Watershed characteristics and their hydrological responses can have severe effects on the occurrence and extent of floods. Therefore, this study focuses on the integration of geospatial techniques and remote sensing data to identify watershed terrain characteristics and evaluate the influence of these characteristics on flood susceptibility in South Australia. Data from the Shuttle Radar Topography Mission (SRTM) and geologic and topographic maps and a geographic information system (GIS) were used to delineate drainage basins, measure morphometric parameters and link different parameters to evaluate the degree of flood vulnerability. Depending on their relations to the flood hazards, the morphometric parameters were categorized into two groups; then, a rank score was assigned to each group. Finally, the flood susceptibility of the basins was visualized, and the basins were classified into low, intermediate and high flood hazard areas. The results show that approximately 45.7, 44.7 and 9.7% of the study area is at risk of high, medium and low degrees of flooding, respectively. The results were validated through secondary data relating to historic floods. The causes of flooding were analysed using rainfall and road density data, while the consequences of flooding were verified by the population distribution across the study area. The findings of this study can be used to support decision-makers in planning and investing in mitigation measures, especially in highly susceptible areas of South Australian basins.

流域特征及其水文响应可能对洪水的发生和程度产生严重影响。因此，本研究的重点是整合地理空间技术和遥感数据，以识别流域的地形特征，并评估这些特征对南澳大利亚洪水敏感性的影响。来自航天飞机雷达地形任务（SRTM）和地质地形图以及地理信息系统（GIS）的数据被用于描绘流域轮廓，测量形态参数并链接不同的参数以评估洪水的脆弱性程度。根据形态参数与洪水灾害的关系，将形态参数分为两类。然后，给每个组分配一个等级分数。最后，对流域的洪水敏感性进行可视化，并将流域分为低，中和高洪水灾害区。结果表明，分别有大约45.7、44.7和9.7％的研究区域处于高，中和低洪灾程度的风险中。通过有关历史洪水的辅助数据验证了结果。使用降雨和道路密度数据分析了洪水的成因，而洪水的后果则通过研究区域内的人口分布进行了验证。这项研究的结果可用于支持决策者计划和投资减缓措施，特别是在南澳大利亚盆地的高度敏感地区。研究区域的7％和9.7％分别处于高，中和低度洪灾的风险中。通过有关历史洪水的辅助数据验证了结果。使用降雨和道路密度数据分析了洪水的成因，而洪水的后果则通过研究区域内的人口分布进行了验证。这项研究的结果可用于支持决策者计划和投资减缓措施，特别是在南澳大利亚盆地的高度敏感地区。研究区域的7％和9.7％分别处于高，中和低度洪灾的风险中。通过有关历史洪水的辅助数据验证了结果。使用降雨和道路密度数据分析了洪水的成因，而洪水的后果则通过研究区域内的人口分布进行了验证。这项研究的结果可用于支持决策者计划和投资减缓措施，特别是在南澳大利亚盆地的高度敏感地区。而洪水的后果则通过研究区域内的人口分布得到了证实。这项研究的结果可用于支持决策者计划和投资减缓措施，特别是在南澳大利亚盆地的高度敏感地区。而洪水的后果则通过研究区域内的人口分布得到了证实。这项研究的结果可用于支持决策者计划和投资减缓措施，特别是在南澳大利亚盆地的高度敏感地区。