T366 Approaches to Applied Modeling for Industry and the Public (Posters)

Wednesday, 25 October 2017
9:00 AM - 6:30 PM
Halls 4EF


CALIBRATION OF A HYDROLOGIC AND STREAM TEMPERATURE MODEL TO THE NORTH FORK OF THE STILLAGUAMISH RIVER FOR CLIMATE CHANGE MODELING

Paper number: T366-2
Program: Technical Sessions
Time: 9:00 AM – 6:30 PM


Authors


Abstract

The North Fork of the Stillaguamish River in northwest Washington State is a valuable regional water resource and critical habitat for endangered salmon species. The basin is about 730 km2 with relief ranging from 55 m to 2100 m. About 58% of the basin is above 500 m elevation and is snow dominated in the winter months. Snowpack is the main contributor to spring and summer streamflow in the Stillaguamish, and is highly sensitive to fluctuations in temperature during mild maritime winters. Global climate change is projected to increase winter temperatures in the Pacific Northwest, leading to an increase in precipitation falling as rain. To assess shifts in snowpack, streamflow, and stream temperature in the North Fork basin due to climate change, we apply gridded meteorological surface data with a physically based stream flow model, the Distributed Hydrology Soil Vegetation Model (DHSVM), and a stream temperature model, the River Basin Model (RBM).

Initial model set-up involves digital processing of 50 m spatial inputs such as elevation, soil depth, soil type, vegetation, and a stream network. The high resolution allows for the spatial heterogeneity of these parameters to be taken into account, resulting in a more accurate representation of the hydrology of the basin. We apply observational meteorological gridded data developed by Linveh et al. (2013) and calibrate the DHSVM to streamflow from a USGS stream gauge near the mouth of the North Fork of the Stillaguamish. Field work was conducted in the summer of 2017 to determine stream morphology, discharge, and stream temperatures at a number of stream segments for the RBM calibration. We present our methodology and calibration results, and the framework for projected climate change modeling using downscaled meteorological data from global climate models.


Geological Society of America Abstracts with Programs. Vol. 49, No. 6

doi: 10.1130/abs/2017AM-306102

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