沙漠研究 24-1, 141-144 (2014)
Ἃ₍◊✲ 24-1, 141 - 144 (2014)
Journal of Arid Land Studies
Journal of Arid Land Studies－ DT11 Refereed Paper －㸫DT11 Refereed Paper㸫

Quantifying Crop Water Use in Arid and Semi-Arid Regions- Opportunities Based on Soil-Plant Water Relations Xuejun DONG*1), Daniel LESKOVAR 1), Kevin CROSBY2) and Thomas MAREK3)
Abstract: Proper management of water is vitally important to maintain and sustain crop production in arid and semi-arid regions,where water is often a limiting factor of crop growth. Despite progress made in the past decade, accurate prediction of water flow inthe soil-plant system remains challenging. This paper briefly reviews opportunities for improving the precision of water use
estimation for field crops considering current knowledge of soil-plant water relations and related multidisciplinary sciences. In
addition to making full use of currently available soil/plant sensors and wireless technology, the combined use of crop
coefficient-based approach and those involving dynamic modeling of soil-plant-atmosphere system water flow is helpful for robust
and sensitive estimation of crop water requirements under variable environmental conditions.
Key Words: Crop coefficient, Root water uptake, Transpiration rate, Water demand, Water supplyagriculture.

1. Introduction
In settings of agricultural production, the amount of water acrop uses is often closely linked to biomass accumulation(Monteith, 1986). Yet, the quantity of water use in different
growth stages of the crop can vary greatly depending on
various biotic and abiotic factors (Jagtap and Jones, 1989; Ojhaet al., 2009; Leskovar et al., 2012; Djaman and Irmak, 2013).
Determining the water requirement of a crop is especially
important for optimal irrigation water scheduling, considering
the growing trend of water scarcity worldwide. To make thebest use of every drop of water in agricultural production, land
managers need to effectively regulate soil water status in plantroot zone by controlling major components of the soil-plantsystem influencing water flow. Under certain instances,moderate level of water stress developed in the root zone may
not significantly curb crop yield (Fereres and Soriano, 2007).
In recent years, with the development of quantitative models,soil/plant sensors, and the wide access of wireless technology,
there are opportunities for improving the accuracy of cropwater use estimation under field conditions (Greenwood et al.,2010). However, a timely synthesis of the related ideas
and/or integrated approaches directly applicable to theirrigation management of field crops is lacking. In thismini-review, we discuss current methods of estimating cropwater use, soil water flow dynamics and root water uptake withthe emphasis of identifying opportunities for the use ofrelatively simple models of soil-plant system water flow thatcan directly benefit optimal irrigation scheduling in irrigated* Corresponding Author: xuejun.dong@ag.tamu.edu

2. Demand-based Method for Estimating Crop Water
Use
One of the most important components of soil waterbalance is evapotranspiration (ET). The demand-based cropwater use estimation uses a two-step approach, whereby crop
ET is computed by potential ET and a crop specific coefficient(Kc) (Allen et al., 1989). This approach has been widely usedto determine the growth stage-specific crop water use inirrigation management of various crops (Ko et al., 2009;Leskovar et al., 2012; Djaman and Irmak, 2013; Ghamarnia etal., 2013). As shown by Piccinni et al. (2009), the applicationof the crop coefficient method for crop ET estimation can save
up to 25% of water use in spinach crop in southwest Texas,
USA. As the crop coefficient method of ET estimation isbased on potential ET, the crop ET may be overestimatedunder water-limited conditions as shown by Djaman and Irmak(2013) in maize growing in Nebraska, USA. Also, the crop
coefficient for a particular crop may fluctuate under different
environmental conditions (Jagtap and Jones, 1989; Annandaleand Stockle, 1994), making the application of the crop
coefficients developed at one location difficult to use inlocations with different climate and/or soil/management
conditions. It may be possible to mitigate the shortcomingsof the crop coefficient method by considering the water supply
to plant roots and the dynamic shoot-root interactions. For
example, this is important, under situations of deficit irrigation(Costa et al., 2007; Fereres et al., 2007).
㸦Received, September 23rd, 2013; Accepted, February 12th, 2014㸧Uvalde, TX 78801 USA
1) Texas A&M AgriLife Research and Extension Center2) Department of Horticultural Sciences, Texas A&M University, College Station

3) Texas A&M AgriLife Research and Extension Center

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3. Supply-Based Method for Estimating Crop Water UseMonteith (1986) outlined a simplified framework of watersupply and demand for crop growth and proposed a scheme for
optimal irrigation scheduling. It is unknown, however, if thisheuristic understanding has received enough attention in thepractice of crop irrigation management. Based on asimplified soil-plant system water flow model of Campbell andDiaz (1998), Annandale et al. (2000) proposed a dynamic
approach to estimate crop water requirement under both fulland deficit irrigation. Soil water potential and root density
distribution in the soil profile were used to predict root water
extraction from different soil layers. These models also need
input data such as crop thermal time requirements foremergence, reproductive development, leaf senescence andmaturity, as well as the transpiration-biomass ratio. Theauthors suggested that their approach may provide a moreaccurate prediction of crop water use under conditions ofvariable water availability than the crop coefficient-based ET
estimation method.
Nonetheless, similar to the crop coefficient-based approach,the model of Annandale et al. (2000) also relies on computed
potential (instead of actual) transpiration. In addition,transpiration modeling based solely on root distribution may
bypass some subtle but important mechanisms by which plantroots absorb water and nutrients from the soil medium underconditions of water stress. One example is the compensatedand active uptake of water and nutrients by plant roots, as
shown both by theoretical analysis (Lai and Katul, 2000) andcomputer simulations supported by field observed data of soil
water contents (Adiku et al., 2000; Li et al., 2001; Skaggs et al.,2006; ŠimĤnek and Jopmans, 2009; Yadav et al., 2009; Donget al., 2010). The compensated root uptake of water andnutrient is defined as the increased uptake from one part of soil
depth (where water or nutrient is readily available) tocompensate for the reduced uptake at soil depths where wateror nutrient is limiting. It emphasizes the importance of rootactivity (as opposed to root mass/length density) in taking up
water and nutrients (Lai and Katul, 2000). The degree ofcompensation may reflect a crop’s ability of maintaining water
uptake under moderate stress. This mechanism may beutilized to yield additional water saving in deficit irrigation,
including the technique of partial root drying (Costa et al.,2007; Pereres and Soriano, 2007; Leskovar and Piccinni, 2005),
if the amount of water a crop can mine from the soil throughcompensated uptake can be quantified under field conditions.
To our knowledge, few studies have investigated thispossibility.
Most of the models and analysis leading to thecompensated uptake mechanism have some importantdifferences from the simplified transpiration models ofCampbell and Diaz (1998) and Annandale et al. (2000). The
first difference is that these models typically employ additional
empirical parameters to modify root water uptake (in additionto having a root distribution function similar to the lattermodels). Despite increased flexibility in adjusting root water
uptake capacity (and correctly simulating root uptake
compensation), it is usually difficult to link the compensateduptake with specific biological mechanisms (ŠimĤnek andJopmans, 2009), primarily due to the empiricism of using theadditional modifying parameters.
These ‘compensated’models also differ from the model of Annandale et al. (2000) inthat the Richards equation, instead of the cascade scheme, isused in describing water flow. For management-orientatedapplications, however, these models may sometimes havestability problems due mainly to the highly nonlinear nature of
the soil hydraulic functions as used in association with theRichards equation. The difficulty of obtaining complete
information of the hydraulic functions from different soil
depths and across a study field will further limit the applicationof these ‘compensated’ models. Fortunately, with theavailability of the wireless-enabled soil water sensors(Greenwood et al., 2010) and the appropriate data assimilation
technique (Lü et al., 2011; Shin et al., 2012), the problem of
uncertainty in soil hydraulic properties will to some extent beameliorated. Finally, similar to the models of Campbell andDiaz (1998) and Annandale et al. (2000), in these‘compensated’ models water to be partitioned among roots
located in different soil layers comes from potential
transpiration, instead of actual transpiration. The problem
with the approaches using potential transpiration is thatstomatal control of transpiration may sometimes override theeffect of root water uptake compensation under drought stressconditions.

4. Field Measurements in Support of the Estimation ofActual Crop Transpiration
Dong et al. (2010) showed that plants growing in themixed-grass prairie of North Dakota, USA exhibitedcompensated root water uptake, which enabled the plants toefficiently absorb soil water both during a dry period and underample water supply following a heavy rain event. In themeantime, some other models not including the mechanism forcompensated uptake (such as that by Annandale et al., 2000)
also accurately simulated soil water depletion during thegrowing season of a crop. A question that arises naturally isthat if there is a water stress threshold that triggers the uptake
compensation in a crop under particular growing condition?
Answering this question may (a) help to clarify the143

physiological mechanisms responsible for the root water
uptake compensation, and (b) lead to more accurate predictionof crop transpiration and assist in efficient delivery of deficit
irrigation to field crops. This also motivates the use of simple
models describing stomatal control of water loss, because,
similar to the situation in root water uptake, the most likely
situation for canopy water loss is that both the total leaf areaindex (LAI) and stomatal conductance play a role under water
limited situations. Models developed by Johnson et al.
(1991) and Gao et al. (2002) are of heuristic value for thisefforts because they are relatively simple and consider thestomatal function from a “macroscopic” perspective. Yet, thesimplicity goes along with the requirements of experimental
data needed to estimate model parameters. This calls forreliable field measurements of leaf stomatal conductance, leaf
area index, soil water content and evapotranspiration, as can bedetermined using a lysimeter (Marek et al., 2006). Due tonon-linearity, the model of Gao et al. (2002) may not be giving
reliable results under very dry conditions. It should be
beneficial to calibrate several models (demand-, supply- andstomatal-based) within the same field experimental system for
improved estimation of crop water use under varied field
conditions. This may also offer opportunities for identifying
conditions under which the water use estimation fromparticular models becomes off-bound (unreliable). The
combined use of different classes of models can offer bothrobustness and sensitivity in crop water use estimation, withthe crop coefficient-based method (demand-based) providingbase-line values for the growth-stage specific ET, and thesupply- and stomatal-based models giving further fine-tuning
for the ET estimations and the possibility of saving additionalamount of irrigation water while maintaining crop harvest
index. Field experiments of crop water use are needed tosubstantiate this scheme.

5. Opportunities for Future Research
The development and availability of soil/plant sensors andwireless technology provide opportunities for deploying a large
number of soil sensors in the field for measuring soil water andsalinity. This will significantly expand researchers’ ability ofcalibrating soil-plant system water flow models aimed atirrigation management. The availability of high quality dataof soil water can to some extent compensate for the lack of soil
hydraulic properties for solving the water flow equations.
Future availability of high resolution satellite-based surface
soil water data (such as that from the Soil Moisture Active
Passive (SMAP) satellite, which will provide top 5 cm soil
water content at a 2-3 days cycle and 6 square mile spatial
resolution for the globe; http://smap.jpl.nasa.gov), along withapplications of new data assimilation methods (Shin et al.,2012), will facilitate improved prediction of crop
evapotranspiration.
The release of new crop varieties with improved traits fordrought/heat stress tolerance will provide opportunities fortesting different crop water use models considering genotype,environment, and management interactions (Jones et al., 2003;
Sinclair and Muchow, 2009; White, 2009; Boote et al.,2013).
The most desirable models of crop water use for assisting
farmer’s decision-making in irrigation water management inworld’s dryland regions should be relatively simple ones, theuse of which should not require an extensive user input, but
can give a robust prediction of water dynamics while reducing
the risk of yield loss under uncertain climate. The combined
use of conceptually different transpiration models in
conjunction with experimental data, computing (Shin et al.,2012; McCarthy et al., 2013) and web support (Geogiev andHoogenboom, 1999) may allow this to happen sooner.

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