| This dissertation investigates the interannual variability of soil moisture as related to large-scale climate variability, and oceanic-atmospheric patterns. Firstly, a three-layer hydrological model VIC-3L (Variable Infiltration Capacity Model - 3 layers) was used in the Upper Colorado River basin at a daily time step and a 1/8 spatial resolution over a 50-year (1950 to 2000) period. Using wavelet analysis, deep soil moisture was compared to the Palmer Drought Severity Index (PDSI), precipitation, and streamflow to determine whether deep soil moisture is an indicator of climate extremes.; Secondly, this research evaluates the spatial and temporal variability of soil moisture by using map analysis and t-test statistical method. The soil moisture in drought years was significantly different from the soil moisture in normal and wet years. An extended temporal soil moisture evaluation was performed in pre-drought, drought, and post-drought periods. The results show that soil moisture may be a potential drought indicator, which could improve drought predictability. Finally, the correlation between soil moisture and oceanic-atmospheric patterns, such as Sea Surface Temperatures (SSTs), El Nino-Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), and the Atlantic Multidecadal Oscillation (AMO) were evaluated. Singular Variable Decomposition (SVD) was used in evaluating the relation between soil moisture and Pacific Ocean SSTs.; The current research resulted in several significant contributions: The main contributions of this research are: (a) the development of a 1/8 spatial resolution and a temporal daily time step soil moisture dataset for the Upper Colorado River basin, (b) the evaluation of the soil moisture as a drought indicator, (c) improving the comprehensive understanding of how spatial and temporal variability of soil moisture varies during drought periods, and (d) the coupling of oceanic-atmospheric/patterns with soil moisture to improve long-term drought forecasts. |
