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Cluster-based delineation of optimal sites for managed aquifer recharge: a case study of Lower Betwa River Basin, India
被引:0
|作者:
Ankit Tewari
Prabhat Kumar Singh
Shishir Gaur
Shreyansh Mishra
Ranveer Kumar
机构:
[1] Indian Institute of Technology (Banaras Hindu University),Department of Civil Engineering
来源:
Environmental Earth Sciences
|
2024年
/
83卷
关键词:
Groundwater flow modelling;
MODFLOW–NWT;
MAR;
K-means clustering;
AHP;
D O I:
暂无
中图分类号:
学科分类号:
摘要:
Managed Aquifer Recharge (MAR) has emerged as a multi-facet, sustainable and effective technique to replenish dwindling groundwater resources. Suitable site selection is an important step in the design phase of MAR process. Conventional methods of site suitability studies using GIS and Multi Criteria Decision Analysis (MCDA) does not address the aquifer’s response to MAR, while limited modelling-based studies have considered the effect of surface hydraulic factors. In this paper, a fresh approach is presented, that utilises decision model, K-mean clustering technique and numerical model to identify optimal sites for MAR interventions. The methodology was applied in a semi-arid region of Lower Betwa River Basin (LBRB), India. Four different parameter combinations were employed that incorporated the impact of surface and subsurface parameters. Multiple model runs were executed using MODFLOW–NWT to assess the groundwater head response to the infiltrated volume of water. The results indicated that under the least head change category (< 0.7 m), the north and south–east regions of the LBRB were the most appropriate sites. The coalition of geomorphology and drainage density along with aquifer properties such as hydraulic conductivity, specific yield and aquifer thickness were found to be the best suited combination for site selection in LBRB, with maximum spatial coverage (16%) under it. It was observed that the choice of parameter combinations affected the range of groundwater head variations and depended upon the site-specific criteria of accepted head change ranges for determining the best suitable parameter combinations for MAR site selection.
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