Evaluation of Recharge and Groundwater Dynamics of a Shallow Alluvial Aquifer in Central Ganga Basin, Kanpur (India)

Dhar, Anirban; Dey, Saumava; Sahoo, Madhumita

doi:10.1007/s11053-014-9251-y

Cited by 38 publications

(8 citation statements)

References 17 publications

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“…For the G factor, the unconfined aquifer is assigned the highest potentiality result (0.6-1) compared to that of confined aquifer (0.2) (column 2). This is qualitatively due to the fact that the unconfined aquifer top is directly exposed to higher surface water recharge infiltration unlike the confined aquifer top (Sahoo et al, 2016a andDhar et al, 2014). Further in the O factor's column, the numerical value 0.8 i.e.…”

Section: The 1-d Schlumberger Depth Sounding Survey Resultsmentioning

confidence: 99%

Modeling of geoelectric parameters for assessing groundwater potentiality in a multifaceted geologic terrain, Ipinsa Southwest, Nigeria – A GIS-based GODT approach

Mogaji

Omobude

2017

NRIAG Journal of Astronomy and Geophysics

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Modeling of groundwater potentiality zones is a vital scheme for effective management of groundwater resources. This study developed a new multi-criteria decision making algorithm for groundwater potentiality modeling through modifying the standard GOD model. The developed model christened as GODT model was applied to assess groundwater potential in a multi-faceted crystalline geologic terrain, southwestern, Nigeria using the derived four unify groundwater potential conditioning factors namely: Groundwater hydraulic confinement (G), aquifer Overlying strata resistivity (O), Depth to water table (D) and Thickness of aquifer (T) from the interpreted geophysical data acquired in the area. With the developed model algorithm, the GIS-based produced G, O, D and T maps were synthesized to estimate groundwater potential index (GWPI) values for the area. The estimated GWPI values were processed in GIS environment to produce groundwater potential prediction index (GPPI) map which demarcate the area into four potential zones. The produced GODT model-based GPPI map was validated through application of both correlation technique and spatial attribute comparative scheme (SACS). The performance of the GODT model was compared with that of the standard analytic hierarchy process (AHP) model. The correlation technique results established 89% regression coefficients for the GODT modeling algorithm compared with 84% for the AHP model. On the other hand, the SACS validation results for the GODT and AHP models are 72.5% and 65%, respectively. The overall results indicate that both models have good capability for predicting groundwater potential zones with the GIS-based GODT model as a good alternative. The GPPI maps produced in this study can form part of decision making model for environmental planning and groundwater management in the area.

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Section: The 1-d Schlumberger Depth Sounding Survey Resultsmentioning

confidence: 99%

Modeling of geoelectric parameters for assessing groundwater potentiality in a multifaceted geologic terrain, Ipinsa Southwest, Nigeria – A GIS-based GODT approach

Mogaji

Omobude

2017

NRIAG Journal of Astronomy and Geophysics

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“…Recharge in SWAT is calculated as (Dhar et al 2014): where w rchrg , i is the amount of recharge entering the aquifer on day i(mm); δ gw is the delay time or drainage time of the overlying geologic formations (days); w seep is the total amount of water exiting the bottom of the soil profile on day i (mm); and w rchrg , i − 1 is the amount of recharge entering the aquifer on day i − 1(mm). A distributed parameter model, SWAT, has been used for estimating the average groundwater recharge rate for Balasore district in Odisha, India.…”

Section: Recharge Ratementioning

confidence: 99%

Delineation of Groundwater Potential Zones of Coastal Groundwater Basin Using Multi-Criteria Decision Making Technique

Mandal

Munusamy

Dhar

et al. 2016

Water Resour Manage

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106

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Delineation of groundwater potential zones (GWPZ) has been performed for a coastal groundwater basin of eastern India. The groundwater potential zone index (GWPZI) map is generated by using Analytic Hierarchy Process (AHP) from different influencing features, e.g., Land Use/Land Cover (LU/LC), soil (S), geomorphology (GM), hydrogeology Water Resour Manage (HG), surface geology (SG), recharge rate (RR), drainage density (DD), rainfall (RF), slope (Sl), surface water bodies (SW), lineament density (LD), and Normalized Difference Vegetative Index (NDVI). Recharge rate values are estimated from hydrological water balance model. Overlay weighted sum method is used to integrate all thematic feature maps to generate GWPZ map of the study area. Four zones have been identified for the coastal groundwater basin [very good: 36.39 % (273.53 km 2 , good: 43.57 % (327.47 km 2 ), moderate: 18.27 % (137.30 km 2 ), and poor: 1.77 % (13.27 km 2 )]. Areas in north to south-west and south-east direction show very good GWPZ due to the presence of low drainage density. GWPZ map and well yield values show good agreement. Sensitivity analysis reveals that exclusion/absence of rainfall and lineament density increases the poor groundwater potential zones. Omission of hydrogeology, soils, surface geology, and NDVI show maximum increase in good GWPZ. Obtained GWPZ map can be utilized effectively for planning of sustainable agriculture. This analysis demonstrates the potential applicability of the methodology for a general coastal groundwater basin.

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“…The study area is an aquifer of central Ganga basin, Kanpur city, India (Dhar 2013;Dhar et al 2014a). The general altitude of the area varies from 116 to 128 m above mean sea level.…”

Section: Study Areamentioning

confidence: 99%

Identification of groundwater potential zones considering water quality aspect

Dhar

Sahoo

2015

Environ Earth Sci

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To evolve a proper management scenario for groundwater utilization, identification of groundwater potential zones is an important step. In the present study, an attempt has been made to identify possible groundwater potential zones both in terms of quantity and quality. A methodology is proposed for identification of groundwater potential index (GWPI) and a new water quality index (WQI) based on analytic hierarchy process. The proposed methodology has been applied to the shallow alluvial aquifer of central Ganga basin, Kanpur (India). Land use/land cover, soil, geology, recharge rate, drainage density, rainfall, slope, elevation, normalized difference vegetation index, groundwater depth or depth to groundwater table are used for GWPI calculation. Moreover, WQI considers alkalinity (as CaCO 3 ), magnesium (Mg 2? ), total dissolved solids and fluoride (F -) as influencing attributes. Final integration of attributes yield GWPI and WQI map. The resulting GWPI map has been classified into three groundwater potential zones namely: good, moderate and poor covering 26.94, 43.76, and 29.30 %, area, respectively. The WQI map has been classified into five quality zones namely: above permissible limit, poor, moderate, good, very good covering 12. 39, 7.63, 15.17, 38.18, and 26.64 % area, respectively. Monitoring data from well locations along with GWPI and WQI map reveals the proper potential zones. This analysis demonstrates the potential applicability of the methodology for a general aquifer system.

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Evaluation of Recharge and Groundwater Dynamics of a Shallow Alluvial Aquifer in Central Ganga Basin, Kanpur (India)

Cited by 38 publications

References 17 publications

Modeling of geoelectric parameters for assessing groundwater potentiality in a multifaceted geologic terrain, Ipinsa Southwest, Nigeria – A GIS-based GODT approach

Modeling of geoelectric parameters for assessing groundwater potentiality in a multifaceted geologic terrain, Ipinsa Southwest, Nigeria – A GIS-based GODT approach

Delineation of Groundwater Potential Zones of Coastal Groundwater Basin Using Multi-Criteria Decision Making Technique

Identification of groundwater potential zones considering water quality aspect

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