印度马哈拉施特拉邦尼拉河流域微流域集水结构影响评价

Trupti Raskar, Himanshu Gaikwad, O. Kadekar, B. Umrikar
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引用次数: 1

摘要

强烈建议在地下水位下降趋势和部分补充的含水层中进行人工补给。此外,量化这些措施对含水层的补给在水资源预算、开发和规划中具有重要意义。为了实现这一目标,我们选择了代表不同地貌的9个地点,并监测了集水结构附近挖井的地下水位。月地下水位与降雨量的关系图显示,7月份出现了高降雨量,但8月份由于补给过程延迟,地下水位上升。水位数据还表明,到2020年2月底,大多数井的水柱可达5米至6米左右。回灌潜力带图上覆盖的集水结构代表优秀(13.1%)、非常好(12.3%)、良好(23.3%)、中等(25.2%)和差(26.1%)区域。对这些结构的人工补给计算表明,储水量大、填充量大的结构具有较高的补给能力。此外,还进行了地球物理电阻率测量,以了解距离构造50m, 100m和150m的每个位置的饱和度。综合所有数据发现,Shivajinagar的补给量最高,其次是Pisalwadi, Kanheri, Zagalwadi 2, Kavathe, Ansur, Bholi, Limbachidwadi, Zagalwadi 1和Kesurdi。因此,研究得出结论,集水结构的影响因地形、土地坡度、地貌、集水区大小和岩性而异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Impact Assessment of Water Harvesting Structures in Micro-Watersheds of Nira River Basin, Maharashtra, India
Artificial recharge is highly recommended in declining groundwater level trends as well as partially replenished aquifers. Moreover, the quantification of the recharge to aquifers due to such measures is important in water resource budgeting, development and planning. With this objective nine locations representing varied geomorphology were selected and the groundwater levels from the dug well in the proximity of water harvesting structures were monitored. The plot of monthly groundwater levels versus rainfall depicts that in the month of July high rainfall occurred but the groundwater levels raised in August due to delayed recharge process. The water level data also indicate the availability of water column of about 5m to 6m in most of the wells till the end of February, 2020. Water Harvesting structures overlaid on the Recharge Potential Zone map represent excellent (13.1%), very good (12.3%), good (23.3%), moderate (25.2) and poor (26.1) zones. The computation of artificial recharge from these structures depict that the structures having high storage capacity with a greater number of fillings have higher recharge. Also, the geophysical resistivity surveys were conducted to understand the degree of saturation at each location up to 50m, 100m and 150m distances from the structure. After integrating all datasets, it has been found that the structure at Shivajinagar has highest recharge followed by Pisalwadi, Kanheri, Zagalwadi 2, Kavathe, Ansur, Bholi, Limbachidwadi, Zagalwadi 1 and Kesurdi. Thus, the study concludes that the impact of water harvesting structures varies according to topography, land slope, geomorphology, size of catchment and lithology.
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