Advanced Search
October 5, 2022
Water is on the world’s mind because of the severe, sustained droughts that have plagued Africa, Asia, Europe, and the United States throughout the summer of 2022. The three-year period from August 2019 to July 2022 ranked as the second-driest period on record in the United States, according to National Oceanic and Atmospheric Administration data. Drought is especially dangerous for the American West, with seven states sourcing their water from the Colorado River, which is now in its 23rd year of drought.
While drought has a variety of causes, one key variable is climate change, which can decrease precipitation, increase precipitation variability, dry out soil, and reduce surface water, all leading to increasingly difficult droughts. However, the unprecedented lows facing the Colorado River are also the result of water overuse, which jeopardizes the future for the millions of people who depend on this critical water source for household, agricultural, and hydropower uses. The dire circumstances call for drastic improvements in how water is managed and used. Water data tools are one way of ensuring the more efficient usage of scarce water resources.
The Colorado River Basin (CRB) encompasses roughly 246,000 square miles and delivers fresh water to nearly 40 million people and 5.5 million acres of agricultural land in seven states and 29 tribal territories. The two-decade drought and low runoff conditions have contributed to historically low water levels for both Lake Mead and Lake Powell, threatening both water supplies and power generation capacity. As of September 2022, Lake Mead (in Nevada and Arizona) was 28 percent full and Lake Powell (in Utah and Arizona) was 25 percent full.
According to the Alliance for Global Water Adaptation, the 1922 Colorado Compact and subsequent agreements overallocated the CRB’s water based on predictions and assumptions about the amount of water that would be available from Rocky Mountain snowmelt—predictions that didn’t take into account climate change. Rising temperatures are expected to lead to snowpack losses in high elevation areas of the CRB. And because many water management systems rely on spring snowpack melt, these losses can be a big problem.
Furthermore, the water allocation plans did not anticipate the high population growth in CRB states, not to mention the needs of the many tourists who visit the region. The U.S. Census Bureau expects an average population increase of 53 percent from 2000 to 2030 for the CRB states. In addition, agriculture uses 80 percent of the water in the CRB across properties totaling 5.5 million acres that produce about 15 percent of the nation’s crops.
In order to protect the vitality of the Colorado River and the huge variety of people, animals, and ecosystems it serves, digital tools need to be effectively deployed to maximize water usage efficiency. The Inflation Reduction Act (P.L. 117-169) allocates $4 billion for mitigating drought in the 17 western states. However, without improved strategies for effectively managing limited water, the investment could fall short of its intended goals.
With a lower environmental impact and quicker deployment than traditional built infrastructure, digital tools that integrate data into decision-making processes are key allies in the fight against water scarcity and drought. Digital tools can improve how water managers understand the environment and physical infrastructure, enhance responsiveness to changing water availability and operational conditions, and identify maintenance issues when—or before—they arise. With modern digital water efficiency tools, water usage planners can have a fuller picture of what conditions they face in order to refine their decisions.
It is important to note that good water data management does not replace good water usage policy. States and local governments will still need to take a long look at how other policy factors like infrastructure, use regulations, waste water recycling, and utilizing multi-crop systems can help mitigate the impacts of water shortages. However, paired with systemic changes, effective deployment of water data tools can go a long way in improving water usage in the CRB and beyond.
One way that data can improve water usage efficiency is through data infrastructure modernization. To be usable by digital visualization, optimization, and predictive tools, water data must be collected, standardized, and organized into a machine-readable format. In the Colorado River Basin, several key tools are being used to modernize data infrastructure and provide open data for water management.
The Internet of Water (IoW) Coalition works to develop “open-source technologies for sharing and integrating water data.” It partners with data producers and users to provide standardized water data that can help improve water management decisions. The coalition is collaborating with New Mexico’s Bureau of Geology and Mineral Resources to identify upgrades in data collection and utilization needed in the Pecos Valley Region.
As IoW Director Peter Colohan explained, better water data reporting and monitoring in the Roswell-Artesian Basin, which is prone to water stress, will provide water users with the latest data, allowing them to make better irrigation decisions.
“More rapid access to well withdrawal data allows the irrigation district to understand the influence of well usage on the surface water of the river, as the two are connected hydrologically,” explained Colohan. “This allows them to be more informed in their irrigation decisions.”
Stacy Timmons, a hydrogeologist who leads the implementation of the New Mexico Water Data Initiative, added more context: “In this region, farming and irrigation is supported entirely by groundwater pumping, and the Pecos River must be managed carefully to flow through the region into the next region, where they are allocated surface water to irrigate.”
“We are working closely with the irrigation district, the regulators, and the water managers at federal agencies to try and illuminate the groundwater and surface water changes over time,” noted Timmons. “Ideally, irrigation practices can evolve to directly respond to impacts on groundwater. For example, where water levels are declining, they can make decisions to shift pumping to other regions temporarily to allow for recovery. “
The Water Data Exchange (WaDE) program is one of IoW’s “data hubs,” or data networks. Work on WaDE began in 2011, growing out of a need for states in the Western States Water Council (WSWC) to understand and respond to conditions of drought and population growth impacting water availability.
“Generally, here in the West… it is mostly not well-measured or [it is] really hard to easily know how much water is being used,” explained WaDE Program Manager Adel Abdallah. “We're on a mission to change that through data standardization and sharing.”
WaDE provides a common, downloadable set of data on water rights, regulations impacting water use, water use at a local level, and aggregate water use at the watershed level, including detailed documentation on where the data comes from.
This data is not real-time—rather it is updated yearly from state reports—yet it is still an important resource for potential users. WaDE’s description of end-user personas for its Western States Water Data Access and Analysis Tool provides examples of users who could benefit from the information, including governors looking to identify water rights during times of drought, land use managers wanting to compare historic water usage, and conservation managers hoping to find water rights available to purchase near environmentally sensitive areas. Thus, many different types of users can find useful data for water problem-solving.
Another organization paving the way for open-source water data is OpenET, which came online in 2021 and provides remote-sensing satellite water data. The “ET” stands for evapotranspiration, or the process of water being released from land surfaces, including vegetation, as the sun heats the earth. OpenET collects highly accurate satellite information on evapotranspiration to measure consumptive use—the amount of water that cannot be returned to a stream or aquifer—on croplands in the 17 western states. For agriculture, which accounts for the vast majority of water use in the CRB, understanding how water is leaving the basin is key to maximizing water usage efficiency.
“Managing water without ET data is like trying to manage your household budget without knowing how much money you are spending day-to-day,” explained Robyn Grimm, director of climate resilient water systems at the Environmental Defense Fund.
In the West, OpenET has been used as a data source to help comply with crop water usage regulations, understand the impact of forest restoration on water supply, and plan ways to decrease water usage, just to name a few examples.
Another powerful way of using water data to improve usage efficiency is through predictive analytics and modeling tools that help analyze data and draw conclusions.
One important environmental modeling tool using water data is RiverWare, which models river basin systems and forecasts water conditions over years and decades. RiverWare is used nationwide but the software is particularly important in the CRB, where it is used by federal agencies to inform operational, efficiency, and water allocation decisions.
RiverWare is maintained and updated by the University of Colorado Center for Advanced Decision Support for Water and Environmental Systems (CADSWES). This modeling technology is able to digitally represent natural hydrological systems, human-built infrastructure, and rules that govern water management activities (such as when water is stored or released in reservoirs). To manage the CRB, the Bureau of Reclamation uses two specialized models available in the RiverWare software that are updated on a monthly basis and can provide short- and long-term forecasting.
According to CADSWES Director Edith Zagona, logical rules are input into a RiverWare model to meet system objectives, which may range from simply supplying water to users with rights, to producing hydroelectric energy, preventing floods, providing environmental services, and sustaining flows and levels for recreation.
“For example, an operating policy may be to release a certain amount from a reservoir based on time of year, level in the reservoir, water demands downstream, forecast of future inflows or other considerations. Also, the model can be used to ‘experiment’ with different operating policies to decide on one that best meets the objectives,” Zagona explained.
Due to ongoing drought and climate change, there is a broad consensus that water supplies in the Colorado River will be lower in the next 100 years than they were in the last 100. Because the recent operating agreements to address shortages will expire in 2026, Zagona explained that “the water managers and stakeholders need to come up with a new plan for operating and allocating shortages in the future—and it will be informed by analysis using RiverWare model projections of the future.”
Along with informing long-term planning decisions, RiverWare can also be used to manage day-to-day operations of water infrastructure. Southern Company, a hydroelectric dam operator in the Southeast, uses RiverWare to project environmental conditions 7-10 days out. They are then able to apply those projections to operational decisions, such as the number of hours hydropower units should be run each day.
Data and modeling can be used to increase operational efficiency beyond the simulation of environmental conditions. With enough data, operators of water infrastructure such as hydroelectric plants can predict rare but costly events like equipment failures and generally improve efficiency.
One organization working to use data to improve operational efficiency is the Hydropower Research Institute (HRI), a nonprofit supported by members that own hydropower assets. The members provide HRI with both data and fees, and they are able to access all of HRI’s anonymized data to conduct their own analyses or compare operations. Outside organizations can also pay to access the data for research purposes.
Those managing water infrastructure—in this case hydroelectric power plants—rarely have the quantity of data or specialized personnel available to maximize the possibilities of predictive analytics. As Andrew Bulmer, operations manager for HRI through Sapere Consulting, explained, “your model’s ability to predict will improve based on the amount of data that you can consume.” HRI works to improve its forecasting by aggregating data from a number of different hydropower sources. Data is anonymized, sorted, and examined to detect signals, including indications that a piece of equipment will need maintenance.
The U.S. Department of Energy (DOE) purchased a subscription to HRI data for the National Renewable Energy Laboratory (NREL), which resulted in improved understanding of hydropower maintenance. Kirk Hudson, HRI president, discussed how NREL created an algorithm using HRI data to determine the best time to conduct maintenance.
“It's kind of like your car,” Hudson explained. “You change the oil every 3,000 to 5,000 miles or so many months, and it is similar in hydropower plants—a lot of owners just have a regular time interval that they do maintenance. But NREL said you can use your operational data to determine when you should do your maintenance, rather than just picking a standard timeframe.”
Predicting the optimal time to do maintenance is critical to preventing unplanned outages of turbines and generators, which can be costly in terms of time, money, and water that could otherwise have been used to generate carbon-free electricity. With enough advance warning, preventative maintenance can save valuable resources.
An effective tool within modeling and predictive analytics is the digital twin, which is a model that directly corresponds to an actual piece of infrastructure. The model requires extensive sensor data to run simulations that test the equipment under various conditions, detecting stress points and allowing for scenario planning, similar to how RiverWare can model river basins for planning purposes.
Operational Optimization
The Bureau of Reclamation’s Technical Service Center, in conjunction with the U.S. Army Corps of Engineers, developed a digital tool called HydrOS, which uses algorithms to support decisions related to water use and electricity generation. HydrOS is used in three power plant and reservoir control centers, including the Glen Canyon Dam in the CRB. Since deployment in 2013, this digital technology has improved plant efficiency by an average of 1.75 percent, conserving water while adhering to generation requirements.
Federal agencies recognize the importance of digital twin technology. The DOE Water Power Technologies Office is seeking to optimize hydropower plant operations by collecting data and refining models of hydropower systems through the Digital Twin for Hydropower Systems – Open Platform Framework. Once launched, the framework is intended to provide an affordable and accessible platform for collecting and analyzing data from hydropower units.
While predictive analytics and modeling technology are already being used to make day-to-day and long-term planning decisions for water management, these digital tools hold tremendous promise for more and improved applications when combined with better data collection and infrastructure management. Data modernization and predictive analytics can be powerful tools in optimizing the efficiency of water usage in key areas like the Colorado River Basin. But much more work will need to be done—digital water efficiency tools are just a drop in the bucket of solutions needed in order to mitigate the human activities that have led to extreme drought and water shortages in the United States and abroad.
Authors: Amber Todoroff and Molly Brind’Amour
Contributor: Emilie Austin
We'll deliver a dose of the latest in environmental policy and climate change solutions straight to your inbox every 2 weeks!
Sign up for our newsletter, Climate Change Solutions, here.
Top-Rated Climate Nonprofit – 4-Star Charity