Climate Modeling to Support Urban Water Management in the Wasatch Range

Presenter Information

Courtenay Strong

Location

ECC 216

Event Website

http://water.usu.edu/

Start Date

4-4-2012 1:30 PM

End Date

4-4-2012 12:50 PM

Description

Urban water management involves providing water supply, stormwater drainage control, and wastewater management in cities. In the metropolitan areas along the Wasatch Front metropolitan areas area faced with numerous urban water management challenges and climate is a factor in most cases. This is similar to most other metropolitan areas in the world. However, along the Wasatch Front and elsewhere, due to many factors those responsible for urban water management have yet to embrace climate information in the management of water resources. As part of the Cyberinfrastructure to Advance High Performance Water Resource Modeling (CI-WATER) project, we are developing software tools to bridge the computationally expensive gap between global climate models (~100-km spatial scale) and urban water resource models (scale). We are also developing analysis capacity and data resources in cooperation with local urban water management professionals to aid the transformation of advanced climate-water resources modeling into a tool used by the urban water management community. Our first step focuses on understanding the future of water along the Wasatch front and how it impacts urban water management. For example, Pacific modes of variability such as the El Niño-Southern Oscillation (ENSO) influence Wasatch precipitation over a range of time scales (Hidalgo and Dracup, 2003; Wang et al. 2010). The latest climate model projections for the next century (CMIP5; Taylor et al. [2011]) remain widely varied in their simulation of ENSO (Guilyardi et al. 2012), and quantifying water resources in the Wasatch and Intermountain West in general will require quantifying how the uncertain state of the Pacific combines with projected climate change to alter the probability space of total precipitation, rainsnow partitioning, and melt timing. Our second step will utilize basin-scale statistical downscaling and dynamical downscaling of coarse-scale climate model output into forms useable by urban water supply system, urban watershed, and stormwater runoff models. The urban water modeling systems will be embedded within a stochastic simulation framework to enable uncertainty analysis to be added into urban water management. The research is investigating urban water management modeling needs that can be informed by downscaled climate model output and the impacts of natural variability versus climate change projections on urban water management systems. Guilyardi, E., H. Bellenger, P. Braconnot, M. Collins, S. Ferett, J. Leloup, W. Cai, A. Wittenberg, S.-W. Yeh, and Y.-G. Ham, 2012: A first look at ENSO in CMIP5. WCRP Workshop on CMIP5 Model Analysis, University of Hawaii, Honolulu, HI, 5-9 March 2012. Hidalgo, Hugo G., John A. Dracup, 2003: ENSO and PDO Effects on Hydroclimatic Variations of the Upper Colorado River Basin. J. Hydrometeor, 4, 5–23. Taylor, K.E., Stouffer, R.J., and Meehl, G.A. (2011). “An overview of CMIP5 and the experiment design.” Bulletin of the American Meteorological Society, DOI 10.1175/BAMS-D-11-00094.1 Wang, Shih-Yu, Robert R. Gillies, Jiming Jin, Lawrence E. Hipps, 2010: Coherence between the Great Salt Lake Level and the Pacific Quasi-Decadal Oscillation. J. Climate, 23, 2161–2177.

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Apr 4th, 1:30 PM Apr 4th, 12:50 PM

Climate Modeling to Support Urban Water Management in the Wasatch Range

ECC 216

Urban water management involves providing water supply, stormwater drainage control, and wastewater management in cities. In the metropolitan areas along the Wasatch Front metropolitan areas area faced with numerous urban water management challenges and climate is a factor in most cases. This is similar to most other metropolitan areas in the world. However, along the Wasatch Front and elsewhere, due to many factors those responsible for urban water management have yet to embrace climate information in the management of water resources. As part of the Cyberinfrastructure to Advance High Performance Water Resource Modeling (CI-WATER) project, we are developing software tools to bridge the computationally expensive gap between global climate models (~100-km spatial scale) and urban water resource models (scale). We are also developing analysis capacity and data resources in cooperation with local urban water management professionals to aid the transformation of advanced climate-water resources modeling into a tool used by the urban water management community. Our first step focuses on understanding the future of water along the Wasatch front and how it impacts urban water management. For example, Pacific modes of variability such as the El Niño-Southern Oscillation (ENSO) influence Wasatch precipitation over a range of time scales (Hidalgo and Dracup, 2003; Wang et al. 2010). The latest climate model projections for the next century (CMIP5; Taylor et al. [2011]) remain widely varied in their simulation of ENSO (Guilyardi et al. 2012), and quantifying water resources in the Wasatch and Intermountain West in general will require quantifying how the uncertain state of the Pacific combines with projected climate change to alter the probability space of total precipitation, rainsnow partitioning, and melt timing. Our second step will utilize basin-scale statistical downscaling and dynamical downscaling of coarse-scale climate model output into forms useable by urban water supply system, urban watershed, and stormwater runoff models. The urban water modeling systems will be embedded within a stochastic simulation framework to enable uncertainty analysis to be added into urban water management. The research is investigating urban water management modeling needs that can be informed by downscaled climate model output and the impacts of natural variability versus climate change projections on urban water management systems. Guilyardi, E., H. Bellenger, P. Braconnot, M. Collins, S. Ferett, J. Leloup, W. Cai, A. Wittenberg, S.-W. Yeh, and Y.-G. Ham, 2012: A first look at ENSO in CMIP5. WCRP Workshop on CMIP5 Model Analysis, University of Hawaii, Honolulu, HI, 5-9 March 2012. Hidalgo, Hugo G., John A. Dracup, 2003: ENSO and PDO Effects on Hydroclimatic Variations of the Upper Colorado River Basin. J. Hydrometeor, 4, 5–23. Taylor, K.E., Stouffer, R.J., and Meehl, G.A. (2011). “An overview of CMIP5 and the experiment design.” Bulletin of the American Meteorological Society, DOI 10.1175/BAMS-D-11-00094.1 Wang, Shih-Yu, Robert R. Gillies, Jiming Jin, Lawrence E. Hipps, 2010: Coherence between the Great Salt Lake Level and the Pacific Quasi-Decadal Oscillation. J. Climate, 23, 2161–2177.

https://digitalcommons.usu.edu/runoff/2012/AllAbstracts/58