Evaluating reference evapotranspiration and the effects of climate change and soil parameterization within distributed hydrologic models

Abstract

Parsimonious methods to estimate potential evapotranspiration (ET) based on temperature and solar radiation data are attractive alternatives to more data intensive methods in areas with limited data availability or when developing algorithms for estimating ET from remotely sensed data. In the first part of this dissertation, the performances of the most commonly used ET models have been investigated and methods to improve their performance in a variety of climates have been proposed. In addition, linear models to evaluate potential ET at annual and seasonal time scales have also been developed. These models have a simple structure and are useful for evaluating spatial distribution of ET, assessing historical annual and growing season ET, performing baseline checks, or evaluating ET trends based on output from global climate models. In the second part of this work, a complex Richards equation based hydrologic model has been used in which soil parameterization was varied. Model simulation results showed that both the soil moisture retention curve and the saturated hydraulic conductivity control the level and spatial variability of soil moisture and affect the shape, timing, and magnitude of the hydrograph. Results from these virtual experiments provide insights for model calibration and for the site locations useful for field data collection to best inform the distributed hydrologic model. Finally, the last topic investigates hydrologic modeling at a larger scale and in the context of climate change. A fine-scale, distributed hydrologic model, DHSVM, has been used to investigate the role of the vegetation cover density and extent on streamflow timing and magnitude for a high elevation basin located in the Sierra Nevada Mountains, California. Model simulations have indicated that in this area, when temperatures are rising, snow melts faster in the presence of forests mostly due to increases in net longwave radiation. The findings from this study are important to identify forest management actions in the Sierra Nevada that have the potential to increase snow retention at high elevations and increase summer flows.