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Plant Water Use
Dean E. Eisenhauer, Derrel L. Martin, Derek M. Heeren, Glenn J. Hoffman
Pages 49-77 (doi: 10.13031/ISM.2021.4) in Irrigation Systems Management. ,
Abstract. See https://www.asabe.org/ISM for a PDF file of this entire textbook at no cost.
4.1 Introduction
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| Figure 4.1. Example of water use and time of growth stages for corn in the Northern High Plains of the U. S. |
How much irrigation water is required for a 100-acre field next week? Is one inch enough or do you need two? Do you need a pump capable of delivering 900 gallons per minute or will 750 be adequate? How different is water use for small plants compared to a fully developed crop? How long does water need to be applied to the fairway on the eighteenth fairway? How large of canal is needed for a reservoir to supply an irrigation district? These questions can be answered if we know how plants use water. Evapotranspiration is the term used to describe plant water use.
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| Figure 4.2. Frequency distribution of water use for well-watered alfalfa with full cover in southern Idaho (adapted from Wright and Jensen, 1972). |
The seasonal water use pattern is critical for irrigation management. If the rate of water use is known, managers can determine when to irrigate and the depth of water to apply. Curves that show the rate of water use during the season can be used to estimate future water needs (Figure 4.1). It is important to know the seasonal amount of water use to plan for irrigation requirements, cropping area, and other management decisions. The seasonal total is especially important where water supplies are limited or regulated as often occurs for irrigation projects supplied from reservoirs.
The rate of water use varies annually; therefore, the average water use curve is frequently inadequate. A distribution of the water use rate for well-watered alfalfa is shown in Figure 4.2. The 50% line represents the average water use rate. The 90% line represents a rate that will only be exceeded once in 10 years. Curves such as Figure 4.2 are useful in deciding the risk involved with a management strategy. Water and money can be saved by reducing the amount applied, i.e., using an average water use rate. However, the manager would be more confident that the crop would not be stressed if a higher probability were used.
4.2 Water Use Processes
Understanding how plants use water and evaluating the effect of weather on water use require consideration of fundamental processes. Plants extract water from the soil and transport water to the leaves. The stomata, very small openings, located on the upper and lower surfaces of the leaves, allow for the intake of carbon dioxide required for photosynthesis and plant growth. Water vapor is lost from the plant leaves by evaporation in the stomatal cavity and the flow of water vapor from the stomata into the atmosphere. This is transpiration.
Transpiration is necessary to cool the plant and maintain productivity. Converting liquid water to vapor (i.e., evaporation) requires a large amount of energy. If plants did not transpire, the incoming solar energy would heat the plant, perhaps to lethal temperatures. When plants are stressed from lack of water the stomata close, restricting the flow of water and carbon dioxide. When plants are stressed transpiration decreases, but so does photosynthesis. For this reason, crop yield and seasonal transpiration are closely related.
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| Figure 4.3. Example of the stages of evaporation from a bare soil. |
Water at the soil surface and on plant leaves or mulch evaporates when solar radiation or hot, dry winds supply energy. Initially, evaporation from a wet soil surface progresses at a maximum energy limiting rate (Figure 4.3). As evaporation continues the soil surface begins to dry and water below the soil surface moves upward replacing soil water lost by evaporation. As the soil dries the resistance to water flow increases. Eventually the rate of water flow in the soil limits evaporation rather than the amount of energy available to evaporate water. This is called the soil limiting phase of evaporation. During the soil limiting phase the rate of evaporation is less than during the energy limiting phase (Figure 4.3). During the soil limiting phase, energy that could have been used to evaporate water is available to heat the soil and air near the soil surface. The heating is most pronounced when there is no crop or when plants are small. If the process persists for a long period, the soil and air become quite hot as in desert climates.
Evaporation and transpiration are difficult to measure or predict separately, because water vapor moves from different surfaces into a dynamic environment that varies with time. Measuring devices can alter the local climate around plants and change the actual rate of evaporation or transpiration. Therefore, evaporation and transpiration are usually combined and called evapotranspiration (ET).
Evaporation may be a large component of ET of annual crops early in the season when crops are small, but later in the season, transpiration becomes dominant (Figure 4.4). Evaporation generally constitutes 20 to 30% of the total ET for the crop growing season for irrigated corn in the Great Plains.
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| Figure 4.4. Example of seasonal patterns of evaporation, transpiration, and ET for irrigated corn in the Great Plains. |
Transpiration and evaporation from soil, plant leaves, and mulch are evaporative processes. Considerable energy is required to evaporate water. The energy absorbed by plants on a sunny and windy summer day would evaporate enough water to cover the soil surface to a depth of approximately 0.4 inches. For an area of one acre, this would equal about 11,000 gal/d.
The energy available for ET comes from several sources (Figure 4.5). Much of the energy comes from extraterrestrial radiation emitted by the sun. Some extraterrestrial radiation is absorbed or reflected in the atmosphere. The radiant energy that ultimately reaches the crop canopy is called solar radiation. Plant and soil surfaces reflect some solar radiation back into the atmosphere. The portion of the solar radiation absorbed varies depending on the color of the surface and other soil and plant properties. The fraction of the solar radiation reflected to the atmosphere is called the albedo. The albedo for plant and soil surfaces ranges from 35% for snow covered soils to 10% for dark soils that are wet. A commonly used value for the albedo of actively growing crops is 23%. In this case, 77% of the solar radiation is absorbed and used for ET and photosynthesis.
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| Figure 4.5. Diagram of energy sources for evapotranspiration. |
Long-wave radiationis the second component of the radiation balance. Energy is transferred due to the temperature difference between objects. In both cropped and uncropped landscapes, the exchange is between the plant and soil surfaces to the atmosphere. Because the atmosphere is cold relative to the sur-face of the earth, long-wave energy is lost from the plant-soil system.
Radiant energy available for ET is called net radiation equal to the absorbed solar radiation minus the emitted long-wave radiation.
Advection is the lateral or horizontal transfer of mass, heat, or other property. Hot, dry winds supply energy for ET due to advection. The amount of energy transferred depends on the wind speed and the vapor pressure of the air. According to Dalton’s law of partial pressure, the pressure exerted by a mixture of gases is equal to the sum of the pressures exerted by each gas if it alone occupied the space. Moist air obeys Dalton’s law. The portion of the barometric pressure due to water vapor is independent from the other gases. The partial pressure due to water vapor is the vapor pressure of the air.
At an air water interface, water molecules continually flow from the water into the air and from the air back into the liquid. If the air is dry, more molecules leave the liquid than enter the liquid resulting in evaporation. If air in a sealed container is left in contact with water long enough, the rate of molecules leaving and entering the liquid surface reach an equilibrium. When equilibrium exists with pure water, the air is saturated with water vapor. The pressure exerted by vapor at this equilibrium condition is the saturation vapor pressure. The saturation vapor pressure depends on the air temperature. The ratio of the actual vapor pressure to the saturation vapor pressure when expressed as a percentage is the relative humidity.
Air in the soil and the stomatal cavity of plants is often near saturation; thus, it has a high vapor pressure. If air surrounding the plant and soil is at the same temperature, but much drier, the vapor pressure will be lower. Water vapor moves from locations of high vapor pressure toward locations with low vapor pressure. If the air around the crop were contained in a chamber, it would become saturated with water vapor and ET would then be negligible because the air could not hold any additional water. If the saturated air were replaced with dry air, ET would resume. The more rapidly the air is exchanged and the drier the air, the higher the ET rate. In windy-arid locations, advection may contribute as much to ET as radiation. However, in humid locations or in areas with little wind, advection may be quite low.
Two other energy sources for ET are the exchange of heat between plants and the soil (called soil heat flux), or between plants and the surrounding air. For example, if the soil is warmer than plants, energy is transferred from the soil to the plants. This energy may increase transpiration. Conversely, if the canopy is warmer than the soil, energy flows toward the soil and transpiration may decrease. The same type of energy transfer occurs between plants and air. Plants that are not stressed for water are generally cooler than the ambient air during the middle of the day. However, if stressed for water, plants will often be warmer than the ambient air (USDA-SCS, 1993).
Two additional factors impact ET. First, there must be a source of water in the soil to supply that used by plants. Second, water must move from the soil to the point where evaporation occurs or into and through the plant to the stomatal cavity where transpiration occurs. If the soil is dry, there is more resistance to water transport in the soil. Also, as plants are stressed, the stomata begin to close and the resistance to water flow from the plant increases. Therefore, ET can be limited by either the amount of evaporative energy or amount of water in the soil.
4.3 Measurement of Evapotranspiration
Plant water use is an important management input; thus, it is critical to quantify ET. Several methods have been developed to measure ET. A few are summarized here.
4.3.1 Aerodynamic Methods
One method of determining ET is to measure the rate of water vapor leaving the plant canopy. The vapor pressure of the air and air flow velocities can be measured at several levels above a plant canopy. By evaluating these measurements, the instantaneous ET rate can be determined. Summing measurements provides an estimate of ET for a day. This technique requires very accurate equipment because the air moves erratically above the canopy.
Another method relies on the Bowen ratio to estimate ET. The Bowen ratio is the ratio of the amount of energy used to heat the air relative to the amount used to evaporate water. Equipment has been developed to measure the Bowen ratio and to compute ET. A major problem is that advection is ignored in the Bowen ratio method which may be an unacceptable assumption for some locations.
4.3.2 Soil Water Methods
Soil water is the source for ET, and several methods have been used to relate changes in soil water to plant water use. The primary components of the soil water balance are illustrated in Figure 4.6. The soil water balance can be expressed as:
where: ET = amount of ET during the period,
AWb = amount of available soil water in the root zone at the beginning of a period,
AWe = amount of available soil water in the root zone at the end of a period,
P = total precipitation during the period,
dg = gross irrigation during the period,
Uf= groundwater contribution to water use during the period,
Ri = surface water that runs onto the area during the period,
Ro = surface runoff that leaves the area during the period, and
dp = deep percolation from the root zone during the period.
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| Figure 4.6. Diagram illustrating the components of the soil water balance. |
The ET can be estimated from Equation 4.1 if all other terms are known or can be approximated. If the groundwater table is more than 6 ft below the soil surface, the contribution from groundwater can be ignored. Rain and irrigation from sprinklers are usually measured with rain gages or similar devices. Measuring devices have been developed for surface irrigation applications. Soil water content can be measured using neutron scattering or other techniques described in Chapter 2. Deep percolation is difficult to measure and is often assumed to be insignificant unless large rains occur, or large irrigations are applied. A significant problem with the soil water balance technique is that repetitive measurements must be made throughout the season. One week is usually the shortest period for using the soil water balance method to estimate ET. If deep percolation or runoff is significant, the soil water balance method is further limited because of the lack of measuring capabilities.
4.3.3 Lysimetry
Lysimeters are specially designed open-top tanks that are filled with soil, preferably undisturbed soil, and planted to the same crop as the surrounding area. The tanks are buried in the field. Water used for ET by plants grown in the lysimeter must come from the soil water within the tank. ET can be measured by monitoring soil water contents and water applications from irrigation or rain. The soil tank is used to isolate soil water from the surrounding area and to prevent run on, runoff, upward groundwater flow, and drainage. For some applications drainage is allowed and the volume of deep percolation is measured. The soil water within the tank can be measured with traditional methods such as neutron probes. The amount of water in the tank can also be determined by weighing the tank, soil, plants, and soil water. Since soil water is the only item that changes significantly over short time periods, the change in weight equals the amount of water used for ET.
Various types of lysimeters have been utilized to measure ET. The most elaborate and accurate lysimeters are called weighing lysimeters (Figure 4.7). These lysimeters use weighing devices to measure water lost from the soil tank. Large plants with deep root zones usually require large lysimeters. Short plants, with shallow root systems, can be measured by lifting small lysimeters and weighing with a scale. The most sophisticated weighing devices are high precision and can be used to measure small changes of weight. A good description of precision lysimeters is given by Marek, et al. (1988). Such systems have counter balanced weighing systems resulting in a measurement accuracy approaching 0.001 inches of ET. The high accuracy is required for daily measurements.
 Cutaway Sketch of Precision-Weighing Lysimeter  | |
| Installation of Large Precision-Weighing Lysimeter | Small Weighing Lysimeter for Turf Grass Measurements |
| Figure 4.7. Examples of weighing lysimeters (picture of large lysimeter is courtesy of USDA-ARS, Bushland, Texas). | |
Other types of lysimeters do not weigh the soil-plant-water system. Non-weighing lysimeters function the same as the field water balance method except upward flow of groundwater and runoff or run on are prevented by the sides and the bottom of the lysimeter. A drainage system is usually installed in the bottom of the lysimeter to measure deep percolation and to prevent water from ponding at the bottom of the lysimeter. Water table lysimeters, common in humid regions, are a second type. With this design, deep percolation is prevented, and a water table is maintained in the lysimeter. Changes in soil water and the elevation of the water table are measured along with other soil water balance terms. Non-weighing and water table lysimeters are usually only accurate enough for estimating the amount of ET over a period of approximately 1 week. More elaborate methods are needed to measure daily or hourly ET rates.
Besides being expensive to install and operate, lysimeters pose several problems. Using lysimeters to measure ET was summarized by Allen, et al. (1991). The best lysimeters are those filled with an undisturbed soil column. These are termed monolithic lysimeters, and if they are large, their filling can be difficult and expensive (Figure 4.7). Regular and careful maintenance of the lysimeter and the surrounding area is required to maintain accuracy. Spatial variability can be significant when measuring ET and several lysimeters may be required. Lysimeters are usually research tools and are too complex and labor intensive for water management.
4.3.4 Plant Monitoring Methods
Plant transpiration can be measured using several techniques. One of these is the autoporometer. With this instrument, a small chamber is clamped onto a growing plant leaf and changes in the humidity and temperature of the air within the chamber are used to compute transpiration during that period. The transpiration rate and other plant responses change very rapidly due to external factors. Therefore, the porometer can only remain on the leaf for a few minutes. Another limitation of the porometer is that only a small part of one leaf is used for measurement. Characterizing the transpiration for an entire crop canopy requires numerous measurements. Further, these measurements only provide instantaneous transpiration rates. Generally, irrigation management requires plant water use for daily and longer time periods. Thus, porometers are primarily used in experiments to investigate plant response to stress and for very short-term water use estimates.
A second method uses infrared thermometers to predict transpiration based upon the difference between the plant temperature and the air temperature. The infrared thermometer has been used successfully to detect plant stress and to predict irrigation timing. If the incoming solar radiation and other energy terms are known, the ET rate can be estimated using the techniques of Hatfield (1983) and Jackson (1982). These techniques are complex and require extensive calculation as well as continuous monitoring of plant temperature. The infrared plant monitoring method can be used to help schedule and manage irrigation but needs further development to estimate ET.
4.4 Calculating ET
Knowledge of plant water use rates is essential to manage irrigation systems accurately. Because measurement of ET is difficult and time consuming, equations have been developed to predict water use rates. These equations are based on weather factors, plant species, and stage of plant development and soil water status. The equations can estimate past water use and forecast future water use which are both essential in planning, designing, and scheduling irrigations.
The simplest equation to predict plant water use is based on two factors:
ET = Kc ETo
where: ET = actual crop or plant ET rate,
Kc = crop coefficient, and
ETo = reference crop ET rate.
Crop coefficients are used to describe the behavior of agricultural crops. The reference ET represents the amount of energy available for ET. This is expressed as the water use rate of a reference crop.
4.5 Reference Crop ET
Reference crop ET is defined as the ET rate from a large expanse of a uniform canopy of dense, actively growing, vegetation provided with an ample supply of soil water. The reference is a hypothetical crop (vegetation) (Allen et al., 1998). Two references are commonly used: (1) a short crop (grass clipped to maintain a height of 5 inches) and (2) a tall crop (alfalfa that is about 20 inches tall). For this text, the short reference crop is used.
Other terms have been used to represent the amount of energy in the environment that is available to evaporate water. Potential ET was widely used historically to represent this energy. Currently some authors are beginning to use reference surface ET. Both terms are synonymous with reference crop ET.
Reference crop ET can be predicted using a standardized equation that utilizes appropriate coefficients and standardized procedures. Numerous methods have been developed to estimate reference crop ET (ETo). The simplest methods generally use average air temperature. The most complex methods require hourly data for solar radiation, air temperature, wind speed, and vapor pressure. There are many approaches between these extremes. The Penman-Monteith equation (Jensen and Allen, 2016) has proven to be reliable for computing reference crop ET for most locations.
The Penman-Monteith equation and associated relationships for calculating coefficients were presented by Allen, et al. (1998). They utilized a short reference crop and presented procedures for either daily or hourly computations. Only the daily version of the procedure is presented here. The short reference crop and daily time steps can be used for many situations. If computations are necessary for mountainous or coastal regions, readers should refer to Allen, et al. (1998) or Jensen and Allen (2016) for appropriate methods.
The Penman-Monteith equation to predict water use of the reference crop was given by Allen, et al. (1998) as:
where: ETo = ET for a short reference crop,
Rn = calculated net radiation at the crop surface,
G = soil heat flux density at the soil surface,
es= saturation vapor pressure of air,
ea = actual vapor pressure of the air,
? = slope of the saturation vapor pressure versus temperature curve,
? = psychrometric constant,
Kt = unit conversion constant,
?a = density of air,
cp = specific heat of air,
ra = aerodynamic resistance of water vapor movement,
rs = bulk resistance of crop and soil surfaces, and
? = heat of vaporization of water.
The amount of energy available to evaporate water determines ET rates. However, the rate of water movement from the soil and plants into the atmosphere also depends upon the resistance to the movement of water vapor within and out of the plant canopy. Wind in the atmosphere above the crop canopy causes air movement to be turbulent which results in mixing of air in the atmosphere. Thus, any water vapor that enters the atmosphere above the canopy readily mixes with air in the atmosphere and there is little resistance to water vapor movement. The flow of air within the upper portion of the crop canopy and in the air layer immediately above the crop is much less turbulent. Since there is little mixing of air from the lower portion of the plant with the air at the top of the canopy, the only way that water vapor can leave the soil plant system is due to vapor pressure gradients. Water vapor flows from areas of high vapor pressure to locations with low vapor pressure. The rate of transfer can be estimated if the difference in vapor pressure is known along with the resistance to the flow of water vapor. The aerodynamic resistance (Figure 4.8) represents the resistance to water vapor movement in the boundary layer just above the crop.
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| Figure 4.8. Diagram of resistances to water vapor flow for evapotranspiration. |
Below the boundary layer the resistance to water vapor flow is controlled by soil and plant properties. For evaporation to occur water must flow through the soil pores to reach the soil/air interface. Resistance to water vapor flow also occurs within the stomata and cuticle of plant leaves. Stomatal resistance varies with the degree of water stress that plants experience, while soil resistance varies with water content. However, for reference conditions, the combined effect of these resistances can be combined into the bulk surface resistance as in Figure 4.8.
While the form of the Penman-Monteith equation in Equation 4.3 is the most accurate, it requires extensive calculations. Equations associated with calculation of variables and the derivations of constants required in Equation 4.3 are very complicated and are explained in more detail by Allen et al. (1998). An American Society of Civil Engineers task force reviewed the use of the Penman-Monteith equation for 82 site-year combinations across the United States (ASCE-EWRI, 2004). They found that a simplified form of the equation provided acceptable results while simplifying calculation procedures. The reduced form of the Penman-Monteith equation for computing daily ET for a short reference crop (clipped grass approximately 5 inches tall) is given by:
where: ETo = daily reference crop ET (in/d),
Rn= net radiation (MJ/m2/d),
U2 = daily wind run measured 2 m above the ground (mi/d),
T = mean daily air temperature measured at height of 1.5 to 2.5 m (°F),
es= saturation vapor pressure of air (kPa),
ea= actual vapor pressure of the air (kPa),
? = slope of the saturation vapor pressure versus temperature curve (kPa/°C), and
? = psychrometric constant (kPa/°C).
The left bracketed term in Equation 4.4 corresponds to the radiation component of the reference ET while the right bracketed term corresponds to the aerodynamic component.
This reduced form of the Penman-Monteith equation does not include the soil heat flux. The soil heat flux for daily data can generally be neglected; however, if shorter or longer time steps (i.e., hourly, or monthly) are considered, the soil heat flux should be included into the computation of ETo as described by Jensen and Allen (2016).
| Table 4.1. Effect of air temperature on saturation vapor pressure and slope of saturation vapor pressure. | |||
| Air Temperature | Saturation Vapor Pressure, es(kPa)[a] | Slope of Saturation Vapor Pressure, ? (kPa /°C) | |
| (°F) | (°C) | ||
| 20 | -7 | 0.37 | 0.029 |
| 25 | -4 | 0.46 | 0.034 |
| 30 | -1 | 0.56 | 0.041 |
| 35 | 2 | 0.69 | 0.049 |
| 40 | 4 | 0.84 | 0.059 |
| 45 | 7 | 1.02 | 0.070 |
| 50 | 10 | 1.23 | 0.082 |
| 55 | 13 | 1.48 | 0.097 |
| 60 | 16 | 1.77 | 0.113 |
| 65 | 18 | 2.11 | 0.132 |
| 70 | 21 | 2.50 | 0.154 |
| 75 | 24 | 2.96 | 0.178 |
| 80 | 27 | 3.50 | 0.206 |
| 85 | 29 | 4.11 | 0.237 |
| 90 | 32 | 4.81 | 0.272 |
| 95 | 35 | 5.62 | 0.311 |
| 100 | 38 | 6.55 | 0.354 |
| 105 | 41 | 7.60 | 0.403 |
| 110 | 43 | 8.79 | 0.457 |
| 115 | 46 | 10.14 | 0.518 |
| 120 | 49 | 11.67 | 0.584 |
[a] Note a pressure of 1 kPa = 0.145 lb/in2. The atmospheric pressure at sea level averages about 101 kPa. | |||
The mean daily air temperature to be used in Equation 4.4 is calculated as the average of the maximum temperature for the day (Tmax) and the minimum temperature for the day (Tmin). The slope of the saturation vapor pressure curve (?) depends on the mean daily air temperature (T). Values of ? can be determined from Table 4.1. The value of the psychrometric constant (?) depends on the elevation of the site that the computations represent. Values for ? are given in Table 4.2. Equations for computing ? and ? are provided by Allen, et al. (1998).
Table 4.2. Value of the psychrometric constant (?) as a function of elevation. at the location of consideration. | |
| Elevation Above Sea Level(ft) | PsychrometricConstant, ? (kPa/°C) |
| 0 | 0.067 |
| 500 | 0.066 |
| 1000 | 0.065 |
| 1500 | 0.064 |
| 2000 | 0.063 |
| 2500 | 0.062 |
| 3000 | 0.060 |
| 3500 | 0.059 |
| 4000 | 0.058 |
| 4500 | 0.057 |
| 5000 | 0.056 |
| 5500 | 0.055 |
| 6000 | 0.054 |
| 6500 | 0.053 |
| 7000 | 0.052 |
The saturation vapor pressure (es) for Equation 4.4 is calculated from:
where eo(Tmax) and eo(Tmin) are the saturation vapor pressure at the maximum (Tmax) and minimum (Tmin) air temperatures for the day, respectively. The actual vapor pressure (ea) is computed as the saturation vapor pressure at the dew point temperature of the air (Tdew). The dew point temperature is usually a direct input from the weather data or is derived from the weather data, then Table 4.1 can be used with Tdew.
Computation of the net radiation (Rn) for estimating ETo involves several steps. First, the amount of solar radiation that would be received on a clear day is determined as a function of the day of the year and the elevation of the site above mean sea level. Figure 4.9 can be used to determine the clear-sky radiation (Rso). Then, the net outgoing long-wave radiation (Rnl) can be determined from Figure 4.10 using the maximum, minimum, and dew point temperatures along with the ratio of the measured solar radiation for the day (Rs) compared to the clear-sky radiation for that date. The net radiation is then computed from:
Rn = (1 – a) Rn – Rnl
where a is the albedo equal to 0.23 for the short reference crop. Use of these figures and equation 4.6 will be illustrated in Example 4.1.
Determination of the reference ET using Equation 4.4 involves numerous computations. A graphical procedure has been developed to accomplish the calculations. Equation 4.4 contains two bracketed sections. The left portion, within the first set of brackets, represents the reference ET that results from solar radiation. The right portion of the equation, in the second set of brackets, represents ET due to the humidification of the air. The second portion is referred to as the aerodynamic component, i.e., the ET due to advection. Figure 4.11 can be used to determine the amount of reference ET from radiation and Figure 4.12 can be used to determine the amount of reference ET from humidifying the air. Example 4.1 illustrates the procedure.
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| Figure 4.9. Diagram to determine clear-sky radiation (Rso) for the northern hemisphere. |
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| Figure 4.10. Diagram to determine net outgoing long-wave radiation. |
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| Figure 4.11. Diagram to determine reference ET from radiation from Equation 4.4. |
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| Figure 4.12. Diagram for determining reference ET from aerodynamic term for Equation 4.4. |
4.6 Crop Coefficients
Evapotranspiration from crops depends on the type of crop, stage of growth, water content of the soil, and the amount of energy available to evaporate water. The reference crop evapotranspiration rate (ETo) is used to represent the amount of energy available. The ET for crops is computed relative to the ETo using the crop coefficient (Kc):
ET = Kc ETo
The crop coefficient consists of the basal crop coefficient (Kco) which represents crops with adequate soil water to maintain transpiration tempered by a stress factor (Ks) to account for water stress and a factor (Kw) to adjust for increased evaporation from a wet soil surface. The crop coefficient is calculated by:
Kc = KcoKs+ Kw
where: Kco = basal crop coefficient for unstressed crops with a dry soil surface,
Ks = stress factor to account for effects of water stress on ET, and
Kw = soil wetness factor to account for increased evaporation from wet soils.
The crop coefficient depends on the growth and development of the crop canopy. A measure of crop canopy development is the leaf area index (LAI). The LAI is the ratio of the amount of leaf area relative to the underlying land area. For example, if the total surface area of one side of the leaves is 2,600 in2 for a 3-ft square area of a field (i.e., 1,296 in2), then the LAI is about 2. The maximum LAI for many irrigated crops often exceeds 5 but depends on the crop variety, plant density and geographical location of the field. An example of the LAI for an annual crop during the year is illustrated in Figure 4.13.
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| Figure 4.13. General shape of crop coefficient curve for an annual crop and the relationship to leaf area index. |
The basal crop coefficient (Kco) resembles the LAI curve during the season (Figure 4.13). Early in the growing season, the basal crop coefficient is small for an annual crop. As the crop sprouts and seedlings start to grow, transpiration contributes a larger portion of daily water use, thus, the crop coefficient increases with canopy development. At some point the canopy develops sufficiently so that the crop coefficient reaches a maximum value. This time is referred to as the effective cover date. After effective cover, the crop coefficient is essentially constant for a period even though the plant canopy continues to expand. The crop coefficient decreases as the crop matures and leaves senesce. For crops that are harvested before senescence, the crop coefficient may remain at or near the peak value until harvest. Some perennial crops, such as citrus, maintain a near constant canopy from one season to the next year. Conversely, some perennial crops, such as fruit trees and grasses, emerge from dormancy and develop vegetation during the initial periods of growth. The initial crop coefficient for a crop breaking dormancy is often higher than for annual plants.
When the plant canopy is small the soil surface is not completely shaded and evaporation from wet soil contributes significantly to ET. When the soil surface is dry the rate of evaporation is small. Following a rain or irrigation the evaporation rate increases. Therefore, the crop coefficient increases immediately following a rain or irrigation (Figure 4.13). As the soil dries the crop coefficient decreases back to the rate for dry soil surfaces. As the canopy expands, the crop shades larger portions of the soil surface and absorbs energy that earlier would have been used to evaporate water from the soil. The effect of evaporation from wet soil, therefore, decreases as the canopy develops.
The crop ET rate decreases when plants are stressed by lack of water. Processes involved in reducing ET are complex but relate to the increased difficulty for the plant to extract soil water. For computing irrigation water requirements, the effect of water stress on ET can be estimated by decreasing the crop coefficient as in Figure 4.13.
4.6.1 Basal Crop Coefficients
The crop coefficient system presented by Allen, et al. (1998) provides a comprehensive list of basal crop coefficients. The basal coefficients represent water use of a healthy, well-watered crop where the soil surface is dry. Allen’s basal crop coefficients are matched to the short reference crop used in this chapter. With this method the growing season is divided into four stages:
(1) initial stage: the period from planting through seedling growth when the soil is minimally shaded by the crop (ground shade < 10%).
(2) vegetative: the period from the initial stage to the time that the crop effectively shades the soil surface (ground shade ?70 to 80%).
(3) midseason: period from full cover until the start of maturation when leaves begin to change color or senesce.
(4) maturing: the period from end of midseason until physiological maturity or harvest.
The progression of the basal crop coefficient during the season is illustrated in Figure 4.14 for field corn at an example site. The fraction of the growing season method developed by Stegman (1988) is used to normalize the time length of the crop growing season. The fraction of the growing season is defined as the ratio of the elapsed time since planting to the time between planting and harvest. During the initial stage, the primary water loss is due to evaporation from the soil. Since the basal curve represents dry soil surfaces, it has a constant value of 0.15 during this period. The initial value of the basal crop coefficient is denoted by Kci.
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| Figure 4.14. Development of the basal crop coefficient throughout the growing season for field corn. |
To compute the crop coefficient during other periods, four points need to be defined. The first point is the fraction of the growing season where canopy development begins (point 1 in Figure 4.14). At this point, the value of Kco = Kci (usually equal to 0.15) is known. The second point occurs when the canopy has developed adequately to provide effective cover. This is when the basal crop coefficient reaches its peak value. Thus, for the second point (point 2 in Figure 4.14), both the peak value of the crop coefficient (Kcp') and FS2 are needed.
The third point in Figure 4.14 is the time when the crop begins to mature (loses vitality). The only value needed for the third point is the time (FS3) since the crop coefficient at that point equals the peak value. The fourth point in Figure 4.14 represents crops that senesce before harvest. To define this point, the value of the basal crop coefficient at harvest (Kcm') must be known. If the crop is harvested before the plant begins to mature, the crop coefficient remains constant at the peak value until harvest.
The five factors needed to compute the basal crop coefficient (FS1, FS2, FS3, Kcp', Kcm') are labeled in Figure 4.14. The values presented in Figure 4.14 are FS1= 0.18, FS2 = 0.41, FS3 = 0.71, Kcp' = 1.15 and Kcm' = 0.15.
| Table 4.3. Basal crop coefficient information for selected crops (adapted from Allen, et al. 1998). | ||||||||
| Crop | Crop coefficients | Fraction of growing season | Soil water stress threshold, frc[a] | |||||
| Kci | Kcp' | Kcm' | FS1 | FS2 | FS3 | |||
| Alfalfa, first cuttings | 0.30 | 1.15 | 1.10 | 0.13 | 0.53 | 0.87 | 0.45 | |
| Alfalfa, later cuttings | 0.30 | 1.15 | 1.10 | 0.11 | 0.56 | 0.78 | 0.45 | |
| Beans, dry | 0.15 | 1.00 | 0.80 | 0.25 | 0.50 | 0.80 | 0.55 | |
| Beans, green | 0.15 | 1.00 | 0.80 | 0.22 | 0.56 | 0.89 | 0.55 | |
| Carrot | 0.15 | 0.95 | 0.85 | 0.17 | 0.42 | 0.83 | 0.65 | |
| Corn, field | 0.15 | 1.15 | 0.15 | 0.18 | 0.41 | 0.71 | 0.45 | |
| Corn, sweet | 0.15 | 1.10 | 1.00 | 0.30 | 0.60 | 0.90 | 0.50 | |
| Cotton | 0.15 | 1.10 | 0.50 | 0.17 | 0.44 | 0.75 | 0.35 | |
| Cucumber | 0.15 | 0.95 | 0.70 | 0.19 | 0.48 | 0.86 | 0.50 | |
| Grapes, table | 0.15 | 0.80 | 0.40 | 0.10 | 0.34 | 0.71 | 0.65 | |
| Grapes, wine | 0.15 | 0.65 | 0.40 | 0.10 | 0.34 | 0.71 | 0.55 | |
| Hay, Bermuda grass | 0.50 | 0.95 | 0.80 | 0.07 | 0.19 | 0.74 | 0.45 | |
| Hay, rye grass | 0.85 | 1.00 | 0.95 | 0.07 | 0.19 | 0.74 | 0.40 | |
| Lentil | 0.15 | 1.05 | 0.20 | 0.15 | 0.35 | 0.76 | 0.50 | |
| Lettuce | 0.15 | 0.90 | 0.90 | 0.29 | 0.67 | 0.90 | 0.70 | |
| Pepper, bell | 0.15 | 1.00 | 0.80 | 0.14 | 0.33 | 0.86 | 0.70 | |
| Potato | 0.15 | 1.10 | 0.65 | 0.27 | 0.45 | 0.88 | 0.65 | |
| Rice | 1.00 | 1.15 | 0.55 | 0.20 | 0.40 | 0.80 | 0.80 | |
| Sorghum, grain | 0.15 | 1.00 | 0.35 | 0.16 | 0.44 | 0.76 | 0.45 | |
| Soybeans | 0.15 | 1.10 | 0.30 | 0.14 | 0.39 | 0.82 | 0.50 | |
| Sugar beet | 0.15 | 1.15 | 0.90 | 0.28 | 0.50 | 0.78 | 0.45 | |
| Sunflower | 0.15 | 1.10 | 0.25 | 0.19 | 0.46 | 0.81 | 0.55 | |
| Tomato | 0.15 | 1.10 | 0.70 | 0.23 | 0.48 | 0.81 | 0.60 | |
| Watermelon | 0.15 | 0.95 | 0.70 | 0.18 | 0.45 | 0.73 | 0.60 | |
| Wheat, spring | 0.15 | 1.10 | 0.15 | 0.15 | 0.33 | 0.78 | 0.45 | |
| Wheat, winter[b] | 0.15 / 0.50 | 1.10 | 0.15 | 0.48 | 0.70 | 0.93 | 0.45 | |
| Pasture, rotated grazing | 0.30 | 0.90 | 0.80 | 0.05 | 0.15 | 1.00 | 0.40 | |
| Pasture, continuous grazing | 0.30 | 0.70 | 0.70 | 0.05 | 0.15 | 1.00 | 0.40 | |
| Citrus, no ground cover | ||||||||
70% canopy | 0.65 | 0.60 | 0.65 | 0.16 | 0.41 | 0.74 | 0.50 | |
50% canopy | 0.60 | 0.55 | 0.60 | 0.16 | 0.41 | 0.74 | 0.50 | |
20% canopy | 0.45 | 0.40 | 0.50 | 0.16 | 0.41 | 0.74 | 0.50 | |
| Citrus, with ground cover | ||||||||
70% canopy | 0.75 | 0.70 | 0.75 | 0.16 | 0.41 | 0.74 | 0.50 | |
50% canopy | 0.75 | 0.75 | 0.75 | 0.16 | 0.41 | 0.74 | 0.50 | |
20% canopy | 0.80 | 0.80 | 0.85 | 0.16 | 0.41 | 0.74 | 0.50 | |
| Apples, cherries, pears | ||||||||
No ground cover, killing frost | 0.35 | 0.90 | 0.65 | 0.13 | 0.33 | 0.88 | 0.50 | |
No ground cover, no frost | 0.50 | 0.90 | 0.70 | 0.13 | 0.33 | 0.88 | 0.50 | |
Ground cover, killing frost | 0.45 | 1.15 | 0.90 | 0.13 | 0.33 | 0.88 | 0.50 | |
Ground cover, no frost | 0.75 | 1.15 | 0.80 | 0.13 | 0.33 | 0.88 | 0.50 | |
[a] The critical fraction remaining (frc) is discussed in section 4.6.2. [b] Larger value for initial period is when fallow wheat provides full ground cover, but the soil is not frozen. | ||||||||
Factors needed to compute basal crop coefficients for some crops are summarized in Table 4.3. Factors for crops not shown in Table 4.3 are reported by Allen, et al. (1998) or Doorenbos and Pruitt (1977). Locally developed crop coefficients can be used when available and reliable.
Doorenbos and Pruitt (1977) stress that “crop coefficient values relate to ET of a disease-free crop grown in large fields under optimum soil water and fertility conditions and achieving full production under the given growing environment.” Crops not meeting these provisions generally use less water unless raised in small fields where the effects of field boundaries can cause ET to be significantly different.
The crop coefficient depends upon the prevailing climatic conditions. The ET of tall crops, such as trees, is affected more by wind than short crops such as grass. This effect is amplified in arid climates. Therefore, Allen, et al. (1998) recommended that the basal crop coefficient be adjusted based on wind speed and humidity. The basal crop coefficient is computed from the values listed in Table 4.3 plus the adjustment factor in Table 4.4.
| Table 4.4. Crop coefficient adjustment factor (Kcf) for wind speeds and relative humidity. | |||||||
| Wind Run(mi/d) | Average Minimum Relative Humidity (%) | ||||||
| 20 | 30 | 40 | 50 | 60 | 70 | 80 | |
| Crop height, 2 ft | |||||||
| 50 | 0.03 | 0.01 | -0.02 | -0.04 | -0.06 | -0.09 | -0.11 |
| 100 | 0.06 | 0.03 | 0.01 | -0.02 | -0.04 | -0.07 | -0.09 |
| 150 | 0.08 | 0.05 | 0.03 | 0.00 | -0.02 | -0.05 | -0.07 |
| 200 | 0.10 | 0.08 | 0.05 | 0.03 | 0.00 | -0.02 | -0.05 |
| 250 | 0.12 | 0.10 | 0.07 | 0.05 | 0.02 | 0.00 | -0.03 |
| 300 | 0.15 | 0.12 | 0.10 | 0.07 | 0.05 | 0.02 | 0.00 |
| 350 | 0.17 | 0.14 | 0.12 | 0.09 | 0.07 | 0.04 | 0.02 |
| Crop Height, 4 ft | |||||||
| 50 | 0.04 | 0.01 | -0.02 | -0.05 | -0.08 | -0.11 | -0.14 |
| 100 | 0.07 | 0.04 | 0.01 | -0.02 | -0.05 | -0.08 | -0.11 |
| 150 | 0.10 | 0.07 | 0.04 | 0.01 | -0.02 | -0.06 | -0.09 |
| 200 | 0.12 | 0.09 | 0.06 | 0.03 | 0.00 | -0.03 | -0.06 |
| 250 | 0.15 | 0.12 | 0.09 | 0.06 | 0.03 | 0.00 | -0.03 |
| 300 | 0.18 | 0.15 | 0.12 | 0.09 | 0.06 | 0.03 | 0.00 |
| 350 | 0.21 | 0.18 | 0.15 | 0.11 | 0.08 | 0.05 | 0.02 |
| Crop Height, 6 ft | |||||||
| 50 | 0.05 | 0.01 | -0.02 | -0.06 | -0.09 | -0.12 | -0.16 |
| 100 | 0.08 | 0.04 | 0.01 | -0.02 | -0.06 | -0.09 | -0.13 |
| 150 | 0.11 | 0.08 | 0.04 | 0.01 | -0.03 | -0.06 | -0.10 |
| 200 | 0.14 | 0.11 | 0.07 | 0.04 | 0.00 | -0.03 | -0.07 |
| 250 | 0.17 | 0.14 | 0.10 | 0.07 | 0.03 | 0.00 | -0.04 |
| 300 | 0.20 | 0.17 | 0.13 | 0.10 | 0.06 | 0.03 | 0.00 |
| 350 | 0.23 | 0.20 | 0.16 | 0.13 | 0.10 | 0.06 | 0.03 |
| Crop Height, 8 ft | |||||||
| 50 | 0.05 | 0.01 | -0.02 | -0.06 | -0.10 | -0.14 | -0.17 |
| 100 | 0.09 | 0.05 | 0.01 | -0.03 | -0.06 | -0.10 | -0.14 |
| 150 | 0.12 | 0.08 | 0.04 | 0.01 | -0.03 | -0.07 | -0.11 |
| 200 | 0.15 | 0.12 | 0.08 | 0.04 | 0.00 | -0.03 | -0.07 |
| 250 | 0.19 | 0.15 | 0.11 | 0.07 | 0.04 | 0.00 | -0.04 |
| 300 | 0.22 | 0.18 | 0.15 | 0.11 | 0.07 | 0.03 | -0.01 |
| 350 | 0.25 | 0.22 | 0.18 | 0.14 | 0.10 | 0.07 | 0.03 |
| Multiplier for Other Crop Heights (multiply times values for 6-ft crop) | |||||||
| Crop Height, ft | 10 | 12 | 14 | 16 | 20 | 25 | |
| Multiplier | 1.17 | 1.23 | 1.29 | 1.34 | 1.44 | 1.53 | |
The initial value Kci is not modified; however, Kcp' and Kcm' are adjusted according to the following equations:
Kcp = Kcp' + Kcf
and Kcm = Kcm' + Kcf
where Kcp and Kcm are the adjusted coefficients, Kcp' and Kcm' are the tabular values of the coefficients (Table 4.3), and Kcf is the crop coefficient adjustment factor for crop height and wind speed (Table 4.4).
The climatic data used to adjust the crop coefficient are average values for the appropriate time of year for a specific region. Daily measured climatic conditions are not used to make the adjustment. The minimum relative humidity used in Table 4.4 can be computed by:
(4.10)
Crop coefficient varies linearly with the fraction of the growing season during the vegetative and maturing growth stages. During the vegetative stage, the crop coefficient is computed with the following equation:
(4.11)
During the maturing stage, the crop coefficient is computed with:
(4.12)
4.6.2 Water Stress Effects
If management or water supply limitations restrict irrigation, the effect of water stress on ET should be considered. For managing irrigation, the effect of water stress on ET can be described using a stress factor Ks which is based on soil water content. A linear function (Figure 4.15) has been used by Hanks (1974) and Ritchie (1973). With this method the stress factor is based on the fraction of the available soil water that is stored in the crop root zone. The stress factor (Ks) is computed as:
Ks= 
for fr < frc
= 1 for fr>frc
where: Ks = stress factor,
fr = fraction of the available soil water that remains, and
frc = critical threshold of fr when stress begins (Table 4.3).
Crops vary in the ability to withstand soil water stress. Some crops are tolerant and maintain ET rates under relatively dry conditions. Other crops are sensitive and ET rates decrease when soil is wetter (Figure 4.15). Values for the soil water stress threshold are in Table 4.3. Threshold values for other crops are available from Allen, et al. (1998).
 | Figure 4.15. Relationship of the soil water stress factor (Ks) to available soil water. |
4.6.3 Wet Soil Evaporation
The increased rate of evaporation due to a wet soil surface is influenced by the amount of canopy development, the energy available to evaporate water, and the hydraulic properties of the soil. The factor (Kw) can be used to predict the amount of wet soil evaporation. The total amount of evaporation from a wet soil should be less than the amount of water received by rain or irrigation.
The method of Wright (1982) has been adapted to account for wet soil evaporation:
Kw = Fw (Kcmax – Kco) ft
Kcmax = 1.2 + Kcf
where: Kw = wet soil evaporation factor,
Kcmax = maximum crop coefficient for wet soil evaporation,
Kcf = crop coefficient adjustment factor (Table 4.4),
Fw = fraction of surface wetted,
t = time since last wetting of soil surface (d),
td = duration of wet soil evaporation (d), and
ft = wet soil decay function.
The fraction of the surface wetted depends on the type of irrigation system (Table 4.5). The duration of wet soil evaporation depends on the type of soil. Sandy soils dry quicker than fine-textured soils. Representative values of the drying duration are given in Table 4.6. Local observations can also be used to determine values for the drying duration.
| Table 4.5. Fraction of the soil surface wetted for various types of irrigation systems. | |
| Wetting Method | Fw |
| Rain | 1.0 |
| Sprinkler irrigation: Above canopy sprinklers In-canopy sprinklers LEPA systems (alternate furrows wetted) | 1.0 0.75 0.5 |
| Borders and basin irrigation | 1.0 |
| Furrow irrigation: Large application depth Small application depth Alternate furrows irrigated | 1.0 0.5 0.5 |
| Surface trickle or drip irrigation | 0.25 |
| Subsurface drip irrigation: Large applications Normal applications | 0.1 0.0 |
| Table 4.6. Duration of wet soil evaporation (td) for selected soil textures and values of the wet soil decay function (ft) for time since wetting (t). | ||||||
| Time Since Wetting, (t), days | Soil Texture | |||||
| Clay | Clay Loam | Silt Loam | Sandy Loam | Loamy Sand | Sand | |
| Duration of wet soil evaporation (td), days | ||||||
| 10 | 7 | 5 | 4 | 3 | 2 | |
| Values of ft | ||||||
| 0 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
| 1 | 0.68 | 0.62 | 0.55 | 0.50 | 0.42 | 0.29 |
| 2 | 0.55 | 0.47 | 0.37 | 0.29 | 0.18 | 0.00 |
| 3 | 0.45 | 0.35 | 0.23 | 0.13 | 0.00 | |
| 4 | 0.37 | 0.24 | 0.11 | 0.00 | ||
| 5 | 0.29 | 0.15 | 0.00 | |||
| 6 | 0.23 | 0.07 | ||||
| 7 | 0.16 | 0.00 | ||||
| 8 | 0.11 | |||||
| 9 | 0.05 | |||||
| 10 | 0.00 | |||||
4.6.4 Methods to Describe Canopy Development
Every year the weather is different causing the rate of crop growth to vary even for the same planting date. Methods are needed to ensure that the predicted rate of canopy development is accurate. The elapsed time (days) since planting and the cumulative growing degree days (sometimes called heat units) since planting are often used as the basis to estimate crop growth. The elapsed time since planting is easier to use; however, some of the annual variation of canopy development can be accounted for using growing degree days.
The definition for growing degree days is:
where: GDDn = cumulative growing degree days on the nth day after planting,
n = total number of days since planting,
Ti = average air temperature [0.5 × (Thigh + Tlow)] on day i, (°F),
Tbase = base temperature at which crop photosynthesis and growth begins,
Thigh = the smaller of the daily maximum temperature and 86°F, and
Tlow = the larger of the minimum temperature and Tbase
The base temperature depends on the crop species. The base temperature for warm weather crops such as corn is typically 50°F, while 40°F is commonly used for cool season crops such as wheat and barley. Because of local variations, the base temperature for specific crops at a location should be determined from regional information.
Growing degree days can be used to determine the fraction of the growing season for computing the crop coefficient:
where: GDDn = the cumulative growing degree days from planting to day n and
GDDm = the cumulative growing degree days needed to reach maturity.
4.7 Intercropping
Some irrigated fields are divided into more than one area for crop rotations. In these cropping systems only one crop is irrigated at a time, so only the ET for that species is relevant for managing that sector. However, interest has grown recently in various forms of intercropping. Intercropping involves growing two or more crops simultaneously juxtaposed within parts of the field. Intercropping includes various forms (Figure 4.16). Mixed intercropping is a complete mixture of multiple species in the same area. Row intercropping involves growing two or more crops at the same time within crop rows. This is common in developing countries and small holdings where an upper story crop—often corn—is first planted and then a shorter crop such as beans is planted in the furrow between crop rows. The crops occupy the same space but may have different growth schedules so the composition of the vegetation changes throughout the season. Alley and strip cropping involves alternating strips of single crops. Strip cropping generally involves paths of equal width off alternating crops. Alley cropping is frequently a form of agroforestry where tree lines are planted beside strips of crops. The width of crop strips in strip and alley cropping is usually some multiple of farming equipment width. Relay and/or cover cropping involves starting a second crop before the first crop is mature or harvested. Crop establishment can be difficult for the second crop in the series.
Computation of water use for intercropped systems is difficult because crops in the mixture have different characteristics. The distribution of leaf area usually involves some shading of lower crops as illustrated for alley cropping in Figure 4.16. Determining the capture of radiation requires information of leaf area distribution vertically and horizontally. Multiple stories of vegetation alter wind patterns within and above crops in the mixture. Rooting characteristics may be quite different leading to dissimilar levels of water stress. The development of the canopy for crops in the mixture may progresses at different rates and the plant density of species in the mixture may vary considerably from field to field. The leaf area, plant geometry and general crop health may be quite different than for single crop fields represented by crop coefficients—especially for small holdings in developing countries. These complexities require more elaborate procedures than simple crop coefficients. Methods are presented by Allen et al. (1998) to estimate compound crop coefficients. Computer models are also available for simulating micrometeorological processes in complex canopies. Methods to estimate intercropped ET are multifaceted and beyond procedures present in this text.
 | Figure 4.16. Examples of intercropping (upper left photo courtesy of USDA-NRCS). |
Irrigation of intercropped systems, especially strip and alley cropping, is difficult to achieve efficiently. Water needs of one crop may differ from requirements of the adjacent crop and some irrigation systems are incapable of applying water in that configuration. The soil water along the boundary between crops is often different than in the middle of the strip or alley. This dissimilarity amplifies the distribution of water need within the strip and confounds soil water monitoring. Soil water monitoring can be effective in row intercropping system like shown in Figure 4.16.
Landscapes contain a mixture of vegetation that is irrigated at the same time, so the composite ET is needed (Figure 4.16). It is difficult to measure ET for such plantings because of the interactions occurring in the landscape and due to the variability of species in landscapes. Planting densities vary considerably among landscapes. Young landscapes contain less leaf area than mature plantings and are less capable of absorbing radiation; thus, mature landscapes usually have higher transpiration rates. A landscape of trees with underlying shrubs or groundcover captures more radiation and will require more water than trees underlain with mulch. Many landscapes include a range of microclimates varying from shaded or protected areas to hot, sunny, and windy areas. These variations influence ET in ways not representative of large areas of homogeneous vegetation inherent in crop coefficients.
Costello and Jones (2014) provide updates to a method to estimate ET using landscape coefficients for multiple species:
ET = KL × ETo
where KL is the landscape coefficient. The amount of ET for a landscape varies as a function of the species planted, the density of vegetation, and microclimate conditions. Assigning numerical values for these factors enables estimation of the landscape coefficient:
KL = KP × KD × KM
where KP is the plant species factor, KD is the density factor and KM is the microclimate factor. The range of values for each factor for types of vegetation are presented in Table 4.7.
The landscape coefficient procedure differs from the crop coefficient procedure regarding the adequacy of water. Crop coefficients approximate water use for crops under well-watered conditions intended to maximize production. Landscape coefficients approximate the water needed to maintain the aesthetic or functional acceptability of a landscape. Rather than a measure of how much water can be lost from an area, the landscape coefficient is an estimate of the water needed to maintain landscape quality.
| Table 4.7 Range of plant species, density, and microclimate factors for landscape coefficients (adapted from Costello and Jones, 2014). | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Type of Vegetation | Species Factor (KP) | Density Factor (KD) | Microclimate Factor (KM) | ||||||||
| High | Avg. | Low | High | Avg. | Low | High | Avg. | Low | |||
| Trees | 0.9 | 0.5 | 0.2 | 1.3 | 1.0 | 0.5 | 1.4 | 1.0 | 0.5 | ||
| Shrubs | 0.7 | 0.5 | 0.2 | 1.1 | 1.0 | 0.5 | 1.3 | 1.0 | 0.5 | ||
| Groundcover | 0.7 | 0.5 | 0.2 | 1.1 | 1.0 | 0.5 | 1.2 | 1.0 | 0.5 | ||
| Mixed: trees, shrubs, and groundcover | 0.9 | 0.5 | 0.2 | 1.3 | 1.1 | 0.6 | 1.4 | 1.0 | 0.5 | ||
| Turf grass | 0.8 | 0.7 | 0.6 | 1.0 | 1.0 | 0.6 | 1.2 | 1.0 | 0.8 | ||
Species factors (Kp) for five types of vegetation are included in Table 4.7. Three levels are included for each type of vegetation depending on the water use characteristics of the plants included in the landscape. Mixed species plantings have a range of water use like those of tree, shrub, and groundcover species. The values presented in Table 4.7 represent the range assumed for individual species. Costello and Jones (2014) provide species for a very large number of specific plant species to develop an integrated species factor for the landscape.
The density of vegetation within a landscape varies considerably. Even though individual plants in a sparsely planted landscape may use more water for a given leaf area than individual plants in a dense landscape, water lost from the entirety of the dense planting will likely be greater than for the sparse landscape. To account for these differences, the density factor varies from a low of 0.5 to a high of 1.3. The density factor involves estimating the percent ground cover for a portion of the landscape. Canopy cover is defined as the percentage of ground shaded. A 50% ground cover will shade half of the land area in the landscape. With a canopy cover less than 60% a reduction in KD is appropriate. Trees with a canopy cover of 25% or less should have a density factor of 0.5.
An upward adjustment of KD is warranted when trees are the prevailing vegetation, but shrubs and groundcover also occur. Essentially, the groundcover or shrub represents another tier of vegetation where water loss occurs. Total water use would be expected to be greater for multiple tiers than for a single tier. Shrubs and groundcover are equivalent in KD values. A complete or nearly complete cover (about 90%) with either shrubs or groundcover represents the average condition for these vegetation types and has a density factor 1.0. Higher density values may result when plantings are predominately groundcover or shrubs, but another vegetation type also occurs. Density values for high-density mixed plantings are greater than for other three vegetation types. High density plantings with three vegetation types would be assigned a maximum density factor of 1.3. Low-density mixed plantings may also occur and a commensurate reduction in the density factor is appropriate. Young or widely spaced plantings also qualify for a low-density value.
Environmental conditions vary significantly within a landscape. Buildings and other structures and paving typical of urban landscapes strongly influence foliar and air temperatures, wind, and humidity. For example, trees in parking lots are subject to higher temperature and lower humidity than trees in parks. Areas within a landscape that have different environmental conditions are called microclimates. Microclimates must be considered in estimating water needs. The microclimate factor accounts for such differences.
The microclimate factors are relatively easy to set. An average microclimate condition is where buildings, pavement, slopes, and reflective surfaces do not influence the microclimate. Essentially, this condition is like that for the reference ET conditions. For these conditions, the microclimate climate factor (KM) is set to 1.0.
In a “high” microclimate condition, features increase the evaporative condition in the irrigation zone. Landscape surrounded by heat-absorbing surfaces or reflective surfaces or those exposed to particularly windy conditions would be assigned high microclimate factors. For example, medians, parking lots, west sides of buildings, west and south sides of slopes, and wind tunnel areas would be assigned a higher climate factor. Such areas might have a microclimate climate value between 1.0 and 1.4. See Figure 4.17 for examples of high and low microclimate factors.
“Low” microclimate conditions are as common as high microclimate conditions. Plantings that are shaded by buildings or other landscape features for part or most of the day, or that are protected from winds, would be assigned low microclimate values. Examples of conditions that should receive low microclimate factors include areas on the north sides of buildings, courtyards, under wide building overhangs, and the north side of slopes. Such situations would be assigned microclimate values between 0.5 and 1.0 (Figure 4.17).
 | Figure 4.17. Landscapes with varying plant density and microclimate factors. |
Application of the landscape methodology is very well developed by Costello and Jones (2014) but is complicated. That publication should be utilized for specific applications. The method may also offer a basis for estimating ET for other intercropped systems.
4.8 Accessing Climatic Information
The rate plants use water determines irrigation schedules and ultimately the depth of irrigation water to apply. Without this information it is difficult to efficiently manage irrigation systems. The methods in this chapter rely on data for reference crop conditions with the Penman-Monteith equation. This involves accurate measurement of several climatic variables. Most irrigators will not measure these variables at their field.
Fortunately, weather data networks have been established across the United States to provide data for the Penman-Monteith method. In most situations, networks also compute the reference crop ET. Care must be taken to ensure that the reference ET provided by the service is for a short reference crop (i.e., grass clipped to a height of 5 inches). Providers of the climatic data may also compute water use rates for crops grown in the local vicinity. While these calculations should be carefully monitored for accuracy and reliability, the computed values can often be used directly for managing irrigation. Readers should refer to the local Extension Service at their university for assistance in locating climatic data for their location. An example of data provided from the High Plains Regional Climate Center is provided in Table 4.8. These data can be used in irrigation scheduling and other applications.
Smith (1992) developed a decision support program to estimate crop water requirements for a wide range of crops. The program can utilize local weather data or historical climatic information to develop average water requirements for planning purposes. The program can be used for irrigation scheduling and is useful for managing whole-farm irrigation systems.
Data are also becoming available from analysis of Landsat and other remote sensing systems. Techniques have been developed to predict ET and crop coefficients. There are several current and emerging techniques along with new satellite capabilities that promise future opportunities for irrigation planning and management. The example from Barker, et al. (2018) shows that remote sensing can accurately predict crop coefficients periodically throughout the growing season. Methods like that by Barker et al. (2018) also provide methods to estimate ET and crop coefficients between the days that satellites pass over the specific locations. Currently, these methods are still being developed but promise substantial opportunity for real-time irrigation management in the future.
| Table 4.8. Example weather, reference crop ET and growing degree day data from High Plains Regional Climate Center. | ||||||||||
| Month | Day | Air Temperature, °F | WindSpeed(mi/hr) | SolarRadiation(Lang/d) | Rain(in) | ETo(in/d) | GrowingDegreeUnits | |||
| Max. | Min. | Average | Dew Point | |||||||
| 7 | 2 | 89.5 | 63.9 | 76.7 | 70.4 | 8.2 | 559 | 0.16 | 0.26 | 25 |
| 7 | 3 | 87.5 | 63.1 | 75.3 | 65.9 | 5.4 | 651 | 0 | 0.27 | 25 |
| 7 | 4 | 88.4 | 64.6 | 76.5 | 68.3 | 4.1 | 668 | 0 | 0.26 | 25 |
| 7 | 5 | 86.7 | 64.3 | 75.5 | 67.8 | 3.0 | 542 | 0 | 0.21 | 25 |
| 7 | 6 | 91.1 | 65.6 | 78.4 | 70.2 | 4.5 | 600 | 0 | 0.25 | 26 |
| 7 | 7 | 91.3 | 67.4 | 79.4 | 69.6 | 9.5 | 659 | 0 | 0.34 | 27 |
| 7 | 8 | 92.2 | 62.6 | 77.4 | 66.0 | 11.4 | 643 | 0.62 | 0.38 | 24 |
| 7 | 9 | 83.8 | 59.9 | 71.9 | 65.6 | 5.0 | 638 | 0 | 0.24 | 22 |
| 7 | 10 | 88.7 | 62.5 | 75.6 | 68.8 | 6.7 | 597 | 0.01 | 0.26 | 24 |
| 7 | 11 | 85.0 | 62.0 | 73.5 | 66.0 | 5.8 | 647 | 0 | 0.26 | 24 |
| 7 | 12 | 85.1 | 58.1 | 71.6 | 64.0 | 4.5 | 548 | 0 | 0.22 | 22 |
| 7 | 13 | 91.8 | 63.1 | 77.5 | 68.0 | 8.7 | 636 | 0.14 | 0.33 | 25 |
| 7 | 14 | 77.8 | 63.4 | 70.6 | 65.3 | 6.4 | 407 | 0.01 | 0.16 | 21 |
| 7 | 15 | 81.4 | 60.8 | 71.1 | 63.3 | 4.2 | 584 | 0 | 0.22 | 21 |
4.9 Summary
Management of irrigation systems depends on knowledge of the rate that plants use water. This chapter presents methods to compute the evapotranspiration rate for field crops. The methods are based on the Penman-Monteith equation used to compute the ET of a healthy and well-watered grass reference crop that is approximately five inches tall. Climatic data for air temperature, relative humidity, solar radiation, and wind speed are needed to compute the reference ET. The water use of crops and vegetables is computed by multiplying the reference ET times a crop coefficient. The crop coefficient represents the effect of canopy development as well as plant water stress and increased evaporation from wet soils.
Questions
1. Explain what a grass reference crop is and why this concept is used in estimating crop water use.
2. Describe the sources of energy that affect ET. Which sources are most important in semiarid locations?
3. An irrigation district must establish a schedule for water delivery to the 1,000 producers that they serve. Describe and explain the procedure you would use to develop the schedule.
4. Why does a cotton crop have a higher ET rate than field beans when they both completely shade the soil (i.e., after effective cover)?
5. List and explain three ways data on the rate of crop ET are used in irrigation management.
6. Compute the basal crop coefficient on July 1 for tomatoes planted on May 1 in the Central Valley of California.
7. Given the following information:
Maximum daily air temperature = 95°F Daily solar radiation = 28 MJ/m2/d
Minimum daily air temperature = 72°F Elevation above sea level = 1,500 ft
Dew point temperature = 68°F Latitude = 30°N
Daily wind run = 200 mi/d Date is July 25
a. Compute the daily reference ET using the Penman-Monteith method.
b. What fraction of the total ETo is due to the aerodynamic term?
c. What fraction of ETo is caused by the radiation term?
8. The reference ET is 0.30 in/d, the basal crop coefficient is 0.6, and it has been two days since a thorough rain occurred. The soil water depletion is about 20% of the available water holding capacity for the silt loam soil. How much crop ET occurs for these conditions if frc = 0.5? Assume that Kcf = 0.
9. A crop is irrigated with a subsurface drip irrigation system. The reference ET is 0.25 in/d and the basal crop coefficient is 1.05. The soil water depletion is 50% before irrigating, and frc = 0.5. The root depth is 4 ft, and the soil is a sandy loam. How many days will a 2-inch irrigation last if Kcmax = 1.2 and Kcf = 0.0?
| Weeks after May 1 | Average ETo(in/d) | Weeks after May 1 | Average ETo (in/d) | |
| 1 | 0.21 | 11 | 0.26 | |
| 2 | 0.22 | 12 | 0.26 | |
| 3 | 0.23 | 13 | 0.25 | |
| 4 | 0.24 | 14 | 0.25 | |
| 5 | 0.24 | 15 | 0.21 | |
| 6 | 0.24 | 16 | 0.23 | |
| 7 | 0.25 | 17 | 0.22 | |
| 8 | 0.25 | 18 | 0.20 | |
| 9 | 0.26 | 19 | 0.18 | |
| 10 | 0.26 | 20 | 0.17 |
10. How many growing degree days would accumulate in one day if the maximum and minimum air temperatures were 90° and 65°F, respectively and the base temperature was 50°F?
11. Given the following data:
Corn planted on May 1.
Effective cover date July 10 (end of week 10).
Maturity date is September 10 (end of week 19).
Irrigated to prevent soil water stress.
The crop is irrigated, or it rains once a week.
The soil is silt loam.
a. Compute the average daily ET for corn for each week of the season.
b. What is the total seasonal ET?
References
Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998). Crop evapotranspiration: Guidelines for computing crop water requirements. Irrigation and Drainage Paper No. 56. 300(9), D05109. Rome, Italy: Food and Agricultural Organization of the United Nations.
Allen, R. G., Howell, T. A., Pruitt, W. O., Walter, I. A., & Jensen, M. E. (1991). Lysimeters for evapotranspiration and environmental measurements. Proc. International Symposium on Lysimetry. ASCE.
ASCE-EWRI. (2004). The ASCE standardized reference evapotranspiration equation. Standardization of Reference Evapotranspiration Task Committee Final Report. Reston, VA: ASCE Environmental and Water Resources Institute.
Barker, J. B., Neale, C. M., Heeren, D. M., & Suyker, A. E. (2018). Evaluation of a hybrid reflectance-based crop coefficient and energy balance evapotranspiration model for irrigation management. Trans. ASABE, 61(2), 533-548.
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Hatfield, J. L. (1983). Evaporation obtained from remote sensing methods. In D. Hillel (Ed.), Advances in irrigation (Vol. 2, pp. 395-415). New York, NY: Academic Press.
Jackson, R. D. (1982). Canopy temperature and crop water stress. In D. Hillel (Ed.), Advances in irrigation (Vol. 1, pp. 43-81). New York, NY: Academic Press.
Jensen, M.E., & Allen, R. G. 2016. Evaporation, evapotranspiration, and irrigation water requirements, ASCE Manuals and Reports on Engineering Practice No. 70. 2nd ed. Reston, VA : American Society of Civil Engineers.
Marek, T. H., Schneider, A. D., Howell, T. A., & Ebeling, L. L. (1988). Design and construction of large weighing monolithic lysimeters. Trans. ASAE, 31(2), 477-484.
Ritchie, J. T. (1973). Influence of soil water status and meteorological conditions on evaporation from a corn canopy. Agron. J., 65, 893-897.
Smith, M. (1992) CROPWAT: A computer program for irrigation planning and management. Irrigation and Drainage Paper No. 46. Rome, Italy: Food and Agricultural Organization of the United Nations.
Stegman, E. C. (1988). Corn crop curve comparisons for the central and northern plains of the U.S. Appl. Eng. Agric., 4(3), 226-233.
USDA-SCS. (1993). National engineering handbook. Part 623, Ch. 2. Irrigation water requirements. Washington, DC: USDA-SCS.
Wright, J. L. (1982). New evapotranspiration crop coefficients. J. Irrig. Drain. Div., ASCE, 108(IR2), 57-74.
Wright, J. L., & Jensen, M. E. (1972). Peak water requirements of crops in southern Idaho. J. Irrig. Drain. Div. ASCE, 98(IR2), 93-201.