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: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=636363
• 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.

在加拿大许多地区和世界各地，来自城市、农业和工业的水资源在水质和水量方面的压力都在增加，这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(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系统等产生重大影响，进而对水和粮食安全产生影响。社区缓解和适应这类复杂问题的能力目前受到许多因素的制约，这些因素包括：(1)许多流域缺乏可帮助支持水资源建模和管理的水资源数据；(2)难以对非线性和非平稳的水资源变量提供高度准确的预测，并为决策者提供不确定性评估；(3)主要利益攸关方缺乏对水资源建模和管理的切实参与，加上我们对水资源系统物理和社会经济活动复杂耦合的知识和建模能力有限。