IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v213y2019icp309-323.html
   My bibliography  Save this article

A conceptual agricultural water productivity model considering under field capacity soil water redistribution applicable for arid and semi-arid areas with deep groundwater

Author

Listed:
  • Chen, Shilei
  • Huo, Zailin
  • Xu, Xu
  • Huang, Guanhua

Abstract

Agricultural water productivity (AWP) model is an essential tool for irrigation water management that is highly dependent on soil water processes. Soil hydrological models based on numeric solution to the Richards’ equation are time-consuming and difficult to measure, and models based on soil water balance approach are favored especially for crop water simulation because of the less parameters requirement and higher operational efficiency. In most of the soil water balance models such as Williams-Ritchie water balance model, AquaCrop model and Hydrobal model, the under field-capacity redistribution (the redistribution during the period of soil water content below the field-capacity) is omitted and this treatment does not adequately simulate AWP for arid and semi-arid areas with deep groundwater. In these areas, AWP is the ratio between crop yield achieved and the sum of actual evapotranspiration and deep percolation at field scale. Since no more water supply for crop growth except for low frequency irrigation and tiny amount of precipitation, high evapotranspiration will aggravate an upward flow that can enhance transpiration and thus benefit crop growth while deep percolation not available for crop is sustainably accumulated to a considerable volume in under field-capacity redistribution process. To take into consideration the beneficial effects of upward flow on crop growth and the considerable under field-capacity deep percolation loss, a conceptual soil hydrological model considering under field-capacity redistribution (CSHMUR) is developed and coupled with the EPIC crop growth model. In CSHMUR model, soil water redistribution is characterized by two sequential water flows: downward flows affected by the gradient of gravitational potential and upward flows affected by the gradient of matric potential. These two flows are mainly used to simulate deep percolation occurring in redistribution processes and upward flows resulting from matric potential, respectively. The CSHMUR-EPIC model is calibrated and validated with field data for a typical arid area of northwestern China, and it is then applied for the simulation of seven irrigation scenarios. The study highlights that the upward flows aggravated by drought conditions and the under field-capacity deep percolation are remarkable enough and should not be neglected in the AWP estimation for arid and semi-arid areas with deep groundwater. The developed CSHMUR-EPIC model can effectively simulate upward flows and the under field-capacity deep percolation, and thus soil water content (SWC) both in lower and upper soil profiles, actual evapotranspiration and crop growth, resulting in an precise estimation of AWP. As upward flows and the under field-capacity deep percolation vary with irrigation schedule, the model is also helpful in exploring various irrigation schedule to obtain a sustainable agricultural water resources management.

Suggested Citation

  • Chen, Shilei & Huo, Zailin & Xu, Xu & Huang, Guanhua, 2019. "A conceptual agricultural water productivity model considering under field capacity soil water redistribution applicable for arid and semi-arid areas with deep groundwater," Agricultural Water Management, Elsevier, vol. 213(C), pages 309-323.
  • Handle: RePEc:eee:agiwat:v:213:y:2019:i:c:p:309-323
    DOI: 10.1016/j.agwat.2018.10.024
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377418307297
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.agwat.2018.10.024?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. Wang, Jun & Huang, Guanhua & Zhan, Hongbin & Mohanty, Binayak P. & Zheng, Jianhua & Huang, Quanzhong & Xu, Xu, 2014. "Evaluation of soil water dynamics and crop yield under furrow irrigation with a two-dimensional flow and crop growth coupled model," Agricultural Water Management, Elsevier, vol. 141(C), pages 10-22.
    2. Masikati, P. & Manschadi, A. & van Rooyen, A. & Hargreaves, J., 2014. "Maize–mucuna rotation: An alternative technology to improve water productivity in smallholder farming systems," Agricultural Systems, Elsevier, vol. 123(C), pages 62-70.
    3. Rijsberman, Frank R., 2006. "Water scarcity: Fact or fiction?," Agricultural Water Management, Elsevier, vol. 80(1-3), pages 5-22, February.
    4. Karandish, Fatemeh & Šimůnek, Jiří, 2016. "A field-modeling study for assessing temporal variations of soil-water-crop interactions under water-saving irrigation strategies," Agricultural Water Management, Elsevier, vol. 178(C), pages 291-303.
    5. Bellot, Juan & Chirino, Esteban, 2013. "Hydrobal: An eco-hydrological modelling approach for assessing water balances in different vegetation types in semi-arid areas," Ecological Modelling, Elsevier, vol. 266(C), pages 30-41.
    6. Xu, Xu & Huang, Guanhua & Sun, Chen & Pereira, Luis S. & Ramos, Tiago B. & Huang, Quanzhong & Hao, Yuanyuan, 2013. "Assessing the effects of water table depth on water use, soil salinity and wheat yield: Searching for a target depth for irrigated areas in the upper Yellow River basin," Agricultural Water Management, Elsevier, vol. 125(C), pages 46-60.
    7. Zhao, Wenzhi & Liu, Bing & Zhang, Zhihui, 2010. "Water requirements of maize in the middle Heihe River basin, China," Agricultural Water Management, Elsevier, vol. 97(2), pages 215-223, February.
    8. Pereira, Luis S. & Cordery, Ian & Iacovides, Iacovos, 2012. "Improved indicators of water use performance and productivity for sustainable water conservation and saving," Agricultural Water Management, Elsevier, vol. 108(C), pages 39-51.
    9. Stockle, Claudio O. & Martin, Steve A. & Campbell, Gaylon S., 1994. "CropSyst, a cropping systems simulation model: Water/nitrogen budgets and crop yield," Agricultural Systems, Elsevier, vol. 46(3), pages 335-359.
    10. Li, Jiang & Mao, Xiaomin & Li, Mo, 2017. "Modeling hydrological processes in oasis of Heihe River Basin by landscape unit-based conceptual models integrated with FEFLOW and GIS," Agricultural Water Management, Elsevier, vol. 179(C), pages 338-351.
    11. Jiang, Yao & Xu, Xu & Huang, Quanzhong & Huo, Zailin & Huang, Guanhua, 2015. "Assessment of irrigation performance and water productivity in irrigated areas of the middle Heihe River basin using a distributed agro-hydrological model," Agricultural Water Management, Elsevier, vol. 147(C), pages 67-81.
    12. Amarasingha, R.P.R.K. & Suriyagoda, L.D.B. & Marambe, B. & Rathnayake, W.M.U.K. & Gaydon, D.S. & Galagedara, L.W. & Punyawardena, R. & Silva, G.L.L.P. & Nidumolu, U. & Howden, M., 2017. "Improving water productivity in moisture-limited rice-based cropping systems through incorporation of maize and mungbean: A modelling approach," Agricultural Water Management, Elsevier, vol. 189(C), pages 111-122.
    13. DeJonge, K.C. & Ascough, J.C. & Andales, A.A. & Hansen, N.C. & Garcia, L.A. & Arabi, M., 2012. "Improving evapotranspiration simulations in the CERES-Maize model under limited irrigation," Agricultural Water Management, Elsevier, vol. 115(C), pages 92-103.
    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. Wang, Rong & Huang, Guanhua & Xu, Xu & Ren, Dongyang & Gou, Jiachao & Wu, Zhangsheng, 2022. "Significant differences in agro-hydrological processes and water productivity between canal- and well-irrigated areas in an arid region," Agricultural Water Management, Elsevier, vol. 267(C).
    2. Mo, Yan & Li, Guangyong & Wang, Dan & Lamm, Freddie R. & Wang, Jiandong & Zhang, Yanqun & Cai, Mingkun & Gong, Shihong, 2020. "Planting and preemergence irrigation procedures to enhance germination of subsurface drip irrigated corn," Agricultural Water Management, Elsevier, vol. 242(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. Xu, Xu & Jiang, Yao & Liu, Minghuan & Huang, Quanzhong & Huang, Guanhua, 2019. "Modeling and assessing agro-hydrological processes and irrigation water saving in the middle Heihe River basin," Agricultural Water Management, Elsevier, vol. 211(C), pages 152-164.
    2. Liu Liu & Zezhong Guo & Guanhua Huang & Ruotong Wang, 2019. "Water Productivity Evaluation under Multi-GCM Projections of Climate Change in Oases of the Heihe River Basin, Northwest China," IJERPH, MDPI, vol. 16(10), pages 1-17, May.
    3. Ren, Dongyang & Xu, Xu & Engel, Bernard & Huang, Quanzhong & Xiong, Yunwu & Huo, Zailin & Huang, Guanhua, 2021. "A comprehensive analysis of water productivity in natural vegetation and various crops coexistent agro-ecosystems," Agricultural Water Management, Elsevier, vol. 243(C).
    4. Liu, Minghuan & Jiang, Yao & Xu, Xu & Huang, Quanzhong & Huo, Zailin & Huang, Guanhua, 2018. "Long-term groundwater dynamics affected by intense agricultural activities in oasis areas of arid inland river basins, Northwest China," Agricultural Water Management, Elsevier, vol. 203(C), pages 37-52.
    5. Wang, Xiangping & Liu, Guangming & Yang, Jingsong & Huang, Guanhua & Yao, Rongjiang, 2017. "Evaluating the effects of irrigation water salinity on water movement, crop yield and water use efficiency by means of a coupled hydrologic/crop growth model," Agricultural Water Management, Elsevier, vol. 185(C), pages 13-26.
    6. Haorui Chen & Zhanyi Gao & Wenzhi Zeng & Jing Liu & Xiao Tan & Songjun Han & Shaoli Wang & Yongqing Zhao & Chengkun Yu, 2017. "Scale Effects of Water Saving on Irrigation Efficiency: Case Study of a Rice-Based Groundwater Irrigation System on the Sanjiang Plain, Northeast China," Sustainability, MDPI, vol. 10(1), pages 1-18, December.
    7. Jiang, Yao & Xu, Xu & Huang, Quanzhong & Huo, Zailin & Huang, Guanhua, 2015. "Assessment of irrigation performance and water productivity in irrigated areas of the middle Heihe River basin using a distributed agro-hydrological model," Agricultural Water Management, Elsevier, vol. 147(C), pages 67-81.
    8. Ramos, T.B. & Simionesei, L. & Jauch, E. & Almeida, C. & Neves, R., 2017. "Modelling soil water and maize growth dynamics influenced by shallow groundwater conditions in the Sorraia Valley region, Portugal," Agricultural Water Management, Elsevier, vol. 185(C), pages 27-42.
    9. 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).
    10. Genxiang Feng & Zhanyu Zhang & Zemin Zhang, 2019. "Evaluating the Sustainable Use of Saline Water Irrigation on Soil Water-Salt Content and Grain Yield under Subsurface Drainage Condition," Sustainability, MDPI, vol. 11(22), pages 1-18, November.
    11. Liu, Yi & Zeng, Wenzhi & Ao, Chang & Lei, Guoqing & Wu, Jingwei & Huang, Jiesheng & Gaiser, Thomas & Srivastava, Amit Kumar, 2022. "Optimization of winter irrigation management for salinized farmland using a coupled model of soil water flow and crop growth," Agricultural Water Management, Elsevier, vol. 270(C).
    12. Wang, Rong & Huang, Guanhua & Xu, Xu & Ren, Dongyang & Gou, Jiachao & Wu, Zhangsheng, 2022. "Significant differences in agro-hydrological processes and water productivity between canal- and well-irrigated areas in an arid region," Agricultural Water Management, Elsevier, vol. 267(C).
    13. Wei, Zheng & Paredes, Paula & Liu, Yu & Chi, Wei Wei & Pereira, Luis S., 2015. "Modelling transpiration, soil evaporation and yield prediction of soybean in North China Plain," Agricultural Water Management, Elsevier, vol. 147(C), pages 43-53.
    14. Feng, Genxiang & Zhu, Chengli & Wu, Qingfeng & Wang, Ce & Zhang, Zhanyu & Mwiya, Richwell Mubita & Zhang, Li, 2021. "Evaluating the impacts of saline water irrigation on soil water-salt and summer maize yield in subsurface drainage condition using coupled HYDRUS and EPIC model," Agricultural Water Management, Elsevier, vol. 258(C).
    15. Nouri, Milad & Homaee, Mehdi & Pereira, Luis S. & Bybordi, Mohammad, 2023. "Water management dilemma in the agricultural sector of Iran: A review focusing on water governance," Agricultural Water Management, Elsevier, vol. 288(C).
    16. Wang, Xiangping & Huang, Guanhua & Yang, Jingsong & Huang, Quanzhong & Liu, Haijun & Yu, Lipeng, 2015. "An assessment of irrigation practices: Sprinkler irrigation of winter wheat in the North China Plain," Agricultural Water Management, Elsevier, vol. 159(C), pages 197-208.
    17. Liu, Meihan & Shi, Haibin & Paredes, Paula & Ramos, Tiago B. & Dai, Liping & Feng, Zhuangzhuang & Pereira, Luis S., 2022. "Estimating and partitioning maize evapotranspiration as affected by salinity using weighing lysimeters and the SIMDualKc model," Agricultural Water Management, Elsevier, vol. 261(C).
    18. Li, Jiang & Mao, Xiaomin & Li, Mo, 2017. "Modeling hydrological processes in oasis of Heihe River Basin by landscape unit-based conceptual models integrated with FEFLOW and GIS," Agricultural Water Management, Elsevier, vol. 179(C), pages 338-351.
    19. Rodrigues, Gonçalo C. & Paredes, Paula & Gonçalves, José M. & Alves, Isabel & Pereira, Luis S., 2013. "Comparing sprinkler and drip irrigation systems for full and deficit irrigated maize using multicriteria analysis and simulation modelling: Ranking for water saving vs. farm economic returns," Agricultural Water Management, Elsevier, vol. 126(C), pages 85-96.
    20. Wang, Youzhi & Guo, Shanshan & Yue, Qing & Mao, Xiaomin & Guo, Ping, 2021. "Distributed AquaCrop simulation-nonlinear multi-objective dependent-chance programming for irrigation water resources management under uncertainty," Agricultural Water Management, Elsevier, vol. 247(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:213:y:2019:i:c:p:309-323. 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.