H13S-03
Quantifying the Sensitivity of Water Yield to Forest Disturbances Across a Diverse Set of Unmanaged Watersheds throughout the Continential United States

Monday, 14 December 2015: 14:10
3020 (Moscone West)
Brian Buma, University of Alaska Southeast, Juneau, United States and Ben Livneh, Cooperative Institute for Research in Environmental Sciences, Boulder, CO, United States
Abstract:
Water is one of the most critical natural systems for human and ecosystem health and well-being. Understanding the influence of changes in land cover on hydrology is critical to anticipating future water availability and impacts on agriculture/industry, ecosystems, and residential water supplies. In the United States, most major water sources originate in forested watersheds, and thus we aim to understand how changes in forest cover influence water supplies over those areas, specifically identifying which types of watersheds exhibit marked rapid changes in water yield as a result of disturbance processes (e.g., fire). Using a set of 601 primarily unmanaged watersheds (2000-2010) across the US and a 30m forest disturbance dataset, we explored the relationship between changes in water resources, measured in terms of detrended runoff ratios, and forest disturbance severity. Preliminary results find some watersheds nearly completely disturbed due to fire, while others undisturbed. Most watersheds were relatively insensitive--in terms of their expected runoff ratios--to disturbances during that time period, but several were highly sensitive. Areas which showed major increases in water yield post-disturbance generally had larger disturbances occur in areas coincident with higher average precipitation. Soils in these areas had comparatively moderate to low infiltration rates and little subsurface water exchange, and were typically at higher slopes with a lower wetland component. They also had less water storage in the system. Overall, the results from this study are expected to be broadly relevant to communities and scientists seeking to anticipate the hydrologic impacts of large-scale land-cover disturbance.