Evaluation and forecasting of daily groundwater outflow in a small chalky watershed

• Published in: Hydrological processes Vol. 17; no. 8; pp. 1561 - 1577
• Main Authors: Lallahem, S., Mania, J.
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 15-06-2003; Wiley
• Subjects: back propagation algorithm; chalk; Earth sciences; Earth, ocean, space; Exact sciences and technology; fractured rock; groundwater; Hydrogeology; Hydrology. Hydrogeology; neural networks; stopped training approach; Pas-de-Calais France; Paris Basin; France; Western Europe; algorithms; carbonate rocks; Europe; mathematical models; neural networks; ground water; digital simulation; groundwater; stopped training approach; sedimentary rocks; drainage basins; back propagation algorithm; piezometric surface; chalk; fractured materials; fractured rock; hydrographs
• ISSN: 0885-6087; 1099-1085
• DOI: 10.1002/hyp.1199

The purpose of this research is to include expert knowledge as one part of the modelling system and therefore offer the chance to create a productive interaction system between expert, mathematical model (MMO8) and artificial neural networks (ANNs). In the present project, the first objective is to determine some parameters by the MMO8 model, introduced as ANN input parameters to forecast spring outflow. The second objective is first to investigate the effect of temporal information by taking current and past data sets and then to forecast spring outflow. The good results obtained reveal the merit of the ANNs–MMO8 combination, and specifically multilayer perceptron (MLP) models. This methodology, for a network with lower, lag and number hidden layer, consistently produced better performance. Copyright © 2003 John Wiley & Sons, Ltd.