Our Most Precious Resource   Page 1Page 3

Ironically, Earth’s most abundant 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 Moran. 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. "Often times, farmers look at weather variables and then schedule irrigation based on that information. But if they had better information, they could use scientific models and equations to compute more precisely how much water their crop is using."

Rather than guessing their crop’s potential need for water based upon weather variables, 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.


Irrigation System
This photo shows a movable linear irrigation system with an imaging system attached. Such devices can be programmed, based on remote sensing data, to provide the right amount of water at the right time to different areas within a field. (Photograph courtesy USDA Agricultural Research Service)


Crop Monitoring

The basic concept is that as a plant grows, it takes in sunlight, nutrients from the soil, and water to build plant structures during photosynthesis. Some of the incoming sunlight is reflected, while some is absorbed and either used for photosynthesis or converted into heat. Similar to the way humans perspire to cool off, healthy plants use a process called "transpiration" to keep cool. There are tiny pores on plants’ leaves, called "stomata," that can open to allow water droplets to evaporate, thereby releasing heat. But a plant that is under stress does not transpire well and begins to overheat. At a certain temperature threshold, the plant’s internal functions begin to break down. The plant begins to whither and change its texture or shape or color, or all of the above, and there is potential for damage. Remote sensors can measure the temperature of plants; or to be more precise, they can measure how much energy plants emit at thermal infrared wavelengths of the spectrum.

Moran explains that her computer model takes a given plant’s physical attributes into consideration when making its calculations. As they are gathered, new remote sensing data are also input into the model to indicate which variables–such as air temperature or soil moisture–are changing over time and by how much. She then uses mathematical formulas to relate the plants’ temperature to the surrounding air temperature and calculate how much water the plant is using. The model’s output value falls somewhere on an index scale of from 0 (meaning no stress) to 1 (serious stress and the crop is probably damaged). Corn, for example, could go as high as 0.4 on the crop water stress index and still produce a harvest, whereas cotton has a much lower stress threshold.

Moran concludes 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 cites 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 offset the cost."

next Data Requirements for Precision Farming
next At the Right Place and Time


These three false-color images over the Maricopa Agricultural Center were acquired by the Daedalus sensor flying aboard a NASA aircraft. The top image shows the color variations determined by crop density (also referred to as "Normalized Difference Vegetation Index," or NDVI), where dark blues and greens indicate lush vegetation and reds show areas of bare soil. The middle image is a map of water deficit, derived from the Daedalus' reflectance and temperature measurements. The image shows an ongoing flood irrigation in the northern Field 7 and Field 107, in which greens and blues indicate wet, bare soil and reds are dry, bare soil. The bottom image shows where crops are under serious stress, as is particularly the case in Fields 120 and 199 (indicated by red and yellow pixels). These fields were due to be irrigated the following day. (Image courtesy Susan Moran, Landsat 7 Science Team)

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