GIS, Remote Sensing and AHP-Based Groundwater Potential Zone Mapping in the Wainganga River Basin, Madhya Pradesh, India
Pushplata Aherwar
Department of Soil and Water Engineering, JNKVV, Jabalpur, (M.P.), India.
S. K. Pyasi
Department of Soil and Water Engineering, JNKVV, Jabalpur, (M.P.), India.
S. K. Sharma
Department of Soil and Water Engineering, JNKVV, Jabalpur, (M.P.), India.
Y. K. Tiwari
Department of Soil and Water Engineering, JNKVV, Jabalpur, (M.P.), India.
Umesh Singh
Department of Mathematics and Statistics, JNKVV, Jabalpur, (M.P.), India.
*Author to whom correspondence should be addressed.
Abstract
Background: Groundwater is one of the most important natural resources for domestic, agricultural, and industrial purposes. Due to increasing population, urbanization, and irregular rainfall patterns, groundwater resources are under severe stress in many parts of India. Due to explosive population growth, there has been a regular increase in water demand. This has led to overexploitation of water, particularly groundwater in different parts of the country, transforming them into water dark zones.
Aim: The present study focuses on the identification of groundwater potential zones in the Wainganga River Basin of Madhya Pradesh using Geographic Information System (GIS), Remote Sensing, and Analytical Hierarchy Process (AHP) techniques.
Method: Nine thematic layers, namely geomorphology, geology, lineament density, soil, slope, drainage density, rainfall, land use/land cover (LULC), and elevation, were prepared and integrated through weighted overlay analysis. The weights of the thematic layers were assigned using Saaty’s AHP method. The consistency ratio (CR) obtained was 0.039, which indicates acceptable consistency in weight assignment.
Results: The results classified the study area into five groundwater potential zones: very poor, poor, moderate, good, and very good. The moderate groundwater potential zone occupied the largest portion of the study area (47.55%), followed by poor (20.87%), good (14.20%), very poor (12.79%), and very good (3.64%) zones. The eastern and western parts of the basin showed better groundwater potential due to favourable conditions such as forest cover, dense lineament networks, suitable geology, and higher rainfall.
Conclusion: The study demonstrates that the integrated GIS, Remote Sensing, and AHP approach is effective for groundwater resource assessment, planning, and sustainable management.
Keywords: Groundwater resource, remote sensing, analytical hierarchy process, irrigation