IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v256y2021ics0378377421003954.html
   My bibliography  Save this article

Prediction model for irrigation return flow considering lag effect for arid areas

Author

Listed:
  • Jie, Feilong
  • Fei, Liangjun
  • Li, Shan
  • Hao, Kun
  • Liu, Lihua
  • Zhu, Hongyan

Abstract

Irrigation return flow (RF) in arid areas has a significant lag, and current RF prediction models have an inadequate consideration of this. This study proposed the concepts of lag time contour (LTC) and area frequency curve (AFC), both of which can be used for describing the spatial distribution of RF lag time in an arid area. AFC can be determined from LTC or obtained from RF observations and use of the trial-and-error method. A new RF prediction model was developed for arid regions based on LTC and AFC, and the model couples deep percolation (DP) and lag time in order to achieve the prediction of RF. This model was applied in the eastern part of the Jingdian irrigation district in northwest China, and the results indicate that the model predictions fit well with the observations and that the model is reliable. Analysis of DP and RF in the study area between 2000 and 2020 proved that when lag time is not greater than half a year, the main factor that influences yearly-scale RF is DP, and when lag time is greater than one year, the factors that influence yearly-scale RF are DP and lag time. The main influences on monthly-scale RF are DP and lag time, but this is to a lesser extent than their influence on yearly-scale RF. LTC and AFC help understand the process of RF production in arid regions and the influence lag time has on RF. Additionally, the RF prediction model developed for this study is suitable for RF prediction at different time scales, and also for RF predictions in arid areas where there is insufficient hydrogeological data. This is of great significance for the efficient use of water resources in arid regions’ irrigation areas.

Suggested Citation

  • Jie, Feilong & Fei, Liangjun & Li, Shan & Hao, Kun & Liu, Lihua & Zhu, Hongyan, 2021. "Prediction model for irrigation return flow considering lag effect for arid areas," Agricultural Water Management, Elsevier, vol. 256(C).
    • Handle: RePEc:eee:agiwat:v:256:y:2021:i:c:s0378377421003954
    DOI: 10.1016/j.agwat.2021.107119
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377421003954
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2021.107119?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. Poch-Massegú, R. & Jiménez-Martínez, J. & Wallis, K.J. & Ramírez de Cartagena, F. & Candela, L., 2014. "Irrigation return flow and nitrate leaching under different crops and irrigation methods in Western Mediterranean weather conditions," Agricultural Water Management, Elsevier, vol. 134(C), pages 1-13.
    2. Wu, Di & Cui, Yuanlai & Wang, Yitong & Chen, Manyu & Luo, Yufeng & Zhang, Lei, 2019. "Reuse of return flows and its scale effect in irrigation systems based on modified SWAT model," Agricultural Water Management, Elsevier, vol. 213(C), pages 280-288.
    3. Mohan, S. & Vijayalakshmi, D.P., 2009. "Prediction of irrigation return flows through a hierarchical modeling approach," Agricultural Water Management, Elsevier, vol. 96(2), pages 233-246, February.
    4. Anuraga, T.S. & Ruiz, L. & Kumar, M.S. Mohan & Sekhar, M. & Leijnse, A., 2006. "Estimating groundwater recharge using land use and soil data: A case study in South India," Agricultural Water Management, Elsevier, vol. 84(1-2), pages 65-76, 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. Zhongwei Liang & Tao Zou & Yupeng Zhang & Jinrui Xiao & Xiaochu Liu, 2022. "Sprinkler Drip Infiltration Quality Prediction for Moisture Space Distribution Using RSAE-NPSO," Agriculture, MDPI, vol. 12(5), pages 1-32, May.
    2. Feilong Jie & Liangjun Fei & Shan Li & Kun Hao & Lihua Liu & Youliang Peng, 2022. "Effects on Net Irrigation Water Requirement of Joint Distribution of Precipitation and Reference Evapotranspiration," Agriculture, MDPI, vol. 12(6), pages 1-16, June.

    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. Wen, Yeqiang & Shang, Songhao & Rahman, Khalil Ur & Xia, Yuhong & Ren, Dongyang, 2020. "A semi-distributed drainage model for monthly drainage water and salinity simulation in a large irrigation district in arid region," Agricultural Water Management, Elsevier, vol. 230(C).
    2. Wu, Di & Cui, Yuanlai & Wang, Yitong & Chen, Manyu & Luo, Yufeng & Zhang, Lei, 2019. "Reuse of return flows and its scale effect in irrigation systems based on modified SWAT model," Agricultural Water Management, Elsevier, vol. 213(C), pages 280-288.
    3. Wu, Di & Cui, Yuanlai & Li, Dacheng & Chen, Manyu & Ye, Xugang & Fan, Guofu & Gong, Lanqiang, 2021. "Calculation framework for agricultural irrigation water consumption in multi-source irrigation systems," Agricultural Water Management, Elsevier, vol. 244(C).
    4. Wu, Di & Cui, Yuanlai & Luo, Yufeng, 2019. "Irrigation efficiency and water-saving potential considering reuse of return flow," Agricultural Water Management, Elsevier, vol. 221(C), pages 519-527.
    5. Baccar, Mariem & Raynal, Hélène & Sekhar, Muddu & Bergez, Jacques-Eric & Willaume, Magali & Casel, Pierre & Giriraj, P. & Murthy, Sanjeeva & Ruiz, Laurent, 2023. "Dynamics of crop category choices reveal strategies and tactics used by smallholder farmers in India to cope with unreliable water availability," Agricultural Systems, Elsevier, vol. 211(C).
    6. 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).
    7. Bali, Khaled M. & Mohamed, Abdelmoneim Zakaria & Begna, Sultan & Wang, Dong & Putnam, Daniel & Dahlke, Helen E. & Eltarabily, Mohamed Galal, 2023. "The use of HYDRUS-2D to simulate intermittent Agricultural Managed Aquifer Recharge (Ag-MAR) in Alfalfa in the San Joaquin Valley," Agricultural Water Management, Elsevier, vol. 282(C).
    8. Simons, G.W.H. & Bastiaanssen, W.G.M. & Cheema, M.J.M. & Ahmad, B. & Immerzeel, W.W., 2020. "A novel method to quantify consumed fractions and non-consumptive use of irrigation water: Application to the Indus Basin Irrigation System of Pakistan," Agricultural Water Management, Elsevier, vol. 236(C).
    9. Libutti, Angela & Monteleone, Massimo, 2017. "Soil vs. groundwater: The quality dilemma. Managing nitrogen leaching and salinity control under irrigated agriculture in Mediterranean conditions," Agricultural Water Management, Elsevier, vol. 186(C), pages 40-50.
    10. Huang, Yajie & Ma, Yibing & Zhang, Shiwen & Li, Zhen & Huang, Yuanfang, 2021. "Optimum allocation of salt discharge areas in land consolidation for irrigation districts by SahysMod," Agricultural Water Management, Elsevier, vol. 256(C).
    11. Dokoohaki, Hamze & Gheysari, Mahdi & Mousavi, Sayed-Farhad & Zand-Parsa, Shahrokh & Miguez, Fernando E. & Archontoulis, Sotirios V. & Hoogenboom, Gerrit, 2016. "Coupling and testing a new soil water module in DSSAT CERES-Maize model for maize production under semi-arid condition," Agricultural Water Management, Elsevier, vol. 163(C), pages 90-99.
    12. Vallury, Sechindra & Abbott, Joshua K. & Shin, Hoon C. & Anderies, John M., 2020. "Sustaining Coupled Irrigation Infrastructures: Multiple Instruments for Multiple Dilemmas," Ecological Economics, Elsevier, vol. 178(C).
    13. Hu, Qiuli & Yang, Yonghui & Han, Shumin & Yang, Yanmin & Ai, Zhipin & Wang, Jiusheng & Ma, Fengyun, 2017. "Identifying changes in irrigation return flow with gradually intensified water-saving technology using HYDRUS for regional water resources management," Agricultural Water Management, Elsevier, vol. 194(C), pages 33-47.
    14. Van Camp, M. & Radfar, M. & Walraevens, K., 2010. "Assessment of groundwater storage depletion by overexploitation using simple indicators in an irrigated closed aquifer basin in Iran," Agricultural Water Management, Elsevier, vol. 97(11), pages 1876-1886, November.
    15. He, Yong & Liang, Hao & Hu, Kelin & Wang, Hongyuan & Hou, Lingling, 2018. "Modeling nitrogen leaching in a spring maize system under changing climate and genotype scenarios in arid Inner Mongolia, China," Agricultural Water Management, Elsevier, vol. 210(C), pages 316-323.
    16. Woli, Prem & Hoogenboom, Gerrit, 2018. "Simulating weather effects on potato yield, nitrate leaching, and profit margin in the US Pacific Northwest," Agricultural Water Management, Elsevier, vol. 201(C), pages 177-187.
    17. Shi, Jianchu & Wu, Xun & Zhang, Mo & Wang, Xiaoyu & Zuo, Qiang & Wu, Xiaoguang & Zhang, Hongfei & Ben-Gal, Alon, 2021. "Numerically scheduling plant water deficit index-based smart irrigation to optimize crop yield and water use efficiency," Agricultural Water Management, Elsevier, vol. 248(C).
    18. Kumar, P. & Sarangi, A. & Singh, D.K. & Parihar, S.S. & Sahoo, R.N., 2015. "Simulation of salt dynamics in the root zone and yield of wheat crop under irrigated saline regimes using SWAP model," Agricultural Water Management, Elsevier, vol. 148(C), pages 72-83.
    19. Chen, Yong & Marek, Gary W. & Marek, Thomas H. & Porter, Dana O. & Brauer, David K. & Srinivasan, Raghavan, 2021. "Simulating the effects of agricultural production practices on water conservation and crop yields using an improved SWAT model in the Texas High Plains, USA," Agricultural Water Management, Elsevier, vol. 244(C).
    20. Li, Danfeng, 2020. "Quantifying water use and groundwater recharge under flood irrigation in an arid oasis of northwestern China," Agricultural Water Management, Elsevier, vol. 240(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:256:y:2021:i:c:s0378377421003954. 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.