title: Sustainable management of a coupled groundwater-agriculture hydrosystem using multi-criteria simulation based optimisation.
abstract: 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.
authors.affiliation: TU Dresden, Institute of Hydrology and Meteorology, 01062 Dresden, Germany. jens.grundmann@tu-dresden.de
authors.forename: Jens
authors.initials: J
authors.lastname: Grundmann
authors.forename: Niels
authors.initials: N
authors.lastname: Schütze
authors.forename: Franz
authors.initials: F
authors.lastname: Lennartz
mesh_terms: D000383:Agriculture; D000465:Algorithms; D018533:Biomass; D003198:Computer Simulation; D060587:Groundwater; D016571:Neural Networks, Computer; D054712:Salinity; D014872:Water Movements; D014881:Water Supply