Potential Predictability of Streamflow and Soil Moisture in a Humid Alabama-Coosa-Tallapoosa River Basin using the National Water Model
Type of DegreeMaster's Thesis
Forestry and Wildlife Science
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This study investigates predictability of daily streamflow and soil moisture in the Alabama-Coosa-Tallapoosa (ACT) river basin in southeastern United States. The study employs the state-of-the-art National Water Model (NWM), and compares and contrasts effects of initial soil moisture condition with that of seasonal climate forecast on streamflow and the soil moisture forecasts skill. We had designed and implemented seasonal streamflow forecast ensemble experiments following the methodology suggested by Dirmeyer et al. (2013). The study also compares the soil moisture variability in the NWM with the in-situ observations and remote sensing data from the Soil Moisture Active and Passive (SMAP) satellite. The NWM skillfully simulates the observed streamflow in the ACT basin from 1990 to 2018. The soil moisture variability is 46% smaller in the NWM compared with the SMAP data, mainly due to a weaker amplitude of seasonal cycle in the NWM. This study finds that initial soil moisture condition is a major source of predictability for the seasonal streamflow forecast. Contribution of the initial soil moisture condition is comparable or even higher than that of seasonal climate anomalies effects in the dry seasons. Specifically, in the boreal summer season, the initial soil moisture condition contributes to 65%, and 48% improvements in the seasonal streamflow, and soil moisture forecast skill, respectively. This study attributes a higher improvement in the streamflow forecast skill to the lag effects between the soil moisture and streamflow anomalies. Results of this study can inform development and improvement of the operational streamflow forecasting system.