The state of the groundwater inverse problem is synthesized. Emphasis is placed on aquifer
characterization, where modelers have to deal with conceptual model uncertainty (notably …

An attempt has been made to develop Artificial Neural Network (ANN) model for prediction
of nitrate concentration in groundwater of Kadava River basin, Nashik District, Maharashtra …

This paper presents a hybrid local‐global sensitivity analysis method termed the Distributed
Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important …

Groundwater resources constitute the main source of clean fresh water for domestic use and
it is essential for food production in the agricultural sector. Groundwater has a vital role for …

VARS-TOOL is a software toolbox for sensitivity and uncertainty analysis. Developed
primarily around the “Variogram Analysis of Response Surfaces” framework, VARS-TOOL …

Four algorithms are outlined, each of which has interesting features for predicting
contaminant levels in groundwater. Artificial neural networks (ANN), support vector …

In this paper, a support vector machine (SVM) model was developed to predict nitrate
concentration in groundwater of Arak plain, Iran. The model provided a tool for prediction of …

In this study, a methodology has been developed to emulate a time consuming Monte Carlo
(MC) simulation by using an Artificial Neural Network (ANN) for the assessment of model …

Landslides are one of the most common and a destructive natural hazard in mountainous
terrain and thus evaluating their potential locations and the conditions under which they may …

Water supply in semiarid Botswana is, to a large extent, based on groundwater. In the
planning of a groundwater abstraction scheme, criteria for the sustainability of the …