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Hydrologic Landscape Classification to Estimate Bristol Bay Watershed Hydrology
Todd, J. AND P. Wigington. Hydrologic Landscape Classification to Estimate Bristol Bay Watershed Hydrology. AWRA Spring Conference Water-Energy-Environment, Anchorage, AK, April 25 - 27, 2016.
The purpose of this abstract is for an oral presentation to be presented at the American Water Resources Association Spring Meeting in Anchorage, Alaska from April 25-27, 2015.
The use of hydrologic landscapes has proven to be a useful tool for broad scale assessment and classification of landscapes across the United States. These classification systems help organize larger geographical areas into areas of similar hydrologic characteristics based on climate, terrain and underlying geology. Such characterization of landscapes into areas of common hydrologic character is particularly instructive where site specific hydrologic data is sparse or spatially incomplete. Within Bristol Bay, much of the region remains understudied with many areas having minimal to nonexistent hydrologic data, and those areas that are well studied limited to individual reaches or small watersheds. By using broad scale landscape metrics to organize the landscape into discrete, characterized units, natural resources managers can gain valuable understanding of the region’s hydrologic character and how locations may be differentially affected by a variety of environmental stressors ranging from land use change to climate change. The heterogeneity of aquatic habitats and undisturbed hydrologic regimes within Bristol Bay watershed are a known principal driver for its overall fisheries stability and the use of hydrologic landscapes offers the ability to better characterize the hydrologic and landscape influences on structuring biotic populations at a regional scale. Here we classify the entire Bristol Bay region into discrete hydrologic landscape units based on indices of annual climate and seasonality, terrain, and geology. Areas of available gauged records were grouped into river basin type based on visual differentiation of hydrograph shape in regards to baseflow contribution, timing and magnitude of peak flows and resident hydrologic landscape distributions therein compared. Finally, using these observed relationships between river basin type and hydrologic landscape composition, we estimate hydrologic condition in locations where streamflow data is lacking, but with known hydrologic landscape distribution. This demonstration of hydrologic landscapes in Bristol Bay, Alaska shows the utility of using large-scale datasets on climate, terrain and geology to infer broad scale hydrologic character within a data poor area. Disclaimer: The authors views expressed here do not necessarily reflect views or policies of U.S. EPA.