Application of geospatial technology for delineating groundwater potential zones in the Gandheswari watershed, West Bengal

Identification of groundwater potential zones needs an understanding of different hydro-geological parameters of the concerned region. This present study done on Gandheswari watershed of West Bengal is mainly based on RS and GS techniques. Seven important parameters are taken into consideration namely geology, lineament, slope, drainage, soil, rainfall, and land use and land cover which are mutually interdependent to each other in the groundwater development process. Satellite image of Landsat-8, SRTM-DEM of USGS, rainfall data of IMD, topographical sheets of SOI, geological map of GSI, soil map of NBSS&LUP are collected and processed as per requirements in the ArcGIS, Erdas Imagine and PCI Geometica software to create or extract layers for all the parameters. The MIF technique is applied to assign weight to each parameter based on its level of influence to other parameters. All the layers are now integrated together adopting weighted overlay method in ArcGIS software. The prepared final map shows the groundwater potential zones of the Gandheswari watershed. An accuracy assessment is done based on groundwater fluctuation data of last 10 years (2018–2009) from CGWB calculating Kappa co-efficient to validate the study. The study reveals that an area of 275.9 km 2 (69.86%) is found to be good prospect of groundwater. The overall accuracy level of the study is calculated to be 84.62%, while the result of the Kappa co-efficient is 88% for the same.

[1]  T. Acharya,et al.  Study of fractures in Precambrian crystalline rocks using field technique in and around Balarampur, Purulia district, West Bengal, India , 2015, Journal of Earth System Science.

[2]  Robert J. Abrahart,et al.  Practical hydroinformatics : computational intelligence and technological developments in water applications , 2008 .

[3]  S. Khan,et al.  Delineation of groundwater potential zones using GIS and multi influence factor (MIF) techniques: a study of district Swat, Khyber Pakhtunkhwa, Pakistan , 2018, Environmental Earth Sciences.

[4]  P. Singh,et al.  Understanding factors influencing groundwater levels in hard-rock aquifer systems by using multivariate statistical techniques , 2015, Environmental Earth Sciences.

[5]  A. Viera,et al.  Understanding interobserver agreement: the kappa statistic. , 2005, Family medicine.

[6]  V. Chowdary,et al.  Groundwater assessment in Salboni Block, West Bengal (India) using remote sensing, geographical information system and multi-criteria decision analysis techniques , 2010 .

[7]  Aidan A. Cronin,et al.  Water in India: situation and prospects , 2014 .

[8]  Rajat Gupta,et al.  Applied Hydrogeology of Fractured Rocks , 1999 .

[9]  Peiyue Li,et al.  Deciphering groundwater potential zones using MIF technique and GIS: A study from Tirupati area, Chittoor District, Andhra Pradesh, India , 2019, HydroResearch.

[10]  Lakshmanan Elango,et al.  Geological and geomorphological controls on groundwater occurrence in a hard rock region , 2017, Applied Water Science.

[11]  Sudhakar D. Pardeshi,et al.  Integration of different influencing factors in GIS to delineate groundwater potential areas using IF and FR techniques: a study of Pravara basin, Maharashtra, India , 2018, Applied Water Science.

[12]  B. Fagbohun,et al.  Integrating GIS and multi-influencing factor technique for delineation of potential groundwater recharge zones in parts of Ilesha schist belt, southwestern Nigeria , 2018, Environmental Earth Sciences.

[13]  Richard John Huggett,et al.  Fundamentals of Geomorphology , 2022 .

[14]  R. Huggett Fundamentals of Geomorphology, 3rd edition , 2011 .

[15]  N. S. Magesh,et al.  Assessment of groundwater potential zones in Vellore district, Tamil Nadu, India using geospatial techniques , 2019, Earth Science Informatics.

[16]  S. Mandal,et al.  Identification of groundwater potential zones of the Kumari river basin, India: an RS & GIS based semi-quantitative approach , 2019, Environment, Development and Sustainability.

[17]  Balamurugan Guru,et al.  Frequency ratio model for groundwater potential mapping and its sustainable management in cold desert, India , 2017 .

[18]  Borgaon-Indore-Ujjain Transect GEOLOGICAL SURVEY OF INDIA GOVERNMENT OF INDIA , 2002 .

[19]  S. Anbazhagan,et al.  Modeling groundwater probability index in Ponnaiyar River basin of South India using analytic hierarchy process , 2016, Modeling Earth Systems and Environment.

[20]  Sujit Das Delineation of groundwater potential zone in hard rock terrain in Gangajalghati block, Bankura district, India using remote sensing and GIS techniques , 2017, Modeling Earth Systems and Environment.

[21]  Cheng-Haw Lee,et al.  GIS for the assessment of the groundwater recharge potential zone , 2009 .

[22]  Satiprasad Sahoo,et al.  Delineation of Groundwater Potential Zones of Coastal Groundwater Basin Using Multi-Criteria Decision Making Technique , 2016, Water Resources Management.

[23]  S. Kuester The Nature and Properties of Soils , 1953, Soil Science Society of America Journal.

[24]  N. Chandrasekar,et al.  Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques , 2012 .

[25]  R. Jaiswal,et al.  Role of remote sensing and GIS techniques for generation of groundwater prospect zones towards rural development--an approach , 2003 .

[26]  J. Roy,et al.  Groundwater potential modelling in a soft rock area using a GIS , 2000 .

[27]  L. S. Rathore,et al.  Water resources and climate change: An Indian perspective , 2006 .

[28]  Ralph C. Heath,et al.  WHAT ABOUT GROUND WATER , 1973 .

[29]  Valère Carin Jofack Sokeng,et al.  Delineating groundwater potential zones in Western Cameroon Highlands using GIS based Artificial Neural Networks model and remote sensing data , 2016 .

[30]  Subodh Chandra Pal,et al.  Modeling and mapping of groundwater potentiality zones using AHP and GIS technique: a case study of Raniganj Block, Paschim Bardhaman, West Bengal , 2018, Modeling Earth Systems and Environment.

[31]  Biswas Arkoprovo,et al.  Application of Remote Sensing, GIS and MIF technique for Elucidation of Groundwater Potential Zones from a part of Orissa coastal tract, Eastern India , 2013 .

[32]  Sadhan Malik,et al.  Modeling groundwater potential zones of Puruliya district, West Bengal, India using remote sensing and GIS techniques , 2018, Geology, Ecology, and Landscapes.

[33]  V. M. Chowdary,et al.  Delineation of groundwater recharge zones and identification of artificial recharge sites in West Medinipur district, West Bengal, using RS, GIS and MCDM techniques , 2009 .

[34]  G. Mohan,et al.  Assessment of the groundwater potential and quality in Bhatsa and Kalu river basins of Thane district, western Deccan Volcanic Province of India , 2006 .

[35]  M. Rahimzadegan,et al.  Delineation of groundwater potential zones using remote sensing, GIS, and AHP technique in Tehran–Karaj plain, Iran , 2017, Environmental Earth Sciences.

[36]  Arun K. Saraf,et al.  Integrated remote sensing and GIS for groundwater exploration and identification of artificial recharge sites , 1998 .

[37]  Delineation of groundwater potential zones in South East part of Anantapur District using remote sensing and GIS applications , 2019, Sustainable Water Resources Management.

[38]  Arvind Pandey,et al.  Delineation of groundwater potential zone in hard rock terrain of India using remote sensing, geographical information system (GIS) and analytic hierarchy process (AHP) techniques , 2015 .

[39]  Ercan Kahya,et al.  Mapping of groundwater potential zones in the Musi basin using remote sensing data and GIS , 2009, Adv. Eng. Softw..

[40]  Chadi Abdallah,et al.  Use of remote sensing and GIS to determine recharge potential zones: the case of Occidental Lebanon , 2006 .

[41]  Satiprasad Sahoo,et al.  Future scenarios of land-use suitability modeling for agricultural sustainability in a river basin , 2018, Journal of Cleaner Production.

[42]  Madhya Pradesh,et al.  Census of India 2011 , 2011 .

[43]  Mustafa Neamah Jebur,et al.  Spatial prediction of flood susceptible areas using rule based decision tree (DT) and a novel ensemble bivariate and multivariate statistical models in GIS , 2013 .

[44]  Seyed Amir Naghibi,et al.  GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran , 2015, Environmental Monitoring and Assessment.

[45]  Mustafa Neamah Jebur,et al.  Earthquake induced landslide susceptibility mapping using an integrated ensemble frequency ratio and logistic regression models in West Sumatera Province, Indonesia , 2014 .

[46]  B. K. Purandara,et al.  IDENTIFICATION OF GROUNDWATER POTENTIAL ZONES USING , 2016 .

[47]  P. Ghosh,et al.  Mapping of groundwater potential zones in hard rock terrain using geoinformatics: a case of Kumari watershed in western part of West Bengal , 2016, Modeling Earth Systems and Environment.

[48]  V. Jayaraman,et al.  An approach to demarcate ground water potential zones through remote sensing and a geographical information system , 1996 .

[49]  Bahareh Kalantar,et al.  Groundwater potential mapping using a novel data-mining ensemble model , 2018, Hydrogeology Journal.

[50]  Subodh Chandra Pal,et al.  Simulating the impact of climate change on soil erosion in sub-tropical monsoon dominated watershed based on RUSLE, SCS runoff and MIROC5 climatic model , 2019, Advances in Space Research.

[51]  Hamid Reza Pourghasemi,et al.  Application of analytical hierarchy process, frequency ratio, and certainty factor models for groundwater potential mapping using GIS , 2015, Earth Science Informatics.

[52]  M. Garba,et al.  Groundwater Potential Zones Mapping Using Remote Sensing and Geographic Information System Techniques (GIS) in Zaria, Kaduna State, Nigeria , 2016 .

[53]  Yongzhang Zhou,et al.  Remote Sensing and GIS Based Groundwater Potential Zone Mapping in Ariyalur District, Tamil Nadu , 2018, Journal of the Geological Society of India.

[54]  N. Greggio,et al.  Impact of Population Growth and Climate Change on the Freshwater Resources of Lamu Island, Kenya , 2015 .

[55]  Satiprasad Sahoo,et al.  Impact of water demand on hydrological regime under climate and LULC change scenarios , 2018, Environmental Earth Sciences.

[56]  S. K. Nag,et al.  Assessment of groundwater quality from Bankura I and II Blocks, Bankura District, West Bengal, India , 2017, Applied Water Science.

[57]  R. Thapa,et al.  Assessment of groundwater potential zones using multi-influencing factor (MIF) and GIS: a case study from Birbhum district, West Bengal , 2017, Applied Water Science.

[58]  R. Avtar,et al.  Identification and analysis of groundwater potential zones in Ken–Betwa river linking area using remote sensing and geographic information system , 2010 .

[59]  S. K. Nag,et al.  Deciphering Groundwater Potential Zones Using Geospatial Technology: A Study in Bankura Block I and Block II, Bankura District, West Bengal , 2014, Arabian Journal for Science and Engineering.

[60]  Amitesh Gupta,et al.  Exploring groundwater potential zones using MIF technique in semi-arid region: a case study of Hingoli district, Maharashtra , 2017, Spatial Information Research.

[61]  T. Acharya,et al.  Analysis of lineament swarms in a Precambrian metamorphic rocks in India , 2012, Journal of Earth System Science.

[62]  D. O'leary,et al.  Lineament, linear, lineation: Some proposed new standards for old terms , 1976 .

[63]  V. Kale,et al.  Introduction to Geomorphology , 2001 .

[64]  N. Kalantari,et al.  Delineation of groundwater potential zones using remote sensing (RS), geographical information system (GIS) and analytic hierarchy process (AHP) techniques: a case study in the Leylia–Keynow watershed, southwest of Iran , 2018, Carbonates and Evaporites.

[65]  Roopal Suhag Overview of Ground Water in India , 2016 .

[66]  A. Hoekstra,et al.  Four billion people facing severe water scarcity , 2016, Science Advances.