Directory UMM :Data Elmu:jurnal:A:Agricultural Water Management:Vol43.Issue2.Mar2000:
Agricultural Water Management 43 (2000) 139±149
Simulation of soil moisture content of a
prairie field with SWAP93
St. Elmaloglou*, N. Malamos
Agricultural University of Athens, Department of Natural Resources and Agricultural Engineering,
Laboratory of Agricultural Hydraulics, Iera Odos 75, 11855, Athens, Greece
Accepted 9 April 1999
Abstract
A simulation study of the soil moisture content under a prairie field, in Gembloux Belgium, by
the use of the one-dimensional model SWAP93, was carried out. In order to determine the optimum
relationship that Smax is following, two concepts of maximum water extraction rate were examined.
The first one assumed a linear variation of Smax with depth z and the second assumed a
homogeneous distribution of Smax with depth z. Five statistical criteria were used to compare the
quality of simulation results, such as average error (AE), root mean square error (RMSE), root mean
square (RMS), modeling efficiency (EF) and coefficient of residual mass (CRM). The differences
between the criteria, showed that the assumption of the homogeneous distribution of Smax
throughout the soil profile resulted in a more accurate prediction of soil moisture content. The
agreement between measured and simulated water content profiles, throughout the regarded period,
was satisfactory for depths >30 cm. The deviation between simulated and experimental values for
depth 30 cm
for both cases (Figs. 5 and 6). In case of homogeneous Smax (Fig. 5) there was a better
agreement with the experimental values, which is apparent mainly from the statistical
S. Elmaloglou, N. Malamos / Agricultural Water Management 43 (2000) 139±149
145
Fig. 5. Measured (symbols) and simulated (lines) water content profiles for Smax 0.005, for Julian dates: 86,
111, 140, 161.
Fig. 6. Measured (symbols) and simulated (lines) water content profiles for Smax 0.007±0.00005|z|, for Julian
dates: 86, 111, 140, 161.
146
S. Elmaloglou, N. Malamos / Agricultural Water Management 43 (2000) 139±149
Table 2
Values of the statistical parameters used in comparison for Smax
Smax
Depth (cm)
AE (cm3/cm3)
RMSE (%)
RMS (%)
EF
CRM
0.007±0.00005|z|
20
50
70
ÿ0.008
0.006
ÿ0.002
10.64
2.50
3.72
2.35
0.69
1.13
0.830
0.951
0.757
0.038
ÿ0.022
0.006
0.005
20
50
70
ÿ0.004
0.004
ÿ0.003
8.43
2.07
3.09
1.86
0.57
0.94
0.899
0.967
0.848
0.017
ÿ0.015
0.009
analysis results (Table 2). It should be noted that the deviation between simulated and
experimental values for depth 30 cm. Differences between five statistical criteria calculated to assess the difference
between measured and calculated values of against time, at three different depths,
showed that the assumption of the homogeneous distribution of Smax throughout the soil
profile resulted in a more accurate prediction of soil moisture content.
The small overall differences imply that the model is successful and can be a useful
tool in predicting the different components of the soil-water balance of a prairie field.
Acknowledgements
The authors wish to thank Prof. S. Dautrebande (Agricultural University of Gembloux,
Belgium) for providing the data concerning the soil physical characteristics and the
meteorological data. Copy of the SWAP93 model, was obtained from Prof. J.G.
Wesseling (DLO-Winard Staring Centre, Wageningen, Netherlands).
References
Belmans, C., Wesseling, J.G., Feddes, R.A., 1983. Simulation of the water balance of a cropped soil: SWATRE.
J. Hydrol. 63, 217±286.
Belmans, C., 1985. SWATRER Reference manual. Laboratory of Soil and Water Engineering, Katholieke
Universiteit Leuven, Belgium, pp. 112.
Benson, V.W., Potter, K.N., Bogusch, H.C., Goss, D., Williams, J.R., 1992. Nitrogen leaching sensitivity to
evapotraspiration and soil water storage estimates in EPIC. J. Soil Wat. Conserv. 47(4), 271±286.
Black, T.A., Gardner, W.R., Thurnell, G.W., 1969. The prediction of evaporation, drainage and soil water storage
for a bare soil. Soil Sci. Soc. Am. J. 33, 655±660.
Boesten, J.J.T.I., Stroosnijder, L., 1986. Simple model for daily evaporation from fallow tilled soil under spring
conditions in a temperate climate. Neth. J. Agric. Sc. 34, 75±90.
Boisvert, J.B., Dyer, J.A., Brewin, D., 1992b. The Versatile Soil Moisture Budget Reference Manual-VB4.
Center for Land and Biological Resources Research, Agriculture Canada, Ottawa, ON.
Childs, S.W., Gilley, J.R., Splinter, W.E., 1977. A simplified model of corn growth under moisture stress. Trans.
ASAE 20(5), 858±865.
Clemente, R.S., De Jong, R., Hayhoe, H.N., Reynolds, W.D., Hares, M., 1994. Testing and comparison of three
unsaturated soil water flow models. Agric. Water Manage. 25, 135±152.
Elmaloglou, S., 1992. Contribution to the Mathematical Simulation of the Water Balance in Soil covered by
Prairie. In: Proceedings of the Hellenic Hydrotechnical Association Symposium, November 1992, at Larisa,
Greece, pp. 3±10.
Feddes, R.A., Kowalik, P.J., Zaradny, H., 1978. Simulation of field water use and crop yield. Simulation
monographs, Pudoc, Wageningen, Netherlands.
Hack-ten Broeke, M.J.D., Hegmans, J.H.B.M., 1995. Use of soil physical characteristics from laboratory
measurements or standard series for modelling unsaturated water flow. Agric. Water Manage. 29, 201±213.
Hoogland, J.C., Feddes, R.A., Belmans, C., 1981. Root water uptake model depending on a soil water pressure
head and maximum extraction rate. Acta Horti. 119, 123±136.
Lafolie, F., 1991. Modeling water flow, nitrogen transport and root uptake including physical non-equilibrium
and optimization of the root water potential. Fert. Res. 27, 215±231.
Loague, K., Green, R.E., 1991. Statistical and graphical methods for evaluating solute transport models:
overview and application. J. Contamin. Hydrol. 7, 51±73.
Nimah, M.N., Hanks, R.J., 1973a. Model for estimating soil water, plant and atmospheric interrelations: I.
Description and sensitivity. Soil Sci. Soc. Am. Proc. 37, pp. 522±527.
S. Elmaloglou, N. Malamos / Agricultural Water Management 43 (2000) 139±149
149
Nimah, M.N., Hanks, R.J., 1973b. Model for estimating soil water, plant and atmospheric interrelations: II. Field
test of model. Soil Sci. Soc. Am. Proc. 37, pp. 528±532.
Radcliffe, D.E., Philips, R.E., Egli, D.B., Meckel, L., 1986. Experimental test of a model of water uptake by
soybean. Agron. J. 78, 526±530.
Ritchie, J.T., 1972. Model for predicting evaporation from a row crop with incomplete cover. Water Resour. Res.
8(5), 1204±1213.
Ritchie, J.T., 1985. A user oriented-model of the soil water balance in wheat. In: Day, W., Atkin, R.K., (Eds.),
Wheat Growth and Modeling. Plenum Publishing Corporation, NY, 293±305.
Smets, S.M.P., Kuper, M., Van Dam, J.C., Feddes, R.A., 1997. Salinization and crop transpiration of irrigated
fields in Pakistan's Punjab. Agric. Water Manage. 35, 43±60.
Van Aelst, P., Ragab, R.A., Feyen, J., Raes, D., 1988. Improving Irrigation Management by Modelling the
Irrigation Schedule. Agric. Water Manage. 13, 113±125.
Van den Broek, J.B., Van Dam, J.C., Elbers, J.A., Feddes, R.A., Huygen, J., Kabat, P., Wesseling, J.G., 1994.
SWAP 1993, input instructions manual. Report 45, Dep. Water Resources, Wageningen Ag. Univ.,
Netherlands.
Wagenet, R.J., Hutson, J.L., 1987. LEACHM: Leaching Estimation and Chemistry Model. A process based
model of water and solute movement, transformations, plant uptake and chemical reactions in the
unsaturated zone. Continuum Vol. 2. Water Resour. Inst., Cornell Univ., Ithaca, NY.
Wesseling, J.G., Elbers, J.A., Kabat, P., Van den Broek, B.J., 1991. SWATRE, instructions for input. Internal
report, DLO-Winard Staring Centre, Wageningen, Netherlands.
Simulation of soil moisture content of a
prairie field with SWAP93
St. Elmaloglou*, N. Malamos
Agricultural University of Athens, Department of Natural Resources and Agricultural Engineering,
Laboratory of Agricultural Hydraulics, Iera Odos 75, 11855, Athens, Greece
Accepted 9 April 1999
Abstract
A simulation study of the soil moisture content under a prairie field, in Gembloux Belgium, by
the use of the one-dimensional model SWAP93, was carried out. In order to determine the optimum
relationship that Smax is following, two concepts of maximum water extraction rate were examined.
The first one assumed a linear variation of Smax with depth z and the second assumed a
homogeneous distribution of Smax with depth z. Five statistical criteria were used to compare the
quality of simulation results, such as average error (AE), root mean square error (RMSE), root mean
square (RMS), modeling efficiency (EF) and coefficient of residual mass (CRM). The differences
between the criteria, showed that the assumption of the homogeneous distribution of Smax
throughout the soil profile resulted in a more accurate prediction of soil moisture content. The
agreement between measured and simulated water content profiles, throughout the regarded period,
was satisfactory for depths >30 cm. The deviation between simulated and experimental values for
depth 30 cm
for both cases (Figs. 5 and 6). In case of homogeneous Smax (Fig. 5) there was a better
agreement with the experimental values, which is apparent mainly from the statistical
S. Elmaloglou, N. Malamos / Agricultural Water Management 43 (2000) 139±149
145
Fig. 5. Measured (symbols) and simulated (lines) water content profiles for Smax 0.005, for Julian dates: 86,
111, 140, 161.
Fig. 6. Measured (symbols) and simulated (lines) water content profiles for Smax 0.007±0.00005|z|, for Julian
dates: 86, 111, 140, 161.
146
S. Elmaloglou, N. Malamos / Agricultural Water Management 43 (2000) 139±149
Table 2
Values of the statistical parameters used in comparison for Smax
Smax
Depth (cm)
AE (cm3/cm3)
RMSE (%)
RMS (%)
EF
CRM
0.007±0.00005|z|
20
50
70
ÿ0.008
0.006
ÿ0.002
10.64
2.50
3.72
2.35
0.69
1.13
0.830
0.951
0.757
0.038
ÿ0.022
0.006
0.005
20
50
70
ÿ0.004
0.004
ÿ0.003
8.43
2.07
3.09
1.86
0.57
0.94
0.899
0.967
0.848
0.017
ÿ0.015
0.009
analysis results (Table 2). It should be noted that the deviation between simulated and
experimental values for depth 30 cm. Differences between five statistical criteria calculated to assess the difference
between measured and calculated values of against time, at three different depths,
showed that the assumption of the homogeneous distribution of Smax throughout the soil
profile resulted in a more accurate prediction of soil moisture content.
The small overall differences imply that the model is successful and can be a useful
tool in predicting the different components of the soil-water balance of a prairie field.
Acknowledgements
The authors wish to thank Prof. S. Dautrebande (Agricultural University of Gembloux,
Belgium) for providing the data concerning the soil physical characteristics and the
meteorological data. Copy of the SWAP93 model, was obtained from Prof. J.G.
Wesseling (DLO-Winard Staring Centre, Wageningen, Netherlands).
References
Belmans, C., Wesseling, J.G., Feddes, R.A., 1983. Simulation of the water balance of a cropped soil: SWATRE.
J. Hydrol. 63, 217±286.
Belmans, C., 1985. SWATRER Reference manual. Laboratory of Soil and Water Engineering, Katholieke
Universiteit Leuven, Belgium, pp. 112.
Benson, V.W., Potter, K.N., Bogusch, H.C., Goss, D., Williams, J.R., 1992. Nitrogen leaching sensitivity to
evapotraspiration and soil water storage estimates in EPIC. J. Soil Wat. Conserv. 47(4), 271±286.
Black, T.A., Gardner, W.R., Thurnell, G.W., 1969. The prediction of evaporation, drainage and soil water storage
for a bare soil. Soil Sci. Soc. Am. J. 33, 655±660.
Boesten, J.J.T.I., Stroosnijder, L., 1986. Simple model for daily evaporation from fallow tilled soil under spring
conditions in a temperate climate. Neth. J. Agric. Sc. 34, 75±90.
Boisvert, J.B., Dyer, J.A., Brewin, D., 1992b. The Versatile Soil Moisture Budget Reference Manual-VB4.
Center for Land and Biological Resources Research, Agriculture Canada, Ottawa, ON.
Childs, S.W., Gilley, J.R., Splinter, W.E., 1977. A simplified model of corn growth under moisture stress. Trans.
ASAE 20(5), 858±865.
Clemente, R.S., De Jong, R., Hayhoe, H.N., Reynolds, W.D., Hares, M., 1994. Testing and comparison of three
unsaturated soil water flow models. Agric. Water Manage. 25, 135±152.
Elmaloglou, S., 1992. Contribution to the Mathematical Simulation of the Water Balance in Soil covered by
Prairie. In: Proceedings of the Hellenic Hydrotechnical Association Symposium, November 1992, at Larisa,
Greece, pp. 3±10.
Feddes, R.A., Kowalik, P.J., Zaradny, H., 1978. Simulation of field water use and crop yield. Simulation
monographs, Pudoc, Wageningen, Netherlands.
Hack-ten Broeke, M.J.D., Hegmans, J.H.B.M., 1995. Use of soil physical characteristics from laboratory
measurements or standard series for modelling unsaturated water flow. Agric. Water Manage. 29, 201±213.
Hoogland, J.C., Feddes, R.A., Belmans, C., 1981. Root water uptake model depending on a soil water pressure
head and maximum extraction rate. Acta Horti. 119, 123±136.
Lafolie, F., 1991. Modeling water flow, nitrogen transport and root uptake including physical non-equilibrium
and optimization of the root water potential. Fert. Res. 27, 215±231.
Loague, K., Green, R.E., 1991. Statistical and graphical methods for evaluating solute transport models:
overview and application. J. Contamin. Hydrol. 7, 51±73.
Nimah, M.N., Hanks, R.J., 1973a. Model for estimating soil water, plant and atmospheric interrelations: I.
Description and sensitivity. Soil Sci. Soc. Am. Proc. 37, pp. 522±527.
S. Elmaloglou, N. Malamos / Agricultural Water Management 43 (2000) 139±149
149
Nimah, M.N., Hanks, R.J., 1973b. Model for estimating soil water, plant and atmospheric interrelations: II. Field
test of model. Soil Sci. Soc. Am. Proc. 37, pp. 528±532.
Radcliffe, D.E., Philips, R.E., Egli, D.B., Meckel, L., 1986. Experimental test of a model of water uptake by
soybean. Agron. J. 78, 526±530.
Ritchie, J.T., 1972. Model for predicting evaporation from a row crop with incomplete cover. Water Resour. Res.
8(5), 1204±1213.
Ritchie, J.T., 1985. A user oriented-model of the soil water balance in wheat. In: Day, W., Atkin, R.K., (Eds.),
Wheat Growth and Modeling. Plenum Publishing Corporation, NY, 293±305.
Smets, S.M.P., Kuper, M., Van Dam, J.C., Feddes, R.A., 1997. Salinization and crop transpiration of irrigated
fields in Pakistan's Punjab. Agric. Water Manage. 35, 43±60.
Van Aelst, P., Ragab, R.A., Feyen, J., Raes, D., 1988. Improving Irrigation Management by Modelling the
Irrigation Schedule. Agric. Water Manage. 13, 113±125.
Van den Broek, J.B., Van Dam, J.C., Elbers, J.A., Feddes, R.A., Huygen, J., Kabat, P., Wesseling, J.G., 1994.
SWAP 1993, input instructions manual. Report 45, Dep. Water Resources, Wageningen Ag. Univ.,
Netherlands.
Wagenet, R.J., Hutson, J.L., 1987. LEACHM: Leaching Estimation and Chemistry Model. A process based
model of water and solute movement, transformations, plant uptake and chemical reactions in the
unsaturated zone. Continuum Vol. 2. Water Resour. Inst., Cornell Univ., Ithaca, NY.
Wesseling, J.G., Elbers, J.A., Kabat, P., Van den Broek, B.J., 1991. SWATRE, instructions for input. Internal
report, DLO-Winard Staring Centre, Wageningen, Netherlands.