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Microwave brightness temperature observations from the NASA Soil Moisture Active Passive (SMAP) mission and gauge‐based precipitation data over the United States are used to reconstruct the soil water loss function and then historical (1979–2019) hydrological fluxes in the form of evapotranspiration (ET) and drainage (D) are quantified. Over the period of study, with the exception of snowy and hyper‐arid regions, we observe a correlation of R2 > 0.6 between SMAP‐precipitation derived drainage estimates and streamflow measurements from the U.S. Geological Survey (USGS). There is a bias between estimated drainage and USGS streamflow with an underestimation of about 1 mm day−1 in southwest United States to 3 mm day−1 in parts of the eastern United States. SMAP‐derived sensitivities of drainage and ET partitioning with respect to precipitation anomalies are also calculated. In parts of the Great Plains the drainage partitioning exhibits a near‐linear response, while in the southeast United States, the response is nonlinear. Partitioning also is examined for 6 four‐digit hydrologic unit basins wherein year‐to‐year variations in drainage partitioning are shown to be key mediators in translating precipitation anomalies into streamflow anomalies. Observation‐driven drainage and ET estimates are obtained without relying on full hydrologic and Land Surface Models (LSMs). This independence (isolation from model parameterization assumptions) provides a path toward using satellite‐derived landscape hydrological diagnostics to assess hydrologic models and LSMs as well as to guide their further development. Key Points: A large amount of hydrologic information is encoded within satellite remote sensing observations of soil moistureSMAP‐era soil moisture and precipitation information, without reliance on models, can characterize landscape hydrological partitioningHistorical remote sensing and precipitation‐based drainage estimates closely track streamflow measurements across the United States [ABSTRACT FROM AUTHOR]

The Northern Great Plains (NGP) experienced a transition from a long drought cycle to a deluge cycle in the late 1900s. Embedded within this long‐term transition were shorter‐term decadal‐scale dry and wet periods. A recent NGP drought (1999–2004) was followed in 2005 by a wet period that continues to present day. However, how surface hydrology in a northern glaciated landscape responds to increased precipitation is poorly understood and a physically based modeling framework is needed to clarify the underlying processes. This study utilizes a physically based hydrologic model to investigate the impacts of increased precipitation on the water budget by examining its partition into intermediate processes from 2004–2017 in the Mauvais Coulee Basin (MCB). The MCB model evaluations against snow observations (2016–2017) and outlet streamflow observations (2004–2017) imply strong model performance. Simulated snow exhibits high spatiotemporal variation due to variability in precipitation, snow redistribution from stubble fields to wooded areas, and snow accumulation in small depressions. Our modeling results identify two major phases (before and after 2011) exhibiting different hydrologic responses. The period before 2011 is dominated by streamflow and evapotranspiration (ET), while extreme ET dominance is observed after 2011. This switch is due to climatic conditions involving changes in the vapor density difference and depressional and subsurface storage by intermediate processes. A clear contrast in the prewinter soil moisture‐streamflow relationship between before and after 2011 is reported. Our findings help illuminate the important influences of increased precipitation upon the intermediate processes in controlling streamflow in a northern glaciated prairie landscape. Key Points: A physically‐based model is used to investigate mechanisms of hydrologic change to recent wetting in a cold region agricultural basinDuring recent wetting, the hydrological system transitioned from a moderate ET‐controlled to an extreme ET‐dominated regimeInterannual streamflow variations are due to complex interaction of peak SWE, fall soil moisture, frozen soil conditions, and rain on snow [ABSTRACT FROM AUTHOR]

Sandbars are ubiquitous in sandy‐braided rivers throughout the world. In the Great Plains of the United States, recovery and expansion of emergent sandbar habitat (ESH) has been a priority in lowland rivers where the natural extent of sandbars has been degraded. Recovery efforts are aimed at protection of populations of the interior least tern (Sterna antillarum) and piping plover (Charadrius melodus). But quantitative observations of deposition and erosion dynamics of populations of sandbars across long segments of rivers are rare. We present a three‐part case study which used Bayesian regression models to examine relations between hydrology, channel morphology, and ESH responses in the Platte River, eastern Nebraska. Logistic regression indicates presence of ESH is positively related to the Parker, (1976) stability criterion and a gradient in sediment transport mode, and negatively related to presence of vegetation. Hierarchical linear regression modeling shows direct coupling between sandbar top‐surface height and formative flood magnitude, but the gap between formative flood stage and sandbar top‐surface increases with increasing discharge. Finally, linear regression modeling of sandbar erosion demonstrates rates of ESH erosion are on the order of 10−1 ha/day during high‐flow periods and 10−2 during low‐flow periods, but sandbar persistence is largely a function of sandbar starting size. The collective observations highlight the importance of large floods (>3‐year recurrence) in creating very large sandbars that persist as high‐quality ESH over periods of years whereas lower‐magnitude, more‐frequent flood events create lower‐quality ESH that typically does not persist into the following nesting season. Key Points: Potential to deposit emergent sandbars is a positive function of Parker (1976) stability criteria and a gradient in sediment transport modeEmergent sandbar top‐surface height grows linearly with formative flood magnitude at a rate that lags growth of formative flood stageEmergent sandbar persistence is largely dependent on sandbar starting size, which itself is dependent on formative flood magnitude [ABSTRACT FROM AUTHOR]