Floods are among the most common natural hazards around the world. Mapping and evaluating potential flood hazards are essential for flood risk management and mitigation strategies, particularly in coastal areas. Several factors play significant roles in flooding and recognizing the role of these flood-related factors may enhance flood disaster prediction and mitigation strategies. This study focuses on using Shannon’s entropy model to predict the role of seven factors in causing floods in the Governorate of Muscat, Sultanate of Oman, and mapping coastal flood-prone areas. The seven selected factors (including ground elevation, slope degree, hydrologic soil group (HSG), land use, distance from the coast, distance from the wadi, and distance from the road) were initially prepared and categorized into classes based on their contribution to flood occurrence. In the next step, the entropy model was used to determine the weight and contribution of each factor in overall susceptibility. Finally, results from the previous two steps were combined using ArcGIS software to produce the final coastal flood susceptibility index map that was categorized into five susceptibility zones. The result indicated that land use and HSG are the most causative factors of flooding in the area, and about 133.5 km² of the extracted area is threatened by coastal floods. The outcomes of this study can provide decision-makers with essential information for identifying flood risks and enhancing adaptation and mitigation strategies. For future work, it is recommended to evaluate the reliability of the obtained result by comparing it with a real flooding event, such as flooding during cyclones Gonu and Phet.

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使用香农熵模型绘制沿海洪灾敏感区的地图：以阿曼马斯喀特省为例

洪水是世界上最常见的自然灾害之一。绘制和评估潜在的洪水灾害对于洪水风险管理和缓解策略至关重要，尤其是在沿海地区。有几个因素在洪水中起着重要作用，认识到这些与洪水有关的因素可能会增强洪水灾害的预测和减灾策略。这项研究的重点是使用香农的熵模型来预测七个因素在马斯喀特，阿曼苏丹国和南部沿海洪灾易发区中引发洪水的作用。选择的七个因素（包括地面海拔，坡度，水文土壤组（HSG），土地使用，与海岸的距离，与旱谷的距离，距离道路的距离和距离）进行了初步准备，并根据它们对洪水发生的贡献进行了分类。在下一步中，将使用熵模型来确定总体敏感性中每个因素的权重和贡献。最后，使用ArcGIS软件将前两个步骤的结果进行组合，以生成最终的沿海洪灾敏感性指数图，该图可分为五个敏感性区域。结果表明，土地利用和HSG是该地区洪水的最主要成因，约133.5 km 使用ArcGIS软件将前两个步骤的结果进行组合，以生成最终的沿海洪水敏感性指数图，该图被分为五个敏感性区域。结果表明，土地利用和HSG是该地区洪水的最主要成因，约133.5 km 使用ArcGIS软件将前两个步骤的结果进行组合，以生成最终的沿海洪水敏感性指数图，该图被分为五个敏感性区域。结果表明，土地利用和HSG是该地区洪水的最主要成因，约133.5 km²所提取的面积被洪水沿海的威胁。这项研究的结果可以为决策者提供确定洪水风险和增强适应和减灾策略的基本信息。在以后的工作中，建议将所得结果与真实的洪水事件（如旋风Gonu和Phet期间的洪水）进行比较，以评估所得结果的可靠性。