基于远程数据和综合方法的干旱-半干旱地区MAR站点适宜性制图:以巴基斯坦俾路支省为例

IF 0.8 Q4 WATER RESOURCES
S. Hayat, Zsóka Szabóa, Á. Tóth, J. Mádl-Szőnyi
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引用次数: 6

摘要

气候变化,加上人口的快速增长和水资源管理不善,导致全球地下水的质量和数量下降。俾路支省是巴基斯坦最大、最干旱的省份,位于该国西南部。该地区正遭受地下水位下降、地面沉降和严重的土壤侵蚀。人口的快速增长、海平面的上升、气温的升高、年平均降水量的减少以及短时间的强降雨和减少的渗透速率进一步加剧了这种情况。含水层管理补给(MAR)被认为是减少地下水资源压力和实现对气候变化的适应能力的一种解决方案。创建MAR适宜性地图可能是实现可持续地下水管理的步骤之一。该研究绘制了俾路支省人口最密集的城市奎达河谷以及遭受海水入侵的Poralai和Hingol沿海盆地的第一张MAR适宜性地图。首先利用在线INOWAS平台缩小适合的MAR选择范围,构建MAR适宜性图。然后,识别地质、坡度、土地覆盖、降水、排水密度和土壤6个影响因子,并利用GIS工具和多影响因子(Multi - influence factor, MIF)方法对每个因子的栅格图进行评分和加权。利用ArcGIS中的“加权叠加分析”工具和多准则决策分析(GIS-MCDA),将所有因素按其权重进行综合,生成最终的MAR适宜性图。适宜性图将研究区域划分为高、中、低和极低适宜性等级。结果表明,80%的Poralai盆地、10%的Hingol盆地和不到5%的Quetta山谷处于MAR高适宜区,特别是沟、沟、沟和漏坝。首份俾路支省流域海洋生物多样性适宜性地图可以作为指导和筛选工具,将具体地点的研究重点放在非常适合实施海洋生物多样性的地区。在研究的下一阶段,对水源、水质和最终用途的分析将有助于根据当地条件和需要设计和开发具体的MAR结构。该方法适用于其他干旱半干旱区的MAR适宜性研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MAR site suitability mapping for arid–semiarid regions by remote data and combined approach: A case study from Balochistan, Pakistan
Climate change, along with the rapid increase in population and mismanagement of water resources, resulted in a decline in the quality and quantity of groundwater worldwide. Balochistan, the largest and driest province of Pakistan, is located in the south western part of the country. This region is suffering from the declining water table, land subsidence, and intense soil erosion. Rapidly increasing population, sea level rise, increasing temperature, declining average annual precipitation, and short-duration intense rainfalls with reduced percolation rates are further aggravating the situation. Managed Aquifer Recharge (MAR) is considered as a solution to reduce the stress on groundwater resources and achieve resilience to climate change. Creating a MAR suitability map may be one of the steps to be taken to reach sustainable groundwater management. This study produced the first MAR suitability map of the Quetta Valley, the most densely populated city of Balochistan, and Poralai and Hingol coastal basins suffering from seawater intrusion. To construct the MAR suitability map, the online INOWAS platform was first used to narrow down the suitable MAR options. Then, the six influencing factors including geology, slope, land-cover, precipitation, drainage density, and soil were identified, and the raster map of each factor was scored and weighted using GIS tools and the Multi Influencing Factor (MIF) method. All the factors were integrated according to their weight by using the ‘Weighted Overlay Analysis’ tool and the Multi-Criteria Decision Analysis (GIS-MCDA) in ArcGIS to produce the final MAR suitability map. The suitability map divided the study area into high, moderate, low, and very low suitability classes. The results depict that 80% of Poralai Basin, 10% of Hingol Basin and less than 5% of Quetta Valley falls in the high MAR suitability zone especially for trenches, ditches, furrows, and leaky dams. The first MAR suitability map for the basins of Balochistan can serve as the guidance and screening tool to focus site specific studies for highly suitable areas for MAR implementation. In the following phase of the study, an analysis of source, quality, and final use of water can serve to design and develop the specific MAR structures according to local conditions and needs. The displayed method is applicable to further MAR suitability studies for other arid-semiarid regions.
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来源期刊
CiteScore
1.80
自引率
50.00%
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36
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