Abstract & Overview
Increasing urbanization and the population's demand for water shortages in urban and rural areas leads to a decline in groundwater resources, to the need to plan artificial groundwater recharge. This study shows the ability of three decision-making approaches, namely fuzzy logic (FL), analytical hierarchy process (AHP) and integrated Fuzzy-AHP techniques in groundwater potentiality mapping. A total eight parameters such as geology, geomorphology (GM) landuse/landcover (LULC), soil types, drainage density (DD), water level fluctuations (WLF) in the pre and post monsoon, vadose zone (VZ), and slope are assessed through satellite and conventional data sources. All these parameters and their sub-parameters are assigned weights to implement FL, AHP and integrated Fuzzy-AHP models based on existing knowledge. Three result maps have been prepared up that integrate all these parameters and their respective weights into the GIS software. Accuracy results show that the map made with the integrated Fuzzy-AHP model is more efficient (78% validation) than AHP (76% validation) and FL approaches (72% validation). This study concludes that the integrated AHP-Fuzzy model is more reliable for estimating the groundwater potential. However, the impact of the study on the impact of knowledge of the criteria has shown that the ability of the technique to accurately predict depends on the integrity of the classification of the criteria used. The study found that a simple GIS-based integrated approach is suitable for making accurate and reliable predictions, especially if the order of the criteria used for expectation is consistent. Such findings have shown that planners in regions with a lack of data have an accurate knowledge of groundwater sources through the integrated methodology based on an analysis of geospatial data. In this manner, advancement for the inescapable plan of groundwater research can be created in a compelling manner.