Incorporating Climate Nonstationarity and Snowmelt Processes in Intensity–Duration–Frequency Analyses with Case Studies in Mountainous Areas
Abstract
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.
- Authors:
-
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Publication Date:
- Research Org.:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE; USDOD
- OSTI Identifier:
- 1580112
- Report Number(s):
- PNNL-SA-132327
Journal ID: ISSN 1525-755X
- Grant/Contract Number:
- AC05-76RL01830; RC-2546
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Hydrometeorology
- Additional Journal Information:
- Journal Volume: 20; Journal Issue: 12; Journal ID: ISSN 1525-755X
- Publisher:
- American Meteorological Society
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; Climate change; Snow cover; Statistical techniques; Time series; Regional models; Trends
Citation Formats
Hou, Zhangshuan, Ren, Huiying, Sun, Ning, Wigmosta, Mark S., Liu, Ying, Leung, Lai-Yung Ruby, Yan, Hongxiang, Skaggs, Richard, and Coleman, Andre. Incorporating Climate Nonstationarity and Snowmelt Processes in Intensity–Duration–Frequency Analyses with Case Studies in Mountainous Areas. United States: N. p., 2019.
Web. doi:10.1175/jhm-d-19-0055.1.
Hou, Zhangshuan, Ren, Huiying, Sun, Ning, Wigmosta, Mark S., Liu, Ying, Leung, Lai-Yung Ruby, Yan, Hongxiang, Skaggs, Richard, & Coleman, Andre. Incorporating Climate Nonstationarity and Snowmelt Processes in Intensity–Duration–Frequency Analyses with Case Studies in Mountainous Areas. United States. https://doi.org/10.1175/jhm-d-19-0055.1
Hou, Zhangshuan, Ren, Huiying, Sun, Ning, Wigmosta, Mark S., Liu, Ying, Leung, Lai-Yung Ruby, Yan, Hongxiang, Skaggs, Richard, and Coleman, Andre. Tue .
"Incorporating Climate Nonstationarity and Snowmelt Processes in Intensity–Duration–Frequency Analyses with Case Studies in Mountainous Areas". United States. https://doi.org/10.1175/jhm-d-19-0055.1. https://www.osti.gov/servlets/purl/1580112.
@article{osti_1580112,
title = {Incorporating Climate Nonstationarity and Snowmelt Processes in Intensity–Duration–Frequency Analyses with Case Studies in Mountainous Areas},
author = {Hou, Zhangshuan and Ren, Huiying and Sun, Ning and Wigmosta, Mark S. and Liu, Ying and Leung, Lai-Yung Ruby and Yan, Hongxiang and Skaggs, Richard and Coleman, Andre},
abstractNote = {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.},
doi = {10.1175/jhm-d-19-0055.1},
journal = {Journal of Hydrometeorology},
number = 12,
volume = 20,
place = {United States},
year = {Tue Dec 10 00:00:00 EST 2019},
month = {Tue Dec 10 00:00:00 EST 2019}
}
Web of Science
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