HYDROLOGIC MODELING IN THE NOOKSACK RIVER BASIN USING DOWNSCALED GRIDDED SURFACE CLIMATE DATA

The Nooksack River drains an approximately 2000 km² watershed in the North Cascades in Whatcom County, Washington and is a valuable freshwater resource for regional municipalities, industry, and agriculture, and provides critical habitat for endangered salmon species. Nooksack River streamflow is largely influenced by precipitation and snowmelt in the spring, and glacial melt throughout the warmer summer months when precipitation is minimal. Regional climate projections through the end of the 21^stcentury indicate an increase in average annual air temperature, a decrease in summer precipitation, and an increase in winter precipitation. Due to a lack of spatially distributed long-term historical weather observations in the basin for downscaling purposes, we apply publically available statistically derived gridded surface data along with the Distributed Hydrology Soil Vegetation Model (DHSVM) with newly developed coupled dynamic glacier module to predict the impacts of future climate scenarios on snowpack, glaciation, and streamflow in the Nooksack River basin.

We calibrate and validate the DHSVM to observed glacial mass balance and areal extent as well as streamflow and SNOTEL data in the Nooksack basin using observational data (1950-2011) gridded at a spatial resolution of 1/16 degree lat/long developed by Linveh et al. (2013). Grid points that provide the highest model calibration efficiency are used to predict the impacts of climate change on basin hydrology using publically available, future climate datasets trained with the Livneh data. The downscaled future climate data were developed by Abatzoglou and Brown (2011) using the multivariate adaptive constructed analogs method (MACA). The MACA downscaled data incorporates 20 global climate models of the CMIP5 using RCP4.5 and RCP8.5 forcing scenarios. Here, we address the methodology, set-up, calibration, and validation of the DHSVM and preliminary future streamflow results under forecasted climate change.