Mapping of Mount Semeru Volcanic Mudflow Susceptibility Along the Rejali River using the GIS-based AHP-TOPSIS Ensemble Approach

Sonia Oktariyanti, Entin Hidayah, Saifurridzal, M. F. Ma’ruf, N. Hayati, Zulkifli Yusop
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Abstract

Volcanic mudflow floods occur when rainfall runoff combines with volcanic material and flows downstream. These devastating events cause significant damage to infrastructure, disrupt economies, and result in injuries and casualties. One area where the flow of volcanic material greatly affects the situation is the Rejali River, which receives a substantial amount of volcanic debris from Mount Semeru. To address this issue and begin mitigating the associated risks, it is crucial to start by mapping the potential distribution of volcanic mudflow floods. Therefore, this study aimed to assess factors impacting volcanic mudflow flood susceptibility and to create a corresponding susceptibility map. The study employed the Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to determine the influence of various factors and classify the areas, respectively. These methods were integrated with the Geographic Information System (GIS) to enhance the analysis. The weighted analysis results showed that the most impactful factors conditioning volcanic mudflow floods, in descending order, were rainfall (42.40%), land cover (13.89%), elevation (13.39%), slope (12.51%), distance from the river (7.09%), soil type (6.58%), and rock distribution (4.13%). The TOPSIS calculation further highlighted that rainfall intensity between 104.03 and 109.65 mm day-1 had the greatest influence on susceptibility. The successful integration of AHP and TOPSIS methods with GIS helped develop a volcanic mudflow flood susceptibility model with an outstanding accuracy of 0.969. The model showed that approximately 46.40% of the areas along the Rejali River exhibited very high susceptibility to volcanic mudflow floods, while an additional 16.21% indicated high susceptibility and substantial risk in most regions. Therefore, the generated susceptibility map offered important insights for shaping future mitigation strategies and influencing policy decisions.
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利用基于地理信息系统的 AHP-TOPSIS 组合方法绘制雷加利河沿岸塞梅鲁火山泥石流易发区地图
当降雨径流与火山物质结合并顺流而下时,就会发生火山泥石流洪水。这些破坏性事件对基础设施造成严重破坏,扰乱经济,并造成人员伤亡。雷加利河就是一个受到火山物质流动严重影响的地区,这里有大量来自塞梅鲁火山的火山碎屑。要解决这一问题并开始减轻相关风险,首先必须绘制火山泥流洪水的潜在分布图。因此,本研究旨在评估影响火山泥流洪水易发性的因素,并绘制相应的易发性地图。研究采用了层次分析法(AHP)和理想解相似度排序偏好法(TOPSIS),分别确定各种因素的影响并对区域进行分类。这些方法与地理信息系统(GIS)相结合,增强了分析效果。加权分析结果显示,对火山泥石流洪水影响最大的因素依次为降雨(42.40%)、土地覆盖(13.89%)、海拔(13.39%)、坡度(12.51%)、与河流的距离(7.09%)、土壤类型(6.58%)和岩石分布(4.13%)。TOPSIS 计算进一步突出表明,日降雨量在 104.03 至 109.65 毫米之间的降雨强度对易发性的影响最大。AHP 和 TOPSIS 方法与地理信息系统的成功结合有助于建立火山泥石流洪水易发性模型,其精确度高达 0.969。该模型显示,热加里河沿岸约 46.40% 的地区对火山泥石流洪水表现出极高的易感性,另有 16.21% 的地区在大多数情况下表现出高易感性和巨大风险。因此,生成的易感性地图为制定未来的减灾战略和影响政策决策提供了重要启示。
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20
审稿时长
15 weeks
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