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DC Field | Value | Language |
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dc.contributor.author | Shaw, Souvick Kumar | - |
dc.contributor.author | Sravani, Nowdu | - |
dc.contributor.author | Sharma, Anurag | - |
dc.date.accessioned | 2024-03-20T04:34:49Z | - |
dc.date.available | 2024-03-20T04:34:49Z | - |
dc.date.issued | 2023-12 | - |
dc.identifier.citation | 28th International Conference on Hydraulics, Water Resources, River and Coastal Engineering(HYDRO), NIT Warangal, India, 21-23 December 2023 | en_US |
dc.identifier.uri | http://hdl.handle.net/2080/4489 | - |
dc.description | Copyright belongs to proceeding publisher | en_US |
dc.description.abstract | Now a days, due to rapid growth of population and industries; some economic developments and urbanization, surface water cannot meet the entire agricultural demand mainly in some arid and semi-arid regions in India. Due to the presence of large area occupied by cropland, pediment pediplain complex, there may be high possibility of good to excellent groundwater potential zone in Sundargarh district, Orissa (study area). It may highly satisfy the existing and future water demand for the crops due to the limitation of surface water. The aim of this present study was lying in finding the possible zones of groundwater by Frequency Ratio (FR) method which is an important statistical bivariate approach. Eight thematic layers viz. geomorphology, rainfall, slope, drainage density, lineament density, soil, land use/ land cover (LULC) and normalized difference vegetation index (NDVI) were used to delineate probable zones of groundwater. Final groundwater potential zone (GWPZ) map was categorized into four classes viz. poor (16.5%), fair (23.2%), good (34.6%) and excellent (25.7%). Validation was done by taking 70% training dataset (66 dug wells) and 30% testing dataset (28 dug wells) during pre-monsoon season of 2021 by Receiver Operating Characteristics (ROC) method. AUC value for success and prediction rate curve for FR model were measured as 0.719 and 0.747 respectively. Performance of the FR model was checked by using Radial Bias Function (RBF) tool in SPSS 23 and Map removal sensitivity analysis (MRSA) was also studied to show the percentage contribution of each factor. | en_US |
dc.subject | Frequency Ratio | en_US |
dc.subject | Bivariate approach | en_US |
dc.subject | Thematic layers | en_US |
dc.subject | ROC | en_US |
dc.subject | Success and Prediction rate curve | en_US |
dc.subject | Percentage contribution | en_US |
dc.title | Application of Frequency Ratio Model for The Mapping of Groundwater Potential Zone | en_US |
dc.type | Article | en_US |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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2023_HYDRO_NSravani_Application.pdf | 1.49 MB | Adobe PDF | View/Open Request a copy |
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