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Interannual changes in low, median, and high regimes of streamflow have important implications for flood control, irrigation, and ecologic and human health. The Gravity Recovery and Climate Experiment (GRACE) satellites record global terrestrial water storage anomalies (TWSA), providing an opportunity to observe, interpret, and potentially utilize the complex relationships between storage and full-flow-regime streamflow. Here we show that utilizable storage-streamflow correlations exist throughout vastly different climates in the continental US (CONUS) across low- to high-flow regimes. A panoramic framework, the storage-streamflow correlation spectrum (SSCS), is proposed to examine macroscopic gradients in these relationships. SSCS helps form, corroborate or reject hypotheses about basin hydrologic behaviors. SSCS patterns vary greatly over CONUS with climate, land surface, and geologic conditions. Data mining analysis suggests that for catchments with hydrologic settings that favor storage over runoff, e.g., a large fraction of precipitation as snow, thick and highly-permeable permeable soil, SSCS values tend to be high. Based on our results, we form the hypotheses that groundwater flow dominates streamflows in Southeastern CONUS and Great Plains, while thin soils in a belt along the Appalachian Plateau impose alimit on water storage. SSCS also suggests shallow water table caused by high-bulk density soil and flat terrain induces rapid runoff in several regions. Our results highlight the importance of subsurface properties and groundwater flow in capturing flood and drought. We propose that SSCS can be used as a fundamental hydrologic signature to constrain models and to provide insights thatlead usto better understand hydrologic functioning.

Plain Language Summary: Water storage on land is the sum of surface water, soil moisture, and groundwater. Rainfall can partition into direct runoff and infiltration into the ground. The direction runoff part leaves no signal in water storage, while the part that infiltrates and exfiltrates does. By looking at the correlations between storage and streamflow and combining it with other information, we can infer a great deal about how a basin partitions and processes precipitation. With the GRACE satellites, which measure water storage on land, we now have the opportunity to observe, interpret and possibly utilize storage-streamflow relationships. We propose a novel framework, the storage-streamflow correlation spectrum (SSCS), to synthesize these relationships. SSCS patterns present important clues about hydrology, e.g., storage on the Appalachian Plateau is limited by thin soils, compacted soils in northern Ohio lead to shallow water table that limits storage, and northern Great Plains and Southeast Atlantic regions are groundwater-dominated. SSCS provides a new observation dimension to understanding hydrology. In addition, it points out key dynamics for models to capture to predict streamflow accurately.