Modeling and groundwater potential mapping using data driven ensemble model EBF-Index of entropy (case study: najaf abad aquifer)

Groundwater considered as the main source of future water supply, irrigation, and food production under impacts of global climate changes phenomena. Main aquifers around the world are under pressure to meet the growing demands of water due to population growth. Management of groundwater reserves in a sustainable manner is a major challenge. A goal of groundwater resource assessment is to provide information on the current status of the resource and provide insights about the future availability of ground water. In recent years, several authors have attempted to assessment groundwater potential using different data-driven and knowledge-driven techniques combined with remote sensing (RS) and geographic information system (GIS). The main objective of this research is identification of effective parameters in groundwater recharge and assessment of groundwater potential using data-driven combined method in najaf-abad aquifer.
The study area lies between (32° 18′ 06″- 32° 50′ 12) latitude and (50° 52′ 46″- 51° 41′ 48″) longitude. It extends over an area of about 966.11 km2. In general, four steps must be implemented to groundwater potential mapping using combined approache. These steps are: (1) prepare groundwater well inventory map and divided into two sets: training and testing. The training data is used to investigate the statistical relationship between well locations and Geo-environmental factors influence on groundwater occurrences. The testing set is used to validate the results. (2) Build the database. In this step layers of groundwater occurrence factors are prepared using different resources such as field survey, and RS. All thematic layers must be converted to raster format to use in further analysis. (3) computation the relationship between training well locations and groundwater occurrence factors using shanoon model and their classes using EBF model are investigated. The groundwater potential map is then computed and classified into four classes using Natural Break scheme (4) the validation of the results and compare the effectiveness of model in prediction groundwater potential zones with indivdal models.
The results of the multicollinearity analysis among 20 Geo-environmental factors influence on groundwater occurrences used in this study showed that the Tolerance and VIF of 15 variables were ≥0.1 and ≤10, respectively. As a result, this parameters are selected for modeling. The computed weights for each factor using Index of entropy model, indicated that the most influencing factors on groundwater occurrence in the study area were distance from fault, LULC and geology. The results of validation of models indicate that The AUC for EBF, index of entropy and EBF-index of entropy models were 0.660, 0.431 and 0.899, respectively implying that the EBF-index of entropy was better than EBF and index of entropy.
Conclution: The main conclusions of this study is that The ensembled approach of EBF-Index of entropy combining with RS and GIS technologies provide a powerful tool for groundwater potential mapping in the study area. The results of this study could be used for efficient managing groundwater resources in the study area. Based on results of ensemble model, The areas covered by very high groundwater potential zones occupy 45.26 % of the total area, indicating that the groundwater potential is high in study area.