Wildfire in the West: Characterizing Spatial Trends in Post-Disturbance Hydrologic and Sediment Response at the Watershed Scale
Conference Proceeding
Overview
abstract
Wildfires are expected to increase in both size and severity in the western U.S. These; disasters cause important, often lasting changes to watershed dynamics, particularly in; sediment mobilization processes, and create problems for downstream reservoirs and water; treatment facilities. Therefore, it is essential to improve our understanding of wildfiredriven changes in streamflow and suspended sediment loading (SSL) to mitigate damages.; Previous efforts to model wildfire effects have often focused on a small subset of sites and; a limited number of post-fire hydrologic processes changes such that the insights gained; have generally lacked transferability due to regional variations in the drivers of these; responses. Additionally, scarcity of observational sediment data provides a further; challenge for finding generalizable influences on post-fire sediment response useful for; modeling in areas with little to no available sediment data, which represent the vast; majority of basins in the West. In this research, we seek to improve understanding of postdisturbance hydrology and sedimentation by first characterizing streamflow and sediment; relationships through commonly used rating curve parameters at a diverse set of gaged; locations across the western U.S. We combine this with basin topographical and water; infrastructure development information from the GAGES-II dataset. We then select a; relatively undeveloped basin from this dataset (the Rio Puerco near Bernardo, NM) that; has been affected by five observed fire events between 1999 and 2014 as a testbed for; measuring the viability of a set of increasingly data-intensive approaches for finding a; detectable post-fire sediment response signal. We begin by applying a statistical model to; pre-fire stream gage data and forecasting the post-fire season, comparing differences in; suspended sediment loading (SSL) magnitudes between the forecast and observations. We; subsequently add precipitation data from Daymet (basin-averaged, then gridded), and fire; extent data from the Monitoring Trends in Burn Severity (MTBS) dataset to improve postfire sediment signal strength. Future work will see further exploration of novel detection; techniques, as well as the eventual application of these methodologies to other western; basins in an effort to uncover regional influences on sediment response to wildfire. This; study carries implications for post-fire sediment modeling, water management, and; reservoir operations.
