IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v254y2021ics0378377421002419.html
   My bibliography  Save this article

AquaCrop-OSPy: Bridging the gap between research and practice in crop-water modeling

Author

Listed:
  • Kelly, T.D.
  • Foster, T.

Abstract

Crop-growth models are powerful tools for supporting optimal planning and management of agricultural water use globally. However, use of crop models for this purpose often requires advanced programming expertize and computational resources, limiting the potential uptake in integrated water management research by practitioners such as water managers, policymakers, and irrigation service providers. In this article, we present AquaCrop-OSPy (ACOSP), an open source, Python implementation of the crop-water productivity model AquaCrop. The model provides a user friendly, flexible and computationally efficient solution to support agricultural water management, which can be readily integrated with other Python modules or code bases and run instantly via a web browser using the cloud computing platform Google Colab without the need for local installation. This article describes how to run basic simulations using AquaCrop-OSPy, along with more advanced analyses such as optimizing irrigation schedules and evaluating climate change impacts. Each use case is paired with a Jupyter Notebook, which offer an interactive learning environment for users and can be readily adapted to address a range of common irrigation planning and management challenges faced by researcher, policymakers and businesses in both developed and developing countries (https://github.com/thomasdkelly/aquacrop).

Suggested Citation

  • Kelly, T.D. & Foster, T., 2021. "AquaCrop-OSPy: Bridging the gap between research and practice in crop-water modeling," Agricultural Water Management, Elsevier, vol. 254(C).
    • Handle: RePEc:eee:agiwat:v:254:y:2021:i:c:s0378377421002419
    DOI: 10.1016/j.agwat.2021.106976
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377421002419
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2021.106976?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. Igbadun, Henry E. & Tarimo, Andrew K.P.R. & Salim, Baanda A. & Mahoo, Henry F., 2007. "Evaluation of selected crop water production functions for an irrigated maize crop," Agricultural Water Management, Elsevier, vol. 94(1-3), pages 1-10, December.
    2. Closas, Alvar & Molle, Francois, . "Chronicle of a demise foretold: state vs. local groundwater management in Texas and the high plains aquifer system," Papers published in Journals (Open Access), International Water Management Institute, pages 11(3):511-5.
    3. Fawen Li & Dong Yu & Yong Zhao, 2019. "Irrigation Scheduling Optimization for Cotton Based on the AquaCrop Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(1), pages 39-55, January.
    4. Olutobi Adeyemi & Ivan Grove & Sven Peets & Tomas Norton, 2017. "Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation," Sustainability, MDPI, vol. 9(3), pages 1-29, February.
    5. Martínez-Romero, A. & Domínguez, A. & Landeras, G., 2019. "Regulated deficit irrigation strategies for different potato cultivars under continental Mediterranean-Atlantic conditions," Agricultural Water Management, Elsevier, vol. 216(C), pages 164-176.
    6. Foster, T. & Brozović, N., 2018. "Simulating Crop-Water Production Functions Using Crop Growth Models to Support Water Policy Assessments," Ecological Economics, Elsevier, vol. 152(C), pages 9-21.
    7. Olga Wilhelmi & Donald Wilhite, 2002. "Assessing Vulnerability to Agricultural Drought: A Nebraska Case Study," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 25(1), pages 37-58, January.
    8. Attia, Ahmed & Rajan, Nithya & Xue, Qingwu & Nair, Shyam & Ibrahim, Amir & Hays, Dirk, 2016. "Application of DSSAT-CERES-Wheat model to simulate winter wheat response to irrigation management in the Texas High Plains," Agricultural Water Management, Elsevier, vol. 165(C), pages 50-60.
    9. Geerts, S. & Raes, D. & Garcia, M., 2010. "Using AquaCrop to derive deficit irrigation schedules," Agricultural Water Management, Elsevier, vol. 98(1), pages 213-216, December.
    10. 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.
    11. Blonquist, J.M. Jr. & Jones, S.B. & Robinson, D.A., 2006. "Precise irrigation scheduling for turfgrass using a subsurface electromagnetic soil moisture sensor," Agricultural Water Management, Elsevier, vol. 84(1-2), pages 153-165, July.
    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. 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).
    2. Xiong, Lvyang & Jiang, Yao & Li, Xinyi & Ren, Dongyang & Huang, Guanhua, 2023. "Long-term regional groundwater responses and their ecological impacts under agricultural water saving in an arid irrigation district, upper Yellow River basin," Agricultural Water Management, Elsevier, vol. 288(C).
    3. 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).
    4. Serra, J. & Paredes, P. & Cordovil, CMdS & Cruz, S. & Hutchings, NJ & Cameira, MR, 2023. "Is irrigation water an overlooked source of nitrogen in agriculture?," Agricultural Water Management, Elsevier, vol. 278(C).
    5. Aster Tesfaye Hordofa & Olkeba Tolessa Leta & Tena Alamirew & Abebe Demissie Chukalla, 2022. "Response of Winter Wheat Production to Climate Change in Ziway Lake Basin," Sustainability, MDPI, vol. 14(20), pages 1-17, October.
    6. Liu, Xiao & Yang, Dawen, 2021. "Irrigation schedule analysis and optimization under the different combination of P and ET0 using a spatially distributed crop model," Agricultural Water Management, Elsevier, vol. 256(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. 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).
    2. Alaa Jamal & Raphael Linker, 2020. "Genetic Operator-Based Particle Filter Combined with Markov Chain Monte Carlo for Data Assimilation in a Crop Growth Model," Agriculture, MDPI, vol. 10(12), pages 1-22, December.
    3. Wang, Yufeng & Kang, Shaozhong & Li, Fusheng & Zhang, Xiaotao, 2021. "Modified water-nitrogen productivity function based on response of water sensitive index to nitrogen for hybrid maize under drip fertigation," Agricultural Water Management, Elsevier, vol. 245(C).
    4. Dahri, Shahzad Hussain & Shaikh, Irfan Ahmed & Talpur, Mashooque Ali & Mangrio, Munir Ahmed & Dahri, Zakir Hussain & Hoogenboom, Gerrit & Knox, Jerry W., 2024. "Modelling the impacts of climate change on the sustainability of rainfed and irrigated maize in Pakistan," Agricultural Water Management, Elsevier, vol. 296(C).
    5. Zhong, Honglin & Sun, Laixiang & Fischer, Günther & Tian, Zhan & van Velthuizen, Harrij & Liang, Zhuoran, 2017. "Mission Impossible? Maintaining regional grain production level and recovering local groundwater table by cropping system adaptation across the North China Plain," Agricultural Water Management, Elsevier, vol. 193(C), pages 1-12.
    6. Wang, Yue & Jiang, Kongtao & Shen, Hongzheng & Wang, Nan & Liu, Ruizhe & Wu, Jiujiang & Ma, Xiaoyi, 2023. "Decision-making method for maize irrigation in supplementary irrigation areas based on the DSSAT model and a genetic algorithm," Agricultural Water Management, Elsevier, vol. 280(C).
    7. Cui, Yi & Jiang, Shangming & Jin, Juliang & Ning, Shaowei & Feng, Ping, 2019. "Quantitative assessment of soybean drought loss sensitivity at different growth stages based on S-shaped damage curve," Agricultural Water Management, Elsevier, vol. 213(C), pages 821-832.
    8. Wang, Xiao-Ling & Duan, Pei-Ling & Yang, Shen-Jiao & Liu, Yu-Hua & Qi, Lin & Shi, Jiang & Li, Xue-Lin & Song, Peng & Zhang, Li-Xia, 2020. "Corn compensatory growth upon post-drought rewatering based on the effects of rhizosphere soil nitrification on cytokinin," Agricultural Water Management, Elsevier, vol. 241(C).
    9. Himanshu, Sushil Kumar & Ale, Srinivasulu & Bordovsky, James & Darapuneni, Murali, 2019. "Evaluation of crop-growth-stage-based deficit irrigation strategies for cotton production in the Southern High Plains," Agricultural Water Management, Elsevier, vol. 225(C).
    10. Rouhi Rad, Mani & Haacker, Erin M.K. & Sharda, Vaishali & Nozari, Soheil & Xiang, Zaichen & Araya, A. & Uddameri, Venkatesh & Suter, Jordan F. & Gowda, Prasanna, 2020. "MOD$$AT: A hydro-economic modeling framework for aquifer management in irrigated agricultural regions," Agricultural Water Management, Elsevier, vol. 238(C).
    11. Lina Eklund & Jonathan Seaquist, 2015. "Meteorological, agricultural and socioeconomic drought in the Duhok Governorate, Iraqi Kurdistan," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 76(1), pages 421-441, March.
    12. Lankford, B. & Makin, Ian & Matthews, N. & McCornick, Peter G. & Noble, A. & Shah, Tushaar, "undated". "A compact to revitalise large-scale irrigation systems using a leadership-partnership-ownership 'Theory of Change'," Papers published in Journals (Open Access) H047459, International Water Management Institute.
    13. Giorgio Baiamonte & Mario Minacapilli & Giuseppina Crescimanno, 2020. "Effects of Biochar on Irrigation Management and Water Use Efficiency for Three Different Crops in a Desert Sandy Soil," Sustainability, MDPI, vol. 12(18), pages 1-19, September.
    14. Hong Wu & Donald Wilhite, 2004. "An Operational Agricultural Drought Risk Assessment Model for Nebraska, USA," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 33(1), pages 1-21, September.
    15. Motazedian, Azam & Kazemeini, Seyed Abdolreza & Bahrani, Mohammad Jafar, 2019. "Sweet corn growth and GrainYield as influenced by irrigation and wheat residue management," Agricultural Water Management, Elsevier, vol. 224(C), pages 1-1.
    16. Cao, Jingjing & Tan, Junwei & Cui, Yuanlai & Luo, Yufeng, 2019. "Irrigation scheduling of paddy rice using short-term weather forecast data," Agricultural Water Management, Elsevier, vol. 213(C), pages 714-723.
    17. Pardo, J.J. & Martínez-Romero, A. & Léllis, B.C. & Tarjuelo, J.M. & Domínguez, A., 2020. "Effect of the optimized regulated deficit irrigation methodology on water use in barley under semiarid conditions," Agricultural Water Management, Elsevier, vol. 228(C).
    18. Shamsuddin Shahid & Houshang Behrawan, 2008. "Drought risk assessment in the western part of Bangladesh," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 46(3), pages 391-413, September.
    19. Shi, Xinrui & Batchelor, William D. & Liang, Hao & Li, Sien & Li, Baoguo & Hu, Kelin, 2020. "Determining optimal water and nitrogen management under different initial soil mineral nitrogen levels in northwest China based on a model approach," Agricultural Water Management, Elsevier, vol. 234(C).
    20. Zhang, Chao & Xie, Ziang & Wang, Qiaojuan & Tang, Min & Feng, Shaoyuan & Cai, Huanjie, 2022. "AquaCrop modeling to explore optimal irrigation of winter wheat for improving grain yield and water productivity," Agricultural Water Management, Elsevier, vol. 266(C).

    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:254:y:2021:i:c:s0378377421002419. 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.