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Landscape entropy approach to demarcate pathways for oozing of water in a desert area in India

机译:景观熵方法在印度沙漠地区划定渗水途径

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Oozing of groundwater in Jodhpur city in the desert area of Rajasthan, India has caused weakening of foundations and cellars of buildings and shops. It has become more significant since 1996 when Kaylana lake was connected with Rajiv Gandhi Lift Canal (RGLC) water supply and filling of the lake had started. This has resulted in fear among dwellers about any future calamity. The hydrogeological, hydrochemical and isotopic studies clearly indicated that the lake water is responsible for the oozing phenomenon in the area. This article highlights a landscape entropy approach to assess pathways causing rise in the level of groundwater integrating the measured lake water level and groundwater table in a few selected wells in the city. With the fractional information of lake water and groundwater, marginal entropies of lake water and depths to groundwater in the selected wells sites are calculated. Mutual information, on common uncertainty associated in the measurements of lake water and groundwater, is also provided. Subsequently, ratios of mutual information to marginal entropy of the lake water are used as a measure for demarcating the pathways of weak zones, which correlate well with the lineaments delineated from satellite imagery. The results of this study represent a base for additional insight on future work, which will help in tracing the connectivity of weak zones causing oozing of water in Jodhpur city, and evolving a plan for remedial measures.
机译:印度拉贾斯坦沙漠地区的焦特布尔市地下水渗水导致建筑物和商店的地基和地窖变弱。自从1996年Kaylana湖与Rajiv Gandhi Lift Canal(RGLC)供水连接并开始注水以来,这一点变得更加重要。这导致居民对未来的任何灾难感到恐惧。水文地质,水化学和同位素研究清楚地表明,湖水是造成该地区渗水现象的原因。本文着重介绍了一种景观熵方法,用于评估导致地下水水位上升的各种路径,并结合城市中选定的几口井中测得的湖泊水位和地下水位。利用湖水和地下水的分数信息,可以计算出所选井场中湖水的边际熵和对地下水的深度。还提供了关于湖泊水和地下水测量中常见不确定性的相互信息。随后,互信息与湖水边际熵之比被用作划定薄弱区域路径的度量,这些薄弱区域与卫星图像描绘的地貌很好地相关。这项研究的结果为进一步了解未来的工作奠定了基础,这将有助于追踪造成焦特布尔市渗水的薄弱地区的连通性,并制定补救措施计划。

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