Flooding is a major environmental problem facing Anambra State of Nigeria, which also threatens food security in the state. To address this issue, continual flood vulnerability mapping exploring more efficient methods is needed to facilitate flood risk management in the state. The advantages of employing spatial information technologies such as Remote Sensing (RS) and Geographic Information System (GIS) in flood vulnerability mapping has been widely documented; the limitations of employing GIS alone in effective vulnerability analysis have also been documented by researchers. To overcome these limitations, this study adopted the use of GIS and the integration of Interval Value Fuzzy Rough Number (IVFRN), Decision Making Trial and Evaluation Laboratory (DEMATEL), and Analytical Network Process (ANP) method in vulnerability assessment of flood hazard. The result of the study shows that the state is very vulnerable to flood with 73% of the total area of the state lying between Very High and Medium vulnerable zones. The most vulnerable Local Government Area (LGA) in the State is Anambra West with 95% of the total area of the LGA lying between Very High and Medium vulnerable zones. Furthermore, the obtained values of show that Rainfall Intensity factor is the major cause of flood in the study area with the highest positive value of 1.55 and Soil factor is the major effect with the highest negative value of -0.93. The IVFRN-DEMATEL-ANP assessment model was validated using AUC-ROC method; an AUC value of 0.946 was obtained, this indicates that the model has excellent prediction accuracy. This study was able to establish the feasibility of integrating the IVFRN, DEMATEL and ANP methods in flood vulnerability assessment. It is recommended that the provision of adequate drainage systems should be prioritized to areas of high flood vulnerability index; to help mitigate flood hazards in the State. Also, strategic planning of infrastructures and emergency routes for moving people and key assets from vulnerable areas especially during the rainy season should be geospatial-based and systematic.

中文翻译：

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使用集成 IVFRN-DEMATEL-ANP 模型对阿南布拉州进行基于 GIS 的洪水脆弱性建模


洪水是尼日利亚阿南布拉州面临的重大环境问题，也威胁着该州的粮食安全。为了解决这个问题，需要不断地绘制洪水脆弱性地图，探索更有效的方法，以促进该州的洪水风险管理。在洪水脆弱性测绘中采用遥感（RS）和地理信息系统（GIS）等空间信息技术的优势已被广泛记录；研究人员也记录了在有效脆弱性分析中单独使用 GIS 的局限性。为了克服这些局限性，本研究采用GIS并结合区间值模糊粗糙数（IVFRN）、决策试验与评估实验室（DEMATEL）和分析网络过程（ANP）方法进行洪水灾害脆弱性评估。研究结果表明，该州非常容易遭受洪水侵袭，该州总面积的 73% 位于极高和中等脆弱区域之间。该州最脆弱的地方政府区域 (LGA) 是阿南布拉西区，LGA 总面积的 95% 位于极高和中等脆弱区域之间。此外，获得的值表明，降雨强度因子是研究区洪水的主要原因，其正值最高为1.55，土壤因子是主要影响因素，其负值最高为-0.93。采用AUC-ROC方法对IVFRN-DEMATEL-ANP评估模型进行验证；得到的AUC值为0.946，这表明该模型具有优异的预测精度。本研究确立了将 IVFRN、DEMATEL 和 ANP 方法整合到洪水脆弱性评估中​​的可行性。 建议优先为洪水脆弱性指数高的地区提供足够的排水系统；帮助减轻该州的洪水灾害。此外，特别是在雨季期间，用于从脆弱地区转移人员和重要资产的基础设施和应急路线的战略规划应该基于地理空间和系统性。