title: Groundwater resources management through the applications of simulation modeling: a review.
abstract: The global population is increasing rapidly and expected to touch the 9.5 billion mark by 2050 from the current 7.2 billion. The management of the groundwater resources is a challenging task worldwide against the backdrop of the growing water demand for industrial, agricultural, and domestic uses and shrinking resources. Moreover, this task has been hampered significantly due to declining/rising groundwater levels and associated contamination. A broad range of solutions could be considered to address the aforementioned problems of groundwater management, but the effectiveness of all the solutions and their combinations cannot be verified with field experiments. Given their predictive capability, simulation models are often the only viable means of providing input to management decisions, as they can forecast the likely impacts of a particular water management strategy. This paper presents a comprehensive review on the simulation modeling applications for the management of groundwater resources. The past papers on the overview of groundwater simulation models, use of remote sensing and GIS in groundwater modeling, and application of simulation models in arid and semiarid regions are described in detail. Conclusions are drawn where gaps exist and more research needs to be focused.
authors.affiliation: Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur, West Bengal 721302, India. Electronic address: erajay07@yahoo.co.in.
authors.forename: Ajay
authors.initials: A
authors.lastname: Singh
mesh_terms: D000383:Agriculture; D003247:Conservation of Natural Resources / Q000379:methods*; D004784:Environmental Monitoring; D060587:Groundwater / Q000032:analysis*; D008956:Models, Chemical; D062066:Water Resources / Q000706:statistics & numerical data*; D014881:Water Supply / Q000706:statistics & numerical data*
keywords: Groundwater depletion: remote sensing; Groundwater management; Semiarid region; Simulation modeling