Institute for Disaster Management and Reconstruction, Sichuan University-Hong Kong Polytechnic University, Chengdu, 610065, China; State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource & Hydropower, Sichuan University, Chengdu, 610065, China.
Institute for Disaster Management and Reconstruction, Sichuan University-Hong Kong Polytechnic University, Chengdu, 610065, China; State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource & Hydropower, Sichuan University, Chengdu, 610065, China; School of Emergency Management, Xihua University, Chengdu, 610039, China.
J Environ Manage. 2024 Aug;366:121831. doi: 10.1016/j.jenvman.2024.121831. Epub 2024 Jul 16.
Climate change and intensified human activities are exacerbating the frequency and severity of extreme precipitation events, necessitating more precise and timely flood risk assessments. Traditional models often fail to dynamically and accurately assess flood risks due to their static nature and limited handling of spatiotemporal variations. This study confronts these challenges head-on by developing a novel coupled hydrological-hydrodynamic model integrated with a Block-wise use of the TOPMODEL (BTOP) and the Rainfall-Runoff-Inundation (RRI) model. This integrated approach enables the rapid acquisition of high-precision flood inundation simulation results across large-scale basins, addressing a significant gap in dynamic flood risk assessment and zoning. A critical original achievement of this research lies in developing and implementing a comprehensive vertical-horizontal combined weighting method that incorporates spatiotemporal information for dynamic evaluation indicators, significantly enhancing the accuracy and rationality of flood risk assessments. This innovative method successfully addresses the challenges posed by objective and subjective weighting methods, presenting a balanced and robust framework for flood risk evaluation. The findings from the Min River Basin in China, as a case study, demonstrate the effectiveness of the BTOP-RRI model in capturing the complex variations in runoff and the detailed simulations of flood processes. The model accurately identifies the timing of these peaks, offering insights into the dynamic evolution of flood risks and providing a more precise and timely assessment tool for policymakers and disaster management authorities. The flood risk assessment results demonstrate good consistency with the actual regional conditions. In particular, high-risk areas exhibit distinct characteristics along the river channel, with the distribution area significantly increasing with a sudden surge in runoff. Intense precipitation events expand areas classified as moderate and high risk, gradually shrinking as precipitation levels decrease. This study significantly advances flood risk assessment methodologies by integrating cutting-edge modeling techniques with comprehensive weighting strategies. This is essential for improving the scientific foundation and decision-making processes in regional flood control efforts.
气候变化和人类活动的加剧正在使极端降水事件的频率和严重程度加剧,因此需要更精确和及时的洪水风险评估。传统模型由于其静态性质和对时空变化的有限处理,往往无法动态和准确地评估洪水风险。本研究通过开发一种新的耦合水文水力模型,结合了块式 TOPMODEL(BTOP)和降雨径流洪水(RRI)模型,直面这些挑战。这种集成方法能够快速获取大流域高精度的洪水淹没模拟结果,解决了动态洪水风险评估和分区的重大差距。这项研究的一个关键的原创性成就是开发并实施了一种全面的垂直-水平组合加权方法,该方法将时空信息纳入动态评估指标,显著提高了洪水风险评估的准确性和合理性。这种创新方法成功解决了客观和主观加权方法带来的挑战,为洪水风险评估提供了一个平衡而稳健的框架。以中国闽江流域为例的案例研究表明,BTOP-RRI 模型能够捕捉径流的复杂变化,并对洪水过程进行详细模拟。该模型准确地识别了这些峰值的时间,深入了解了洪水风险的动态演变,并为决策者和灾害管理机构提供了更精确和及时的评估工具。洪水风险评估结果与实际区域条件具有良好的一致性。特别是,高风险区域沿河道呈现出明显的特征,随着径流量的突然增加,分布面积显著增加。强降水事件使中等风险和高风险区域的面积扩大,随着降水强度的降低而逐渐缩小。本研究通过将先进的建模技术与全面的加权策略相结合,极大地推进了洪水风险评估方法学的发展。这对于提高区域防洪工作的科学基础和决策过程至关重要。