Space-time scale sensitivity of the Sacramento model to radar-gage precipitation inputs

Abstract

Abstract Runoff timing and volume biases are investigated when performing hydrologic forecasting at space-time scales different from those at which the model parameters were calibrated. Hydrologic model parameters are inherently tied to the space-time scales at which they were calibrated. The National Weather Service calibrates rainfall runoff models using 6-hour mean areal precipitation (MAP) inputs derived from gage networks. The space-time scale sensitivity of the Sacramento model runoff volume is analyzed using 1-hour, 4 × 4 km2 next generation weather radar (NEXRAD) precipitation estimates to derive input MAPs at various space-time scales. Continuous simulations are run for 9 months for time scales of 1, 3 and 6 hours, and spatial scales ranging from 4 × 4 km2 up to 256 × 256 km2. Results show surface runoff, interflow, and supplemental baseflow runoff components are the most sensitive to the space-time scales analyzed. Water balance components of evapotranspiration and total channel inflow are also sensitive. A preliminary approach for adjusting model parameters to account for spatial and temporal variation in rainfall input is presented.