parameter selection and testing the soil water model soil

Journal o f Hydrology

ELSEVIER Journal of Hydrology 195 (1997) 312-334

Parameter selection and testing the soil water model SOIL

M.B. M c G e c h a n a, R. G r a h a m a, A.J.A. Vinten b, J.T. Douglas c, P.S. H o o d a a

"Scottish Centre of Agricultural Engineering, SAC, Penicuik EH26 OPH, UK bSoil$ Deparonent, SAC, Edinburgh EH9 3JG, UK CSoils Department, SAC, Penicuik EH26 OPH, UK

dBiochemical Sciences Department, SAC, Auchincruive, Ayr KA6 5HW, UK

Received 11 October 1995; revised 1 May 1996; accepted 26 June 1996

Abstract

The soil water and heat simulation model SOIL was tested for its suitability to study the processes of transport of water in soil. Required parameters, particularly soil hydraulic parameters, were determined by field and laboratory tests for some common soil types and for soils subjected to contrasting treatments of long-term grassland and tilled land under cereal crops. Outputs from simulations were shown to be in reasonable agreement with independently measured field drain outflows and soil water content histories.

1. Introduct ion

Simulation models are valuable tools for the study of complex weather-related agricultural processes and interactions, and can be more efficient, in terms of researchers' time and resources, than extensive field experiments. Soil water dynamics are well suited to study in this way. Some soil water simulation models have already been developed, mainly for the study of plant/soil/water interactions. However, it is intended to apply these further to the study of environmental pollution problems, and particularly to the transport of pollutants through the soil to watercourses following the land spreading of wastes, for which a description of the processes of soil water

movement is a prerequisite. This paper describes the selection of parameter values and testing of the soil water model SOIL in readiness for its application for the study of the transport of water-borne pollutants.

0022-1694/97/$17.00 O 1997- Elsevier Science B.V. All rights reserved Pll S0022-1694(96)03229-5

M.K McGechan et alJJournal of Hydrology 195 (1997) 312-334

2. The soft water model SOIL

313

2.1. Existing models and previous applications

Existing soil water simulation models either include a very simple treatment of drainage (Witney et al., 1982) - used previously for estimating workdays for tillage (Witney and Eradat Oskoui, 1982) - or are more complex, such as WATBAL (Berghuijs-VanDijk, 1990), SWATRE (Feddes et al., 1978; Belmans et al., 1983), SOIL (Jansson, 1996) and MACRO (Jarvis, 1994). All these models include representations of soil water balance, with the means of simulating these processes with historical weather data. Soil nitrogen dynamics represents another set of processes important to the study of environmental pollution from land spreading of wastes, and these processes are very dependent on soil water status and movement. The soil nitrogen dynamics model SOILN (Bergstrtm et al., 1991) must operate in conjunction with SOIL, and ANIMO (Rijtema and Kroes, 1990) is intended to operate with SWATRE or WATBAL.

The SOIL model was used in earlier studies by McGechan and Cooper (1994) and Cooper and McGechan (1994) to estimate numbers of workdays for carrying out winter field operations (including field spreading of wastes) which are limited by the water content of the top soil layer. This model is most appropriate for the current study of the transport of water through the soil, for a number of reasons. It is a multilayer model, so can indicate the soil water content and horizontal movement of water to field drain backfill at different depths. It combines the most sophisticated treatment of soil heat processes including freezing, and representation of falling and lying snow, which have a major influence on surface runoff and watercourse pollution from field spreading of wastes. Most important of all, it includes representation of very fast movements of water by so- called 'macropore flow' or 'by-pass flow'; this is commonly associated with water movements through fissures or cracks in very dry soil, but also occurs in aggregated or structured soils at water contents near to saturation (Jarvis, 1994; Jarvis et al., 1991).

2.2. Representation of processes within the soil

The model SOIL simulates water and heat flows through and between layers inthe soil profile. Assumptions are made about flows as the result of gradients in water potential (Darcy's Law, formulated as Richard' s equation, Richards, 1931) and in temperature (Fourier's Law), together with the laws of conservation of mass and energy. These give a pair of coupled differential equations, which are solved by an explicit forward difference (Euler Integration) method. Water movements through the soil matrix take place under all conditions, including upward capillary rise under dry soil conditions, while macropore flows are superimposed through cracks under dry conditions and around soil aggregates under wet conditions. Boundary conditions include infiltration of rainwater into the top soil layer, heat transfer at the soil surface, evaporation from the soil surface, flow to deep groundwater (at a specified rate in proportion to the height of the watertable above a specified base level), and flows out of soil layers into field drain backfill. Horizontal movements of water through saturated soil layers above and below field drain level follow classical drainage theory according to Hooghoudt's (Hooghoudt, 1940) equation (as

314 M.B. McGechan et alYJournal of Hydrolosy 195 (1997) 312-334

described by Nwa and Twocock, 1969 and by Wesseling, 1973). Surface runoff is also represented if the rate of precipitation exceeds the infiltration capacity of the surface layer. Heat processes simulated include freezing and thawing of water.

Soil water movements in a particular soil depend on the soil water characteristic (the curve of soil water tension against water content), and the hydraulic conductivity which varies with water tension. The solution of the differential equations in a soil water model requires that the variation in these quantities over the range of tensions should be represented by mathematical equations; in the case of SOIL, the equations proposed by Brooks and Corey (1964) are used. However, for soil water contents near saturation, hydraulic conductivity is given, not by the Brooks and Corey equation, but by a linear relationship with water content going from the Brooks and Corey value at saturation minus the macroporosity to the saturated value which includes macropore flow at saturation. These equations are described by Jansson (1996) and differ slightly from those used for earlier studies with the model such as by Jolmsson and Jansson (1991), and McGechan and Cooper (1994), which assumed a fixed value of 4% for the macroporosity. The latest (1996) version of the SOIL model allows the user to specify a macroporosity different from the default value of 4%. In the Brooks and Corey equations, the water release curve is defined by the pore size distribution index, the soil water tension at air entry and the residual water content. Hydraulic conductivity is defined by the saturated conductivity value for soil matrix flow, with its decline with increase in tension defined by the three parameters of the water release curve.

2.3. Representation of processes above the soil surface

Processes represented at the boundary between the soil and atmosphere include snow melt, interception of precipitation (as rain or snow), heat transfer and evaporation and transpiration.

Johnsson and Jansson (1991) used weather variables to enable evaporation to be estimated within the SOIL model. Net radiation energy is first partitioned between the plant canopy and the soil surface according to the crop leaf area index (LAI) at that time (with all the energy reaching the ground if the soil is bare). Precipitation is also partitioned with a fraction proportional to the LAI being intercepted and retained on the plant surfaces. Three separate applications of the Penman-Monteith combination equation (Monteith, 1965) are made, to calculate evaporation of rainwater from the plant surfaces, true transpiration from leaf stomata, and evaporation from the soil surface. For each application of the equation, there is a contribution to evaporation from the net radiation term, and from the 'aerodynamic term' with assumptions about the surface resistance and roughness length; surface resistance is assumed to be very low for evaporation of surface rainwater from plant surfaces. Evaporation from the soil surface and extraction of water by roots from each soft layer are both reduced if the soil water tension at the surface or in the layer is above a critical value. If there is rainwater on the plant surfaces, the plant canopy fraction of net radiation energy is allocated first to evaporation of surface water, with evapotranspiration taking place (using the remaining energy) only if the energy has been sufficient to evaporate all the surface water.

The model was also mn with daily values of potential evapotranspiration as input. This

M.B. McGechan et al./Journal of Hydrology 195 (1997) 312-334 315

is partitioned in the model to provide separate estimates of evaporation from the soil surface, evaporation of intercepted rainwater from the plant surfaces, and true transpiration through the leaf stomata.

3. Materials and methods

3.1. Sites and soils as data sources

Three soil types~and two cropping regimes from sites with long runs of field measurements have been selected (Table 1). Layouts and cropping patterns for the series of hydrologically isolated plots (eight of 300 m2 in the clay loam tilled soil and twelve of 250m 2 in the sandy loam soil), each with equipment for measurement of drainflow quantities and solute concentrations, are described in detail by Vinten et al. (1991, 1992, 1994). On the silty clay loam soil, dralnflow quantities and solute concentrations were measured on four isolated plots, each 0.5 ha in area, two in a typical grassland system receiving mineral nitrogen and slurry, and two in a low input grassland with a grass/clover sward receiving slurry but no mineral nitrogen. Despite having no drainflow measurement equipment, the clay loam grassland site was included in the study, because of its history of measurements of various other variables, and for comparison with the adjacent tilled clay loam site.

3.2. Approach to model parameterisation

The ideal approach to modelling is to develop and parameterise a model using one set of data, then test or 'validate' the model using an independent set of data. In this study with an already developed model, the parameterisation (calibration) procedure consisted of measurement of hydraulic parameters by laboratory and field methods. Validation was carried out by comparing field measurements with results of simulations using historic weather data recorded over the same period at a nearby site. The only fine tuning carried out at this stage concerned the rate of percolation to deep groundwater (see Section 4.2).

Table 1 Sites and soils

Soil type Soil ~ t i o n L o c a t i o n Management/cropping (Bown and Shipley, 1982)

Clay l o a m Winton/Rowanhill/Giffnock G i ~ Mains Farm Penicuik

Clay l o a m Winton/Rowanldll/Giffnock Giencorse Mains Farm Penicuik

Sandy l o a m Winton/Rowanhill/CAffnock Bush Estate, Penicuik

Silty clay loam Sth'ling/Duffns~ow/Carbrook Crichton Royal Farm, Dumfries

Arable; annual tillage for cereals Perennial grass

Arable; annual tillage for ceres Perennial grass

316 M.B. McGechan et al./Journal of Hydrology 195 (1997) 312-334

3.3. Water release characteristics

For each of the two tilled soils (Table 1), two sets of water release data were available. The first set, as reported by Vinten et ai. (1992), covering the tension range 1-1000 kPa, was measured on small samples taken from the middle of the topsoil (about 0.15 m depth) and near the top of the subsoil (about 0.4 m depth), with further samples from two lower depths in the sandy loam soil only. The second set was measured only over the trainable tension range (0-6 kPa) on samples taken at the depths at which hydraulic conductivity measurements were made, with a particular distinction between the surface layer of the topsoil (0-0.1 m depth) which would have received secondary cultivation and drilling treatments, and the main bulk of the topsoil (0.1-0.3 m depth) which would have been disturbed only by ploughing. For the grassland soils, measurements were made only over the drainable tension range. Bulk density measurements were also made on the drainable tension range samples.

Water release curves according to the Brooks and Corey (1964)equation, plus a linear relationship at water contents near to saturation where air entry effects con- tribute to the water tension (assumed to be over the water content range between saturation and saturation minus macroporosity), were initially fitted to each set of measured data by a firing procedure provided with the SOIL model. For some data sets, this procedure (with three fitted parameters) gave unexpected results, with values of the residual water content parameter which appeared too high or too low compared to values published in the literature. It proved more satisfactory to fix the residual water content value as that for the appropriate soil type, as reported by Rawls et al. (1982), and then adjust the other two parameters (pore size distribution index and air entry pressure) manually in a spreadsheet to give a good fit to the data. Parameter values were adjusted to give the best fit over the dralnable tension range at the expense of a poorer fit at low water contents in some cases. For each of the tilled soils there was a slight discrepancy between the values fired for the two available sets of data. It was decided to work with the curves fitted to the trainable tension range datasets for all except the two deep layers of the sandy loam soil. Resulting curves are shown in Fig. 1, and values of the equation parameters estimated by this procedure are listed in Table 2. For the tilled soils, good fits were obtained with the default value of 4% for the macroporosity. However, for the grassland soils, better fits were obtained by assuming different values for the macroporosity, much lower than 4% in the case of the silty clay loam soil.

A comparison was made between these water release data and other published and unpublished data. Lilly (Personal communication, 1993) found similar water release characteristics for clay loam and sandy loam soils of different series but similar particle size distribution to those in the present study. For tilled soils of the Winton/Rowanhill/ Giffnock Association, O'Sullivan and Ball (1993) reported water release characteristics similar to those measured in this study, but the characteristics differed for the same soils subjected to different tillage treatments such as direct drilling. The water release data were also compared with similar data for a range of Scottish soils presented by Bache et al. (1981); there were differences between soil types and treatments similar to those measured in the current study.

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3.4. Hydraulic conductivity

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Hydraulic conductivities for each of the softs were measured by a combination of methods at various depths in each soft profile. A programme of conductivity measurements using tension infiltrometers, as described by Ankeny et al. (1988) and Jarvis et al. (1987), over the tension range 0-1.5 kPa which includes the 'break-point' tension at which soil matrix pores are considered to be full and macropores just empty, was carried out. Measurements were made at the surface (representing the 0-0.1 m depth upper topsoil layer), at 0.15 m depth (a point in the 0.1-0.3 m lower topsoft), and at 0.5 m depth (in the subsoil). A further measurement at a depth of 0.8 m was made in the tilled sandy loam soft only, because drains were at a much greater depth at this site, and the subsoil in this profile was thought to consist of distinct B1 and B2 horizons formed from different parent material. Means of values measured at five (surface and topsoil) and three (subsoil) positions are illustrated in Fig. 2. In all cases except one, the five or three measured values were in close agreement. The exception was at the 0.8 m depth in the tilled sandy loam soft where values differed, reflecting a wide difference in appearance of material excavated at this depth at each location, from very sandy to very stony soil; in this case, the values plotted in Fig. 2 are from one location only. Also shown in Fig. 2 are the curves given by the hydraufic conductivity relationships used in the SOIL model, based on the Brooks and Corey equation at low water contents and a linear relationship near to saturation. For the two tilled soils, the conductivity equation gave good fits to the data with the break-point dividing the linear portion and the Brooks and Corey relationship set to 4% below saturation (corresponding to a macroporosity of 4%). For the grassland softs, much better fits were obtained with a variable break point, and for the silty clay loam soft it was found to he much less than 4%, the same situation as found with the water release curve. Assumed values to give the best fit in Fig. 1 are listed in Table 2.

For all the softs, there is a marked difference in conductivity values between the surface topsoil and lower topsoil layers; in the grassland softs'because the roots are concentrated in the surface layer, and in the tilled softs because the surface layer has received secondary cultivation and drilling treatments whereas the lower topsoil layer has been disturbed only by ploughing. Conductivities in the lower topsoil layer are intermediate between those in the surface layer and those in the subsoil layer. Only the silty clay loam grassland soil and the surface layers of the other softs show a higher saturated conductivity value for macropore flow than for soft matrix flow, and hence a distinct breakpoint tension at which macropore flow ceases. In the tilled clay loam soil a high macropore saturated conductivity was expected because the soil is structured soft and forms distinct aggregates with large pore spaces in the cultivated layer. For the sandy loam soil, field observations suggest that many of the aggregates collapse, so that the macropore conductivity would be expected to be less; in fact, the macropore saturated conductivity for the surface layer of this soft is even higher than that for the clay loam soil. These high macmpore conductivity values in the surface layers of all the soils are of a similar order of magnitude to those reported for a structured clay soil by Jarvis et al. (1991).

Conductivity measurements made by other methods, as used in the earlier studies, were compared as supporting evidence for the current study. For the sandy loam and clay loam tilled soils these included a series of conductivity measurements at a range of tension

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soil

!

! !

1.0

10.0

10

0.0

Soil

wat

er m

uion

(nm

ric

lX~e

n~),

kPa

Fig.

3. H

ydra

ulic

cond

uctiv

ities

(fill

ed so

ils o

nly)

, who

le ra

nge,

loga

rithm

ic sc

ale,

cold

air

met

hod

mea

sure

d dat

a an

d B

rook

s and

Cor

ey fi

tted r

elat

ions

hip.

A, 0

.15

m

dept

h O

ower

tops

oil);

e,

0.5

m d

epth

(sub

soil)

.

! '

1000

.0

tae

322 M.B. McGechan et al./Journal of Hydrology 195 (1997) 312-334

values from 1-100 kPa carded out using a laboratory cold air method (Boels et al., 1978) on topsoil and subsoil samples similar to those used in the water release measurements reported by Vinten et al. (1992). These points are plotted on a logarithmic scale in Fig. 3, alongside the conductivity curves given by the Brooks and Corey equation with the assumed saturated conductivity values given in Table 2 based on the tension infiltrometer measurements. Agreement between the measured points and the assumed curve is extre- mely good for the sandy loam soil over the whole tension range, but somewhat less good for the clay loam soft at low water contents. However, the current study is concerned with the wet end of the soil water spectrum; because agreement was good in this region, discrepancies at the dry end were considered to be of minor importance. For each o f the tilled softs and for one particular layer depending on the drainage scheme, saturated conductivities were also estimated from drain outflow/tensiometric data during drainage recession events using the method of the International Institute for Land Reclamation and Improvement (1974). For the A horizon of the clay loam soil, this gave a conductivity of 11 200 mm day-~, the exact macropore flow saturated conductivity value chosen to fit the tension inliltrometer measurements. For the B2 horizon of the sandy loam soil, the estimated saturated conductivity was 32 mm day-l, similar to that measured with the tension infiltrometer. Broadly similar saturated conductivity values were measured by Lilly (1994) for the subsoil layer of a clay loam soil of Caprington series, and for both layers of a sandy loam soft of Balrowurie series.

Because its field drains were at a greater depth than at any of the other sites, the only site requiring specification of a conductivity value for the C horizon was that with the sandy loam soft. For this, a saturated conductivity of 3.6 mm day-1 was assumed, based on the measurements of Snaebjorrnson (1977).

The hydraulic conductivity values for the two tilled soils in Table 2 imply that the sandy loam soil is very free draining, while the clay loam soil has a greater resistance to drainage, after initial fast loss of a small component of highly mobile water (as described by Parkes et al., 1994); this is an agreement with general observations about the drainage characteristics of these two sites.

3.5. Preparation of soil profile data for simulations

Simulations with the SOIL model can be run with a profile stratification with up to 22 layers with depths specified by the user. For specification of hydraulic properties, each profile was subdivided roughly into its horizon divisions, but this subdivision was too coarse for simulation purposes. Each horizon was therefore subdivided into thinner layers for simulation, as indicated in Table 2. For the tilled sandy loam soft, layers were specified down to a depth of 2 m, since field drains were in the C horizon at this site; also, this was the only profile with different hydraulic properties specified for each of the Bi and B2 horizons. For all other softs and sites, layers were specified down to 1 m. Field (tile) drain depths and spacings specified for simulations with the model are listed in Table 3. This is a slightly simplified representation of the actual drainage system of the clay loam soil plot described by Vinten et al. (1991) which has drains at two depths, because the SOIL model can represent only a single, uniform depth field drain system. A maximum value was also set to the daily rate of percolation to deep groundwater, estimated from soil water balances

M.B, McGechan et aLIJournal of HydrolosY 195 (1997) 312-334

Table 3

Field (file) drain dep~ and ~cings

323

Clay 1oua,filled Sandy io~t,tilled Clay loam,grass Silty clayloem, grins

Drain depth (m) 0.5 1.5 0.5 0.65 Drain spacing (m) 7.5 7.0 7.5 7.0

over the winter months (see Section 4.2). Other items specified included the maximum rooting depth at which crops extract water (Fig. 4), the distribution of root density (and hence of the water extraction rate) over the soil layers at the maximum rooting depth (Table 2), and the critical soil water tension above which actual evapotranspiration drops below its potential Value (Table 2). Selected values for the root density distribution were based on those suggested for cereal and grass crops by Johnsson and Jansson (1991), and for the critical soft water tension on those suggested by Jansson (1994) with a lower value for the sandy loam soft than the other soil types.

3.6. Crop development parameters

LAI values (from which roughness lengths are also derived) over the growing season, for cereal (barley) (Francis and Pidgeon, 1982) and grass (Joimsson and Jansson, 1991) crops, are shown in Fig. 4. A long series of field grass drying experiments at SAC (e.g. Lamond et al., 1988), showed that LAI was roughly equal to the cut grass yield in t ha-t; critical dates in the LAI function correspond to critical O~t_es for root development. How- ever, for the roughness length of bare soil, a value of 0.005 m was assumed as suggested for estimating evaporation using the Penman-Monteith equation by Thompson et al. (1981), rather than 0.01 m assumed by Johnsson and Jansson (1991).

3.7. Weather data for simulations

Simulations using the SOIL model can be carried out using alternative sets of weather variables. For the simpler mode, calculated values of potential evaporation for an open water surface (Penman, 1948) must be provided, as well as daily mean temperature (estimated as the mean of the maximum and minimum temperatures), and daily total precipitation. For the other, more complex, mode of model operation in which SOIL calculates values of potential transpiration, three additional input weather variables are required - net radiation, wind speed and vapour pressure. Values of these data sets for both modes were prepared from daily weather records for the sites at Dumfries and Bush Estate held in the 'METDATA' database (Arnold, 1991). Global radiation was estimated from sunshine hours by the ,~ngstr6m (1924) formula and daylength estimated from trigono- metric relationships. Vapour pressure was estimated from dry bulb and wet bulb temperatures recorded at 0900 h and net radiation was estimated from global radiation, temperature and vapour pressure by the Brunt (1932) formula.

The weekly rainfall recorded at the Glencorse drained plot site (the tilled clay loam plots) was slightly higher than that at the Bush Estate daily weather station about 1 km distant, perhaps due to the topography of the sites; other climatic variables were assumed

324

6

M.R McC, echan et aL/Journal of Hydrology 195 (1997) 312-374

5

2

/7 '\ \

/ \ /

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

0.0

-0.2

-0.4

-0.8

\

I I I I I I I I

Fig, 4. Leaf area index and mot depths umaled for bad©y and O~m.

- I . 0 ' ' '

Jm Nov Dec

to be almost identical at both sites. Rainfall data were therefore adjusted to give the same weekly totals as those measured at Glencorse.

3.8. Data for model validation

Drainflow quantifies recorded at approximately weekly intervals over several years were available for three sites (all except that with the clay loam soil under grass). Shorter

Tab

le 4

A

nnua

l and

win

ter p

erio

d so

il w

ater

~la

nees

(al

l flo

w v

alue

s, d

iffe

renc

es a

nd R

.M.S

. va

lues

are

giv

en in

uni

ts o

f m

m d

ay-i

)

Yea

r St

art

End

Pr

ecip

itatio

n C

hang

e in

E

vapo

rati

on/

Surf

ace

Dra

in

Dee

p D

rain

+

Mea

sure

d D

iffe

renc

e R

.M.S

. of

da

y da

y w

ater

con

tent

ev

apot

rans

pira

tion

runo

ff

flow

pe

rcol

atio

n su

rfac

e dr

ain

flow

m

easu

red-

w

eekl

y (n

un)

runo

ff

sim

ulat

ed

diff

eren

ce

Cla

y L

oam

Til

led

Plot

19

87/8

8 91

91

10

01.9

-7

.4

395.

4 0.

0 55

4.4

57.7

55

4.4

416.

5 30

1 33

26

1.3

10.5

18

.5

0.0

214.

0 17

.47

214.

0 22

8.0

14.0

4.

8 19

88/8

9 90

88

97

7.4

3.7

426.

4 0.

0 49

3.6

53.9

49

3.6

601.

7 10

8.1

7.7

299

26

178.

8 -8

.9

23.1

0.

0 14

7.9

16.1

14

7.9

157.

8 9.

8 4.

3 19

89/9

0 89

86

94

2.5

-3.9

41

9.8

0.6

488.

1 39

.8

488.

7 60

1.0

112.

3 5.

8 30

5 29

28

2.2

12.4

19

.0

0.5

232.

2 15

.7

232.

7 24

5.1

12.4

4.

1 19

90/9

1 87

87

87

9.5

-1.6

37

5.7

0.1

462.

0 44

.2

462.

2 48

6.7

24.6

9.

8 30

4 30

26

3.2

-8.2

20

.4

0.0

236.

0 16

.5

236.

1 21

6.1

-19.

8 8.

3 19

91/9

2 88

87

87

1.7

-2.2

40

2.2

0.4

427.

3 44

.1

427.

7 35

3.7

-74.

1 14

.0

305

31

303.

8 -1

5.6

18.7

0.

4 28

0.7

16.1

28

1.1

242.

9 -3

8.1

21.1

19

92/9

3 88

88

94

5.5

1.5

422.

0 0.

1 47

4.5

47.4

47

4.6

514.

4 39

.8

5.6

312

29

272.

6 2.

1 31

.6

0.0

225.

1 15

.1

225.

2 24

8.9

23.8

8.

8 19

93/9

4 89

89

11

95.4

7.

1 38

6.3

3.0

747.

7 50

.0

750.

7 85

6.9

106.

2 12

.2

303

31

299.

2 16

.9

30.9

2.

3 23

3.7

16.3

23

6.0

344.

6

Mea

n de

ep p

erco

lati

on, w

hole

yea

r (r

am d

ay -t

) 0.

13

Mea

n de

ep p

erco

latio

n, w

inte

r per

iod

(ram

day

-~)

0.18

M

ean

diff

eren

ce b

etw

een

mea

sure

d an

d si

mul

ated

dra

in fl

ows,

who

le y

ear (

mm

day

-*)

0.15

M

ean

diff

eren

ce b

etw

een

mea

sure

d an

d si

mul

ated

dra

in fl

ows,

win

ter p

erio

d (m

m d

ay-*

) 0.

00

9.2

Ove

rall

R.M

.S.

of w

eekl

y di

ffer

ence

, w

hole

yea

r 8.

6 O

vera

ll R

.M.S

. of

wee

kly

diff

eren

ce,

win

ter p

erio

d Sa

ndy

loam

till

ed p

lot

1989

/90

91

90

815.

7 13

.2

339.

9 0.

0 39

9.0

66.4

39

9.0

268.

6 30

5 26

22

2.6

53.4

19

.4

0.0

134.

1 17

.6

134.

1 13

7.3

3.2

10.4

19

90/9

1 91

90

10

03.5

6.

1 31

7.3

0.0

611.

6 70

.7

611.

6 53

8.8

-72.

8 11

.5

304

30

275.

8 -2

4.5

21.1

0.

0 26

3.0

20.1

26

3.0

253.

6 --

9.4

11.5

19

91/9

2 91

91

87

8.6

-29.

9 36

0.6

0.0

480.

5 68

.6

480.

5 31

1.6

-168

.8

9.8

305

31

308.

6 -1

4.5

20.0

0.

0 27

6.2

19.8

27

6.2

249.

8 -2

6.4

12.3

19

92/9

3 92

90

89

1.1

--0.

3 32

9.2

0.0

492.

8 69

.8

492.

8 41

2.9

-79.

9 9.

9

.ee

t~ ! e.

t~

301

29

360.

3 48

A

38.3

0.

0 25

0.6

20.2

19

93/9

4 91

89

11

92.1

54

.0

336.

7 0.

0 72

9.6

71.6

30

5 31

32

2.2

48.5

32

.1

0.0

223.

4 19

.4

Mea

n de

ep p

erco

latio

n, w

hole

yea

r (ra

m d

ay-'

) 0.

19

Mea

n de

ep p

erco

latio

n, w

iate

~r l~

'iod

(nun

day

-i)

0.22

M

ean

diff

eren

ce b

etw

een

mea

ma'

ed a

nd s

imul

ated

dra

in f

low

s, w

hole

yea

r (nu

n da

y-i)

M

ean

diff

eren

ce b

etw

een

mea

sure

d an

d si

mul

ated

dra

in f

low

s, w

inte

r pe

riod

(ra

m d

ay-i

) O

vera

ll R

~I.S

. of

wee

kly

diff

eren

ce,

who

le y

ear

Ove

rall

R.M

.S. o

f wee

kly

clif

fe~e

ace,

win

ter

peri

od

Silty

cla

y lo

am r

ifle

d pl

ot

1994

/95

91

86

1149

.3

0.1

301.

6 0.

0 78

5.4

64.0

30

4 31

44

7,0

3.6

16.2

0.

0 40

7.4

23.1

19

95/9

6 94

91

86

3.2

-12.

7 31

1.0

0.0

514.

7 46

.0

303

31

229.

3 -2

.9

7.2

0.0

205.

5 20

.5

Mea

n de

ep p

erco

latio

n, w

hole

yea

r (nu

n da

y-l)

0.

15

Mea

n de

ep p

erco

latio

n, w

inte

r pe

riod

(ra

m d

ay-'

) 0.

24

Mea

n di

ffer

ence

bet

wee

n m

easu

red

and

sim

ulat

ed d

rain

flo

ws,

who

le y

ear (

mm

day

-')

Mea

n di

ffem

ace

betw

een

mea

sure

d an

d si

mul

ated

dra

in f

low

s, w

inte

r pe

riod

(ram

day

-~)

Ove

rall

R.M

.S. o

f wee

kly

diff

eren

ce,

who

le y

ear

Ove

rall

R.M

.S. o

f wee

kly

diff

eren

ce,

win

ter

peri

od

250.

6 72

9.6

223.

4

785A

40

7A

514.

7 20

5.5

286.

3 96

9.9

405.

8

835.

7 46

7.8

436.

0 14

4.5

35.7

24

0.3

-0.0

4 0.

01

50.3

60

.4

-78.

7 -6

1.0

-0.0

4 0.

00

15.8

18

.9

12.6

12

.5

10.5

13

.8

18.2

8.

5

14.4

11

.1

e~ I

M.B. McGechan et al./Joumal of Hydrology 195 (1997) 312-334 327

runs of neutron probe-measured soft water data were available for two sites and periods, mainly during the s ~ growing season. There was also a short sequence of water table depth data, estimated from tensiometer measurements. The output variables selected (out of a large number possible) for comparison with validation data were total evaporation/ evapotranspiration (nun day-t), surface runoff (mm day-l), drainflow from field (tile) drains (ram day-l), deep percolation flow (mm day-l), volumetric water content of each soil layer (%), and tension in each soil layer (kPa),

4. Results and discussion

4.1. Simulation runs

Simulations with the SOIL model were carded out for the periods and sites corresponding to the field measured data. At each site, field measurements commenced on 1 April in the first year, but simulations were started on 1 January with initial tensions of 5 kPa (and corresponding volumetric water contents as shown in Table 2) for all layers above the drains and saturated conditions below the drain.g. This is a commonly assumed approx- imate value for tension at field capacity in the UK (Wild, 1988). Any discrepancies caused by inaccurate starting values disappear after about one week in simulations with SOIL, in this case long before the start of field measured data.

Conclusions were drawn from simulations with the complex option of all the evaporation/evapotranspiration calculations made within the SOIL model due to its assumed greater scientific rigour. Some simulations with the simpler option of supplying potential evapotranspiration in the weather data file were also carried out for comparison, and gave results similar to those from the complex option.

4.2. Deep percolation from winter water balances

The only parameter which was not estimated from laboratory or other tests independently from simulations was that controlling deep groundwater percolation, because of the difficulty of measuring conductivities of the inaccessible deep soft layers. Alternative options are provided in the SOIL model for controlling deep percolation. The option selected for this study makes the rate of deep percolation proportional to the height of the water table above a specified base depth, chosen as 0.5 m below the field drain depth. The other parameter which must he specified is the maximum rate of deep percolation, ie the rate which would occur if the water table were to reach the surface. This maximum rate was adjusted for each soil to minimise the average difference between simulated and measured drain flows for the winter months November to January, during which evaporation is at its lowest level, in a water balance calculation similar to that described in Section 4.3 for annual balances (Table 4). Data from the final year (1993-94) were omitted from this calculation for the two tilled soils, since there was a suspicion that the drain flows may have been augmented by additional water from a deep groundwater source during this winter in particular. Maximum deep percolation rates are listed in Table 2, giving average

328 M.K McGechan et aL/Journal of Hydrology 195 (1997) 312-334

winter deep percolation values of 0.18 mm day-l for the clay loam soil, 0.22 mm day -1 for the sandy loam soil, and 0.24 mm day -l for the silty clay loam soil.

4.3. Annual water balances

Annual balances, calculated by summation of daily outputs from simulations over the periods 1 April to 31 March in each year, are shown in Table 4. These include incoming precipitation, water losses by evaporation/evapotranspiration, surface runoff, flow to field drains, deep groundwater percolation, and changes in water content of the profile from the beginning to the end of the period. Measured drain flows, also shown in Table 4, were compared with both simulated drain flow totals, and with the sum of drain flows and surface runoff. Surface runoff (occurring during periods of snow melt or rainfall on frozen soil) was at a low level at the tilled clay loam site and did not occur at the other sites. When averaged over a number of years, annual simulated drain flows (with deep percolation estimated from winter balances as discussed in Section 4.2) were in reasonably close agreement with measured values, with simulated drain flows slightly lower than those measured for both tilled soils and slightly higher than measured for the silty clay loam grassland soil. Comparing drain flows in individual years for the two tilled soils, measured drain flows were significantly lower than simulated totals in the year commencing on 1 April 1991. It may be that the dralnflow values for two separate weeks during this year, one when flooding occurred (both sites) and the other when a faulty logger required replacement (clay loam site only), were under-estimated by interpolation between the previous and following weeks. Values of the RMS of the weekly differences suggest reasonable agreement between simulated and measured drainflows, except for the year commencing 1 April 1991 for the tilled soils where higher RMS values can be attributed to these measurement errors, and the results for the silty clay loam grassland soil where for some low rainfall periods measured drainflows were for periods longer than one week, so weekly dralnflows had to be estimated.

4. 4. Cumulative drain flows

Cumulative simulated drain flows from 1 September in each year have been plotted against measured values in Fig. 5. Simulated values are good fits to measured data over the winter period in every year, with slight discrepancies emerging during some years during spring and summer only. Good fits during the winter period are important for this study, because this is when most water-borne pollution from land spread wastes takes place.

4.5. Weekly drainflow totals

Plots of simulated and measured weekly drain flow totals for sample years in which measurements were made at 7-day or shorter intervals are shown in Fig. 6. While the simulated values do not match, perfectly, all the fluctuations in the measured values, the quantity of drain flow in each event is well estimated, particularly in winter. Slight discrepancies in the quantity of drain flow in each event during summer are considered less important for this study. However, in most cases, the first significant event following the

M.B. McGechan et alJJournal of Hydrology 195 (1997) 312-334 329

1200

iooo

6O0

1° 200

0

•I Clay imm m i l e plot I

JI Jl /~ . , ~ , , ,,~ , , ,: / i x; Sl /I / I rl / / ! f / , '~ t i 7 I .i

f I I • I J ' r'

1957 1988 1989 1990 1991 1992 1993 1994

1200

i__ ~0o

600

400

! 0

s l y Iota mbi, p~ /I

~l , I ,4 /i, r I ~ / I f l /I

/I .<, J', l , ! J - , / I / , . I ,l I / I F .

I i / ! I i rr"l I A fS ~J I I ~ ./ t J f

1987 1988 1989 1990 1991 1992 1993 1994

1200

i lOOO

6oo

200

o

(/

1989 1990

silty ~y iota t n m l / l i z

/1 , I i i , f .,ll f ' l Is i ./ I " 1 ) I /I / j

I,--4 Ir-I ._/l li-'l ~ i ; i ' ' ~ I l ! i .

i I 1 I

1991 1992 1993 1994 1995 1996

Fig. 5, Conq~r i son between measured and simulated cumula t ive flows to field drains, i , measured; simulated: - - -, precipitation.

dry summer period is correctly represented in timing if not in quantity. This event is influenced strongly by the soil water content in each layer at commencement of precipitation, since a serious discrepancy in the simulated water content will influence the quantity of rainwater absorbed by the soil before drains begin to flow.

330 M.B. McGechan et aL/Journal of Hydrology 195 (1997) 312-334

i 2

v i l

,~-sa

Clay loam tired plot

Aug-88 Oct-88 Dee-g8 Feb--89

0 , Apt-92 t" , Jun-92

I Clay loam tilled plot I

I X ajl Aug-92 Oc¢-92 Dec-92 Feb-93

80

2O

Apr-gl 'J~gl

,~ndy loam tilled plot

i

Aug-91 O¢i-91 Dee,-91 Feb-92

AW-92 ' ,~9"2

I Sandy loam filled plot I

I i i

'^~,'~ o~-~ ~ - ~ ' F ~

20

AW-94

sots day lmm sr=samd Out ~

'J~-94 ^~,.A 'o~-~ ' ~ , ' F ~

Fig. 6. Comparison between measured and simulated weekly total flows to field drains for selected years. measured; , simulated.

M.B. McGechan et alYJournal of Hydrology 195 (1997) 312-334

4.6. Measured soil water contents

331

Simula ted soil water contents are s h o w n a longs ide s o m e f ie ld va lues measu red with

neutron probes in Fig. 7. Va lues w e r e m e a s u r e d in the sandy l o a m t i l led soil , and in a field

wi th a t i l led clay loam soil ad jacent to the f ie ld wi th the d ra ined plots wi th s imi lar drain

Ci.y tma eu~ ~ 55

• AA

t: I ~ . . . . . .

Apr-M May-S8 Jm-SS Jul-SS AaS4~ Set~8 Oa-SS Nev-S8

Clay Imm ~ rail 55,

1 ~I , , , ,o~.o.,:~ , , $5.

t~ t'~ ~" '"-~. . . . ,~ . ._z~'" ~ -'~ ~I . . . . o~.o.,,.,,,., , AI~-92 M ~ - ~ ~a-92 Jel-92 Ams-~r2 Sep-92 Oot-92 Nov-92 Dw.92

55

25 55

4 5

Study ham lilied rail

0 . 0 - 0 .1 m

• • • • • • • • A A A & A •

I I I I I I

0.1 - 0.2m hy~

i - - & • •

i ! , 1 i , , i

AprO2 May.02 k a - ~ Ja-72 Aul-92 S~-~ Oa.92 Nov-92 13,o-92 Fig. 7. Comparison of simulated water contents with measmmnents made with neutron probe. A, measu~;

, simulated.

332

0.0

M.B. McGechan et al./Journal o f Hydrology 195 (1997) 312-334

-0.2

-0.4

-0.6

-0.S

-1.0

Sandy loam tilled rail

& A •

• A & & ~ | i i i !

5 10 15 20 25 3O December l ~

Fig. 8. Comparison between measured and simulated water table depths. A, measured; , simulated.

depths and spacings. Measured water content histories covered mainly the growing season (April-September) in each year. Simulated values showed moderate agreement with those measured at all depths after carrying out a separate calibration for the top layer to improve fits.

4.7. Measured water table depths

Simulated water table depths are shown alongside values estimated from soil water tensiometer measurements in Fig. 8 for the tilled sandy loam soil during December 1990. The general level of the water table simulated for this soil in winter was very sensitive to the assumed hydraulic conductivity value at the B2 horizon (0.65-0.95 m) depth; this varied considerably according to the position in the vicinity of the plot at which conductivity measurements were made (see Section 3.4). The conductivity values chosen (as illustrated in Fig. 2), are those which give a close approximation to the measured mean water table level. However, with these chosen conductivity values agreement was still poor, with simulated water table depths not showing all the short-term fluctuations in the measured values. This smoothing may have arisen partly because the specified time in daily weather data input to the SOIL model is 1200 h (the mid point of the day), but output parameter values are given at 2400 h which are in effect moving average values over two days.

5. Conclusions

The soil water and heat simulation SOIL model is based on sound theoretical ('mechan- istic') principles, and includes features which make it suitable for the study of water transport processes in northern Europe, where soil is generally wet and subject to periods of frost and snow cover in winter. In this study, parameters required by the model, particularly soil hydraulic parameters, have been determined by field and laboratory tests, for some common soil types and for soils subjected to contrasting treatments of long-term grassland and tilled land under cereal crops. The model has been tested (vali- dated) by comparing outputs from simulations with independent field drain outflow data and some soil water content histories. Following adjusunent of the maximum deep

M.B. McGechan et al./Journal of Hydrology 195 (1997) 312-334 333

groundwater percolation, the only parameter which could not be measured independently from simulatiom, results of simulations show reasonable agreement with measured data, as illustrated in plotted drain flows, water content time series, and annual water balances. These results support the usefulness of the SOIL model for the study of soil water dynamics, and as a basis for future studies of the wansport of water-borne pollutants through the soil.

Acknowledgements

The authors are grateful to Dr P.-E. Jansson of the Department of Soil Sciences, Swedish University of Agricultural Sciences, Uppsala, for permission to use and help with running the SOIL model. Colin Crawford and Robert Ritchie made the field and laboratory measurements of soil hydraufic properties, Rab Howard and Mark Moynagh carried out the dminflow measurements. The Scottish Office Agriculture, Environment and Fisheries Department provided funds to carry out the work.

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