The influence of optimized allocation of agricultural water and soil resources on irrigation and drainage in the Jingdian Irrigation District, China

  • Jingsi Li
  • Liangjun FeiEmail author
  • Shan Li
  • Zhongxing Shi
  • Lihua Liu
Original Paper


Reasonable regulation of irrigation and drainage is an important way to decrease water resource waste and water pollution, and to ensure the sustainable utilization of water resources. In this study, appropriate irrigation and drainage methods are proposed by optimizing agricultural water and soil resources based on the current status of water resource utilization in irrigation district in Northwest China, and as much as possible to reduce the amount of irrigation and drainage while ensuring the necessary for salt leaching. A two-layer model was considered to maximize economic benefits and relative production through a nonlinear algorithm to optimize the crop acreage, irrigation quota and the amount of irrigation water at each crop growth stage. A support vector machine regression model for predicting drainage was constructed, including drainage and irrigation, precipitation, evaporation and groundwater depth. Additionally, the amount of drainage water was compared before and after the optimization of irrigation. The amount of irrigation water demand in a wet year (2014), normal year (2008) and dry year (2013) decreased by 23.85 million m3, 12.85 million m3 and 17.50 million m3, respectively, after optimization of the crop planting structure and irrigation scheduling. Furthermore, the net economic benefit increased by 3.76 billion yuan, 1.14 billion yuan and 2.34 billion yuan, as compared with the actual output value. The amount of drainage water decreased by 8.60%, 8.93% and 5.21% compared to that with no optimization in a wet year (2014), normal year (2008) and dry year (2013), respectively. This method can scientifically allocate the amount of irrigation and drainage, feasibly improve economic benefits and prevent soil salinization, thus providing guidance for efficient water resource utilization and ecological protection in arid areas.



This work is partly supported by the National Natural Science Foundation of China (51779205); Gansu Province Jingtaichuan Electric Pumping Irrigation District Return (Regression) Water Monitoring and Utilization Research Project Contract (ZKGK-2016-023).


  1. Ale S, Bowling LC, Owens PR (2012) Development and application of a distributed modeling approach to assess the watershed-scale impact of drainage water management. Agric Water Manag 107:23–33Google Scholar
  2. Allam A, Negm A (2013) Agricultural drainage water quality analysis and its suitability for direct reuse in irrigation: case study: Kafr El-Sheikh governorate, Egypt. In Seventeenth International Water Technology Conference, IWTC17 Istanbul, pp 5–7Google Scholar
  3. Allen RG, Pereira LS, Raes D, Smith M (1998) FAO Irrigation and drainage paper no. 56 (97). Food and Agriculture Organization of the United Nations, Rome, p. e156Google Scholar
  4. Ayers RS, Westcot DW (1985) FAO irrigation and drainage paper# 29: water quality for agriculture. FAO, Rome, pp 19–31Google Scholar
  5. Davijani MH, Banihabib ME, Anvar AN (2016) Optimization model for the allocation of water resources based on the maximization of employment in the agriculture and industry sectors. J Hydrol 533:430–438Google Scholar
  6. Fleifle AE, Saavedra Valeriano OC, Nagy HM (2012) Simulation-optimization model for intermediate reuse of agriculture drainage water in Egypt. J Environ Eng 139(3):391–401Google Scholar
  7. Ghorbani MA, Zadeh HA, Isazadeh M, Terzi O (2016) A comparative study of artificial neural network (MLP, RBF) and support vector machine models for river flow prediction. Environ Earth Sci 75(6):476Google Scholar
  8. Gunn KM, Fausey NR, Shang Y (2015) Subsurface drainage volume reduction with drainage water management: case studies in Ohio, USA. Agric Water Manag 149:131–142Google Scholar
  9. Hanjra MA, Ferede T, Gutta DG (2009a) Reducing poverty in sub-Saharan Africa through investments in water and other priorities. Agric Water Manag 96(7):1062–1070Google Scholar
  10. Hanjra MA, Ferede T, Gutta DG (2009b) Pathways to breaking the poverty trap in Ethiopia: investments in agricultural water, education, and markets. Agric Water Manag 96(11):1596–1604Google Scholar
  11. Huffman WE, Evenson RE (2001) Structural and productivity change in US agriculture, 1950–1982. Agric Econ 24(2):127–147Google Scholar
  12. Jensen ME (1968) Water consumption by agricultural plants [M]//KOZLOWSKI T T. Plant water consumption and response. Academic Press, New YorkGoogle Scholar
  13. Jing WH, Luo W, Jia ZH (2012) Optimization of agricultural drainage system design with multiple objectives in a vertisol soil district of China based on drain MoD simulations. J Hydraul Eng 43(7):842–851 (in Chinese with English abstract) Google Scholar
  14. Jiang Y, Xu X, Huang Q (2016) Optimizing regional irrigation water use by integrating a two-level optimization model and an agro-hydrological model. Agric Water Manag 178:76–88Google Scholar
  15. Kurosaki T (2003) Specialization and diversification in agricultural transformation: the case of West Punjab, 1903–92. Am J Agr Econ 85(2):372–386Google Scholar
  16. Li S (2017) Water and salinity management and its dynamic of wetland under controlled drainage in irrigated area. X’ian University of Technology, X’ian (in Chinese with English abstract) Google Scholar
  17. Li M, Guo P, Singh VP (2016) An efficient irrigation water allocation model under uncertainty. Agric Syst 144:46–57Google Scholar
  18. Li JS, Fei LJ, Li S, Shi ZX, Chen TS (2019) Advances in simulation and regulation methods of irrigation return flow. J Nat Disasters 28(01):054–064 (in Chinese with English abstract) Google Scholar
  19. Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50(3):885–900Google Scholar
  20. Mohammadpour R, Shaharuddin S, Chang CK, Zakaria NA, Ghani AA, Chan NW (2015) Prediction of water quality index in constructed wetlands using support vector machine. Environ Sci Pollut Res 22:6208–6219Google Scholar
  21. Nash PR, Nelson KA, Motavalli PP (2015) Reducing phosphorus loss in tile water with managed drainage in a claypan soil. J Environ Qual 44(2):585–593Google Scholar
  22. National Research Council (1989) Irrigation-induced water quality problems: what can be learned from the San Joaquin Valley experience. National Academy Press, Washington, p 157Google Scholar
  23. Negm LM, Youssef MA, Jaynes DB (2017) Evaluation of DRAINMOD-DSSAT simulated effects of controlled drainage on crop yield, water balance, and water quality for a corn-soybean cropping system in central Iowa. Agric Water Manag 187:57–68Google Scholar
  24. Rhoades JD, Merrill SD (1976) Man-made factors: assessing the suitability of water for irrigation: theoretical and empirical approaches. FAO Soils Bulletins. FAO, Rome, pp 69–110Google Scholar
  25. Ritzema HP (2016) Drain for gain: managing salinity in irrigated lands-A review. Agric Water Manag 176:18–28Google Scholar
  26. Ross JA, Herbert ME, Sowa SP (2016) A synthesis and comparative evaluation of factors influencing the effectiveness of drainage water management. Agric Water Manag 178:366–376Google Scholar
  27. Shangguan Z, Shao M, Horton R (2002) A model for regional optimal allocation of irrigation water resources under deficit irrigation and its applications. Agric Water Manag 52(2):139–154Google Scholar
  28. Shen RK, Zhang YF, Huang GH (1995) A review of crop-water production functions and problem of irrigation with inadequate water supply. Adv Water Sci 6(3):248–254 (in Chinese with English abstract) Google Scholar
  29. Singh A (2018) Managing the salinization and drainage problems of irrigated areas through remote sensing and GIS techniques. Ecol Ind 89:584–589Google Scholar
  30. Skaggs RW, Breve MA, Gilliam JW (1994) Hydrologic and water quality impacts of agricultural drainage. Crit Rev Environ Technol 24(1):1–32Google Scholar
  31. Skaggs RW, Youssef MA, Gilliam JW (2010) Effect of controlled drainage on water and nitrogen balances in drained lands. Trans ASABE 53(6):1843–1850Google Scholar
  32. Vapnik VN (1995) The nature of statistical learning theory. Springer science and business media, BerlinGoogle Scholar
  33. Wang ZN (2010) Irrigation and drainage engineering. China Agriculture Press, BeijingGoogle Scholar
  34. Wang T, Li P, Li Z, Hou J, Xiao L, Ren Z, Xu GC, Yu KX, Su Y (2019) The effects of freeze–thaw process on soil water migration in dam and slope farmland on the Loess Plateau, China. Sci Total Environ 666:721–730Google Scholar
  35. Wesström I, Messing I, Linner H (2001) Controlled drainage-effects on drain outflow and water quality. Agric Water Manag 47(2):85–100Google Scholar
  36. Xie YL, Xia DX, Ji L (2018) An inexact stochastic-fuzzy optimization model for agricultural water allocation and land resources utilization management under considering effective rainfall. Ecol Ind 92:301–311Google Scholar
  37. Xu WL (2011) Agricultural planting structure optimization based on the efficient use of water resources. Northwest A&F University, Xianyang (in Chinese with English abstract) Google Scholar
  38. Xu WL, Su XL, Shi YJ (2011) The optimization of agricultural planting structure and irrigation system based on the efficient use of water resources-A case study of Minqin. Res Soil Water Conserv 18(1):205–209 (in Chinese with English abstract) Google Scholar
  39. Yan DH, Wang H, Zhang JY (2017) From changing status to improving capability: construction of an ecological sponge-smart river basins. Adv Water Sci 28(1):1–9 (in Chinese with English abstract) Google Scholar
  40. Yang Y, Chen RJ (2013) Current status and trends of China’s apple production cost benefits. Agric Outlook 8(12):29–31Google Scholar
  41. Zhang LP, Xia J, Hu ZF (2009) Situation and problem analysis of water resource security in China [J]. Res Environ Yangtze Basin 18(2):116–120 (in Chinese with English abstract) Google Scholar
  42. Zhao XY (2007) Study on theories and methods of return water volume prediction in large irrigation area. Xian university of technology, Xian (in Chinese with English abstract) Google Scholar
  43. Zhao XY, Fei LJ, Fang SX (2006) Dynamic model for simulation of irrigation return flow based on neural network. J Hydraul Eng 37(6):717–721 (in Chinese with English abstract) Google Scholar
  44. Zhao XY, Yu QF, Fei LJ (2015) Laws for water diversion and drainage water volume in Qingtongxia irrigation area. Water Sav Irrig 03:73–75 (in Chinese with English abstract) Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Jingsi Li
    • 1
  • Liangjun Fei
    • 1
    Email author
  • Shan Li
    • 1
  • Zhongxing Shi
    • 2
  • Lihua Liu
    • 1
  1. 1.State Key Laboratory of Eco-Hydraulics in Northwest Arid Region of ChinaXi’an University of TechnologyXi’anChina
  2. 2.Gansu Jingtaichuan Irrigation Management BureauJingtaiChina

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