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The hydrologic adversaries like high magnitude storms, extreme dryness, aridity, more than normal demand for water etc. often cause a huge stress on the storage structures such as reservoirs and che...
This paper examines the use of genetic algorithm (GA) optimization to identify water delivery schedules for an open-channel irrigation system. Significant objectives and important constraints are iden...
This study presents a methodology for quantifying the tradeoffs between sampling costs and local concentration estimation errors in an existing groundwater monitoring network. The method utilizes hist...
A groundwater management model has been developed that predicts human health risks and uses a noisy genetic algorithm to identify promising risk-based corrective action (RBCA) designs. Noisy genetic a...
The physically realistic functions implemented in nearshore process models are governed by parameters that usually do not represent measurable attributes of the nearshore and, therefore, need to be de...
Success of any forecasting model depends heavily on reliable historical data, among others. Data are needed to calibrate, fine tune and verify any simulation model. However, data are very often contam...
Near-term consumption of groundwater for irrigated agriculture in the High Plains Aquifer supports a dynamic bio-socio-economic system, all parts of which will be impacted by a future transition to su...
Calibration of a model against more than one output variable is important for reliable simulations of internal processes. In this study, a genetic algorithm combined with local optimisation was propos...
The practical application of simulation models in the field is sometimes hindered by the difficulty of deriving the soil hydraulic properties of the study area. The procedure so-called inverse modelli...

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