Spatio-Temporal Assessment of Groundwater Potential Zone in the Drought-Prone Area of Bangladesh Using GIS-Based Bivariate Models

Abstract

Groundwater is one of the most dynamic and renewable natural resources found in the earth’s crust. A spatio-temporal assessment of groundwater potential zone (GWPZ) incorporating different seasons is essential to generate detailed information of groundwater distribution to maintain sustainable management and mitigate the drought consequences. This present study aimed at developing a spatio-temporal groundwater mapping approach by considering climatic factors implementing different bivariate statistic models, namely, frequency ratio (FR), Shannon’s entropy (SE), and weights of evidence. The developed approach was applied in the drought-prone area of Bangladesh to map spatio-temporal variation of GWPZ. Eighteen (18) conditioning factors including six climatic criteria under different thematic components were used, and the produced potential maps were then categorized into five classes for illustrating the spatial view, and all of them were evaluated through the method of receiver operating characteristics considering the validation wells (30%) data. The bivariate statistics models were found highly effective for both Kharif (wet) and Rabi (dry) seasons and suggest that the northeastern part of the study area, namely Bogra, Sirajganj, Pabna, and Joypurhat districts, have adequate groundwater availability; in contrast, the western part covering Chapainawabganj, Naogaon, and Rajshahi district shows scarcity of groundwater. A slight fluctuation observed for all models indicates high availability of groundwater in the Kharif season because of different climatic factors. Besides, the area under the curve score suggests that the FR model was more accurate for both season, and conversely the SE model was found less efficient to predict GWPZ. The findings suggest that the proposed approach is highly significant in mapping spatio-temporal GWPZ to formulate sustainable management strategies and to mitigate future drought consequences.