Soil Water Balance in the Sudano-Sahelian Zone (Proceedings of the Niamey Workshop, February 1991). IAHS Publ. no. 199,1991.

Soil and plant factors affecting the estimation of water extraction by crops

P. J. GREGORY CSIRO Dryland Crops and Soils Research Unit, Private Bag, PO Wembley, Western Australia, 6014, Australia

Abstract This paper briefly reviews some soil and plant factors affecting the estimates of water use by crops. Evapotranspiration is frequently obtained as the residual term in the soil water balance equation so it is important to know the other terms accurately. Direct evaporation from the soil surface is often a substantial component of évapotranspiration (estimates range from 36-75%) and recent advances in micro-lysimetry have provided long-term estimates of this quantity. New developments with time domain reflectometry (TDR) offer prospects of making these measurements in a less time-consuming manner. Estimation of drainage can be made by inspection of changes of water content with time in selected soil layers, but calculation is often difficult because of spatial variability in soil hydraulic properties. The problems of layered and stony soils are discussed and the use of geostatistical approaches and scaling are described. Root systems of arable crops grow deeper during the growing season to secure new supplies of water. The rate of downward root growth of rainfed crops indicates that, for most, crop growth will be limited by the supply of water accessible to the roots.

INTRODUCTION

Measurements of the soil water balance may be undertaken for several purposes (e.g. determination of the amount of drainage to underlying aquifers) but in this paper I shall concentrate on measurement for the purpose of describing water use by crops. Several studies have shown that the amount of dry matter produced by crops is directly proportional to the amount of water transpired (de Wit, 1958; Tanner, 1981) and that if allowance is made for the saturation deficit of the atmosphere then dry matter production per unit of transpiration is a constant dependent on the crop (Monteith, 1990); this relation comes about because of the physiological coupling of C02 and water vapour diffusion via the stomata. However, transpiration is difficult to measure directly and when evaporation is small, measurements of évapotranspiration have also been found to be closely related to dry matter production (Day et al, 1978). Estimates of évapotranspiration are frequently obtained from the soil water balance equation and the development of the neutron probe has greatly facilitated this approach because routine measurements of changes of soil water storage with a degree of

261

P. J. Gregory 262

spatial integration have been possible. This approach has been particularly successful on deep soils with horizons that have similar texture and has led to the development of theories and models that allow the prediction of water extraction and crop productivity (Alaerts et al., 1985; Protopapas & Bras, 1987).

In some soils, however, the change in soil water storage is difficult to measure accurately and estimates of évapotranspiration are complicated by continued drainage and runoff. Moreover, when crop canopies are sparse, évapotranspiration may be a poor indicator of crop productivity. The purpose of this paper is to review briefly the soil and plant factors affecting estimates of water use by crops. In particular I shall discuss the problems of and approaches to estimating water use by crops growing in spatially variable and layered and shallow soils. The importance of roots in extracting water and means of predicting their distribution and activity in using water will be highlighted.

THE SOIL WATER BALANCE

The mass balance for soil water in the root zone is:

P + U = E + T + D+R + AS (1)

where P is precipitation, U is upward capillary flux into the root zone, E is direct evaporation from the soil surface, T is transpiration, D is drainage out of the root zone, R is surface runoff and AS is the change of water stored in the root zone. In the simplest case, U, D and R are, or are assumed to be, zero so that water use (évapotranspiration, ET) is readily estimated from P and AS measured with a neutron probe. From the viewpoint of estimating potential crop production, we should like to know each term in equation (1) so that T is known with certainty; several approaches have been used in conjunction with the neutron probe in attempts to achieve this and some will now be discussed.

Separation of evaporation and transpiration

In many arid and semiarid regions, evaporation from the soil surface is a substantial component of the total crop water use (évapotranspiration) and yield and water use are frequently unrelated. Table 1 shows several examples of almost identical water use for crops managed in different ways; invariably improved agronomy (particularly fertilizer applications) has resulted in greater dry matter production but similar water use. In the winter rainfall regions of northern Syria, Cooper et al. (1987) estimated that up to 75% of the water use of sparse barley crops grown on sandy clay soils was as evaporation; Allen (1990) measured E as 77% of total ET for barley crops in the same region and found that fertilizer applications reduced E by 10%. On sandy soils at the ICRISAT Sahelian Centre, Wallace et al. (1990) estimated that

2 63 Soil and plant factors affecting water extraction

Table 1 Effects of crop management on total water use (ET) and yield of crops grown in rainfed environments

Author Crop Treatment ET E T Shoot dry matter

(mm) (mm) (mm) (kg ha' )

Allen, 1990 Barley + fertilizer 214 144 70 4184 - fertilizer 209 160 49 2946

Cooper et at., 1987 Barley + fertilizer 239 143 96 4470 - fertilizer 235 160 49 3110

Cooper & Gregory, 1987 Lentil + weeds 270 1128 - weeds 237 2038

ICRISAT, 1985 Millet + fertilizer 165 4750 - fertilizer 163 2417

about 36% of the seasonal rainfall would be evaporated from sparse crops of rainfed millet.

Reliable measurements to separate E and T are difficult to make and are very time-consuming. Good measurements of E can be obtained using micro-lysimetry if care is taken in installation (it is most important that surface features such as crusts are not disturbed) and the micro-lysimeters are replaced frequently. Micro-lysimeters have been used successfully in field studies limited to single drying cycles of a few weeks following irrigation (Shawcroft & Gardner, 1983) but there are few long-term studies. Allen (1990) evaluated the technique over a period of 100 days in rainfed barley crops and found that in rain-free periods the micro-lysimeter and water balance measurements of fallow soil agreed to within 0.25 mm day"1. However, when rain fell, E measured by the micro-lysimeters was 0.1-1.1 mm day"1 less than that from the water balance. Because a large proportion of the total E occurred on rainy days, Allen concluded that the usefulness of micro-lysimeters is seriously limited in rainfed systems. An alternative technique for measuring E is to use time domain reflectometry (TDR) which, unlike the neutron probe, is well-suited for work near the soil surface (Topp & Davis, 1985). Recent work at CSIRO Division of Environmental Mechanics, Canberra (White et al, 1988) has shown that non-intrusive surface TDR probes can be used to follow the changes in water content during evaporation.

Transpiration can be measured directly using a porometer and concomitant measurements of leaf temperature, water vapour concentrations in the atmosphere, boundary-layer resistance and green area index. Table 2 compares estimates of transpiration measured with a porometer with ET measured using a neutron probe for millet crops grown in Niamey, Niger at 3 row spacings (Azam-Ali, 1983; Azam-Ali et al, 1984b). On the sandy soil used in this experiment with crops growing in stored water, E would be expected to be a small component of ET once the surface had dried; the general close agreement between T and ET confirms this expectation. Despite the demonstrable accuracy of porometry it is a very time-consuming approach

P. J. Gregory 264

Table 2 Comparison of transpiration (T) estimated using a porometer with water use (ET) measured using a neutron probe for millet grown in 3 row spacings (from Azam-AU, 1983); units mm day'1

Days after sowing

23-26 26-30 30-33 33-37 37-40 40-44 44-52

Total 23-52 (mm)

Row spacing:

Narrow:

T

3.5 4.6 3.3 2.3 2.3 2.0 1.8

76.6

ET

4.0 4.3 3.9 3.2 2.9 2.1 1.1

79.7

Medium:

T

2.9 4.1 4.0 4.0 3.8 3.2 3.9

101.8

ET

3.8 3.7 3.9 3.8 5.0 3.0 2.3

97.9

Wide:

T

0.7 1.4 1.9 2.5 2.8 3.1 3.9

75.5

ET

2.3 2.4 2.1 2.2 3.6 0.9 1.7

59.2

and inappropriate for measurements over a whole growing season; it has, however, been used to good effect over periods of a week or two (e.g. Wallace et al, 1990).

Measurement and estimation of drainage

The need to estimate drainage is often one of the major limitations to estimating crop water use accurately. In deep, uniform soils with predomi­nantly coarse texture it was observed that soils drain to an almost constant water content within a few days of rainfall. This led to the development of the concept of "field capacity" which was later equated to a corresponding value of matric tension and pore size. This concept can be used to estimate drainage in certain limited circumstances. For example, Fig. 1 shows the changes in water content beneath a crop of millet grown on a sandy soil at Niamey, Niger (Azam-Ali et al., 1984b). The crop was irrigated until 15 days after sowing (DAS) but thereafter it grew on moisture stored in the soil profile. Substantial amounts of drainage occurred between 16 and 23 DAS to give water content in the deeper soil layers of 9 to 10%; this corresponded well with values of water content obtained at a suction of 5 kPa.

In many soils, however, particularly where 2:1 clays are present, field capacity is ill-defined and slow drainage may occur for long periods during the growing season. In such circumstances drainage must be estimated, otherwise substantial errors may be introduced into the calculation of crop water use (Rouse, 1969, gives an example of at least 20-30%). Drainage can be estimated using an empirical approach described by McGowan (1974) and McGowan & Williams (1980). Changes of water content in each soil layer are inspected and changes in the rate of water loss interpreted as either drainage or uptake by crops (Fig. 2). As drainage proceeds, the water content in a soil layer decreases, resulting in a smaller hydraulic conductivity and smaller rates of drainage. If a sudden increase in the rate of water loss occurs from a soil

265 Soil and plant factors affecting water extraction

80

160

Volumetric water content (%)

12 _ l

Fig. 1 Changes in volumetric water content beneath a young crop of rainfed millet; figures against each line are days after sowing (from Azam-Ali et al, 1984b).

2%

Depth (cm)

120

May

Fig. 2 beneath of water

June July

Changes in volumetric water content at selected depths a crop of winter wheat; the arrows represent the beginning extraction by roots (from Gregory et al, 1978).

layer it cannot be attributed to drainage and therefore indicates extraction by plants; the discontinuity in rate of water loss thereby provides a means of distinguishing drainage and evaporation. Analysis of changes in soil water content by this method assume that roots do not extract water from a layer while drainage is occurring and vice versa. Supplementary measurements with tensiometers and calculations suggest that this assumption is correct and the technique has been used successfully to obtain values of water use by crops (e.g. Gregory et al., 1978; Goss et al, 1984).

Drainage may also be calculated from measurements of hydraulic conductivity and gradients of hydraulic potential measured at some depth below the depth of rooting (Rose & Stern, 1965). Such calculations assume

P. J. Gregory 266

that lateral water flow can be ignored and that spatial variation in hydraulic properties is either small or can be described adequately. There are many soils where such calculations are extremely difficult and some of the features contributing to this difficulty will now be considered.

SOIL CONSTRAINTS TO ESTIMATES OF CROP WATER USE

Layered soils

Marked changes in texture within a soil profile pose several problems in estimating soil water balances. For example, in the duplex soils (coarse sand overlying kaolinitic clay) of Western Australia the junction between layers is visually obvious but variable in depth over short distances. Using a neutron probe to estimate storage in the profile blurs the distinction between layers and can result in substantial errors in short-term estimations of water use. Moreover, in such soils there is frequently accumulation of water above the less permeable clay resulting in perched water tables for prolonged periods during the growing season. Figure 3 shows the spatial variability of depth to

Fig. 3 Variability in the depth of the perched water table on a duplex soil in Western Australia (a) after about 36 mm of rain (b) and 7 days later.

267 Soil and plant factors affecting water extraction

the perched water table within a field (1.2 ha) and the transient nature of the water table following a large storm (36 mm rain). In such circumstances it is impossible to estimate water use accurately because the use of water from the water table is unknown and, in this case, there is additional evidence suggesting lateral movement of water off the site ("runoff" at the sand/clay interface). Such features are not confined to the soils of Western Australia and layers of clay and ferralitic pans cause similar problems in soils of the Sudano-Sahelian region (Bertrand, 1989).

Shallow and stony soils

Depth and texture of the soil are the major problems affecting the storage of soil water and have a direct effect on the potential length of the growing season in rain-fed environments (Smith & Harris, 1981). On deep soils the additional rain in wet years can be stored at depth and used to extend the period of grain-filling, but on shallow soils there is little benefit from wetter years.

Stones can create many problems with the measurement of water content and, if porous, may also contribute to the store of plant available water. There are few published examples of the effects of stones on water availability to plants but for shallow soils overlying porous materials the contribution may be significant. For example, limestone and chalk contain pores with remarkably uniform diameter that are filled with water that is potentially available to crops. Gregory (1989) found that beneath cereal crops growing on shallow soil (25 cm depth) over chalk, water was depleted to a depth of 3 m during 3 growing seasons. Measurements of the gradients of water potential indicated upward movement of water to the root zone (confined predominantly to the upper 60 cm but with occasional roots to 1 m in fissures). Depletion below 0.9 m amounted to 26-42% of the total depletion and calculation of the upward flux (the hydraulic conductivity was estimated from the moisture characteristic curve for chalk) confirmed the potential for substantial upward movement. Estimates of the dry matter produced by this water showed that the water from below the rooting depth contributed, on average, 8% of the shoot dry matter of winter cereals and 22% of that of spring cereals.

Soil spatial variability

Spatial variation in soil properties has long been recognized but much of the soil physics literature has developed assuming soil was a homogeneous, isotropic material. This approach has led to water and solute flow being described by deterministic equations (the Richard's equation) which, in practice, poorly represent the field situation because of the inherent variation in many of the terms (especially hydraulic conductivity) used to calculate the flux. This realization of the importance of taking account of spatial variability has led to several new approaches to calculating the components of the soil water balance.

P. J. Gregory 268

The problems created by heterogeneity lead to three fundamental questions: first, is it possible to describe the average, large-scale flow of water using the Richard's equation (developed for small-scale movement)? Second, what are the effective parameters determining flow over a large area and how are they related to the localized hydraulic properties? Third, what is the quality of the averaged estimates of flow produced by the measurement and calculation procedures? Put simply, how can results measured in one area best be extended to another? Sharma (1990) has reviewed several of the approaches that have been adopted to answer such questions.

The spatial dependence of a property (Z) can be expressed by a semivariogram function yk:

7k= Knl[ZÇX.)-Z&.+ k)]2 (2) /=1

where n is the number of pairs of measurements for a distance lag k. If yk is approximately constant for k >0, the semivariogram indicates that the observations are spatially independent. However, if values of yk change in a consistent manner as k increases then the observations are spatially dependent. As an example, Fig. 4 shows a semivariogram constructed from observations of the water table depth on a site in northern India (from Warrick & Nielson, 1980). The variogram shows a consistent variance with pairs of water-table depths differing by less than 1 m over a horizontal distance of 2 km. Because the plot of the semivariogram continues to increase with the distance between samples (the lag), the sampling points are not statistically independent, i.e. a distance of at least 2 km between samples would be necessary to remove the spatial dependence. Ideally, the semivariogram should reach an asymptote and the point at which this is achieved is the limit of the range of influence; measurements taken further apart are spatially independent.

1.0

CM

_E n Q. CD

TJ

o 0.5 - Q CO

CD

O

g

0 0 1 2

Lag (km)

Fig. 4 Semivariogram of depth of water table in a 675 ha field in northern India (from Warrick & Nielsen, 1980).

269 Soil and plant factors affecting water extraction

Scaling theory (Miller, 1980) provides a possible means of expressing soil hydraulic variability by a single parameter; the process involves simplifying problems to express them in the smallest number of variables based on concepts of similar media. For example, the spatial variability of the saturated hydraulic conductivity (K) can be expressed as:

* * = « ? * * (3)

where Ksi is Ks at location /, K* is the scaled mean K for all locations and a. is a scaling factor for location i. If the mean of a ; is made equal to 1 then equation (3) can be rearranged to obtain K* from a sample size of n measurements of K.;

SI

K* = [Vn I (Kf5]2 (4) i=l

Now, not only is Ks variable in space, it is also very tedious, time-consuming and requires specialist knowledge to measure. If the scaling factor for an easily measurable soil physical property (e.g. particle size) can be obtained, it should in theory also be possible to use the same scaling factor for Ks. This approach has obvious advantages over the direct measurement of many values of K but is it appropriate to use one scaling factor for several hydraulic properties?

Bonsu & Laryea (1989) compared the scaling factors calculated from measured values of K , sand pore-volume, clay pore-volume, clay content and effective porosity for 109 samples of an Alfisol at the ICRISAT Center, Hyderabad, India. Their results showed that the distribution of scaling factors obtained from measured Ks, clay pore-volume and clay content was very similar for samples containing <10% gravel. However, the presence of gravel in the soil seriously compounded the problem of scaling K .

Although several researchers have demonstrated the variability of individual soil properties and the desirability of including this variation in the calculation of drainage by the use of stochastic models (e.g. Mantoglou & Gelhar, 1987), few attempts have been made to assess the implications for calculations of water use by crops. McGowan (1974) showed that cumulative loss of soil water beneath a spring barley crop was measured as 114, 132, 146 and 206 mm at four replicate points. However, as Table 3 shows, most of

Table 3 Variability in estimates of seasonal soil water depletion, drainage and évapotranspiration beneath spring barley crops (from McGowan, 1974)

Profile Soil water depletion Drainage Evapotranspiration (mm) (mm) (mm)

1 114 8 106 2 132 20 112 3 146 32 114 4 206 76 130

P. J. Gregory 270

this variation was accounted for by differential drainage from the different profiles so that évapotranspiration was much less variable. Whether processes such as évapotranspiration are generally much less variable than individual properties within the soil is open to further investigation. In closed canopies, well- supplied with water, evaporation is likely to be determined principally by large-scale atmospheric conditions. In sparse crops growing in arid conditions, évapotranspiration may indeed be as variable as drainage is in wetter climates. Reichardt et al. (1990) measured water use by maize along a transect of 120 m on an Oxic Paleudalf at Piracicaba, Brazil, and found that ET varied from 1.6 to 3.2 mm day"1 during one sampling period; these data suggest that soil spatial variability does have effects on calculations of ET.

ROOT SYSTEMS AND CROP WATER USE

One feature of the growth of arable crops is that the root system grows deeper during initial growth and thereby secures access to new sources of water deeper in the soil profile. Monteith (1986) inspected seasonal records of neutron probe data to determine the downward rate of growth of root systems and combined this with a simple model of water extraction by a static root system to estimate the supply of water available to crops of sorghum. Passioura (1983) suggested that volumetric water content (9) and time (t) could be related by:

9 = 6aexp (-Kit) (5)

where / is the root length density, K is a constant and Qa can be regarded as the maximum amount of water that roots are capable of extracting from the soil. Examination of neutron probe data (Fig. 5) showed that the effective depth of rooting moved downwards at about 3.5 cm day"1 for sorghum and millet grown on Alfisols and Vertisols. Combining this result with equation (5) gave maximum rates of extraction of about 1.5 mm day"1 from the Vertisol and 1.2 mm day"1 from the Alfisol. Monteith (1986) pointed out that both rates were much less than evaporation from a class A pan (6-7 mm day'1) and it follows that the rate of transpiration (and thus rate of plant growth) must have been limited by the supply of water to the shoots. For most crops growing on stored soil water, the rate of crop growth is therefore dependent on the size and activity of the root system. The requirement to supply water to match the demand imposed on the shoot system means that crops in dry areas generally invest a greater proportion of their dry matter in roots. For example, the root system of young plants of millet grown on an irrigated Alfisol at ICRISAT, Hyderabad, was about 20% of total plant weight (Gregory & Squire, 1979), whereas the same variety grown on a sand at the AGRYMET Centre, Niamey had a root system that was 32% of total plant weight (Azam-Ali et al., 1984a). Similar changes in partitioning have been reported by Hamblin et al. (1990), for wheat crops grown under rainfed conditions in Western Australia. They demonstrated a

271 Soil and plant factors affecting water extraction

Time (days) 0 20 40

0

E

x: a <D

a

100

Fig. 5 Change in the effective rooting depth of three crops of sorghum (k, Alfisol; • and M, Vertisol; and one of pearl millet (o, Alfisol) grown at ICRISAT (from Monteith, 1986).

constant trend of increased partitioning to roots from the most favourable to the least favourable treatments.

Gardner (1983) examined many experiments in which soil water uptake had been measured and, like Monteith (1986), observed that the shape of the extraction zone, once established, seemed to remain almost constant as it moved downward. Examination of the water extraction versus depth curves at the time at which plants first began to wilt showed similarities between many crops. By scaling both axes appropriately, results from 40 experiments were shown to fall on a single curve. If the curve were represented as a straight line such that water uptake decreased from 1 to 0 in going from scaled depth 0.2 to 0.8 then 40% of the total extraction was in the upper 20% of the rooting depth. The corresponding values for the next successive 20% increments were 33%, 20% and 7%.

CONCLUDING REMARKS

Estimation of crop water use using the mass balance equation has become almost routine since the advent of the neutron probe. However, accurate estimates of water flux are more difficult to achieve because there are spatial and temporal variations in both hydraulic conductivity and gradients of matric potential. The recent development of geostatistical and stochastic approaches to calculating water fluxes offer hope for more reliable

P. J. Gregory 272

estimates in the future. In rainfed regions, crops rely on roots to both exploit rain showers at

the soil surface and extract water from deep in the soil profile. The results presented demonstrate the particular importance of downward penetration when crops are grown on water stored in the soil profile.

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