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Prediction of irrigation return flows through a hierarchical modeling approach

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  • Mohan, S.
  • Vijayalakshmi, D.P.

Abstract

The quantity of water available for irrigation is getting scarce in many countries and it assumes great importance for assured crop production, especially in view of the erratic behavior of the monsoon. Thus, there is a pressing need to improve the water efficiency of irrigation systems. One-way of improving the efficiency of the irrigation system is reusing the return flow from the irrigation system. This task requires quantification of return flow, which still remains as a grey area in irrigation water management. The estimation of return flow from the irrigation system is usually obtained using thumb rules depending upon the site-specific conditions like command area conditions and soil properties. In this paper, a hierarchical modeling technique, namely, regression tree is developed for return flow estimation. Regression tree is built through binary recursive partitioning. The effective rainfall, inflow, consumptive water demand, and percolation loss are taken as predictor variables and return flow is treated as the target variable. The applicability of the hierarchical model is demonstrated through a case study of Periyar-Vaigai Irrigation System in Tamil Nadu, India. The model performance shows a good match between the simulated and the field measured return flow values. Results of statistical analysis indicated that the correlation coefficients are high for both single as well as double crop seasons.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:agiwat:v:96:y:2009:i:2:p:233-246
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    Citations

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    Cited by:

    1. Xuezhi Tan & Dongguo Shao & Wenquan Gu, 2018. "Improving Water Reuse in Paddy Field Districts with Cascaded On-farm Ponds using Hydrologic Model Simulations," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(5), pages 1849-1865, March.
    2. 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).
    3. Gordon, Beatrice L. & Paige, Ginger B. & Miller, Scott N. & Claes, Niels & Parsekian, Andrew D., 2020. "Field scale quantification indicates potential for variability in return flows from flood irrigation in the high altitude western US," Agricultural Water Management, Elsevier, vol. 232(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. 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).
    6. 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.
    7. 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).
    8. Adeyemo, Josiah & Otieno, Fred, 2010. "Differential evolution algorithm for solving multi-objective crop planning model," Agricultural Water Management, Elsevier, vol. 97(6), pages 848-856, June.

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