基于多层次分析的ArcGIS技术在斯里兰卡卡纳卡拉扬阿鲁河流域洪水易感度制图中的应用

IF 0.4 Q4 ENGINEERING, MULTIDISCIPLINARY
V. Rajagopalasingam, T. Mikunthan, S. S. Sivakumar
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引用次数: 0

摘要

洪水是在世界各地造成经济、社会和环境破坏的自然灾害之一,斯里兰卡也是如此。洪水易感度图对于防洪和减灾措施至关重要。这项研究的目的是开发和验证斯里兰卡卡纳卡拉扬阿鲁河流域的洪水易感性地图。通过对省灌北省、省灌东省、灾害管理中心和灌溉厅的水利专业人员和专家进行初步资料收集,确定洪水成因的显著性。次要数据包括降雨、数字高程模型和基于gis的专题数据层。采用基于gis的空间多准则决策分析和层次分析法进行研究。确定了高程、坡度、降水、土地利用和土地覆盖、河流邻近度、排水网络密度、地形湿度指数和土壤类型等8个洪水成因。结果表明,降水(33%)、排水密度网(17%)和地表坡度(11%)是影响洪涝风险的三个最重要因素。极高、高、中度洪水风险区分别占流域面积的12.5%、23.4%和27.1%。验证过程是基于地图对不同洪水易感区历史洪水位置的比较来执行的,它提供了显著的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploring Flood Susceptibility Mapping Using ArcGIS Techniques Integrated with Analytical Hierarchy Process under Multi-Criteria Decision Analysis in Kanakarayan Aru River Basin, Sri Lanka
Floods are one of the natural disasters causing economic, social, and environmental damage around the world, including in Sri Lanka. Flood susceptibility mapping is essential for flood prevention and mitigation measures. This study aimed to develop and validate a flood susceptibility map for the Kanakarayan Aru River Basin in Sri Lanka. Primary data were collected from water professionals and experts from Provincial Irrigation-Northern Province, Provincial Irrigation-Eastern Province, Disaster Management Centre, and Irrigation Department to decide the significance of flood causative factors. Secondary data of rainfall, digital elevation model, and GIS-based thematic data layers were collected from different agencies. GIS-based spatial multi-criteria decision analysis and analytical hierarchy process method were used for the study. A total of eight flood causative factors, i.e., elevation, slope, precipitation, land use and land cover, river proximity, drainage network density, topographic wetness index, and soil types were identified. Results show that the three mostrelevant factors of flood risk were precipitation (33%), drainage density network (17%), and surface slope (11%). The very high, high, and moderate flood risks occupy 12.5%, 23.4%, and 27.1% of the river basin areas, respectively. The validation process is executed based on the map's comparison of the historical flood locations of the different flood-susceptible zones and it provides a significant accuracy.
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