14 DAY TRIAL // Companies operating the world's largest dams and adjacent hydrothermal power plants have always been plagued by a massive uncertainty – the level of the river they are squatting. Flowing waters around the world are continuously registering variations in their levels, and knowing them is of great importance for those in charge of producing electricity from it. Also, engineers need to know how much water to release or to keep behind the dam, so as to ensure that nothing happens to the cities downstream, while also keeping production at constant levels, PhysOrg reports.
Countries such as Brazil, Canada, China, the United States, the Russian Federation, Norway, Japan, and Sweden could all benefit from a new medium-term forecasting tool, developed by experts at the Lund University School of Engineering (LTH), in Swede. The new method is relatively straightforward, and works by combining data scaled down from massive computer simulations of the global climate, with information collected locally. According to its developers, the new method covers up to four months in advance, and is about two times more accurate than any other similar tools. Details of the forecast tool will appear in an upcoming issue of the scientific journal Hydrology Research.
“By predicting spring water resources as early as December-January, it is possible to steer electricity production so that water reservoirs are emptied more slowly, thus avoiding dramatic price hikes in subsequent seasons. The need to control water flows is all the greater because the value of water in the dams varies apace with the price of electricity,” explains LTH water resources engineering professor Cintia Bertacchi Uvo, one of the members of the team that developed the method.
“The only thing needed to apply the method locally is to fill in historical data, as far back as possible, about water flows from the river that feeds the power station. It is possible to apply the method in different countries with varying time conditions depending on the country’s climate,” adds water resources engineering expert Kean Foster. “A climate forecast like the one we have devised provides better probability for future run-off scenarios, which makes it possible to plan and prioritize different strategies,” he says.
Cintia Bertacchi Uvo concludes: “A concrete example that illustrates the need for forecasts occurred in the spring of 2003, when energy prices in Sweden more than tripled in a short time. The reason was that precipitation that normally comes in the autumn had not materialized. If the hydroelectric power stations had had access to relevant climate forecasts during the summer and autumn, they would not have emptied the water reservoirs prematurely, which is what happened.”