基于层次分析法和GIS的洪水灾害区划评价与验证——以越南林河流域为例

Pub Date : 2021-01-01 DOI:10.21638/spbu07.2021.410
Ba Dung Nguyen, Quynh Nga Nguyen, T. L. Pham, T. Le, Tuyet Minh Dang
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引用次数: 0

摘要

近年来,林河流域遭受了各种形式的自然灾害,如洪水、洪水、风暴、龙卷风等。其中,洪水已被证明是对流域人民和社会经济发展的最大威胁。此外,与其他自然灾害相比,它是非常频繁的。鉴于这类特大洪水在流域仍在发生,确定其成因,分析影响洪水的各组成部分就显得十分必要。这对发展早期洪水预警系统,从而尽量减少林河流域洪水对人民和设施的负面影响非常重要。本文将层次分析法(AHP)与GIS技术相结合,对林河流域进行洪水风险区制图。用于分析的参数是影响洪水的主要原因。除了坡度、降雨量、土地覆被、土壤、排水密度等5个最常用的因子外,本研究还增加了一个新的因子——相对坡度长度,以计算出更严格、更可靠的模型。并将结果与同一研究区域洪水灾害区划的两种方法——主致洪因子分析法和继承、数据分析与处理法进行了比较。并通过2010年、2013年和2016年3年的历史洪水数据对结果进行了验证。
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Evaluation and validation of flood hazard zoning using Analytical Hierarchy Process and GIS: A case study of Lam River basin (Vietnam)
In recent years, the Lam river basin had suffered various forms of natural disasters such as floods, inundations, windstorms, tornadoes, etc. Among all these, the flood has proved to be the greatest threat to the people and the socio-economic development in the basin. Moreover, it is very frequent as compared to other natural disasters. In view of the fact that such disastrous floods are still occurring in the basin, it becomes a necessity to determine the causes and analyze the components affecting flood. This is important in order to develop an early flood warning system and thus minimize the negative impact of flood in the Lam river basin on the people and the facilities. In this paper, the Analytical Hierarchy Process (AHP) analysis method integrated with GIS technology is used to map flood risk zones in the Lam river basin. The parameters used for the analysis are the main causes affecting the floods. In addition to the 5 most commonly used factors such as slope, rainfall, land cover, soil, and drainage density, this study also includes a new factor - relative slope length to compute a more rigorous and reliable model. The results were compared with the two more methods of flood hazard zoning in the same study area: the method of the main flood caused factor analysis and the method of inheriting, data analyzing, and processing. The results were also validated by the historical flood data of three years 2010, 2013, and 2016.
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