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Optimal decision schemes for agricultural water quality management planning with imprecise objective

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  • Zhang, Xiaodong
  • Huang, Guo H.
  • Nie, Xianghui

Abstract

Agricultural activities are the main sources of water pollution to surface water and groundwater in rural areas. Extensive soil disturbance and application of fertilizer and manure in agriculture cause nonpoint source losses of soil and nutrients such as nitrogen and phosphorus. How to generate preferred decision schemes for agricultural activities that cause such nonpoint source water pollution is a critical issue for the decision makers. In this study, an inexact agricultural water quality management (IAWQM) model is developed and applied to a case study to generate optimal decision schemes for integrated water quality management within an agricultural system. The model is based on a hybrid fuzzy possibilistic robust programming approach, which improves upon the existing fuzzy possibilistic programming and fuzzy robust programming methods by allowing fuzzy information in the model's objective and constraints to be directly communicated into the optimization processes and resulting solutions. Optimal decision schemes for agricultural activities can be generated, including cropping area, manure/fertilizer applied, and livestock husbandry size, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. The results of the case study indicate that useful information can be obtained through the proposed IAWQM model for providing feasible decision schemes, which reflect tradeoffs between economic and environmental considerations. The decision variables are useful for the decision makers to justify and/or adjust the decision schemes for agricultural activities through incorporation of their implicit knowledge on water quality management.

Suggested Citation

  • Zhang, Xiaodong & Huang, Guo H. & Nie, Xianghui, 2009. "Optimal decision schemes for agricultural water quality management planning with imprecise objective," Agricultural Water Management, Elsevier, vol. 96(12), pages 1723-1731, December.
    • Handle: RePEc:eee:agiwat:v:96:y:2009:i:12:p:1723-1731
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    References listed on IDEAS

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    Cited by:

    1. Zeng, Xieting & Kang, Shaozhong & Li, Fusheng & Zhang, Lu & Guo, Ping, 2010. "Fuzzy multi-objective linear programming applying to crop area planning," Agricultural Water Management, Elsevier, vol. 98(1), pages 134-142, December.
    2. Zhang, Y.M. & Lu, H.W. & Nie, X.H. & He, L. & Du, P., 2014. "An interactive inexact fuzzy bounded programming approach for agricultural water quality management," Agricultural Water Management, Elsevier, vol. 133(C), pages 104-111.
    3. Zhang, J.L. & Li, Y.P. & Wang, C.X. & Huang, G.H., 2015. "An inexact simulation-based stochastic optimization method for identifying effluent trading strategies of agricultural nonpoint sources," Agricultural Water Management, Elsevier, vol. 152(C), pages 72-90.
    4. Li, Y.P. & Huang, G.H. & Nie, S.L. & Chen, X., 2011. "A robust modeling approach for regional water management under multiple uncertainties," Agricultural Water Management, Elsevier, vol. 98(10), pages 1577-1588, August.
    5. Liu, M. & Huang, G.H. & Liao, R.F. & Li, Y.P. & Xie, Y.L., 2013. "Fuzzy two-stage non-point source pollution management model for agricultural systems—A case study for the Lake Tai Basin, China," Agricultural Water Management, Elsevier, vol. 121(C), pages 27-41.
    6. Niu, G. & Li, Y.P. & Huang, G.H. & Liu, J. & Fan, Y.R., 2016. "Crop planning and water resource allocation for sustainable development of an irrigation region in China under multiple uncertainties," Agricultural Water Management, Elsevier, vol. 166(C), pages 53-69.
    7. Huang, Y. & Li, Y.P. & Chen, X. & Ma, Y.G., 2012. "Optimization of the irrigation water resources for agricultural sustainability in Tarim River Basin, China," Agricultural Water Management, Elsevier, vol. 107(C), pages 74-85.

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