基于未来情景模拟的城市景观水文弹性措施绩效评估与优化研究

Sustainable management of urban landscape hydrology (ULH) is a vital issue in human settlements construction. Scenario modeling is an important tool to investigate the impacts on ULH and to cater to potential future changes. The scenario matrix architecture integrated Representative Concentration Pathways (RCPs) and Shared Socioeconomic Pathways (SSPs) facilitates projecting the impacts on ULH faced on climate change. However, how to project the changes of ULH based on combined effects of climate change and urbanization? This study integrates the RCPs, SSPs, and urban stormwater management SSPs (SSPusm) to construct a future scenario modeling (RCPs-SSPs-SSPusm) taking into consideration climate change and urbanization. Our previous study found that in the high-density city area, regular rainfall events are more sensitive for futural uncertainty, and the hydrologic response may be impacted more significantly by urbanization, as well as future changes may have more effects on the runoff quality than on quantity. In the face of the above challenges, how to ensure the performance of low impact development (LID) practices as the resilient strategy for maintaining the sustainability of ULH? Zhujiang New Town, located in Guangzhou, has been selected as a case study for simulating by RCPs-SSPs-SSPusm in this study. The hydrological, cost and environmental performances of LID practices in future scenarios have been examined by SUSTAIN, Life Cycle Cost, and Life Cycle Assessment. Then, sensitivity analysis and genetic algorithm analysis of LID practices are carried out, so as to establish the best management objectives and optimize plan of LID practices. The methodology developed in this study could be useful for green infrastructure planning and test the resilient against future change scenarios as a result of urbanization and climate change.

城市景观水文的可持续管理是人居环境建设的重点课题。情景模拟是预估景观水文影响的重要手段。研究表明，典型浓度路径（RCPs）和共享社会经济路径（SSPs）的矩阵模拟可有效预估景观水文受气候变化的影响。那么城市景观水文受城市发展和气候变化的综合影响又该如何预估？本课题整合RCPs、SSPs以及模拟城市发展的SSPusm，构建了RCPs-SSPs-SSPusm的未来情景模拟预估方法。前期研究发现常规降雨事件变率较大，同时城市发展对景观水文影响更为显著，其中水质影响又更为敏感。面对上述挑战，又该如何确保低影响开发（LID）作为景观水文弹性措施的可持续绩效？本课题以广州珠江新城为例，基于RCPs-SSPs-SSPusm情景模拟，通过水文模型、全生命周期成本和评估工具检验LID的综合绩效。进而对LID系统及参数进行敏感性分析和遗传算法分析，以确立LID优化方案，为城市景观水文弹性措施规划提供科学依据。

项目主要围绕城市景观水文情景构建和弹性措施空间优化展开了3个方面的研究工作，包括：（1）评估了典型城市景观水文弹性措施绩效的基准性能，为情景模拟提供基准参照；（2）构建了影响城市景观水文的未来情景模拟评估架构；（3）开发了弹性措施的多阶段决策工具和空间配置模型。本研究基于全生命周期视角，综合了关于多气候模式组下的气候变化影响以及弹性措施自身长期效度的不确定性分析，对城市景观水文的未来情景模拟框架进行构建，并以此为提升弹性措施空间配置的适应性提供科学支撑。在弹性措施空间配置方面，先后构建了基于场地尺度的弹性措施系统组合的空间配置决策方法；耦合未来情景模拟和贝叶斯分类的弹性措施多阶段投资建设和空间配置方法；和可响应高密度城市环境的灰色-绿色基础设施耦合的空间规划方法。系统性的城市景观水文情景模拟和弹性措施的空间配置方法有机会为韧性城市和海绵城市的规划和建设提供技术支持。