WASHINGTON — Scientists will use satellites, ground measurements and other remote sensing technologies to help herders in Afghanistan keep better tabs on threats to their livelihood.
A research team led by scientists at the University of California, Davis, and Texas A&M University in College Station will develop something they are calling the Livestock Early Warning System, under a $4.4 million federal grant from the U.S. Agency for International Development. Work on the project began in October.
The grant for the Pastoral Engagement, Adaptation and Capacity Enhancement (PEACE) project, is designed to aid the nomadic herders of the Kuchi tribe, according to principle investigator Paul Dyke, who is based at Texas A&M University . Data compiled by a team of four scientists based in Afghanistan and processed in the United States will help the herders identify the areas where their livestock — mostly sheep — will have enough plant life for grazing and also identify areas where shortages might occur, Dyke said.
According to an Oct. 19 press release from UC Davis, agriculture once accounted for more than 80 percent of Afghanistan’s national income, but the country now is dependent on international food aid for survival, partially because of conflict in the region, but also the result of years of drought.
The PEACE project is the third that the UC Davis and Texas A&M team has taken on to bring remote sensing technology to struggling, nomadic nations, Dyke said. Nine years ago, the team began a study in East Africa which continues today. The team also has an effort under way in the Gobi region of Mongolia, which began in 2004, Dyke said.
It is important for herders to understand which areas have the kind of plant life that the animals they herd tend to consume, and where supplies of that vegetation may end up running low, Dyke said.
To map those areas, scientists combine different types of data that show a variety of factors, including soil content, where specific types of grasses grow , weather data and the migratory habits of the animal populations.
Satellite data from National Oceanic and Atmospheric Administration (NOAA) instruments such as the Advanced Very High Resolution Radiometer is combined with 350 to 500 ground sampling measurements to identify the vegetation in the various regions, according to Jay Angerer, a research scientist for the program.
The scientists get feedback from herders on their travel patterns. They also rely on NOAA’s weather satellites to get proper climate data, he said. The research group would like to incorporate Landsat, Spot and even hyperspectral data to get a better picture of the soil makeup, which can give further clues about what the animals are digesting, he said.
One of the challenges of working in a region such as Afghanistan is that security concerns keep scientists from having the kind of wide access that they had in East Africa and Mongolia, when collecting data, Dyke said, making the use of remote sensing technology even more essential.
Once the data is collected, the scientists use predictive models to do 30-day, 60-day and 90-day forecasts of where the livestock will be moving and what the landscape and weather will look like when they get there. The data is processed online, but government officials and non government organizations are able to provide farmers with the information.
On previous projects the group also has transmitted some data via satellite using Worldspace International Satellite Radio, Dyke said.
Dyke said his team has received feedback that the forecasts they’ve made in East Africa and Mongolia have been accurate the majority of the time, aiding the herders who use them.
“We really feel like it’s starting to make a difference,” he said.
Angerer said they also have found it helpful to include within their forecasts and maps other information such as the price of livestock in various markets. This means that if a herder realizes that he has too much livestock in an area where there will not be enough vegetation to feed the herd, he can make a decision to sell the animal and get a good price, Angerer said.
The project’s funding lasts for four years. After that the scientists will have to determine how to maintain it. Those costs are not huge. For example, because the projects in East Africa and Mongolia have been in place for some time, those projects only cost between $200,000 and $300,000 a year to keep operating, Angerer said. The biggest challenge in keeping them operational is training and retaining qualified data analysts, Dyke said.
In the future, Angerer said he could see the technology applied to solve similar problems in areas of Central Asia and even in the United States , where drought problems usually only gain attention and funding when the drought is actually occurring, he said.