Water Resources Collections and Archives

Scientists predict that future climate change will effect both human and natural systems. Using two rainfall-runoff modeling methods, this analysis predicts the effects of climate change on the hydrology of upper Alameda Creek, a small drainage area in California’s Coast Range. I analyzed daily rainfall, temperature, and stream flow data collected from field gages for 8 years to develop a numerical predictive model. Using the Army Corps of Engineers Hec-HMS model and autoregressive statistical techniques, I minimized the difference between the predicted and the observed creek discharge. I then generated an altered temperature and precipitation regime based on a high-end climate change prediction downscaled to a 60 square mile grid. For upper Alameda Creek, annual precipitation is predicted to fall by 28.2% and annual temperature is predicted to increase by 5.2°C by 2100. The autoregressive model had the lowest error when compared to the observed data, and predicts a 22% decrease in total discharge and considerably smaller peak flows with climate change. The Hec-HMS model predicts a 46% reduction in total discharge and large reductions in peak flows with climate change. Reduced discharge and peak flows will have adverse impacts on downstream uses, including drinking water supplies for San Francisco, recreational uses at Sunol Regional Wilderness, and habitat for native rainbow trout, alluvial sycamore, California red-legged frog, California tiger salamander, and other rare and endangered species.