Development of advanced calibration methods for computationally expensive hydrologic simulation models

环境或水文模拟模型是对复杂环境系统的数学近似。合理的环境管理决策，如如何减轻未来气候变化对水资源的影响，通常是基于环境模拟模型的预测。我的研究产生了支持这些模型开发的高级工具。使用我的工具的高级建模人员应该能够更快地构建更好的模型。更重要的是，我的工作支持这些模型的应用，这样，当选定的模型应用于给定的案例研究时，我的工具可以确保对过去系统行为的模型预测尽可能准确。对过去系统行为的准确预测通常是使用模拟模型为环境决策提供信息的先决条件。 我们的一些最先进的水文系统模型是如此复杂，以至于在个人计算机上运行可能需要几个小时。不幸的是，这么长的运行时间往往会妨碍它们在决策中的使用。这项研究拨款支持继续开发为应用于非常大的和计算昂贵的模拟模型而量身定做的工具。我的研究将产生多种新的水文模型校准方法，这些方法适用于广泛的计算尺度，并使研究人员和实践者都可以使用。这些新的方法和工具也将考虑到模型预测的不确定性而开发，因为我们对自然的数学描述是不完美的，我们对系统行为的测量也是不完美的。本文的研究结果不仅适用于任何环境模型标定问题，也适用于其他具有相似模型标定要求的工程学科。这项工作的结果将使加拿大特别受益，因为研究中使用的主要模拟案例研究之一是加拿大环境部对五大湖水位和外流的预测和模拟模型。

Environmental or hydrologic simulation models are mathematical approximations of complex environmental systems. Sound environmental management decisions such as how to mitigate future impacts of climate change on water resources are typically based on environmental simulation model predictions. My research generates advanced tools that support the development of these models. Advanced modellers using my tools should be able to build better models faster. Even more important, my work supports the application of these models such that when a selected model is applied to a given case study, my tools make sure the model predictions of the past system behaviour are as accurate as possible. Accurate predictions of past system behaviour is often a prerequisite for using a simulation model to inform environmental decision-making. Some of our most advanced models of hydrologic systems are so complex they can require hours to run on a personal computer. Unfortunately, this long run time often precludes their use in decision-making. This research grant supports the continued development of tools that are tailored for application to very large and computationally expensive simulation models. My research will generate multiple new hydrologic model calibration approaches that are adaptable to a wide range of computational scales and made accessible to both researchers and practitioners. These new approaches and tools will also be developed considering model prediction uncertainty since our mathematical descriptions of nature are imperfect and our measurements of system behaviour are also imperfect. Results of this research are applicable to any environmental model calibration problem as well as other Engineering disciplines with similar model calibration requirements. Results of this work will specifically benefit Canada since one of the major modelling case studies utilized in the research is Environment Canada's forecasting and simulation model of Great Lakes levels and outflows.