Exploring spatiotemporal relations between soil moisture, precipitation, and stream flow for a large set of watersheds in the Contiguous United States.

An understanding of streamflow variability and its response to changes in climate condition is essential for water resource planning and management. This study investigated the relationship between precipitation, soil moisture, and streamflow over a wide range of watershed classes across the United States. Principal component analysis (PCA) and hierarchical clustering were applied to classify the 601 watersheds into six categories based on their long-term climate and physiographic characteristics. Our results indicated the presence of strong periodicity in the soil moisture and streamflow compared to the precipitation over most of the watershed classes. Use of the rank correlation and the wavelet coherence analysis revealed a strong relationship between rainfall, soil moisture, and streamflow. Soil moisture was found to have a higher association with the streamflow relative to precipitation. Results indicated a different strength of the association depends on the watershed classes. Watershed class with higher precipitation and runoff ratio showed higher coherence between rainfall, soil moisture, and streamflow. Besides, a watershed with steep topography showed a weaker association between soil moisture and streamflow. Wavelet analysis showed a higher association between soil moisture and streamflow in the longer time scale compare to short time scale. The findings of this study contribute to growing understanding of the complicated relationship between soil moisture, precipitation and streamflow and could be considered in the examination of streamflow response to changes in climate condition as well as better streamflow modeling and forecasting.