Summer streamflow is an important water resource during the dry summers in the western United States, but the sensitivity of summer minimum streamflow (low flow) to antecedent winter precipitation as compared with summer evaporative demand has not been quantified for the region. We estimate climatic elasticity of low flow (percent change in low flow divided by percent change in climatic forcing variable) with respect to annual maximum snow water equivalent (ESWE), winter precipitation (EPPT), and summer potential evapotranspiration (EPET) for 110 unmanaged headwater catchments in the maritime western U.S. mountains. We find that |EPET| is larger than |EPPT| and |ESWE| in every catchment studied and is 4–5 times larger than both, on average. Spatial variations in E are dominated by three patterns. First, |EPPT|, |ESWE|, and |EPET| are largest and most variable among semiarid catchments and decrease nonlinearly with increasing values of the humidity index (the ratio of annual precipitation to annual evaporative demand). Second, |EPPT| and |EPET| are lower in snow‐dominated catchments than in rain‐dominated catchments, suggesting that snow cover reduces the proportional response of low flows to climatic variability. Third, |EPPT|, |ESWE|, and |EPET| are lower in slow‐draining catchments than in fast‐draining catchments, for which baseflow recession storage coefficients are used to represent the rate at which catchment water storage is translated into streamflow. Our results provide the first comparison of summer low‐flow elasticity to PPT versus PET and its spatial variation in the maritime western U.S. mountains.

River discharge estimation requires knowledge of bathymetry. However, aside from a few locations where surveys have been conducted, bathymetric data are unavailable, even for major rivers. It has been suggested that water surface elevation and flow width measurements from the upcoming Surface Water and Ocean Topography (SWOT) satellite mission (planned launch 2021) may be used to infer the submerged channel geometry; however, the full potential of these measurements for inferring bathymetry has yet to be explored. We apply four different techniques, with varying assumptions about height‐width relationships, to predict unknown bathymetry. We call these “curve‐fitting methods” the linear, slope break, nonlinear, and nonlinear slope break (NLSB) methods. The linear and slope break methods are based on a linear height‐width relationship, while the nonlinear and NLSB methods are based on a height‐width relationship derived from hydraulic geometry equations. We generate SWOT‐like observations of height and width based on 5‐m gridded Upper Mississippi River data and evaluate the performance of each curve‐fitting method given the SWOT‐like observations. The NLSB method predicts bed elevation and low flow area with the least error, although the nonlinear method may be preferred in low data conditions. Additionally, we show that our method outperforms previously suggested methods, and we propose an NLSB‐based bathymetry prior for Bayesian discharge estimation algorithms.

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Hydrologic models predict the spatial and temporal distribution of water and energy at the land surface. Currently, parameter availability limits global-scale hydrologic modelling to very coarse resolution, hindering researchers from resolving fine-scale variability. With the aim of addressing this problem, we present a set of globally consistent soil and vegetation parameters for the Variable Infiltration Capacity (VIC) model at 1/16° resolution (approximately 6 km at the equator), with spatial coverage from 60°S to 85°N. Soil parameters derived from interpolated soil profiles and vegetation parameters estimated from space-based MODIS measurements have been compiled into input files for both the Classic and Image drivers of the VIC model, version 5. Geographical subsetting codes are provided, as well. Our dataset provides all necessary land surface parameters to run the VIC model at regional to global scale. We evaluate VICGlobal’s ability to simulate the water balance in the Upper Colorado River basin and 12 smaller basins in the CONUS, and their ability to simulate the radiation budget at six SURFRAD stations in the CONUS.

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