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Surface water storage and fluxes in rivers, lakes, reservoirs and wetlands are currently poorly observed at the global scale, even though they represent major components of the water cycle and deeply impact human societies. In situ networks are heterogeneously distributed in space, and many river basins and most lakes—especially in the developing world and in sparsely populated regions—remain unmonitored. Satellite remote sensing has provided useful complementary observations, but no past or current satellite mission has yet been specifically designed to observe, at the global scale, surface water storage change and fluxes. This is the purpose of the planned Surface Water and Ocean Topography (SWOT) satellite mission. SWOT is a collaboration between the (US) National Aeronautics and Space Administration, Centre National d’Études Spatiales (the French Spatial Agency), the Canadian Space Agency and the United Kingdom Space Agency, with launch planned in late 2020. SWOT is both a continental hydrology and oceanography mission. However, only the hydrology capabilities of SWOT are discussed here. After a description of the SWOT mission requirements and measurement capabilities, we review the SWOT-related studies concerning land hydrology published to date. Beginning in 2007, studies demonstrated the benefits of SWOT data for river hydrology, both through discharge estimation directly from SWOT measurements and through assimilation of SWOT data into hydrodynamic and hydrology models. A smaller number of studies have also addressed methods for computation of lake and reservoir storage change or have quantified improvements expected from SWOT compared with current knowledge of lake water storage variability. We also briefly review other land hydrology capabilities of SWOT, including those related to transboundary river basins, human water withdrawals and wetland environments. Finally, we discuss additional studies needed before and after the launch of the mission, along with perspectives on a potential successor to SWOT.

Flash drought refers to relatively short periods of warm surface temperature and anomalously low and rapid decreasing soil moisture (SM). Based on the physical mechanisms associated with flash droughts, these events are classified into two categories: heat wave and precipitation P deficit flash droughts. In previous work, the authors have defined heat wave flash droughts as resulting from the confluence of severe warm air temperature T air, which increases evapotranspiration (ET), and anomalously low and decreasing SM. Here, a second type of flash drought caused by precipitation deficits is explored. The authors term these events P-deficit flash droughts, which they associate with lack of P. Precipitation deficits cause ET to decrease and temperature to increase. The P-deficit flash droughts are analyzed based on observations of P, T air, and SM and ET reconstructed using land surface models for the period 1916–2013. The authors find that P-deficit flash droughts are more common than heat wave flash droughts. They are about twice as likely to occur as heat wave flash droughts over the conterminous United States. They are most prevalent over the southern United States with maxima over the southern Great Plains and the Southwest, in contrast to heat wave flash droughts that are mostly likely to occur over the Midwest and the Pacific Northwest, where the vegetation cover is dense.

We studied 34 global reservoirs for which good quality surface elevation data could be obtained from a combination of five satellite altimeters for the period from 1992 to 2010. For each of these reservoirs, we used an unsupervised classification approach using the Moderate Resolution Imaging Spectroradiometer (MODIS) 16‐day 250 m vegetation product to estimate the surface water areas over the MODIS period of record (2000 to 2010). We then derived elevation‐area relationships for each of the reservoirs by combining the MODIS‐based estimates with satellite altimeter‐based estimates of reservoir water elevations. Through a combination of direct observations of elevation and surface area along with documented reservoir configurations at capacity, we estimated storage time histories for each reservoir from 1992 to 2010. We evaluated these satellite‐based data products in comparison with gauge observations for the five largest reservoirs in the United States (Lakes Mead, Powell, Sakakawea, Oahe, and Fort Peck Reservoir). The storage estimates were highly correlated with observations (R = 0.92 to 0.99), with values for the normalized root mean square error (NRMSE) ranging from 3% to 15%. The storage mean absolute error (expressed as a percentage of reservoir capacity) for the reservoirs in this study was 4%. The multidecadal reconstructed reservoir storage variations are in accordance with known droughts and high flow periods on each of the five continents represented in the data set. Key Points Global monitoring of large reservoir storage from satellite remote sensing Data products were validated by gage observations Storage variations are in accord with known droughts and high flow periods

Climate extremes have profound implications for urban infrastructure and human society, but studies of observed changes in climate extremes over the global urban areas are few, even though more than half of the global population now resides in urban areas. Here, using observed station data for 217 urban areas across the globe, we show that these urban areas have experienced significant increases (p-value <0.05) in the number of heat waves during the period 1973-2012, while the frequency of cold waves has declined. Almost half of the urban areas experienced significant increases in the number of extreme hot days, while almost 2 3 showed significant increases in the frequency of extreme hot nights. Extreme windy days declined substantially during the last four decades with statistically significant declines in about 60% in the urban areas. Significant increases (p-value <0.05) in the frequency of daily precipitation extremes and in annual maximum precipitation occurred at smaller fractions (17 and 10% respectively) of the total urban areas, with about half as many urban areas showing statistically significant downtrends as uptrends. Changes in temperature and wind extremes, estimated as the result of a 40 year linear trend, differed for urban and non-urban pairs, while changes in indices of extreme precipitation showed no clear differentiation for urban and selected non-urban stations.

Mountain snowpack stores a significant quantity of water in the western US, accumulating during the wet season and melting during the dry summers and supplying much of the water used for irrigated agriculture, and municipal and industrial uses. Updating our earlier work published in 2005, we find that with 14 additional years of data, over 90% of snow monitoring sites with long records across the western US now show declines, of which 33% are significant (vs. 5% expected by chance) and 2% are significant and positive (vs. 5% expected by chance). Declining trends are observed across all months, states, and climates, but are largest in spring, in the Pacific states, and in locations with mild winter climate. We corroborate and extend these observations using a gridded hydrology model, which also allows a robust estimate of total western snowpack and its decline. We find a large increase in the fraction of locations that posted decreasing trends, and averaged across the western US, the decline in average April 1 snow water equivalent since mid-century is roughly 15–30% or 25–50 km 3 , comparable in volume to the West’s largest man-made reservoir, Lake Mead. Dramatic declines in snowpack in the western US Mountain snowpack stores huge amounts of water in the western US, supplying much of the water used to grow crops. A team of researchers from Oregon State University and UCLA found that spring snowpack declined almost everywhere, especially in the coastal states and other locations with mild winter climate. (Skiers will be relieved that declines were smaller in winter.) Not surprisingly, the declines are mostly related to warming climate. Using a physically-based model of the hydrologic cycle, which takes daily weather as inputs and computes snow accumulation and melt, runoff, etc., the researchers computed the total snowpack in the western US. Total snowpack declined 15–30%, and the amount of that lost water is comparable in volume to the West’s largest man-made reservoir, Lake Mead. Many water managers are already planning for a future with less snow, but this research emphasizes that the future is here.

Summer streamflow variations strongly affect water supply reliability and ecological functioning of western U.S. (WUS) streams. Traditional snow‐based forecasts of summer streamflow are becoming less accurate with warming‐induced reductions in winter snow accumulation. This reflects a rising importance of competing runoff‐generating processes in controlling summer streamflow variations, primarily an increasing role of rainfall in contrast to snowmelt. Here, based on a snowmelt‐rainfall tracking algorithm applied to two hydrological models, we show that cool‐season rainfall provides an important volumetric contribution to summer streamflow for many WUS streams in the current climate, and this contribution will increase under climate warming, especially in years with warm snow droughts and abnormally dry summers. We also show that seasonal rainfall (warm‐/cool‐seasons) dominates the variability of summer streamflow across ∼70% area of WUS. We show that an increasing warm‐season rainfall contribution to summer streamflow (largely replacing snowmelt) results in reduced summer streamflow predictability. Plain Language Summary Summer streamflow is a critical water resource in the generally dry summers of the western U.S. (WUS), and is routinely forecasted using spring snowpack and/or winter total precipitation as primary predictors. However, climate warming leads to reduced snowpacks, exacerbates summer low flows, and reduces the accuracy of snow‐based summer streamflow forecasts. On the other hand, the role of winter rainfall as a control on summer streamflow increases in a warmer climate. Here, we explicitly quantify the contributions from cool‐season rainfall, warm‐season rainfall, and snowmelt to summer streamflow across the WUS, and how they change under a uniformly 1°C warmer climate. We show that the cool‐season rainfall contribution to summer streamflow increases under warming across WUS, especially in streams that currently have low‐to‐moderate snow contributions to runoff, and in years with anomalously warm winters and/or dry summers. We also show that the warm‐season rainfall contribution to summer streamflow increases widely, especially in the southern interior of WUS in a warmer climate, and that increasing warm‐season rainfall contribution to summer streamflow (largely replacing snowmelt) results in reduced summer streamflow predictability. Key Points The cool‐season rainfall contribution to summer streamflow is greatest in low‐elevation coastal streams with dry summers Climate warming leads to an increased contribution of seasonal rainfall to summer streamflow as spring snowmelt contributions decline Summer streamflow predictability declines with reduced snowmelt and increased warm‐season rainfall contribution in a warmer climate

Recent fire seasons have fueled intense speculation regarding the effect of anthropogenic climate change on wildfire in western North America and especially in California. During 1972–2018, California experienced a fivefold increase in annual burned area, mainly due to more than an eightfold increase in summer forest‐fire extent. Increased summer forest‐fire area very likely occurred due to increased atmospheric aridity caused by warming. Since the early 1970s, warm‐season days warmed by approximately 1.4 °C as part of a centennial warming trend, significantly increasing the atmospheric vapor pressure deficit (VPD). These trends are consistent with anthropogenic trends simulated by climate models. The response of summer forest‐fire area to VPD is exponential, meaning that warming has grown increasingly impactful. Robust interannual relationships between VPD and summer forest‐fire area strongly suggest that nearly all of the increase in summer forest‐fire area during 1972–2018 was driven by increased VPD. Climate change effects on summer wildfire were less evident in nonforested lands. In fall, wind events and delayed onset of winter precipitation are the dominant promoters of wildfire. While these variables did not change much over the past century, background warming and consequent fuel drying is increasingly enhancing the potential for large fall wildfires. Among the many processes important to California's diverse fire regimes, warming‐driven fuel drying is the clearest link between anthropogenic climate change and increased California wildfire activity to date. Plain Language Summary Since the early 1970s, California's annual wildfire extent increased fivefold, punctuated by extremely large and destructive wildfires in 2017 and 2018. This trend was mainly due to an eightfold increase in summertime forest‐fire area and was very likely driven by drying of fuels promoted by human‐induced warming. Warming effects were also apparent in the fall by enhancing the odds that fuels are dry when strong fall wind events occur. The ability of dry fuels to promote large fires is nonlinear, which has allowed warming to become increasingly impactful. Human‐caused warming has already significantly enhanced wildfire activity in California, particularly in the forests of the Sierra Nevada and North Coast, and will likely continue to do so in the coming decades. Key Points Annual burned area in California increased fivefold during 1972–2018, mainly due to summer forest fire Anthropogenic warming very likely increased summer forest fire by drying fuels; this trend is likely to continue Large fall fires are likely to become increasingly frequent with continued warming and possibly gradual declines in fall precipitation

This paper describes a publicly available, long-term (1915–2011), hydrologically consistent dataset for the conterminous United States, intended to aid in studies of water and energy exchanges at the land surface. These data are gridded at a spatial resolution of 1 16 0 latitude/longitude and are derived from daily temperature and precipitation observations from approximately 20 000 NOAA Cooperative Observer (COOP) stations. The available meteorological data include temperature, precipitation, and wind, as well as derived humidity and downwelling solar and infrared radiation estimated via algorithms that index these quantities to the daily mean temperature, temperature range, and precipitation, and disaggregate them to 3-hourly time steps. Furthermore, the authors employ the variable infiltration capacity (VIC) model to produce 3-hourly estimates of soil moisture, snow water equivalent, discharge, and surface heat fluxes. Relative to an earlier similar dataset by Maurer and others, the improved dataset has 1) extended the period of analysis (1915–2011 versus 1950–2000), 2) increased the spatial resolution from ⅛° to 1 16 0 , and 3) used an updated version of VIC. The previous dataset has been widely used in water and energy budget studies, climate change assessments, drought reconstructions, and for many other purposes. It is anticipated that the spatial refinement and temporal extension will be of interest to a wide cross section of the scientific community.

Climate warming threatens snowmelt‐derived water supplies in the western US (WUS) by reducing snowfall and snowmelt runoff, yet future rates of these declines remain highly uncertain in an evolving climate. Here, we analyze historical data, land surface model warming experiments, and climate projections across three major WUS river basins. We find that runoff loss become less sensitive to warming as snowpack shrinks, stemming from reduced snowmelt‐radiation feedback, a consequence of smaller snow‐cover changes and shifts in snowmelt timing to lower‐energy periods. Near‐linear projected warming with time (IPCC SSP245) exhibit a stable, possibly decelerating decline in runoff ratios. Although decelerating runoff declines do not eliminate broader water‐management challenges under continued warming, our findings complement the view that snowmelt‐radiation feedback drives runoff decline by highlighting the negative feedback from a shrinking snowpack on runoff warming sensitivity. Our findings should facilitate more comprehensive future water supply assessments in snow‐affected regions. Plain Language Summary Studying runoff sensitivity to warming helps us understand how water availability will change as global temperatures rise. Current understanding of runoff sensitivity mainly relies on long‐term static quantifications, which may overlook evolving sensitivities and future uncertainties. Our study shows that as snow‐cover shrinks in a warming world, runoff becomes less sensitive to further temperature increases. Specifically, in warmer conditions, snowmelt shifts to colder months with less sunlight, reducing the energy available for evaporation, while diminished snow cover limits albedo changes and further lowers energy absorption. These combined effects reduce (further) runoff declines, revealing a negative feedback that challenges static theories that predicting a constant acceleration of runoff loss with warming. Our findings highlight this nonlinearity, offering a more realistic and comprehensive view of water supply uncertainty in snow‐affected regions as the climate warms. Key Points Sensitivities of runoff, snow, and evapotranspiration to warming decrease as temperatures warm for three major western US river basins Responses of runoff loss to warming are generally weaker in subbasins with less snow Decelerated snow cover shrinkage and earlier melt timing weaken snowmelt‐radiation feedback, decreasing runoff sensitivity to warming