Abstract：
Nagaon is one of the highly flood-prone districts of Assam, India that recurrently experiences devastating floods resulting in the loss of lives and property and wreaking havoc on the district\'s socioeconomic infrastructure. Identification and mapping of spatial patterns of flood hazards, flood vulnerability, and flood risk zones (FRZs) of the district are, therefore, crucial for flood management and mitigation. The present study, therefore, attempts to delineate the FRZs of more than 930 villages in the Nagaon district by integrating the flood hazard and vulnerability layers in the geospatial environment using the multi-criteria decision analysis and analytical hierarchy process techniques. Here, seven flood hazard and vulnerability indicators are considered to derive each layer separately. The results indicate that about 15.14% of the district\'s total villages are in the very high FRZ, 27.93% in the high, 46.62% in the moderate, and 10.3% in the low FRZ. Further, bivariate correlation analysis is used to evaluate the results with the percentages of the population, cropland, and animals affected by floods at different temporal scales in order to ensure that the revenue circles with a higher percentage of area under high and very high FRZs genuinely have higher percentages of flood-affected cropland, people, and livestock. The significance of this research is evident in its pragmatic findings that could aid the stakeholders in managing and reducing flood risk at micro-spatial scales.
摘要：
Nagaon是阿萨姆邦最容易发生洪水的地区之一，印度经常经历毁灭性的洪水，造成生命和财产损失，并对该地区的社会经济基础设施造成严重破坏。识别和绘制洪水灾害的空间格局，洪水脆弱性,该地区的洪水风险区(FRZ)是，因此,对于洪水管理和减灾至关重要。本研究,因此,尝试通过使用多准则决策分析和分析层次过程技术将洪水灾害和脆弱性层整合到地理空间环境中，来划定Nagaon地区930多个村庄的FRZ。这里,七个洪水灾害和脆弱性指标被认为分别得出每一层。结果表明，该地区约15.14%的村庄处于非常高的FRZ，27.93%处于高位，在中度的46.62%，和10.3%在低FRZ。Further,双变量相关分析用于评估结果与人口百分比，农田,和受不同时间尺度洪水影响的动物，以确保高和极高FRZs下面积比例较高的收入圈真正拥有较高比例的受洪水影响的农田，人,和牲畜。这项研究的意义在于其务实的发现，可以帮助利益相关者在微观空间尺度上管理和减少洪水风险。
