Seasonal Inflow Forecasting Based on a Physically Based Hydro-Climatic Model for the Shasta Lake Basin, California

Seasonal forecasting is essential for effective water resource management, but it remains challenging, especially in the context of climate change and the added uncertainty it brings. It is becoming increasingly clear that purely statistical inflow forecasting is insufficient. This study applies the seasonal inflow forecasting system, developed by the Hydrologic Research Laboratory at the University of California, Davis, for seasonal forecasting in the Shasta Lake Basin, California. The system is based on the Watershed Environmental Hydrology Hydro-Climate Modelling (WEHY-HCM) System which is a physically based modeling framework. It uses downscaled climate data from the Weather Research and Forecasting Model (WRF) to produce a 15-member ensemble of inflow forecasts. An ensemble of forecasts is produced monthly from January to June, providing forecasts from the month following the initialization through to July. The deterministic inflow forecasts are updated using seasonal exponential smoothing model. The inflow forecasts revealed that the ensembles of deterministic forecasts generally capture monthly inflow well. The statistical updating of these deterministic forecasts in the forecast year 2024 using the seasonal exponential smoothing model significantly improved the accuracy of monthly inflow forecasts further. This system demonstrates strong potential for seasonal inflow forecasting with substantial lead time and could greatly enhance informed water resource management in the Shasta Lake Basin.