considered as prohibitive in terms of computation time, the current scheme circumvents this limitation by using each model independently in a simple multi-objective optimization procedure outside of the main optimization procedure. Once the optimization problem dealing with land and water allocation has been solved, the same models are used to compute optimal irrigation schedules for each crop at each location. During the season, a simplified version of the optimization scheme can be used to update water allocation in response to discrepancies between the actual and forecasted weather or factors such as changes in water quota or crop prices. The proposed scheme is illustrated for a hypothetical farm with four fields near Davis, CA. The model AquaCrop is used to determine optimal cropping and water allocation for simultaneous cultivation of maize and sunflower at that farm.

Suggested Citation

  • Linker, Raphael, 2020. "Unified framework for model-based optimal allocation of crop areas and water," Agricultural Water Management, Elsevier, vol. 228(C).
    • Handle: RePEc:eee:agiwat:v:228:y:2020:i:c:s0378377419311229
    DOI: 10.1016/j.agwat.2019.105859
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377419311229
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2019.105859?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bhabagrahi Sahoo & Anil Lohani & Rohit Sahu, 2006. "Fuzzy Multiobjective and Linear Programming Based Management Models for Optimal Land-Water-Crop System Planning," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(6), pages 931-948, December.
    2. Garg, N.K. & Dadhich, Sushmita M., 2014. "Integrated non-linear model for optimal cropping pattern and irrigation scheduling under deficit irrigation," Agricultural Water Management, Elsevier, vol. 140(C), pages 1-13.
    3. Jiang, Yiwen & Zhang, Lanhui & Zhang, Baoqing & He, Chansheng & Jin, Xin & Bai, Xiao, 2016. "Modeling irrigation management for water conservation by DSSAT-maize model in arid northwestern China," Agricultural Water Management, Elsevier, vol. 177(C), pages 37-45.
    4. Vazifedoust, M. & van Dam, J.C. & Feddes, R.A. & Feizi, M., 2008. "Increasing water productivity of irrigated crops under limited water supply at field scale," Agricultural Water Management, Elsevier, vol. 95(2), pages 89-102, February.
    5. Shangguan, Zhouping & Shao, Mingan & Horton, Robert & Lei, Tingwu & Qin, Lin & Ma, Jianqing, 2002. "A model for regional optimal allocation of irrigation water resources under deficit irrigation and its applications," Agricultural Water Management, Elsevier, vol. 52(2), pages 139-154, January.
    6. Linker, Raphael & Ioslovich, Ilya & Sylaios, Georgios & Plauborg, Finn & Battilani, Adriano, 2016. "Optimal model-based deficit irrigation scheduling using AquaCrop: A simulation study with cotton, potato and tomato," Agricultural Water Management, Elsevier, vol. 163(C), pages 236-243.
    7. Singh, Ajay, 2014. "Simulation–optimization modeling for conjunctive water use management," Agricultural Water Management, Elsevier, vol. 141(C), pages 23-29.
    8. Sethi, Laxmi Narayan & Panda, Sudhindra N. & Nayak, Manoj K., 2006. "Optimal crop planning and water resources allocation in a coastal groundwater basin, Orissa, India," Agricultural Water Management, Elsevier, vol. 83(3), pages 209-220, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xu, Xianghui & Chen, Yingshan & Zhou, Yan & Liu, Wuyuan & Zhang, Xinrui & Li, Mo, 2023. "Sustainable management of agricultural water rights trading under uncertainty: An optimization-evaluation framework," Agricultural Water Management, Elsevier, vol. 280(C).
    2. Chen, Mengting & Linker, Raphael & Wu, Conglin & Xie, Hua & Cui, Yuanlai & Luo, Yufeng & Lv, Xinwei & Zheng, Shizong, 2022. "Multi-objective optimization of rice irrigation modes using ACOP-Rice model and historical meteorological data," Agricultural Water Management, Elsevier, vol. 272(C).
    3. Linker, Raphael & Kisekka, Isaya, 2022. "Concurrent data assimilation and model-based optimization of irrigation scheduling," Agricultural Water Management, Elsevier, vol. 274(C).
    4. Ajay Singh, 2022. "Better Water and Land Allocation for Long-term Agricultural Sustainability," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(10), pages 3505-3522, August.
    5. Li, Shuoyang & Yang, Guiyu & Wang, Hao & Song, Xiufang & Chang, Cui & Du, Jie & Gao, Danyang, 2023. "A spatial-temporal optimal allocation method of irrigation water resources considering groundwater level," Agricultural Water Management, Elsevier, vol. 275(C).
    6. Li, Mo & Cao, Xiaoxu & Liu, Dong & Fu, Qiang & Li, Tianxiao & Shang, Ruochen, 2022. "Sustainable management of agricultural water and land resources under changing climate and socio-economic conditions: A multi-dimensional optimization approach," Agricultural Water Management, Elsevier, vol. 259(C).
    7. Richwell Mubita Mwiya & Zhanyu Zhang & Chengxin Zheng & Ce Wang, 2020. "Comparison of Approaches for Irrigation Scheduling Using AquaCrop and NSGA-III Models under Climate Uncertainty," Sustainability, MDPI, vol. 12(18), pages 1-20, September.
    8. Mandal, Uday & Dhar, Anirban & Panda, Sudhindra N., 2021. "Enhancement of sustainable agricultural production system by integrated natural resources management framework under climatic and operational uncertainty," Agricultural Water Management, Elsevier, vol. 252(C).
    9. Li, Mo & Sun, Hao & Liu, Dong & Singh, Vijay P. & Fu, Qiang, 2021. "Multi-scale modeling for irrigation water and cropland resources allocation considering uncertainties in water supply and demand," Agricultural Water Management, Elsevier, vol. 246(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Niu, G. & Li, Y.P. & Huang, G.H. & Liu, J. & Fan, Y.R., 2016. "Crop planning and water resource allocation for sustainable development of an irrigation region in China under multiple uncertainties," Agricultural Water Management, Elsevier, vol. 166(C), pages 53-69.
    2. Jiang, Yao & Xu, Xu & Huang, Quanzhong & Huo, Zailin & Huang, Guanhua, 2016. "Optimizing regional irrigation water use by integrating a two-level optimization model and an agro-hydrological model," Agricultural Water Management, Elsevier, vol. 178(C), pages 76-88.
    3. Abbas Amini Fasakhodi & Seyed Nouri & Manouchehr Amini, 2010. "Water Resources Sustainability and Optimal Cropping Pattern in Farming Systems; A Multi-Objective Fractional Goal Programming Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(15), pages 4639-4657, December.
    4. Li, Mo & Guo, Ping, 2015. "A coupled random fuzzy two-stage programming model for crop area optimization—A case study of the middle Heihe River basin, China," Agricultural Water Management, Elsevier, vol. 155(C), pages 53-66.
    5. Kelly, T.D. & Foster, T. & Schultz, David M., 2023. "Assessing the value of adapting irrigation strategies within the season," Agricultural Water Management, Elsevier, vol. 275(C).
    6. Liuyue He & Sufen Wang & Congcong Peng & Qian Tan, 2018. "Optimization of Water Consumption Distribution Based on Crop Suitability in the Middle Reaches of Heihe River," Sustainability, MDPI, vol. 10(7), pages 1-17, June.
    7. Liu, J. & Li, Y.P. & Huang, G.H. & Zeng, X.T., 2014. "A dual-interval fixed-mix stochastic programming method for water resources management under uncertainty," Resources, Conservation & Recycling, Elsevier, vol. 88(C), pages 50-66.
    8. 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.
    9. Cervantes-Gaxiola, Maritza E. & Sosa-Niebla, Erik F. & Hernández-Calderón, Oscar M. & Ponce-Ortega, José M. & Ortiz-del-Castillo, Jesús R. & Rubio-Castro, Eusiel, 2020. "Optimal crop allocation including market trends and water availability," European Journal of Operational Research, Elsevier, vol. 285(2), pages 728-739.
    10. Wen, Yeqiang & Shang, Songhao & Yang, Jian, 2017. "Optimization of irrigation scheduling for spring wheat with mulching and limited irrigation water in an arid climate," Agricultural Water Management, Elsevier, vol. 192(C), pages 33-44.
    11. Aurobrata Das & Bhabagrahi Sahoo & Sudhindra N. Panda, 2020. "Evaluation of Nexus-Sustainability and Conventional Approaches for Optimal Water-Energy-Land-Crop Planning in an Irrigated Canal Command," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(8), pages 2329-2351, June.
    12. Li, Xiaojuan & Kang, Shaozhong & Niu, Jun & Du, Taisheng & Tong, Ling & Li, Sien & Ding, Risheng, 2017. "Applying uncertain programming model to improve regional farming economic benefits and water productivity," Agricultural Water Management, Elsevier, vol. 179(C), pages 352-365.
    13. Richwell Mubita Mwiya & Zhanyu Zhang & Chengxin Zheng & Ce Wang, 2020. "Comparison of Approaches for Irrigation Scheduling Using AquaCrop and NSGA-III Models under Climate Uncertainty," Sustainability, MDPI, vol. 12(18), pages 1-20, September.
    14. M. Habibi Davijani & M. E. Banihabib & A. Nadjafzadeh Anvar & S. R. Hashemi, 2016. "Multi-Objective Optimization Model for the Allocation of Water Resources in Arid Regions Based on the Maximization of Socioeconomic Efficiency," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 927-946, February.
    15. Li, Xuemin & Zhang, Jingwen & Cai, Ximing & Huo, Zailin & Zhang, Chenglong, 2023. "Simulation-optimization based real-time irrigation scheduling: A human-machine interactive method enhanced by data assimilation," Agricultural Water Management, Elsevier, vol. 276(C).
    16. Arredondo-Ramírez, Karla & Rubio-Castro, Eusiel & Nápoles-Rivera, Fabricio & Ponce-Ortega, José María & Serna-González, Medardo & El-Halwagi, Mahmoud M., 2015. "Optimal design of agricultural water systems with multiperiod collection, storage, and distribution," Agricultural Water Management, Elsevier, vol. 152(C), pages 161-172.
    17. Pereira, L.S. & Paredes, P. & Jovanovic, N., 2020. "Soil water balance models for determining crop water and irrigation requirements and irrigation scheduling focusing on the FAO56 method and the dual Kc approach," Agricultural Water Management, Elsevier, vol. 241(C).
    18. Madan K. Jha & Richard C. Peralta & Sasmita Sahoo, 2020. "Simulation-Optimization for Conjunctive Water Resources Management and Optimal Crop Planning in Kushabhadra-Bhargavi River Delta of Eastern India," IJERPH, MDPI, vol. 17(10), pages 1-20, May.
    19. Cao, Zhaodan & Zhu, Tingju & Cai, Ximing, 2023. "Hydro-agro-economic optimization for irrigated farming in an arid region: The Hetao Irrigation District, Inner Mongolia," Agricultural Water Management, Elsevier, vol. 277(C).
    20. Kiymaz, Sultan & Ertek, Ahmet, 2015. "Water use and yield of sugar beet (Beta vulgaris L.) under drip irrigation at different water regimes," Agricultural Water Management, Elsevier, vol. 158(C), pages 225-234.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agiwat:v:228:y:2020:i:c:s0378377419311229. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.