Steve McNulty, Ge Sun, and Erika (Cohen) Mack hiked for three hours on a winding trail over steep hills through land thick with trees and vines. They arrived at a pool and looked up at a towering waterfall. If they had stood at the top of the waterfall, they would have seen forested land stretching to the horizon.
It was 2011, and the waterfall was in Nyungwe Forest National Park, an ecotourism destination in western Rwanda that feeds many rivers in this densely populated and ecologically diverse African country comparable in size to the state of Maryland. The U.S. Forest Service Eastern Forest Environmental Threat Assessment Center researchers were on an assignment to perform a rapid assessment of Rwanda’s water resources.
The project followed a workshop in Tanzania sponsored by Forest Service International Programs, during which this Eastern Threat Center team behind the Water Supply Stress Index (WaSSI) model shared information about water research and dynamics of forest water use with about 50 land managers. This knowledge is becoming increasingly critical as Africa faces greater climate variation and more frequent droughts, and WaSSI proved to be a useful educational tool to demonstrate how changes in forest cover, climate, and human population affect water yield.
Soon after the workshop, the WaSSI team began to collaborate with the Wildlife Conservation Society and the Rwanda Agricultural Board to develop the water resource assessment in Rwanda described in a recently published case study co-authored with Southern Research Station research hydrologist Peter Caldwell.
“Water is critical to the security and well-being of any country regardless of the country’s wealth, but water is everything to the people of Rwanda,” says McNulty. On average, the western part of the country with dense mountain forests receives about 63 inches of rain per year, about twice the average rainfall of the eastern part of the country and its low-elevation forest types. Rwandans primarily rely on surface water for drinking, hydroelectric power, and irrigation for agriculture: 70 percent of Rwanda’s land is farmed for subsistence and export crops, including rice, tea, and coffee.
To perform the assessment, the researchers needed streamflow data to test the WaSSI model. Though Rwanda is relatively water rich, it is data poor: only nine streamflow gauges providing infrequent measurements are in use across the country. Researchers found that the Nyungwe Forest National Park gauge station offered the most complete, error-checked dataset sufficient for model validation.
“WaSSI is a simple hydrologic model that requires only a limited number of data inputs. Its premise is that leaf area, latitude, air temperature, and precipitation are the primary drivers of plant water use. If these and a few other variables are known, then ecosystem water use (and therefore water supply) can be predicted,” says McNulty.
The researchers then combined existing streamflow data with climate data based on a future scenario of high population growth and climate-warming greenhouse gas emissions. “Our results suggest that overall climate change impacts on water resources will be minimal, but those impacts do vary across Rwanda through time,” says McNulty.
Rwandan officials received the assessment results and now have the ability to use the web-based model themselves to see how changes in land cover, leaf area, and current and future climate can affect runoff and surface water supplies for watersheds and sectors across the country.
To more accurately assess water resources, researchers recommend that, possibly with international assistance, developing countries consider investing in increased streamflow data collection.
“Model-based hydrologic assessments can support policy development and strategies to reduce risk of water shortages,” explains McNulty. “To gain an accurate understanding of water supplies, we believe that funding for monitoring and assessment is equally as important as the development of projects and programs designed to relieve current or future water stress. We also believe that tested and validated models like WaSSI can be a significant step forward in helping developing countries prepare for climate change impacts.”
For more information, email Steve McNulty at email@example.com.