Delineating groundwater potential zones of agriculture dominated landscapes using GIS based AHP techniques: a case study from Uttar Dinajpur district, West Bengal

Biswas, Siddhartha; Mukhopadhyay, Bhabani Prasad; Bera, Amit

doi:10.1007/s12665-020-09053-9

Cited by 91 publications

(36 citation statements)

References 69 publications

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“…India is considered to be one of the prime countries worldwide, to extract the maximum amount (89%) of groundwater for irrigational purposes, 9% for domestic needs and rest 2% for other industrial practices (Margat and Van Der Gun 2013). Therefore, an appropriate knowledge regarding the hydrochemistry of water is of utmost importance so as to properly evaluate the quality of the groundwater, especially in the rural areas as it significantly affects the usability of the groundwater for irrigation, domestic as well as for industrial needs (Biswas et al 2020;. Several studies (Rabeiy 2018;Aouiti et al 2020;Aravinthasamy et al 2021;Kadam et al 2021;Kamaraj et al 2021;Rao et al 2021;Şener et al 2021) have been conducted earlier regarding hydrochemistry and groundwater suitability for irrigation.…”

Section: Introductionmentioning

confidence: 99%

Suitability assessment of groundwater quality for irrigational use in Sagardighi block, Murshidabad district, West Bengal

et al. 2022

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Groundwater alone comprises nearly about 80% of the available water for irrigation purpose in Murshidabad and this usage of groundwater for irrigation is yet to increase further in the upcoming years. The present study was carried out to access the groundwater’s suitability for different agricultural purposes in and around Sagardighi block of Murshidabad district, West Bengal, India. Groundwater samples from thirty three different locations around Sagardighi were collected and then tested in the laboratory for various physical as well as chemical parameters such as electrical conductivity (EC), total dissolved solids (TDS), pH, some major cations (Ca2+, Mg2+, Na+, K+, Fe2+) and some anions (CO32−, HCO3−, Cl−). To further delineate the suitable groundwater zones for irrigation practices, the irrigation water quality parameters such as sodium adsorption ratio (SAR), sodium percentage (Na%), magnesium adsorption ratio (MAR), permeability index (PI), residual sodium carbonate (RSC), Kelly’s ratio (KR) were also calculated. Results show that most of the water samples had low to medium salinity, while only a very few of the samples show high salinity. Piper trilinear plot reveals that the water is primarily of Ca–Mg–HCO3− facies type. The SAR value of majority of the water samples in the study area are less than 10, which is within safe limits. RSC values indicate that the carbonate content is extremely low in the groundwater of the study area. Overall, the results indicate that majority of the samples are fit to be used for irrigational purpose. The findings of this study would help decision-makers in developing irrigation suitability planning and groundwater resource management in the future.

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Section: Introductionmentioning

confidence: 99%

Suitability assessment of groundwater quality for irrigational use in Sagardighi block, Murshidabad district, West Bengal

et al. 2022

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“…Fields of natural vegetation have been given moderately high weight because the shots gradually decrease the surface flow and increase the penetration rate (Bhattacharya et al 2020;. Agricultural fields offer a lot of groundwater recharge capacity (Biswas et al 2020) and low groundwater recharge due to low infiltration rate in settlement areas.…”

Section: Land Use and Land Cover (Lulc) And Groundwater Potentialitymentioning

confidence: 99%

“…There has been a lot of work done on groundwater potential in hard rock geological regions (Shekhar and Pandey, 2015;Parameswari and Padminni 2018;Pande et al 2019;Das and Pal 2019;Maity and Mandal 2019;Das and Mukhopadhyay 2020;Bhattacharya et al 2020;Maity and Mandal 2019;Das and Mukhopadhyay 2020;Bhattacharya et al 2020;. In comparison, less work has been done in the field of agriculture dependent on alluvial landscape (Saha et al 2010(Saha et al , 2021Patra et al 2018;Biswas et al 2020;Dey et al 2021;Barua et al 2021).…”

Section: Introductionmentioning

confidence: 99%

GIS-based comparative assessment of groundwater potential zone using MIF and AHP techniques in Cooch Behar district, West Bengal

Senapati

Das

2022

Appl Water Sci

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Global warming, change in climate and rapid growth of population have put a huge strain on the world's groundwater resources. The use of excess groundwater has created a drop in the water table. Increased use of groundwater for agriculture in agro-based areas increases the demand for groundwater. The current study has been conducted in Cooch Behar, an agro-based remote district of North Bengal in the Indian state of West Bengal, where the use of high groundwater in agriculture has reduced groundwater levels. Comparative assessment of Multi-Influencing Factor (MIF) and Analytical Hierarchy Process (AHP) techniques has been used to create a perspective mapping of groundwater potential zone for the research region. Land use and land cover (LULC), rainfall, soil texture, geomorphology, lithology, drainage density, Normalized Differential Vegetation Index (NDVI), and Topographic Wetness Index (TWI) have been used to create the map. The MIF and AHP techniques have been used for Groundwater Potential Zones (GPZ) mapping. Output GPZ has been classified into 5 classes, i.e., very poor, poor, moderate, good, and excellent. MIF technique shows that the groundwater potential classes are covering 9% (285 km2), 21% (67 km2), 30% (944 km2), 27% (837 km2) and 13% (410 km2) of the study area, respectively, whereas the output GPZ from AHP technique shows that the groundwater potential classes are covering 8% (271 km2), 15% (508 km2), 24% (813 km2), 33% (1118 km2) and 20% (677 km2), respectively. Finally, the maps have been verified using groundwater fluctuation data through Receivers Operating Characteristic curve (ROC). The MIF technique's Area Under Curve (AUC) score is 76.5%, while the AHP technique reveals 88.9% accuracy. Both techniques for assessing and monitoring GPZ have been accurate and reasonable. Thus, this type of research is reliable for a more appropriate framework for swiftly analyzing groundwater recharge and directing the location of artificial recharge structures and other groundwater management operations of agricultural-based areas.

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“…TWI uncovers the saturated portions in said watershed. The index indicates effects of topography on accumulation of water in a region (Biswas et al 2020), and hence, steep slope and higher elevation have greater run-off and thus reduce the capacity of water accumulation; on contrary, low-lying area has greater potential of topographical wetness or accumulation of water in the study area. The formula, given by Moore et al (1991), is used to compute the TWI in present research.…”

Section: Factors Affecting Groundwater Potential Zonementioning

confidence: 99%

Groundwater potential mapping using multi-criteria decision, bivariate statistic and machine learning algorithms: evidence from Chota Nagpur Plateau, India

Hasanuzzaman¹,

Mandal²,

Hasnine

et al. 2022

Appl Water Sci

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Increased consumption of water resource due to rapid growth of population has certainly reduced the groundwater storage beneath the earth which leads certain challenges to human being in recent time. For optimal management of this vital resource, exploration of groundwater potential zone (GWPZ) has become essential. We have applied Analytical Hierarchy Process (AHP), Frequency Ratio (FR) and two machine learning techniques specifically Random Forest (RF) and Naïve Bayes (NB) here to delineate GWPZ in Gandheswari River Basin in Chota Nagpur Plateau, India. To achieve the goal of the study, twelve factors that determine occurrence of groundwater have been selected for inter-thematic correlations and overlaid with location of wells. These factors include elevation, drainage density, slope, lithology, geomorphology, topographical wetness index (TWI), distance from the river, rainfall, lineament density, Normalized Difference Vegetation Index (NDVI), soil, and Land use and Land cover (LULC). A total 170 points including 85 in well site and 85 in non-well site have been selected randomly and allocated into two parts: training and testing at the share of 70:30. The implemented methods have significantly provided five GWPZs specifically Very Good (VG), Good (G), Moderate (M), Poor (P) and Very Poor (VP) with high and acceptable accuracy. The study also finds that geomorphology, slope, rainfall and elevation have greater importance in shaping GWPZs than LULC, NDVI, etc. Model performance has been tested with receiver operator characteristics (ROC), Accuracy (ACC), Kappa Coefficient, MAE, RMSE, etc., methods. Area under curve (AUC) in ROC curve has revealed that accuracy level of AHP, FR, RF and NB is 78.8%, 81%, 85.3% and 85.5, respectively. The machine learning techniques coupled with AHP and FR unveil effective delineation of groundwater potential area in said river basin which by genetically offers low primary porosity due to lithological constrains. Therefore, the study can be helpful in watershed management and identifying appropriate location wells in future.

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Delineating groundwater potential zones of agriculture dominated landscapes using GIS based AHP techniques: a case study from Uttar Dinajpur district, West Bengal

Cited by 91 publications

References 69 publications

Suitability assessment of groundwater quality for irrigational use in Sagardighi block, Murshidabad district, West Bengal

Suitability assessment of groundwater quality for irrigational use in Sagardighi block, Murshidabad district, West Bengal

GIS-based comparative assessment of groundwater potential zone using MIF and AHP techniques in Cooch Behar district, West Bengal

Groundwater potential mapping using multi-criteria decision, bivariate statistic and machine learning algorithms: evidence from Chota Nagpur Plateau, India

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