Novel Approaches in Statistical Analysis and Coupled Social-Physical Systems Modeling for Integrated and Adaptive Water Resources Management in the Face of Increasing Uncertainty

面对日益增加的不确定性，用于综合和适应性水资源管理的统计分析和耦合社会物理系统建模的新方法

• 批准号: RGPIN-2015-05554
• 负责人: Adamowski, Jan
• 金额: $ 2.48万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=685317
• 关键词: Novel; Approaches; Statistical; Analysis; Coupled

In many parts of Canada and around the world, pressure on water resources, both in terms of water quality and quantity, from urban areas, agriculture, and industry are increasing, resulting in significant challenges in sustainable water resources management. In addition, in many regions of the world climate change will increase the frequency of extreme events (e.g., droughts and floods), which will have significant impacts on, among other things, our ecosystems, water resources, urban areas, and agricultural and food systems, which in turn will have ramifications on water and food security. The capacity of communities to mitigate against, and adapt to, such complex problems is presently constrained by many factors, including: i) a lack of water resources data in many watersheds that can help support water resources modeling and management; ii) challenges in providing highly accurate forecasts of non-linear and non-stationary water resources variables, and providing uncertainty assessments for decision makers; and iii) a lack of meaningful participation of key stakeholders in water resources modeling and management, coupled with our limited knowledge and modeling ability of the complex coupling of physical and social-economic activities in water resources systems.***To directly address these three critical issues, this research program will follow a three pronged approach to develop, test, and implement: i) Methods to improve water resources data records for modeling and management. This will involve new approaches to extend water resources records in short-gauged sites, as well as estimate water resources records in ungauged sites. ii) Methods to improve short term water resources forecasting. This will involve new approaches to address non-linearity, non-stationarity, and uncertainty assessment in water resources forecasting. iii) Methods to improve the incorporation of key stakeholders and social aspects in water resources modeling and management. This will involve a new participatory social-physical systems modeling approach to represent and couple interactions between physical and social-economic processes that govern water resources systems. This research program will facilitate the transition towards more sustainable water resources management, and will provide training of highly qualified personnel in a unique combination of state-of-the-art concepts and approaches in the fields of hydrology and integrated, collaborative, and adaptive water resources management.**

在加拿大和世界各地的许多地区，城市地区、农业和工业对水资源的质量和数量方面的压力都在增加，给可持续水资源管理带来了重大挑战。此外，在世界许多地区，气候变化将增加极端事件（例如干旱和洪水）的发生频率，这将对我们的生态系统、水资源、城市地区以及农业和粮食等产生重大影响。系统，这反过来又会对水和粮食安全产生影响。目前，社区缓解和适应此类复杂问题的能力受到许多因素的限制，包括： i) 许多流域缺乏有助于支持水资源建模和管理的水资源数据； ii) 为非线性和非平稳水资源变量提供高精度预测以及为决策者提供不确定性评估方面面临的挑战； iii) 主要利益相关者缺乏对水资源建模和管理的有意义的参与，加上我们对水资源系统中物理和社会经济活动的复杂耦合的知识和建模能力有限。***直接解决这三个问题针对关键问题，该研究计划将遵循三管齐下的方法来开发、测试和实施： i) 改进水资源数据记录以进行建模和管理的方法。这将涉及扩大短计量地点水资源记录的新方法，以及估计未计量地点的水资源记录。 ii) 改进短期水资源预测的方法。这将涉及解决水资源预测中的非线性、非平稳性和不确定性评估的新方法。 iii) 改进关键利益相关者和社会方面在水资源建模和管理中的纳入的方法。这将涉及一种新的参与性社会物理系统建模方法，以表示和耦合管理水资源系统的物理过程和社会经济过程之间的相互作用。该研究计划将促进向更可持续的水资源管理过渡，并将水文学和综合、协作和适应性水领域最先进的概念和方法独特地结合起来，为高素质人员提供培训资源管理。**