There is a renewed focus on the design of infrastructure resilient to extreme hydrometeorological events. While precipitation‐based intensity‐duration‐frequency (IDF) curves are commonly used as part of infrastructure design, a large percentage of peak runoff events in snow‐dominated regions are caused by snowmelt, particularly during rain‐on‐snow (ROS) events. In these regions, precipitation‐based IDF curves may lead to substantial overestimation/underestimation of design basis events and subsequent overdesign/underdesign of infrastructure. To overcome this deficiency, we proposed next‐generation IDF (NG‐IDF) curves, which characterize the actual water reaching the land surface. We compared NG‐IDF curves to standard precipitation‐based IDF curves for estimates of extreme events at 376 Snowpack Telemetry (SNOTEL) stations across the western United States that each had at least 30 years of high‐quality records. We found standard precipitation‐based IDF curves at 45% of the stations were subject to underdesign, many with significant underestimation of 100 year extreme events, for which the precipitation‐based IDF curves can underestimate water potentially available for runoff by as much as 125% due to snowmelt and ROS events. The regions with the greatest potential for underdesign were in the Pacific Northwest, the Sierra Nevada Mountains, and the Middle and Southern Rockies. We also found the potential for overdesign at 20% of the stations, primarily in the Middle Rockies and Arizona mountains. These results demonstrate the need to consider snow processes in the development of IDF curves, and they suggest use of the more robust NG‐IDF curves for hydrologic design in snow‐dominated environments.

Abstract:Stream temperatures in urban watersheds are influenced to a high degree by changes in landscape and climate, which can occur at small temporal and spatial scales. Here, we describe a modelling system that integrates the distributed hydrologic soil vegetation model with the semi-Lagrangian stream temperature model RBM. It has the capability to simulate spatially distributed hydrology and water temperature over the entire network at high time and space resolutions, as well as to represent riparian shading effects on stream temperatures. We demonstrate the modelling system through application to the Mercer Creek watershed, a small urban catchment near Bellevue, Washington. The results suggest that the model was able to produce realistic streamflow and water temperature predictions that are consistent with observations. We use the modelling construct to characterize impacts of land use change and near-stream vegetation change on stream temperatures and explore the sensitivity of stream temperature to changes in land use and riparian vegetation. The results suggest that, notwithstanding general warming as a result of climate change over the last century, there have been concurrent increases in low flows as a result of urbanization and deforestation, which more or less offset the effects of a warmer climate on stream temperatures. On the other hand, loss of riparian vegetation plays a more important role in modulating water temperatures, in particular, on annual maximum temperature (around 4°C), which could be mostly reversed by restoring riparian vegetation in a fairly narrow corridor -a finding that has important implications for management of the riparian corridor.

In snow‐dominated regions, a key source of uncertainty in hydrologic prediction and forecasting is the magnitude and distribution of snow water equivalent (SWE). With ensemble simulations, this work demonstrates that SWE variability across the mountain ranges of the western United States (represented by 246 Snow Telemetry stations) can largely be captured at the daily time scale by a simple mass and energy‐balance snow model with four physically reasonable parameters—three snow albedo parameters and one snow temperature threshold for precipitation partitioning. The model skill is lower in the maritime Pacific Northwest where SWE variability is more sensitive to errors associated with simulated energy balance (e.g., downward radiation fluxes) and the temperature‐only precipitation partitioning approach. Poor model skill in high‐altitude, windy locations in the Northern Rockies can be attributed to precipitation undercatch and underrepresented wind processes. For the purpose of large‐domain hydrologic applications, regional snow parameters were developed for eight ecoregions characterized by a distinct hydroclimatic regime across the western United States. Results suggest that regionally coherent snow parameterizations are able to capture daily variations in SWE at most Snow Telemetry stations, suggesting that areas with a similar hydroclimate share a similar snow regime. While the three albedo parameters show limited spatial variability across all regions, the regional snow temperature threshold (Ts) shows marked spatial variation correlated with relative humidity; the Ts values increase from 0.2 °C in the higher‐humidity Pacific Northwest to 4.0 °C in the colder, lower‐humidity Rocky Mountains.

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Many plot‐scale studies have shown that snow‐cover dynamics in forest gaps are distinctly different from those in open and continuously forested areas, and forest gaps have the potential to alter the magnitude and timing of snowmelt. However, the watershed‐level impacts of canopy gap treatment on streamflows are largely unknown. Here, we present the first research that explicitly assesses the impact of canopy gaps on seasonal streamflows and particularly late‐season low flows at the watershed scale. To explicitly model forest–snow interactions in canopy gaps, we made major enhancements to a widely used distributed hydrologic model, distributed hydrology soil vegetation model, with a canopy gap component that represents physical processes of snowpack evolution in the forest gap separately from the surrounding forest on the subgrid scale (within a grid typically 10–150 m). The model predicted snow water equivalent using the enhanced distributed hydrology soil vegetation model showed good agreement (R2 > 0.9) with subhourly snow water equivalent measurements collected from open, forested, and canopy gap sites in Idaho, USA. Compared with the original model that does not account for interactions between gaps and surrounding forest, the enhanced model predicted notably later melt in small‐ to medium‐size canopy gaps (the ratio of gap radius (r) to canopy height (h) ≤ 1.2), and snow melt rates exhibited great sensitivity to changing gap size in medium‐size gaps (0.5 ≤ r/h ≤ 1.2). We demonstrated the watershed‐scale implications of canopy gaps on streamflow in the snow‐dominated Chiwawa watershed, WA, USA. With 24% of the watershed drainage area (about 446 km2) converted to gaps of 60 m diameter, the mean annual 7‐day low flow was increased by 19.4% (i.e., 0.37 m3/s), and the mean monthly 7‐day low flows were increased by 13.5% (i.e., 0.26 m3/s) to 40% (i.e., 1.76 m3/s) from late summer through fall. Lastly, in practical implementation of canopy gaps with the same total gap areas, a greater number of distributed small gaps can have greater potential for longer snow retention than a smaller number of large gaps.

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This paper presents the first study to identity, in historical records, regional changes in the mechanisms of extreme water available for runoff (W). We used a quality‐controlled Snowpack Telemetry data set (1979–2017) combined with the nonparametric regional Kendall test to examine changes in annual maximum W under four hydrometeorological conditions (melt only/rain‐on‐snow/all melt/all melt plus rainfall) over the mountainous regions of the western United States. Under a warming climate, our analyses indicated significant declining trends in annual maximum W at regional scale under all four conditions. The annual maximum of all melt plus rainfall decreased significantly by 15% in the southwestern United States, while the frequency of rain‐on‐snow events increased significantly by 32% in the northwestern United States. The annual maximum snowmelt only decreased significantly by 21% across the entire western United States. Our results confirmed that interaction between regional humidity and solar radiation with warming temperature helps drive these changes.

Precipitation extremes are projected to become more frequent along the U.S. West Coast due to increased atmospheric river (AR) activity, but the frequency of less intense precipitation events may decrease. Antecedent soil moisture (ASM) conditions can have a large impact on flood responses, especially if prestorm precipitation decreases. Taken together with increased antecedent evaporative demand due to warming, this would result in reduced soil moisture at the onset of extreme precipitation events. We examine the impact of ASM on AR-related floods in a warming climate in three basins that form a transect along the U.S. Pacific Coast: the Chehalis River basin in Washington, the Russian River basin in Northern California, and the Santa Margarita River basin in Southern California. We ran the Distributed Hydrology Soil Vegetation Model (DHSVM) over the three river basins using forcings downscaled from 10 global climate models (GCMs). We examined the dynamic role of ASM by comparing the changes in the largest 50, 100, and 150 extreme events in two periods, 1951–2000 and 2050–99. In the Chehalis basin, the projected fraction of AR-related extreme discharge events slightly decreases. In the Russian basin, this fraction increases, however, and more substantially so in the Santa Margarita basin. This is due to increases in AR-related extreme precipitation events, as well as the fact that the relationship of extreme precipitation to extreme discharge is strengthened by projected increases in year-to-year volatility of annual precipitation in California, which increases the likelihood of concurrent occurrence of large storms and wet ASM conditions.