UCLA

The current work focuses on assessing the impacts of future climate variability on water resources in southern California. Specifically, this dissertation work includes: (1) developing archetypal watersheds and climate scenarios to obtain regional changes to hydrology and sediment transport and (2) developing a statistical downscaling approach that considers regional climate heterogeneity (commonly neglected in downscaling methods) and using this data to drive hydrologic models. The archetypal or "representative" watersheds exemplify observed physiological features and allow us to model hydrologic trends of coastal watersheds in southern California. Future climate scenarios were developed using historical observations [1955 - 2006] and used as input to the Environmental Protection Agency's Hydrologic Simulation Program-Fortran (EPA HSPF). In the statistical downscaling approach, the CNRM-CM3 GCM model was used to develop daily precipitation and temperature. A k-means clustering analysis was utilized and.extensive testing of predictor-predictand relationships was performed to select optimal monthly predictors. Control, no-clustering method, and clustering approaches, based on mean/total annual temperature/precipitation, annual variance and elevation, were performed for daily temperature and precipitation. The developed downscaling approaches were applied to extreme future climate scenarios A2 (high carbon dioxide emission) and B1 (low emission) and change in hydrologic fluxes for the Ballona Creek Watershed were investigated.

Results from the archetypal framework indicate that precipitation variability is the primary variable in determining the magnitude of change in sediment and hydrologic fluxes. Highly vegetated systems, characterized by low annual flows typical of those found in Santa Barbara County, are expected to experience a significant loss of total annual flow and sediment flux due to rising temperatures and precipitation uncertainty. Highly urbanized (typical in Los Angeles) and moderately urbanized (typical in San Diego) watersheds, are expected to experience a significant change to storm dynamics (peak flow and storm sediments) due to climate change. The downscaling investigation shows that the optimal clustering methods to reconstruct temperature and precipitation were elevation and precipitation variance, respectively. Using the high (A2) and low (B1) emission scenarios, precipitation occurrence and quantity will increase throughout the year. As a result, hydrologic fluxes are expected to increase significantly in Ballona Creek, especially during dry periods. The development of the archetypal framework allows for a broad perspective of how future climate variability and regional land use patterns may influence hydrologic and sediment fluxes; changes in these fluxes may have significant implications for restoration and management of coastal wetlands, bays, and harbors. The statistical downscaling method captures daily temperature well, but further efforts may improve daily precipitation reconstructions. Results from this work have significant application in projects involving ecosystem impacts and regional sustainability studies.