UC Irvine

Numerous studies have highlighted that water resources and hydrologic extremes are sensitive to climate change. An interesting research question is what the role of climate change is in occurrence of extreme events. More importantly, how climate extremes may change under future climate conditions and emission scenarios. Therefore, there exists a strong need to study water resources and hydrologic cycle under different climate change scenarios at the global scale.

In the past decades, numerous methods and models have been developed for assessing climate change impacts on water resources. However, there are still major research gaps from uncertainties in climate model simulations to limitations in the current large scale water cycle (or global hydrologic) models. Some of the current research gaps include: (I) high uncertainty of climate model simulations; (II) limitations and high uncertainties of the global hydrologic model simulations because of calibration challenges at the global scale; and (III) lack of frameworks for accounting for the local resilience and man-made infrastructure in climate impact assessment studies. The overarching goal of this study is to address the above mentioned research gaps.

In this dissertation, several novel evaluation metrics are introduced that can be used for evaluation of errors and biases in input data which is a key factor in the overall uncertainty of climate change studies. Furthermore, this study leads to a better representation of the hydrologic cycle at the global scale through a comprehensive multi-objective calibration framework for global hydrologic models. Then, a modeling framework is presented for accounting for local resilience in climate change studies. Finally, this study outlines a framework for combining top-down and bottom-up approaches for climate change impact assessment.