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Skaggs, Richard

Publications and source records attributed to Skaggs, Richard.

Incorporating Climate Nonstationarity and Snowmelt Processes in Intensity–Duration–Frequency Analyses with Case Studies in Mountainous Areas

In this work, downscaled high-resolution climate simulations were used to provide inputs to the physics-based Distributed Hydrology Soil Vegetation Model (DHSVM), which accounts for the combined effects of snowmelt and rainfall processes, to determine spatially distributed available water for runoff (AWR). After quasi-stationary time windows were identified based on model outputs extracted for two different mountainous field sites in Colorado and California, intensity–duration–frequency (IDF) curves for precipitation and AWR were generated and evaluated at each numerical grid to provide guidance on hydrological infrastructure design. Impacts of snowmelt are found to be spatially variable due to spatial heterogeneity associated with topography according to geostatistical analyses. AWR extremes have stronger spatial continuity compared to precipitation. Snowmelt impacts on AWR are more pronounced at the wet California site than at the semiarid Colorado site. The sensitivities of AWR and precipitation IDFs to increasing greenhouse gas emissions are found to be localized and spatially variable. In subregions with significant snowfall, snowmelt can result in an AWR (e.g., 6-h 100-yr events) that is 70% higher than precipitation. For comparison, future greenhouse gas emissions may increase 6-h 100-yr precipitation and AWR by up to 50% and 80%, respectively, toward the end of this century.

54 ENVIRONMENTAL SCIENCES↗

Next-Generation Intensity–Duration–Frequency Curves to Reduce Errors in Peak Flood Design

Precipitation-based intensity–duration–frequency (PREC-IDF) curves are a standard tool used to derive design floods for hydraulic infrastructure worldwide. In snow-dominated regions where a large percentage of flood events are caused by snowmelt and rain-on-snow events, the PREC-IDF design approach can lead to substantial underestimation or overestimation of design floods and associated infrastructure. In this study, next-generation IDF (NG-IDF) curves, which characterize the actual water reaching the land surface, are introduced into the design process to improve hydrologic design. The authors compared peak design flood estimates from the National Resource Conservation Service TR-55 hydrologic model driven by NG-IDF and PREC-IDF curves at 399 Snowpack Telemetry (SNOTEL) stations across the western United States, all of which had at least 30 years of high-quality records. They found that about 70% of the stations in the western United States showed the potential for underdesign, for which the PREC-IDF curves underestimated peak design floods by as much as 324%. These results demonstrated the need to update the use of PREC-IDF curves to the use of NG-IDF curves for hydrologic design in snow-dominated regions.

Yan, Hongxiang↗

Regional Snow Parameters Estimation for Large-Domain Hydrological Applications in the Western United States

In snow-dominated regions, a critical source of uncertainty in hydrologic prediction and forecasting is the magnitude and distribution of snow water equivalent (SWE). With ensemble simulations, we demonstrate 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 indicate 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.

58 GEOSCIENCES↗

Enhancing Hydrologic Design by Next-Generation Intensity-Duration-Frequency Curves Considering Snowmelt and Climate Nonstationarity

Precipitation intensity-duration-frequency (PREC-IDF) curves are a standard tool to derive design floods for hydraulic infrastructure design worldwide. In snow-dominated regions where a large percentage of flood events are caused by snowmelt and rain-on-snow events, precipitation alone can be a poor predictor of flood risk. Meanwhile, anthropogenic climate change is expected to intensify hydrological cycle and alter hydrologic extremes, potentially increasing the likelihood of infrastructure failure in their design life period. To enhance future hydrologic design, we propose the next-generation IDF (NG-IDF) curves with consideration of both snow process and climate nonstationarity. The NG-IDF curves, which characterize the actual water reaching the land surface (melt + rain), use of the concept of “water available for runoff” rather than “rainfall” for hydrologic design. This paper shows that in the mountainous regions of the western United States, the standard PREC-IDF curves without considering snow process can substantially underestimate the input water intensities and the consequent peak design floods (i.e., the PREC-IDF curves may lead to underestimation of peak design flood by as much as 324%). Under a warming climate, we also observe statistically significant declining trends in both snowpack mass and extreme water available for runoff across the mountainous regions of the western United States from 1979 to 2017, confirming the proclamation that “stationarity is dead” and demonstrating the need to develop nonstationary NG-IDF curves for future hydrologic design.

Yan, Hongxiang↗