Balancing the load: The software managing Kenya's Biggest Dam

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A research team led by Sankar Arumugam at N.C. State has developed computer modeling software that improves water flow management at Masinga Reservoir in the Tana River basin of Kenya. Most of Kenya’s energy load is supplied by hydroelectric stations at dams along the upper Tana River. In order to provide adequate energy for the country’s needs, authorities must constantly monitor the water level, and anticipate how much water they can expect in upcoming rainy seasons. The amount of water utilized for power generation must be balanced with other needs such as irrigation, and preservation of the ecosystem, so a model that improves water management at in the Tana River basin provides a huge benefit for the country.

Up till now, the water flow management task has been addressed using traditional weather prediction methods, which rely upon precipitation forecasts for the region, and provide a more-or-less accurate prediction of rainfall in the area. The forecasts proved inadequate however, when Kenya experienced severe droughts from 1999 to 2001 due to La Nina related weather events. The droughts in those years resulted not only in massive food shortages, but also a severe shortfall in base load energy for the country. It was this double-whammy that elevated the situation in Kenya during those years to an international humanitarian crises.

In order to improve energy and resource allocation, and hopefully prevent future crises, scientists have been working on new methods to improve the predictive power of forecasts in the region and the resulting water flow through the Masinga Reservoir. A paper recently published in the American Meteorological Society journal details a new approach by a multi-university team of scientists. The general approach of the team, led by Sankar Arumugam at N.C. State University, has been to use multiple 'inflow forecasts' which predict the amount of water expected to enter the Masinga Reservoir, and feed this data into a reservoir model they have developed. The model then provides water flow estimates that can allow officials to allocate water for power generation while ensuring that enough is retained to meet seasonal water demands.

So far the results of the team's efforts have been positive, with the research paper concluding that their model is more effective than previous methods, and has allowed them to reduce excess water retention during above-normal inflow years, allowing maximal energy production. They expect that the model will have a similar benefit during below-normal inflow years, when droughts previously caused massive shortfalls in the water supply by the end of the season.

With this new model in place, the Masinga Reservoir will be able to efficiently provide Kenya with a reliable power supply while also meeting other water use demands, such as irrigation and ecosystem needs. Similar models could be applied to the rest of the dams along the Tana River basin, hopefully allowing Kenya to better manage the effects of drought in the future.