An inexact fractional programming model for irrigation water resources optimal allocation under multiple uncertainties

PLoS One. 2019 Jun 13;14(6):e0217783. doi: 10.1371/journal.pone.0217783. eCollection 2019.

Abstract

In reality, severe water shortage crisis has made bad impact on the sustainable development of a region. In addition, uncertainties are inevitable in the irrigation system. Therefore, a fully fuzzy fractional programming model for optimization allocation of irrigation water resources, which aimed at not only irrigation water optimization but also improving water use efficiency. And then the developed model applied to a case study in Minqin County, Gansu Province, China, which selected maximum economic benefit of per unit water resources as planning objective. Moreover, surface and underground water are main water sources for irrigation. Thus, conjunctive use of surface and underground water was taken under consideration in this study. By solving the developed model, a series of optimal crop area and planting schemes, which were under different α-cut levels, were offered to the decision makers. The obtained results could be helpful for decision makers to make decision on the optimal use of irrigation water resources under multiple uncertainties.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Agricultural Irrigation*
  • China
  • Crops, Agricultural
  • Fuzzy Logic
  • Models, Theoretical
  • Resource Allocation*
  • Uncertainty*
  • Water Resources

Grants and funding

This research was supported by the National Science Foundation of China (51809005, 51409006), Certificate of China Postdoctoral Science Foundation Grant (2019M650269), the Technology Foundation for Selected Overseas Chinese Scholars, Department of Personnel in Shaanxi Province of China (2017035), the Water Conservancy Science and Technology Program of Shaanxi Province of China (2018slkj-11), State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi’an University of Technology (2018KFKT-4), National Science Foundation of Shaanxi Province (2018JQ5209) and the Fundamental Research Funds for the Central Universities (300102299105, 300102298306).