Developing a watershed modeling approach for reconstructing past streamflow in the upper Walker River Basin, California

Measured streamflow data in a given basin are important for determining regional patterns of climate and streamflow trends, but are often unavailable or extend back less than 100 years. Observed streamflows can be regressed against tree-ring data that serve as proxies for streamflow to extend the measured record, however this empirical approach cannot account for factors that do not directly affect tree-ring growth, but which may influence streamflow. To reconstruct past streamflows in a more mechanistic way, seasonal water balance models were reviewed and developed for the upper West Walker River basin that can use proxy precipitation and air temperature data derived from treering records. The final model incorporates simplistic relationships between temperature, precipitation, and other components of the hydrologic cycle, and operates at a seasonal time scale. The model was able to reproduce streamflow with an r2 of 0.90, and a RMSE of 7.50 cm with average seasonal air temperature as input. Simulated streamflow was 0.66% greater than observed streamflow for WY 1940 through WY 2006. This model was subsequently used to simulate the effects of wildfire on streamflow in the upper West Walker River Basin. The earliest historical record of wildfire in this basin dates back to 1961, with the most recent recorded in 2005. Evapotranspiration and runoff coefficients were adjusted to simulate reduced vegetation cover as a result of fire, and were applied to the dry season when fire was recorded and the subsequent wet season to reflect time required for re-vegetation to occur. The resulting r2 value decreased to 0.85, with RMSE increasing to 9.02 cm, and the overall streamflow simulation increased to 1.57% greater than observed streamflow. Based on the results of this modeling exercise, the modeling approach with average seasonal air temperature would be appropriate for utilizing proxy tree-ring data as input. The model performed very well using only air temperature and precipitation as input and incorporated 6 parameters representing hydrologic processes influencing streamflow. However, simulating wildfire with this model did not improve streamflow simulations, indicating that the model was sensitive to modeling such landcover manipulations.