Thursday, November 7, 2019

Implications and Context for Effects of Climate Change on Urban Water Demands in the Mountain-West

Posted by Jason Lillywhite

Carly Hansen with Oakridge National Laboratory developed a modeling framework that incorporates multiple drivers of change, uncertainty, and system complexities allowing the user be to address water availability, management, and planning challenges. There are various drivers of change in future residential water use, some of which have clear compounding effects. Strategic planning (e.g. where to focus time and financial resources) requires an understanding of the relative contribution of each of these drivers. Exploring water use through a probabilistic GoldSim model helps address uncertainties inherent with human behavior and multiple scenarios allow for exploration of different drivers of change.

Background

Residents in the mountain-west region of the US consistently rank at the top of water users (measured
by per capita residential use)[1]. Major population centers in the Utah Lake and Jordan River Basins
are no exception, and the majority of residential water use goes towards outdoor watering [2]. For
comparison, the national average of outdoor residential water use is about 30% of total use [3].
Urban water demands and availability are subject to changes in:

  • Climate conditions
  • Growth and development patterns
  • Behavior, perception, and public understanding of water-related issues

Systems models that incorporate multiple drivers of change, uncertainty, and system complexities can
be used to address water availability, management, and planning challenges.

Research Objectives and Questions

  • There is uncertainty in potential future climate conditions. How does urban outdoor water use compare between the range of past and future projected conditions, including during extreme periods of drought?
  • Utah is expecting large population growth over the coming decades. How are those changes compounded by population growth/development?
  • Changing an individual’s water use behavior can be difficult. How much does conservation mitigate changes in demands under various scenarios of potential future climate conditions and growth/development?

Modeling Workflow and Results

Figure 1 - 10-yr moving average SPEI
A 10-year moving average of the Standardized Precipitation-Evapotranspiration Index (SPEI) [4] was used to forecast climate conditions. The data extends from 1950-2099 based on CCSM4 MACA Downscaled Climate Data [5-6] for Utah Lake (Provo) and Jordan River (SLC) Basins. Over the next 80 years, there is a significant drop in SPEI which reflects generally hotter/drier conditions (refer to Figure 1).

Figure 2 - Land use Change 2005-2040
Urban land use change was incorporated in the model assuming “Business as Usual” development practices. Future development was simulated using a Real Estate Market Model (REMM) [7], and outputs were post-processed by researchers in the University of Utah Department of City and Metropolitan Planning (refer to Figure 2).


A GoldSim model of the Utah Lake and Jordan River basins was used to represent water deliveries from water supply sources to users (residents, institutions, irrigation), and then their various endpoints (wastewater treatment plants and receiving waters). This modeling platform incorporates inherent uncertainties through Monte Carlo simulations (e.g. allowing variability in daily per capita water use) and is useful for representing complex interactions and feedback between subsystems. A screen capture of part of the GoldSim model is shown in Figure 3.
Figure 3 - System Model and Scenarios
Twenty-four scenarios are used to explore different “levers” of change as shown in Figure 3. *Some parameters that are influenced in these scenarios are not explored within the scope of this study, but are expected to play major roles in planning and management of water resources in the broader system.
Figure 4 - Annual Residential Water Use
A comparison of annual water use under various scenarios highlights compounding effects and provides context for these changes is shown in Figure 4. For example, Business as Usual (BAU) growth/development leads to a nearly 40% increase during the period of the most extreme projected drought (compared to historical population and climate). However, if conservation targets of 25% residential reduction are met, there would be only a slight increase (4%) in total use, even in the same extreme climate conditions and same BAU growth patterns.

Key Findings

Strategic development, conservation, and planning are essential for dealing with changing residential outdoor water use and urban water systems.
  • There are various drivers of change in future residential water use, some of which have clear compounding effects. Strategic planning (e.g. where to focus time and financial resources) requires an understanding of the relative contribution of each of these drivers.
  • Exploring water use through a probabilistic model helps address uncertainties inherent with human behavior and multiple scenarios allow for exploration of different drivers of change.

Future Research Opportunities

Residential outdoor water use is only one part of a complex water system. Changes in this part of the system need to be linked to other parts of the system (including surface and groundwater sources, and downstream receiving waters). In this particular system, there are several multi-purpose reservoirs, and any changes in demands will have cascading effects outside of residential water use sector (e.g. energy generation, flood control operations). There are also many opportunities to explore mechanisms of change (e.g. lawn irrigation technologies). Additionally, the modeling framework and many of the data sources presented here are widely applicable and available for other urban water systems in the western United States.

Acknowledgements

This article was developed under assistance agreement number 835866-01 awarded by the US Environmental Protection Agency to Dr. Michael Barber. It has not been formally reviewed by EPA. The views expressed in this document are solely those of the authors and do not necessarily reflect those of the agency. EPA does not endorse any products or commercial services mentioned in this publication. Special thanks to Debolina Banerjee from the Department of City and Metropolitan Planning at the University of Utah for processing REMM model data.

Contributors:
Carly Hansen, PhD (with Oak Ridge National Laboratory – Environmental Sciences Division, hansench@ornl.gov)
Steve Burian, PhD (with University of Utah – Civil and Environmental Engineering and the U Water Center)

This model was presented at the 2019 American Water Resources Association Conference in November 2019 as part of the poster showcase. To view the entire poster presentation, click here.

References

[1] Estimated Use of Water in the United States in 2010. USGS Circular 1405, 2014.
[2] State of Utah Municipal and Industrial Water Supply and Use Study Summary 2010. Utah Division of Water Resources. 2014.
[3] How we Use Water. EPA. 
[4] Vicente-Serrano S.M., Santiago Beguería, Juan I. López-Moreno. “A Multi-scalar drought index sensitive to global warming: The Standardized Precipitation Evapotranspiration Index – SPEI”. Journal of Climate. 2010 23: 1696-1718.
[5] Abatzoglou J.T. and Brown T.J. "A comparison of statistical downscaling methods suited for wildfire applications " International Journal of Climatology. 2012.
[6] Taylor, K.E., R.J. Stouffer, G.A. Meehl: An Overview of CMIP5 and the experiment design. MS-D-11-00094.1, 2012.
[8] Development and land use data provided by Wasatch Front Regional Council, based on REMM model for the urban areas of Salt Lake and Utah Counties. Related public data are available here.
[9] 25% reduction in residential use is based on goals established by the Utah Division of Water Resources in 2001. See this page.

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