Watershed‐Scale Effective Hydraulic Properties of the Continental United States. (15th June 2021) - Tashie, Arik; Pavelsky, Tamlin; Band, Lawrence; Topp, Simon
Abstract: In land surface models (LSMs), the hydraulic properties of the subsurface are commonly estimated according to the texture of soils at the Earth's surface. This approach ignores macropores, fracture flow, heterogeneity, and the effects of variable distribution of water in the subsurface on effective watershed‐scale hydraulic variables. Using hydrograph recession analysis, we empirically constrain estimates of watershed‐scale effective hydraulic conductivities ( K ) and effective drainable aquifer storages ( S ) of all reference watersheds in the conterminous United States for which sufficient streamflow data are available ( n  = 1, 561). Then, we use machine learning methods to model these properties across the entire conterminous United States. Model validation results in high confidence for estimates of log( K ) ( r 2  > 0.89; 1% < bias < 9%) and reasonable confidence for S ( r 2  > 0.83; −70% < bias < −18%). Our estimates of effective K are, on average, two orders of magnitude higher than comparable soil‐texture‐based estimates of average K, confirming the importance of soil structure and preferential flow pathways at the watershed scale. Our estimates of effective S compare favorably with recent global estimates of mobile groundwater and are spatially heterogeneous (5–3, 355 mm). Because estimates of S are much lower than the global maximums generally used in LSMs (e.g., 5, 000 mm in Noah‐MP), they may serve both to limit model spin‐up time and to constrain model parameters to more realistic values. These results represent the first attempt to constrain estimates of watershed‐scale effective hydraulic variables that are necessary for the implementation of LSMs for the entire conterminous United States. Plain Language Summary: Modeling the flow of water out of the ground and into streams requires extensive data that describe the hydraulic properties of the ground, including how much water is available to support streamflow (i.e., the volume of mobile groundwater) and how quickly that water may flow through the materials where it is stored (i.e., effective hydraulic conductivity). Currently, most large‐scale numerical models derive estimates of these properties from maps of soil types. These methods are known to be prone to error in many landscapes where bedrock fractures or biological activity (e.g., earthworm tunnels or rotted tree roots) are common, as these structural features may alter the effective properties of the subsurface by several orders of magnitude. To address these shortfalls, we provide empirical estimates of these properties through analysis of historical streamflow and make these data available at the continental scale for the first time. Key Points: Provide empirical estimates of watershed‐scale effective hydraulic variables for the continental United States for the first time Watershed‐scale effective hydraulic conductivities are order(s) of magnitude higher than soil‐texture‐based estimates of average hydraulic conductivities Maximum drainable storage volumes may be used to realistically constrain models and reduce model spin‐up time