Passage Three
Earth’s most rich resource—water—has become one of the most precious resources in the United States as rivers, lakes, and freshwater reservoirs are increasingly exploited for human use . Consequently, using precision farming techniques to refine” irrigation scheduling ” is a research area of particular interest to Susan Moran, a researcher with the U.S. Department of Agriculture. She explains that in the southwest, irrigation is both difficult and expensive .There, she says, farmers have a tendency to over-irrigate, spending both more time and money than is necessary.
“I’m trying to provide new information that could be used by farmers to schedule irrigations to improve their profitability and use less water, ” Moran says. “Farmes often look at weather changes and then schedule irrigation based on that information .But if they had better information , they could use scientific models to compute more precisely how much water their crop is using.”
Rather than guessing their crop’s potential need for water based upon weather changes, farmers can use remote sensors to measure how much water their crop is actually using. This would give them a more accurate measure of how much more water it needs.
Moran believes that if farmers are getting good and timely measurements of plant and air temperature, then they can program when and how much water to give each crop through an irrigation system. No more water would be used than needed, thus saving cost and conserving water.
Moran introduces one study she conducted in Arizona to investigate the use of remote sensing data for scheduling cotton irrigations. Typically, those farmers irrigate ten times per growing season, but evidence showed that some of those farmers could achieve basically the same harvest with only nine irrigations.
“In those cases , one less irrigation saved more than all the cost of remote sensing data, ” she states. “Both irrigation and satellite remote sensing data are expensive. But then again many farmers are used to working together as a group. They are used to sharing. I’m hoping they could do the same with remote sensing data—purchase one scene over a large area to cover many farms, which would further reduce the cost.”
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