Sustainable management of a coupled groundwater-agriculture hydrosystem using multi-criteria simulation based optimisation

Water Sci Technol. 2013;67(3):689-98. doi: 10.2166/wst.2012.602.


In this paper we present a new simulation-based integrated water management tool for sustainable water resources management in arid coastal environments. This tool delivers optimised groundwater withdrawal scenarios considering saltwater intrusion as a result of agricultural and municipal water abstraction. It also yields a substantially improved water use efficiency of irrigated agriculture. To allow for a robust and fast operation we unified process modelling with artificial intelligence tools and evolutionary optimisation techniques. The aquifer behaviour is represented using an artificial neural network (ANN) which emulates a numerical density-dependent groundwater flow model. The impact of agriculture is represented by stochastic crop water production functions (SCWPF). Simulation-based optimisation techniques together with the SCWPF and ANN deliver optimal groundwater abstraction and cropping patterns. To address contradicting objectives, e.g. profit-oriented agriculture vs. sustainable abstraction scenarios, we performed multi-objective optimisations using a multi-criteria optimisation algorithm.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Agriculture*
  • Algorithms*
  • Biomass
  • Computer Simulation
  • Groundwater*
  • Neural Networks, Computer
  • Salinity
  • Water Movements*
  • Water Supply*