Ecohydrology links ecological and hydrological processes and considers interactions between water resources and ecosystems. Modeling tools are not only important for studying the mechanisms of ecological patterns and processes but also for assessing the effects of environmental change on hydrological and ecological processes, providing insights and solutions to issues in water management. This thesis explores various data-driven approaches to monitor and model these processes at 95 watersheds in western USA using a combination of seasonal and annual climate, hydrometric, and remotely sensed vegetation data. In one analysis, we show that a trend in earlier peak in spring vegetation activity may be a linked to reduced runoff availability during drought years compared to non-drought years. We also provide evidence that increase drought severity is consistent with a decrease in runoff ratio in forested catchments through regression analysis, supporting the hypothesis that the relationship among water-balance components may shift during drought events. In another analysis, we show that the type and amount of vegetation coverage, among other catchment characteristics, can affect the accuracy of data-driven runoff models. These results suggest that a better understanding of the ecohydrologic processes and characteristics is vital to development of effective long-term strategies to improve the resilience of watersheds.
Read
