Continued improvement of climate forecasts is resulting in better information about what rainfall and streamflow may look like months in advance. A researcher from North Carolina State University has developed an innovative water management framework that would take advantage of these forecasts to plan for droughts or excess rain in order to make the most efficient use of an area’s water resources.
By using climate forecasts for short-term planning, water managers can better plan for potential shortages due to drought, says Dr. Sankar Arumugam, an assistant professor of civil, construction and environmental engineering at NC State and lead author of the paper. For example, managers could encourage stakeholders to put water-use restrictions in place and launch a water conservation campaign before the drought even arrives. Managers could also use this approach to determine how best to take advantage of surplus water supplies. For example, hydropower facilities could generate additional power instead of spilling the excess water. Arumugam notes that the use of forecasts for planning would also make water managers better able to account for increased water demands due to population growth.
“Our paper proposes a framework that would use forecast data to improve water management, allowing water managers to be proactive with their planning rather than reacting to events after the fact,” Arumugam says. Water managers at the federal, state and local level determine how much water can be allotted to various uses, such as hydropower, agriculture, municipal use, recreation and the protection of aquatic species.
Arumugam says advances in the understanding of how changes in ocean temperature affect the atmosphere and, ultimately, precipitation and temperature, make seasonal or longer-term climate forecasts increasingly reliable. At the same time, Arumugam says, water management is becoming more important due to increasing global population – which means greater water demand – and global climate change, which could stress both humid and arid regions with the former getting wetter and the latter becoming drier.
The proposed framework acknowledges that climate forecasts contain an element of uncertainty, and attempts to mitigate that uncertainty by incorporating water contracts. “These contracts give end-users, such as farmers and municipalities, some idea of what they can expect – allowing them to plan accordingly based on the uncertainty in the climate forecasts,” Arumugam says, “It also offers insurance in the form of compensation if the forecast is incorrect and water managers cannot meet the terms of the contract.” Similarly, Arumugam explains, if the forecast is accurate and the terms of the contract are met, water managers will have made the most efficient use of the available water resources and will receive a performance fee from the end-users who were party to the contract.
“Although there is uncertainty associated with forecasts, they are correct over the long term, and using this framework would result in long-term benefits for both water users and managers,” Arumugam says. For example, the researchers performed a case study looking at the state of Ceara in Brazil, which is an arid region that receives little or no rainfall from June through the following January. “We found there would be significant benefits for the region, primarily in alleviating the vulnerability of poor farming communities if this framework was implemented,” Arumugam says.
The study, “Improved Water Allocation Utilizing Probabilistic Climate Forecasts: Short Term Water Contracts in a Risk Management Framework,” was co-authored by Arumugam, Dr. Upmanu Lall of Columbia University, Dr. Francisco Assis Souza Filho of the Federal University of Fortaleza and Dr. Ashish Sharma of the University of New South Wales. The research was funded by the National Oceanic and Atmospheric Administration and published in the Nov. 11 issue of Water Resources Research.
Note to editors: The study abstract follows.
“Improved Water Allocation Utilizing Probabilistic Climate Forecasts: Short Term Water Contracts in a Risk Management Framework”
Authors: A. Sankarasubramanian, North Carolina State University; Upmanu Lall, Columbia University; Francisco Assis Souza Filho, Federal University of Fortaleza; Ashish Sharma, University of New South Wales
Published: Nov. 11, 2009, Water Resources Research
Abstract: Probabilistic, seasonal to inter-annual streamflow forecasts are becoming increasingly available as the ability to model climate teleconnections is improving. However, water managers and practitioners have been slow to adopt such products, citing concerns with forecast skill. Essentially, a management risk is perceived in “gambling” with operations using a probabilistic forecast, while a system failure upon following existing operating policies is “protected” by the official rules or guidebook. In the presence of a prescribed system of prior allocation of releases under different storage or water availability conditions, the manager has little incentive to change. Innovation in allocation and operation is hence key to improved risk management using such forecasts. A participatory water allocation process that can effectively use probabilistic forecasts as part of an adaptive management strategy is introduced here. Users can express their demand for water through statements that cover the quantity needed at a particular reliability, the temporal distribution of the “allocation”, the associated willingness to pay, and compensation in the event of contract non-performance. The water manager then assesses feasible allocations using the probabilistic forecast that try to meet these criteria across all users. An iterative process between users and water manager could be used to formalize a set of short term contracts that represent the resulting prioritized water allocation strategy over the operating period for which the forecast was issued. These contracts can be used to allocate water each year/season beyond long term contracts that may have precedence. Thus, integrated supply and demand management can be achieved. In this paper, a single period multi-user optimization model that can support such an allocation process is presented. The application of this conceptual model is explored using data for the Jaguaribe Metropolitan Hydro System in Ceara, Brazil. The performance relative to the current allocation process is assessed in the context of whether such a model could support the proposed short term contract based participatory process. A synthetic forecasting example is also used to explore the relative roles of forecast skill and reservoir storage in this framework.