Field-Scale Estimation of Evapotranspiration DOI: http://dx.doi.org/10.5772/intechopen.80945

amount of water lost from a specific field, with a specific crop, under specific

Ks <sup>¼</sup> TAW � Dr

where θFC is the field capacity water content, θWP is the wilting point water content, and Zr is the rooting depth (m). Additional information on calculating Ks is

for water, which is why most ETref equations only require weather data. ETc derived from ETref provides the potential, or maximum, water use by the crop, assuming no crop water stress, or if the Ks is used, only accounts for water stress. One potential issue with this technique is that crops can typically encounter stress from multiple sources throughout the season, especially in arid and semiarid climates. Another issue is the use of limited crop coefficients during the growth cycle. It is more advantageous to use ETa in water planning and irrigation scheduling, but

Since ETref assumes no water limitations, it represents the atmospheric demand

To maximize the effectiveness of irrigation scheduling, ETa is more beneficial than ETref or even ETc. Confusion exists regarding what each ET term corresponds to, which can lead to the use of ETref instead of ETc. Using ETref in irrigation scheduling is considered better than no irrigation scheduling, but it can lead to over application of water, as can ETc. Even though ETc corresponds to the ET of the specific crop, it does not take ET reduction due to stress into account. One problem with using ETa in irrigation scheduling is that ETa can be very difficult to obtain. Where ETref can be calculated from weather parameters, using a relatively simple weather station on a reference surface, ETa requires more advanced (and expensive) instrumentation. Current technologies for determining ETa are described in

ET is used in production agriculture in the practice of irrigation scheduling. This practice involves tracking ET from the field and applying the water balance. The

where ΔS is change in soil moisture, P is precipitation, R is the sum of runoff and run-on, and D is drainage [10]. All units are in mm. The R term is negative when run-on exceeds runoff and positive if runoff is greater. In many arid and semiarid regions, the drainage term is often miniscule. In addition, most current agricultural practices employ measures to control runoff/run-on, such as furrow diking. This practice can make the runoff term minute. In other climates/regions where runoff and run-on can be significant, the values can be estimated from precipitation intensity and infiltration rate [11]. Other methods could also be used, such as from soil moisture sensors or runoff flumes. Drainage, or deep percolation, can be

ΔS ¼ P � ET � R � D (3)

where TAW is the total available soil water, Dr is the root zone depletion (mm), p is the fraction of TAW allowed before the crop experiences water stress (typically 0.50 for most crops [7]), and Dr is typically calculated using a water balance

ð Þ <sup>1</sup> � <sup>p</sup> TAW (1)

TAW ¼ 1000ð Þ θFC � θWP Zr (2)

environmental conditions. Ks is calculated by

Advanced Evapotranspiration Methods and Applications

approach. TAW is calculated as

acquiring ETa can be challenging.

available in [7].

detail below.

6

1.2 Water balance

water balance is based on the equation:

determined from soil moisture content below the root zone. Deep soil moisture can be measured using soil moisture sensors, neutron probes, or soil cores.

In arid and semiarid regions where precipitation does not meet crop water requirements and is supplemented with irrigation, it is also important to account for the effective addition of water by irrigation. In most cases in areas such as the Texas High Plains (where runoff/run-on and drainage are negligible), the water balance is written as

$$P + I + \Delta S = ET \tag{4}$$

In addition, in these drier climates, soil moisture change between the growing seasons is typically minor, so precipitation and irrigation are the main water inputs. Since precipitation is typically small and highly variable in arid and semiarid regions, irrigation is required for maximum agricultural production. One problem in these areas is that water supplies are rapidly diminishing. This illustrates the importance of maximizing the efficiency of water use. With effective irrigation scheduling, producers can apply only the amount of water required for the respective crop.

In Texas, and especially the Texas High Plains, irrigation is the largest consumer of fresh water, most of which comes from the declining Ogallala Aquifer. In a previous study [2], it was found that reducing irrigation applications by 25 mm (1 in.) over the typical summer growing season for all the irrigated acreage in the northern Texas High Plains would save 92.5 million m<sup>3</sup> (75,000 ac-ft) of water, also decreasing pumping costs by over \$6 million. For perspective, that 92.5 million m<sup>3</sup> of water equates to over 2.5 months of municipal water use for the city of Houston, TX, with a population over 2 million.

The water balance approach has been widely used to estimate ET. It can be modeled seasonally by obtaining volumetric water content from soil samples at the beginning and end of the growing season. If precipitation and irrigation is measured, the change in soil moisture can be used to calculate seasonal ET. With soil moisture sensors, the same accounting approach can be performed on any time scale. The spatial resolution, however, of the water balance approach depends on the amount and spacing of soil moisture sensors or soil samples. Installing numerous sensors or taking numerous soil samples is often prohibitive due to time and funding constraints. In addition, both sensors and soil samples are specific to the small area of measurement and may not represent the surrounding field, especially in areas with highly variable soils.
