Determination of soil hydrologic properties under simulated rainfall condition

Agricukural watermanagement ELSEVIER

Agricultural Water Management 29 (1996) 267-281

Determination of soil hydrologic properties under simulated rainfall condition S. Mohanty *, R. Singh Agricultwal

and Food Engineering

Department,

’

Indian Institute of Technology,

Kharagpur

721 302, India

Accepted 4 July 1995

Abstract Two important soil hydrologic properties viz. soil water retention (h-0 relationship) and unsaturated hydraulic conductivity (K-0 relationship), were determined under simulated rainfall conditions. The h-0 relationship was determined using a rainfall simulator infiltrometer (RSI). The resulting hB relation was then used as input to the Van Genuchten’s model (VGM) for determining the K-8 relationship. In order to validate the results obtained through RSI-VGM combination, the commonly adopted instantaneous profile method (IPM) was also applied to develop the K-B relationship independently. Functional sensitivity analysis, conducted to simulate the soil water storage using the model Soil Water Actual Transpiration Rate (SWATR), showed that the simulated results obtained through RSI-VGM combination were in agreement with those from IPM. Kevword.s: Rainfall simulator; Van Genuchten’s model; Instantaneous analysis; Soil water retention curve; Unsaturated hydraulic conductivity

profile method; Functional

sensitivity

1. Introduction Modelling of water movement in soils requires knowledge of the soil hydrological properties, especially the soil water retention curve (h-8 relationship) ; and hydraulic conductivity-water content relationship (K-O relationship). These two basic hydrologic characteristics of a porous material must be measured experimentally. These properties are needed by various models to predict the factors that influence irrigation design, crop yield or leaching requirement. Many investigators have developed extensive mathematical theories to describe soil water movement under different sets of initial and boundary conditions (Hillel, 197 1; Kirkham and Powers, 1972). However, if these theoretically derived equa* Corresponding author. ’ Presently BOYSCASTFellow,

Water Recources Division, DHI, AgemAlle5,

0378-3774/96/$15.00 0 1996 Elsevier Science B.V. All rights reserved .SSDIO378-3774(95)01202-S

DK2970, Horsholm, Denmark.

268

S. Mohantq. R. Singh /Apkultural

Water Management 29 (1996) 267-281

tions are to be applied for the description or prediction of actual processes in the field, a way of measuring pertinent soil parameters on a realistic scale is a must. Therefore, attempts have been made to develop various laboratory (Youngs, 1964; Watson, 1966; Hillel and Gardener, 1970) as well as field methods (Bouma et al., 1971; Hillel et al., 1972; Libardi et al., 1980; Booltink et al., 1991) for the determination of the same. However, laboratory methods often do not give accurate resul ts because of measurement of parameters on discrete and small samples removed from the field. On the other hand, the field methods are expensive and time consuming. Hence, various numerical methods have been developed to determine these properties easily and quickly (Marshall, 1958; Millington and Quirk, 1959; Van Genuchten, 1980). But, before using these numerical methods, their accuracy of prediction has to be established. Further, for the in-situ determination of soil hydrologic properties, the ponded infiltration case is mostly used, and very few attempts have been made to study these soil hydrologic properties under simulated rainfall condition (Jeppson et al., 1975; Touma and Albergel, 1992). In the present study (Mohanty, 1993)) a combination approach, involving a rainfall simulator infiltrometer (RSI) and a numerical method (Van Genuchten, 1980), has been adopted to determine the soil hydrologic properties; and to eliminate the drawbacks associated with laboratory and field methods.

2. Materials and methods 2.1. Rainfall simulator injiltrometer

(RSI)

The RSI developed at Indian Institute of Technology, Kharagpur, India (Bhardwaj and Singh, 1992) was used in this study. The various components of the RSI are drop forming mechanism, water reservoir, pressure head regulator, wind shield, infiltration cylinder and runoff collector. 2.2. Van Genuchten’s

model (VGM)

In this model, the relationship between matric suction (h), in millimetres, water content ( 0) is assumed to be of the following form:

and volumetric

where, S=L

H- H.

(2)

e,- e,-’

8, is saturated water content, 0,. is residual water content, and cr, m, n are parameters. Further, the relationship between hydraulic conductivity and water content is derived on the basis of Mualem’s theory (Mualem, 1976) and is expressed as: K,.(S)

=s”‘[

1 - (1 -S”~~r)n~]2...

(3)

S. Mohanty, R. Singh/Agricultural

Water Management 29 (1996) 267-281

269

Where, K,. is relative hydraulic conductivity with respect to saturated hydraulic conductivity in metres per day. For the determination of K-B relationships by VGM, the value of m is determined from the slope of soil water retention curve (h-13 relationship), and then substituted in Eq. 3. 2.3. Instantaneous

profile method (IPM)

IPM was first developed by Watson ( 1966) ; and later Hillel et al. ( 1972) used it in field condition. This method requires frequent (preferably continuous) and concurrent measurement of the soil wetness and matric suction profiles under conditions of vertical drainage alone (evapotranspiration prevented). The general equation describing the flow of water in a vertical soil profile is given by:

de ag _=at dz”’

(4)

where, q is flux of water, z is vertical depth co-ordinate This equation can be integrated to yield: q=

$2 I

and t is time.

...

Hence from the measurements of matric suction profiles and moisture profiles, it is possible to obtain instantaneous values of potential gradients and fluxes operating within the profile, and therefore, also the hydraulic conductivity values using Darcy’s equation as given below:

K=4

(6)

ahlaz’.’

2.4. Experimentation The experiments were conducted in the Department of Agricultural and Food Engineering, Indian Institute of Technology, Kharagpur for determining the soil water retention curve and hydraulic conductivity-water content relationship. 2.5. Determination

of soil water retention curve (h-8 relationship)

using RSI

On a perfectly levelled plot, six mercury tensiometers at 150 mm, 300 mm, 450 mm, 600 mm, 750 mm and 900 mm depths and an access tube of 1 .l m depth were installed along the periphery of a circle of a radius 600 mm. Another three tensiometers at 300 mm depths were installed on a circle of 350 mm radius in order to check the uniformity of flow of water. The water was applied by the RSI installed at the centre (Fig. l), at an intensity of 100 mm h ’for 1 h each, four times, with 1 h gap in between two consecutive applications. The excess runoff was conveyed to a distant place from the experimental site through a polyethylene pipe. The experiments were carried out with the assumption that the soil is

210

S. Mohut~ty. R. Singh /A~ricultuml

Water Mmnpment

29 (1996) 267-281

e

ACCESS

TUBE

TENSIOMETRIC

600mm

A 300mm A 1 LSOmmm

75Omm 900mm

Ail

Fig.

I Experimental

DEPTHS

??150mmO

dlmens~onz

,n mm

layout for RSI experiments

homogeneous and isotropic for a particular layer. Thus, the water applied at the centre was expected to travel equally to all directions. Then at different times, the simultaneous measurements of matric suction and water content at different depths were taken using tensiometers and neutron moisture meter respectively, to plot the soil water retention curve (hH relationship). 2.6. Deteminution

of K-8 relationship

using IPM

To apply IPM in the field, a perfectly levelled plot of 3 m* size was used. A polyethylene sheet was put around the plot in a 1 m deep trench to avoid the lateral flow of water. An access tube of I. 1 m length and six tensiometers at 1.50 mm, 300 mm, 450 mm, 600 mm, 750 mm and 900 mm depths were installed. Water was ponded on the surface long enough to saturate the entire profile and the plot was covered by a polyethylene sheet to prevent any water flux across the surface (evaporation). The tensiometric and neutron moisture meter readings were taken for 25 days. Though the tensiometric readings were taken every day, the neutron moisture meter readings were taken at 1, 2, 3, 4, 5, 8, 10, 12, 1.5, 16, 19, 22 and 25 days after saturation respectively. In the initial stages, readings were taken everyday, because at this time the moisture content of the soil decreased rapidly. 3. Results and discussion 3. I. Textural analysis of the soil Soil samples were collected from the six depths at which the tensiometers were installed and textural analysis was conducted by using pipette method (Black et al., 1965). Table 1 presents the relevant information.

S. Mohnnty, R. Singh /Agricultural

Water Management 29 (1996) 267-281

271

Table I Textural analysis data Depth (mm)

Sand (%)

Silt (%)

Clay (%)

Bulk density (KNm~‘)

IS0

61 54 54 SO so 49

19 14 18 16 14 13

20 32 28 34 36 38

16.8 16.3 IS.7 IS.9 IS.7 15.9

300 450 600 7.50 900

It is evident from Table 1 that the percent of sand decreases with depth and the percent of clay increases with depth. 3.2. Soil water retention curve using RSI The tensiometric readings obtained from three check tensiometers placed at 300 mm depth and 350 mm radius each were found to be almost identical. This confirmed that the flow of water was same in all directions. The matric suction and water content values obtained from tensiometric and neutron moisture meter readings respectively were used to plot the soil water retention curve (Fig. 2). The figure shows an increase in water retention capacity with depth which is in agreement with the increase in clay with depth.

? m150 ? nndan300 bQ._Q9 450 a-600 ++++, 750 x/xxx 900

10

,,,,,,,,,,,/,,,,II~l~IIIIlIIII~IIlIIIIIII~IIII~I~~I 0 500 1000 1500 2000

matric

suction

(mm)

Fig. 2. Soil water retention curves.

mm mm mm mm mm mm

2500

S. Molzaniy, R. Singlz /Agricultural

212

Table 2 Values of parameters of Van Genuchten’s model Depth

0,

fl,

(mm)

(a)

(%)

Water Management 29 (1996) 267-281

for different layers CY

m

II

150

32.0

6.0

0.0186

0.395

I .653

300

32.5

9.0

0.0165

0.336

I.507

450

34.0

9.0

0.0160

0.340

I.515

600

3.5.0

8.5

0.0139

0.352

I.542

750

37.0

9,s

0.0124

0.407

I.685

900

40.0

13.5

0.0105

0.394

I.653

3.3.

Determination

of K-O relationship using VGMfrom

the developed h-8 relationship

VGM was used for the determination of K-8 relationship from the h-8 relationship in Fig. 2. This model requires the saturated and residual water content values of the soil for the determination of K-0 relationship. Since the residual water content values of the present soil were not known, from the trend of soil-water retention curve and texture of the soil, a range of residual water content ( 0,) values for each layer was obtained. Then for each layer, for different values of 0, within the range, the slope of the soil-water retention curve, S,, was found out at a point 13,,such that e,, = ( O,Y + 0,.) 12. From the obtained values of S,,, the parameter nz was found out using the following equation (Van Genuchten, 1980) : 1 - exp( - 0.8S,,)

m=

l_- 0.5755 S,,

; 0<

I 0.1 I -0.025 S:,

s,,<

1 (7)

;Sp>l

...

S;t

Once m was known, parameters 1 n=iG...

a=‘(21’.~-])‘-.J.,. lzy

n and (Ywere obtained using the following equations:

(8) (9)

where, It,, is matric suction corresponding to 0,,, in millimetres. The values of m, n and (Ythus obtained, for different 0, values were substituted in Eq. 1 to estimate the values of S at different suction heads. Finally the values of 0, resulting in the least mean square deviation between measured and estimated S values, were selected for each layer. Thus obtained value of m was used to find out the K-8 relationship for different layers using Eq. 3. The values of parameters of VGM applicable for different depths are presented in Table 2. 3.4. K-0 relationship using IPM The obtained neutron moisture meter and tensiometric data from IPM are presented in Fig. 3 and Fig. 4 respectively, as moisture profile curves and matric suction profile curves.

S. Mohunty, R. Singh /Agriculturul Water Management 29 (1996) 267-281 50

40

w.c!.!s150 &AAAt+300 Qeeeo450 e 600 w 750 *xIxx 900

x e 38

mm mm mm mm mm mm

30

El u 3Tf 20 .k? E 10

t;r&

(days)

Fig. 3. Moisture protile curves.

~DDoD150 ae_hIe 300 beep 450 **4+* 600 w750 cz_EL= 900

01

,(

)

,,,,,,,,,,,,,,,,,,,

I

0

20 t;rkz

(days)

Fig. 4. Matric suction profile curves.

mm mm mm mm mm mm

I,

213

274

UQQd 1)~ t;ttts XIXXX

Fig. 5. Hydraulic

conductivity-water

450 600 750 YOO

content relationship

The moisture profile curves show the decrease in moisture content of the soil with time for all layers. Moisture profile curves of 300 mm, 450 mm, 600 mm and 750 mm layers are somewhat close to one another, whereas the moisture profile curves of 150 mm and 900 mm layers are away from the above four curves. This most likely results due to more sand in the 150 mm layer and more clay in the 900 mm layer. The matric suction profile curves show an increase in matric suction with time for all depths. The hydraulic head profiles were derived from the tensiometric data by adding matric potential to the gravitational potential at specific points in matric suction profile curves. In this case, the soil surface was taken as the datum for the calculation of gravitational potential. Then, the hydraulic conductivity-water content relationship was derived from the moisture profile curves and hydraulic head profile curves by using IPM. The K-H relationships obtained by this method were found to be exponential for all depths (Fig. 5). The relationships representin g the K-H curves are presented in Table 3. The saturated hydraulic conductivity values for all depths, extrapolated from K-O curves are also presented in Table 3. Further the K-H curves show a very close K-O relationship for 300 mm and 450 mm depths, which indicates that these two belong to a single layer. 3.5. Cornparisorl

qf K-O relationships obtained by RSI-VGA4 and IPM

In order to validate the results obtained by RSI-VGM combination, the K-0relationships obtained from the two approaches are compared (Fig. 6). It is seen that the RSI-VGM method overestimates the hydraulic conductivity value at low moisture contents and underestimates it at high moisture contents for top four layers (Fig. 6(a) ; Fig. 6(b) ; Fig. 6(c) ;

S. Mohunty, R. Singh /Agricultural

Table 3 K-O relationships

obtained from instantaneous

Depth

(mm) 150 300 450 600 750 900 “Saturated hydraulic

Water Management 29 (1996) 267-281

profile method

K-0 relationship K(mmday-I); 0(%)

rG Cm day-‘)

K=2.997 X 10d4 e”.47780 K= 1,446X 10-‘e”~“9”‘~ K= 7.445 X 10-6 eo.s~~3~

1.311 1.136 1.029 0.475 0.172 0.136

K= 1.659 X IO-r e”.4wosf3 K= 1,192~ IO-~~“.~*QO K=2.409

215

X lo-’ e0-3sss0

conductivity.

Fig. 6(d) ) , whereas it underestimates the hydraulic conductivity value for all moisture contents for bottom two layers (Fig. 6(e) ; Fig. 6(f)). For comparing the two methods, statistical tests for the difference of means and for root mean square error (taking logarithmic residuals) were applied. The results of these statistical tests are presented in Table 4. The test for difference of means shows that the difference in results of two approaches is not significant at any depth, whereas the test for root mean square error shows a significant difference between the two methods for the bottom three layers. The difference in the two approaches may be attributed to the fact that the VGM gives an infinite slope (&C/d@ at saturated water content,which amounts to an infinite value of saturated hydraulic conductivity at water content equivalent to the total porosity (Touma and Albergel, 1992). 3.6. Functional

sensitivity analysis through simulation of soil water storage

To further compare the performance of the RSI-VGM method with the IPM, soil water flow, useful in irrigation and drainage planning, was simulated with the model Soil Water Actual Transpiration Rate (SWATR) (Feddes et al., 1978)) which is an one dimensional, finite difference model that deals with the transient water flow in a non-homogeneous soilroot system that is under groundwater influence. It can also handle simpler flow cases i.e. with no roots, without groundwater table etc. However, it is capable of handling two layered soil profile only. Since in the present study five layered soil profile is dealt with, necessary modifications were incorporated in the model. The initial and boundary conditions were kept the same for RSI-VGM as well as IPM and h-0 and K-Bobtained by the two approaches were the main input to the model. The SWATR model was used to make daily calculations of soil water over a period of 25 days for which the neutron probe measured soil water contents were available. The calculated water contents are plotted as function of the measured ones (Fig. 7). It is evident from the figure that, in general, the calculated moisture contents by both approaches agree with the measured values. However, in the middle portion of the measured range, both IPM and RSI-VGM overestimate the moisture content values. The mean error and the root mean square error for the RSI-VGM and IPM estimates are - 0.0979 and -0.0913 (negative sign indicates overestimation) and 0.1259 and 0.1169 respectively. In order to further examine the accuracy of the combination approach with respect to IPM, the calculated

276

S. Mohan~y, R. Singh /A~ricultuml

m 10

15

29 (1996) 267-281

35

moisti_Te (a)

(b) Fig. 6. Comparison

Wuter Manqetnent

of hydraulic conductivity-water

conte2Zt

for

frjr

(W)

150mm

3 ii 13 m 171

content relationships

obtained from RSI-VGM

and [PM.

moisture content values by the two approaches are plotted for different depths over 25 days period (Fig. 8). It is seen that except for 450 mm depth, the calculated moisture contents

S. Mohanty, R. Singh /Agricultural

Water Management 29 (1996) 267-281

E2.sz

am

,,,,(,,,,,,,, I 15

(c)

(d)

for

for

450

600

mm

mm

(PM RSI-VGM

278

~ODOO IPM CC!LC+ RSI-VGM

1

(f)

for

900

mm

S. Mohanty. R. Singh/Agricultural

Table 4 Results of statistical analysis for differences Depth

Difference

(mm)

t value Calculated

150 300 450 600 750 900 *Hypothesis

0.347 0.460 0.443 0.503 0.585 0.660

Water Management 29 (1996) 267-281

between RSI-VGM

219

and IPM approach

of means

Root mean square error

t value Calculated

Table ‘0.99

‘0.95

2.460 2.492 2.492 2.492 2.492 2.492

I .698 1.711 1.711 1.711 1.711 1.711

1.398 0.148 1.507 2.176* 6.368* 9.810*

Table ‘0.99

‘0.95

2.583 2.68 1 2.681 2.68 1 2.681 2.68 1

1.746 1.782 1.782 1.782 1.782 1.782

rejected

are in agreement with each other, which indicates that the RSI-VGM combination could qualify as a substitute of IPM for easier, cheaper and quicker determination of soil water retention and unsaturated hydraulic conductivity relationships.

__ 00~00

1 : 1 Line

IPM values a a A A c RSI-VGM values

20 Measured

Fig. 7. Comparison

25 moisture

30 content

between calculated

35 (W)

moisture contents

*++I-+??+***YIU ***--v--y .+n+w. A*R.~ M

y-we*__ -; x

I

-*-‘--*__

-**-.__

-x-s.-

- * - -._

7 25 w F 0 0

150 150 300 300 450 450 600 600 750

_

--__

- _ -_

mm mm mm mm mm mm mm mm mm

IPM RSI-VGM IPM RSI-VGM IPM RSI-VGM IPM RSI-VGM IPM

‘*---)c-_-x -_

I ~~I:-_--_.:~5

0

5

10 Time

15 (days)

Fig. 8. Comparisonof calculated moisture contents at differentdepths.

4. Conclusions

Hydraulic characteristics obtained with a rainfall simulator infiltrometer in combination with Van Genuchten’s model (RSI-VGM) show similar trends as those obtained with the instantaneous profile method (IPM) . Though at times results obtained with both methods deviate, both approaches give statistically similar results when expressed in terms of calculated soil water contents with the SWATR model. Thus, the advantage of applying functional testing rather than a comparison of raw data is demonstrated. In terms of cost and time to be spent, the RSI-VGM combination proves to be an attractive alternative to the IPM.

References Bhardwaj, A. and Singh. R. 1992. Development ofa and erosion studies. Agric. Water Manage., 22: Black, CA.. Evans, D.D.. White. J.L., Ensminger, American Society of Agronomy Inc., Madison,

portable rainfall simulator infiltrometer for infiltration, runoff 235-248. L.E. and Clarke, F.E. 1965. Methods of Soil Analysis, Part I. WI, 770 pp.

S. Molmrzty, R. Sin& /Agric.dturd

Water Mmqernent

29 (1996) 267-281

281

Booltink, H.W.G., Bouma, .I. and Gimenez, D. 1991. Suction crest infiltrometer for measuring hydraulic conductivity of unsaturated soil near saturation. Soil Sci. Sot. Am. J., 55: 566-568. Bouma. J., Hillel, D.I.. Hole. F.D. and Amerman, C.R. 197 I. Field measurement of unsaturated hydraulic conductivity by infiltration through artificial crusts. Soil Sci. Sot. Am. Proc., 32: 362-364. Feddes, R.A.. Kowalik, P.J. and Zarandy, H. 1978. Simulation of field water use and crop yield. Wiley, New York, 139 pp. Hillel, D. and Gardener, W.R. 1970. Measurement of unsaturated conductivity and diffusivity by infiltration through an impending crust. Soil Sci., 109: 149-153. Hillel, D. 1971. Soil and Water: Physical Principles and Processes. Academic Press, New York, pp. 13 I-153. Hillel, D., Krentos, V.D. and Stylianou, Y. 1972. Procedure and test of an internal drainage method for measuring soil hydraulic characteristics in-situ, Soil Sci., 114: 395400. Jeppson, R.W., Rawls, W.J., Hamon, W.R. and Schreiber, D.L. 1975. Use of axy-symmetric infiltration model and field data to determine hydraulic properties of soils. Water Resour. Res., 11: 127-137. Kirkham, D. and Powers, W.L. 1972. Advanced Soil Physics. Wiley, New York, pp. 245-285. Libardi, P.L., Reichardt, K., Nielson, D.R. and Biggar, J.W. 1980. Simple field methods for estimating soil hydraulic conductivity. Soil Sci. Sot. Am. J., 44: 3-7. Marshall, T.J. 1958. A relation between permeability and size distribution of pores. J. Soil Sci., 9: J-8. Millington, R.I. and Quirk, J.P. 1959. Permeability of porous media. Nature (London), 183: 387-389. Mohanty, S. 1993. Determination of soil hydrologic properties using rainfall simulator infiltrometer. M. Tech. Thesis. hrdian Institute of Technology, Kharagpur, 86 pp. Mualem. Y. 1976. A new model for predicting the hydraulic conductivity of unsaturated porous media. Water Resour. Res.. 12: 5 13-S22. Touma, J. and Albergel, J. 1992. Determining soil hydrologic properties from rain simulator or double ring infiltrometer experiments: a comparison. J. Hydrol., 135: 73-86 Van Genuchten. M. Th. 1980. A closed form equation for predicting the hydraulic conductivity of unsaturated soil. Soil Sci. Sot. Am. J., 44: 892-898. Watson. K.K. 1966. An instantaneous profile method for determining hydraulic conductivity of unsaturated porous materials. Water Resour. Res., 2: 709-715. Young% E.G. 1964. An infiltration method of measuring the hydraulic conductivity of unsaturated porous material. Soil Sci.. 109: 307-3 I I,