The present study, through a multi model assessment approach emphasizes the relevance of prior urban settlement planning with respect to the changing land use pattern. A coupled approach integrating satellite data products of Land Use and Land Cover (LULC) change along with chemical evaluation of As toxicity were modelled to evaluate the groundwater vulnerability. Change detection analysis was incorporated using the satellite images of 2013 and 2016 which shows 10 % increase in the buildings as compared to the total area of the study in given period. The LULC class that has been most compromised in this expansion and got reduced were the vegetation (∼6 %) and the barren areas (∼4 %) and the total surface water sources (0.5 %), all contributing in increased urban sprawl. As per the origin of As contamination in the area it seems that high sediment deposition along the braided Brahmaputra River stretch leads to As contamination which was associated with Fe-(oxy)-hydroxide dissolution. The vulnerability assessment using Artificial Neural Network technique in this region shows that As is present relatively in lesser concentration in the east direction. The continuous expansion of the urban habitation towards the greater As concentration zone will further make the situation critical for the people dependent on groundwater. The study suggests that prior settlement planning must be carried out in accordance to the presence of any toxic constituent in drinking water source to avoid future crisis for potable water.

本研究通过多模型评估方法强调了先前的城市住区规划与不断变化的土地利用模式的相关性。结合土地利用和土地覆被变化（LULC）的卫星数据产品以及砷的化学评估，建立了一种耦合方法，以评估地下水的脆弱性。使用2013年和2016年的卫星图像进行了变化检测分析，该图像显示建筑物在给定时期内比研究总面积增加了10％。在这种扩张中受到最大危害并减少的LULC类是植被（〜6％）和贫瘠地区（〜4％）以及总地表水源（0.5％），所有这些都导致了城市扩张的增加。根据该地区砷污染的起源，似乎沿辫状布拉马普特拉河河段的高沉积物沉积会导致砷污染，这与氢氧化铁（氧）的溶解有关。使用人工神经网络技术对该地区进行的脆弱性评估表明，As在东部方向上的浓度相对较低。城市居住区向更大的As集中区的不断扩展，将进一步使这种状况对于依赖地下水的人们至关重要。研究表明，必须根据饮用水源中任何有毒成分的存在来进行事先定居计划，以避免未来饮用水的危机。