Mapping of Groundwater Potential Zone Based on Remote Sensing and GIS Techniques: A Case Study of Kalmykia, Russia


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Abstract

Around one-third of the world’s population drinks water from groundwater resources. Of this, about 10 percent, approximately 300 million people, obtains water from groundwater resources. This study identify and mapping of groundwater potential zone for growing population, irrigation and industrial development, combining with remote sensing (RS), geographical information system (GIS) and field data for hydrological research in Kalmykia, Russia. Various thematic layers (i.e. land use/cove, soil, geomorphology, lithology, elevation, slope, rainfall, normalized difference vegetation index (NDVI), drainage density, lineament density, degraded land, forest, relief, vegetation, surface water body, land use, agriculture, flow accumulation, flow direction and base map) wear used along with existing maps to prepare groundwater potential zone (GWPZ) map. Weights were assigned to all above factors according to their effectiveness, sensitivity and relevance to ground water potentiality. Furthermore the resulting GWPZ map has been classified into five classes, named very high, high, moderate, low and very low based on hydro-geomorphological condition, covering 0.93, 11.65, 35.45, 43.20 and 8.77% area respectively. The results show that most part of areas with favorable lithology, soil texture, vegetation, slope, optimum rainfall condition has a high potential for groundwater. The results provide significant information and can be use by local authorities for groundwater exploitation and management.

About the authors

M. S. Boori

Samara National Research University; American Sentinel University

Author for correspondence.
Email: msboori@gmail.com
Russian Federation, Samara, 443086; Aurora, CO 80014

K. Choudhary

Samara National Research University; The Hong Kong Polytechnic University

Author for correspondence.
Email: komal.kc06@gmail.com
Russian Federation, Samara, 443086; Kowloon

A. Kupriyanov

Samara National Research University; Image Processing Systems Institute, Russian Academy of Sciences

Author for correspondence.
Email: akupr@smr.ru
Russian Federation, Samara, 443086; Samara, 443001

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