- Email: [email protected]
4M-software package for modelling cropping systems
Europ. J. Agronomy 18 (2003) 389 /393 www.elsevier.com/locate/eja
Short communication
4M-software package for modelling cropping systems Na´ndor Fodor a, , Gabriella Ma´the´ne´-Ga´spa´r a, Kla´ra Pokovai b, Ge´za J. Kova´cs a a
Research Institute for Soil Science and Agriculture Chemistry, Budapest 1022, Heman Otto´ u. 15., Hungary b Debrecen University, Debrecen 4032 Bo¨szo¨rme´nyi u. 138., Hungary
Abstract 4M is an easy-to-handle software that has been designed for both educational and scientific purposes. Our main goal in developing 4M was to preserve the features of CERES in a user-friendly software that can be easily extended with additional modules. The package has several characteristics that make it more than a simple crop model. 4M offers optional routines for several processes of the described soil-plant-atmosphere system. The users can build different system models, according to specific purposes. 4M includes input data generators for estimating soil and weather input data that are difficult to measure. 4M is able to simulate crop rotations by using the final conditions of the system after crop harvest as initial conditions for the following crop. # 2002 Elsevier Science B.V. All rights reserved. Keywords: CERES; Input data generator; Crop rotation; Modelling
1. Introduction During the past decade, while using and developing the crop models of DSSAT package, we felt the need for a flexible software tool for teaching crop science and agronomy, as well as being userfriendly and easy to develop. CERES 3.5, offered to us by Joe T. Ritchie as a basis for development, simulates water balance (Ritchie, 1981), nitrogen balance (Godwin and Jones, 1991), plant phenology and growth (Ritchie et al., 1998) and it was tested for production and environmental purposes
Corresponding author. Tel.: /36-1-3564644; fax: /36-13564682 E-mail address: [email protected] (N. Fodor).
(Kova´cs et al., 1995). 4M inherited all these characteristics. Although we were acquainted with the MS Windows version of CERES (Caldwell, 2000), we aimed at developing a crop model package with additional subroutines that CERES originally did not include. Our first goal was to incorporate a routine to model the water balance of soil profiles affected by shallow water table. In 2001, a small group of Hungarian crop modellers started to develop 4M. The Fortran source code of CERES 3.5 was translated into Delphi. A user-friendly interface was created to handle inputs, outputs and procedures, and several new procedures/modules were incorporated. During the spring semesters of 2001 and 2002 versions 1.0 and 1.5, respectively, were tested at the Debrecen University with positive results.
1161-0301/02/$ - see front matter # 2002 Elsevier Science B.V. All rights reserved. PII: S 1 1 6 1 - 0 3 0 1 ( 0 2 ) 0 0 1 2 6 - 0
390
N. Fodor et al. / Europ. J. Agronomy 18 (2003) 389 /393
2. Software description The main idea behind 4M was to initiate the creation of a system that enables the user to build up his or her own model by selecting procedures made available by the software for each process of the described soil-plant-atmosphere system. The procedures that have been taken over from CERES (source code) are marked, in the following list, with an ‘ ’. The procedures that were developed by the 4M team are marked with a ‘/’. Other scientists have developed the unmarked routines. Their algorithms have been incorporated into 4M (see points 1, 2, 3 below). Since every model needs input data that sometimes (or often) are either missing, incomplete or difficult to measure, a great emphasis is placed on input data estimation (see points 5, 6 below). Since user-friendliness is one of the main goals of the software development, an easy-to-handle interface has been created (see points 13, 14, 15,16 below). Therefore, 4M has the following characteristics: 1)
Optional procedures for different processes are as follows: a) Water balance routines include a capacitive (Ritchie, 1981) and a conductive one (van Dam et al., 1997; Simunek et al., 1998). b) Potential evapotranspiration routines are as follows: Priestley and Taylor (1972) , Sza´sz (1973) , and FAO-24 Penman (Doorenbos and Pruitt, 1977) . c) Canopy growth routines for maize can be selected, either a ‘one leaf’ type (Jones and Kiniry, 1986) or a ‘leaf by leaf’ type (Kova´cs et al., 1989). d) Leaf appearance rate routines can be chosen from Tollenaar et al. (1979), Jones and Kiniry (1986) ; and Jame et al. (1999). e) Routines for describing preferential flow of soil water can be selected for bypass flow in cracked shrinking-swelling soils (Feddes et al., 1988; Fodor, 2002); or bypass flow using bimodal
2)
3)
4) 5)
6)
7)
retention curves (Mohanty et al., 1997 modified by Fodor, 2002). The conductive water balance routine implements a numerical solution of the Richards equation. It uses the Brooks-Corey or the van Genuchten function for describing the retention curve (Brooks and Corey, 1964; van Genuchten, 1980) combined with Mualem’s concept for describing the condictivityhead relationship (Mualem, 1976). 4M is able to describe the water balance of soils that have bimodal porosity by using bimodal retention function and unsaturated hydraulic conductivity function. 4M includes a procedure for describing hysteresis (Kool and Parker, 1987). 4M includes several procedures for estimating soil-related input data. These routines use data, that are easy to measure, such as: bulk density, organic matter content, clay content, etc. a) One can select from two pedotransfer functions for calculating hydraulic conductivity (Campbell, 1985; Wo¨sten et al., 1999). b) Three sets of pedotransfer functions are available for calculating the parameters of the van Genuchten type of retention curve (Rajkai, 1987 ; Wo¨sten et al., 1999; Fodor, 2002 ). c) Two sets of pedotransfer functions can be used for calculating the saturated water content, field capacity and wilting point (Rajkai, 1987; Ritchie et al., 1999). 4M includes two procedures for estimating daily global solar radiation: a) The procedure of Sza´sz (1968) uses sunshine hours. b) The incorporated Fodor-Ritchie’ method (Fodor et al., 2001) is similar to the Bristow and Campbell method (1984) and uses the daily minimum and maximum temperatures. (However, it applies different equations for days with and without precipitation.) 4M includes a module for curve fitting. The Brooks and Corey (1964) and van Genuch-
N. Fodor et al. / Europ. J. Agronomy 18 (2003) 389 /393
8)
9)
10)
11) 12) 13) 14) 15)
16)
ten (1980) types of retention curves can be fitted on the measured pF data using the Levenberg-Marquardt method (Marquardt, 1963). This module is able to fit bimodal retention curves, as well. 4M is able to describe the effect of irrigation, and the effects of inorganic and organic fertilization on crop growth and development. 4M is able to handle 100 year long runs (with crop rotation). The final conditions of the system after crop harvest are used as initial conditions for the following crop. Three crops (maize, wheat, barley) can be simulated in the current version (Ritchie et al., 1998). Weather scenarios can be produced for climate change studies. Potential yield can be simulated by switching off the effect of water and nitrogen stresses. All of the input data are easy to access, change, and save through the user interface. Large weather filed can be imported from Excel. 4M includes a graphical tool that can present two output variables of five runs at the same time. Two dialogue languages are available, Hungarian and English. The German version is under development.
3. Illustrative results 4M (with its new conductive water balance module) was compared to UNSATCHEM (Simunek et al., 1996) and LEACHM (Hutson and Wagenet, 1992), using data collected at two sites in Hungary both were affected by their high water tables (To´th and Jozefaciuk, 2002). The root mean square errors (RMSE) between the simulated and measured soil water contents (m3 m 3) (at 0 /0.3 m depth) are: RMSE /0.142, 0.146, AND 0.147 for UNSATCHEM, LEACHM and 4M, respectively. The capacitive and conductive water balance modules of 4M were compared using the data collected on a site (two profiles, 2 years) having
391
deep water table. Both of the modules simulated the water contents of the profiles within the error of the measurement. This is a notable result, since it is much easier to determine the input data of the capacitive modules. Simulation studies were carried out for a selected profile of the Hungarian Soil Database (Rajkai et al., 1981; Va´rallyay, 1987) having horizons with bimodal porosity. Simulations were made, and the results were compared using two different soil input files, first, with (the parameters of) unimodal retention curves for all of the horizons of the profile, and second, with bimodal retention curves for the horizons having bimodal porosity. Significant differences (/0.10 m3 m 3, Fig. 1.) were observed between the simulated water contents (especially in rainy years: Fig. 1) and 0.3 /22.2% differences were found (depending on the weather) considering the simulated yield. Three kinds of model runs were carried out while testing the preferential flow module of 4M, first, without using the preferential flow module, second, using the module with equally distributed daily rainfall (simulation models often use this assumption), third, using the module supposing that during the summer time, the bigger rainfall events (/20 mm) last for 15 /20 min (rainstorms), something that happens very frequently in Hungary. An example, of the results, is presented on Fig. 2. The incorporated solar radiation estimators have been tested only on Hungarian data sets, so
Fig. 1. Simulated water contents of a soil layer (depth: 0.55 / 0.70 m, Mezo¨tu´r, Hungary, 1987) characterised by bimodal porosity.
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N. Fodor et al. / Europ. J. Agronomy 18 (2003) 389 /393
References
Fig. 2. Simulated water contents of a soil layer of a profile (depth: 0.50 /0.70 m, Nyiro¨lapos, Hungary, 1999) with shrinking /swelling characteristics.
far. The average error (AE) was calculated for two sites, comparing the measured and predicted (obtained by the Fodor-Ritchie method) solar radiation. For Budapest (1968-1987), AE /2.20 MJ m 2, R2 /0.87 and for Debrecen (1970-1974): AE /2.47 MJ m 2, R2 /0.84. The Sza´sz method, using sunshine hours, gave even better results for Budapest (R2 /0.94).
4. System requirements 4M ver. 1.5 runs under WIN95/98/NT/ME/XP. The software requires (at least) 4MB free disk space, 16MB memory, PI processor, and 800 /600 screen resolution. 4M ver. 1.5 can be downloaded from: http:// www.taki.iif.hu/english/agrok/fodor/.
5. Final remarks The 4M group developed a pea model, that is planned to be included in the next version, together with a sunflower and a generic plant model. The group is working on incorporating a weather generator and a module for carrying out economical analysis. In the next phase of development, 4M (point model) will be linked with a digital terrain model in order to handle field conditions more realistically. This research work has been supported by OTKA (T 029217 and T 032768).
Bristow, R.L., Campbell, G.S., 1984. On the relationship between incoming solar radiation and daily maximum and minimum temperature. Agric. For. Meteor. 31, 159 /166. Brooks, R.H., Corey, A.T., 1964. Hydraulic Properties of Porous Media Hydrology Paper 3, Colorado St. Univ., Fort Collins. Caldwell, R.M., 2000. Object-oriented CERES. Annual Meeting Abstract. ASA-CSSA-SSSA, 5-9 November, Minneapolis, Minnesota, p 18. Campbell, G.S., 1985. Soil Physics with BASIC. Transport Models for Soil-Plant Systems. Elsevier, pp. 53 /54. Doorenbos, J., Pruitt, W.O., 1977. Guidelines for predicting crop water requirements. In: Irrigation and drainage paper 24. (2nd edition) FAO, Rome, p 156. Feddes, R.A., Kabbat, P., van Bakel, P.J.T., Bronswijk, J.J.B., Halbertsma, J., 1988. Modelling soil water dynamics in the unsaturated zone-state of art. J. Hydr. 100, 69 /111. Fodor, N., 2002. Modeling the water balance of soil profiles in crop models. Ph.D. thesis. Debrecen University. Fodor, N., Kova´cs, G.J., Ritchie, J.T., 2001. A New Solar Radiation Generator for Hungary. Annual Meeting Abstract. ASA-CSSA-SSSA, 5-9 November, Minneapolis, Minnesota, p 23. Godwin, D.C., Jones, C.A., 1991. Nitrogen dynamics in the soil-plant systems. In: Hanks, J., Ritchie, J.T. (Eds.), Modeling Soil and Plant Systems. ASA Monograph 31., American Society of Agronomy, Medison, WI, pp. 289-321. Hutson, J.L., Wagenet, R.J., 1992. 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. Version 3.0. Department of Soil, Crop and Atmospheric Sciences, Research Series No. 93-3, Cornell University, Ithaca, New York. Jame, Y.W., Cutforth, H.W., Ritchie, J.T., 1999. Temperature response function for leaf appearance rate in wheat and corn. Can. J. Plant Sci. 79, 1 /10. Jones, C.A., Kiniry, J.R. (Eds.), CERES-Maize. A Simulation Model of Maize Growth and Development. Texas A&M University Press 1986. Kool, J.B., Parker, J.C., 1987. Development and evaluation of closed-form expressions for hysteretic soil hydraulic properties. Water Resour. Res. 23, 105 /114. Kova´cs, G.J., Ne´meth, T., Ritchie, J.T., 1995. Testing Simulation Models for Assessment of Crop Production and Nitrate Leaching in Hungary. Agricultural Systems, Elsevier Sci. Ld., Oxford, England, 49 (4) 385 /397. Kova´cs, G. J., Ritchie, J.T., Werner, A., Ma´the´ne´-Ga´spa´r, G., Ma´the´, P., 1989. Modeling the leaf area development of different maize genotypes. In: Proc. of IBSNAT Symposium, Annual Meeting of the American Society of Agronomy, 15-21 October, Las Vegas. Marquardt, D.W., 1963. An algorithm for least-squares estimation of nonlinear parameters. SIAM J. Appl. Math. 11, 431 /441.
N. Fodor et al. / Europ. J. Agronomy 18 (2003) 389 /393 Mohanty, B.P., Bowman, R.S., Hendrickx, J.M.H., van Genuchten, M.T., 1997. New piecewise-continuous hydraulic functions for modeling preferential flow in an intermitted-flood-irrigated field. Water Resour. Res. 33, 2049 / 2063. Mualem, Y., 1976. A new model for predicting the hydraulic conductivity of unsaturated porous media. Water Resour. Res. 12, 513 /522. Priestley, C.H.B., Taylor, R.J., 1972. On the assessment of surface heat flux and evaporation using large-scale parameters. Monthly Water Rev. 100, 81 /92. Rajkai, K., 1987. A talaj vı´ztarto´ke´pesse´ge e´s ku¨lo¨nbo¨zo¨ talajtulajdonsa´gok o¨sszefu¨gge´se´nek vizsga´lata. Agroke´mia e´s Talajtan 36, 15 /28. Rajkai, K., Va`rallyay, Gy., Pacsepszkij, J.A., Cserbakov, R.A., 1981. pf-go¨rbe´k sza´mı´ta´sa a talaj mechanikai o¨sszetetele e´s te´rfogatto¨mege alapja´n. Agrokemia e´s Talajtan 30, 409 / 438. Ritchie, J.T., 1981. Water dynamics in the soil-plant-atmosphere. Plant Soil 58, 81 /96. Ritchie, J.T., Singh, U., Godwin, D.C., Bowen, W.T., 1998. Cereal growth, development and yield. In: Tsuji, G.Y., Hoogenboom, G., Thornton, P.K. (Eds.), Understanding Options for Agricultural Production, Systems Approaches for Sustainable Agricultural Development. Kluwer Academic Publishers, Dordrecht, the Netherlands, pp. 79 /98. Ritchie, J.T., Gerakis, A., Suleiman, A., 1999. Simple model to estimate field-measured soil water limits. Trans. ASAE 42, 1609 /1614. Simunek, J., Suarez, D.L., Sejna, M., 1996. The UNSATCHEM Software package for simulating the onedimensional variably saturated water flow, heat transport, carbon dioxide production and transport, and solute trans-
393
port with major ion equilibrium and kinetic chemistry, Version 2.0, Research Report No. 141, U.S. Salinity Laboratory, USDA-ARS, Riverside, California. Simunek, J., Huang, K., van Genuchten, M.T., 1998. The HYDRUS code for simulating the one-dimensional movement of water, heat, and multiple solutes in variablysaturated media. Version 6.0, Research Report No. 144, U.S. Salinity Laboratory, USDA-ARS, Riverside, California. Sza´sz, G., 1968. A globa´lsuga´rza´s u¨sszegeinek meghata´roza´sa sza´mitı´s a´tja´n. Debreceni Agra´rtudoma´nyi Fo¨iskola Tudoma´nyos Ko¨zleme´nyei 14, 239 /253. Sza´sz, G., 1973. A potencia´lis pa´rolga´s meghata´roza´sa´nak u´j mo´dszere. Hidrolo´giai Ko¨zlo¨ny 10, 435 /442. Tollenaar, M., Daynard, T.B., Hunter, R.B., 1979. Effect of temperature on rate of leaf appearance and flowering date in maize. Crop Sci. 19, 137 /153. To´th, T., Jozefaciuk, G., 2002. Physicochemical properties of a solonetzic toposequence. Geoderma 106, 137 /159. van Dam, J.C., Huygen, J., Wesseling, J.G., Feddes, R.A., Kabbat, P., van Walsum, P.E.V., Groenendijk, P., van Diepen, C.A., 1997. SWAP 2.0 Simulation of waterflow, solute transport and plat growth in Soil-Water-AtmospherePlant environment Department of Water Resources, Wageningen Agricultural University. van Genuchten, M.T., 1980. A closed form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J. 44, 892 /898. Va´rallyay, Gy., 1987. A talaj vizgazda´lkoda´sa Akade´miai doktori e´rtekeze´s. Budapest. Wo¨sten, J.H.M., Lilly, A., Nemes, A., le Bas, C., 1999. Development and use of dataset of hydraulic properties of European soils. Geoderma 90, 169 /185.
Short communication
4M-software package for modelling cropping systems Na´ndor Fodor a, , Gabriella Ma´the´ne´-Ga´spa´r a, Kla´ra Pokovai b, Ge´za J. Kova´cs a a
Research Institute for Soil Science and Agriculture Chemistry, Budapest 1022, Heman Otto´ u. 15., Hungary b Debrecen University, Debrecen 4032 Bo¨szo¨rme´nyi u. 138., Hungary
Abstract 4M is an easy-to-handle software that has been designed for both educational and scientific purposes. Our main goal in developing 4M was to preserve the features of CERES in a user-friendly software that can be easily extended with additional modules. The package has several characteristics that make it more than a simple crop model. 4M offers optional routines for several processes of the described soil-plant-atmosphere system. The users can build different system models, according to specific purposes. 4M includes input data generators for estimating soil and weather input data that are difficult to measure. 4M is able to simulate crop rotations by using the final conditions of the system after crop harvest as initial conditions for the following crop. # 2002 Elsevier Science B.V. All rights reserved. Keywords: CERES; Input data generator; Crop rotation; Modelling
1. Introduction During the past decade, while using and developing the crop models of DSSAT package, we felt the need for a flexible software tool for teaching crop science and agronomy, as well as being userfriendly and easy to develop. CERES 3.5, offered to us by Joe T. Ritchie as a basis for development, simulates water balance (Ritchie, 1981), nitrogen balance (Godwin and Jones, 1991), plant phenology and growth (Ritchie et al., 1998) and it was tested for production and environmental purposes
Corresponding author. Tel.: /36-1-3564644; fax: /36-13564682 E-mail address: [email protected] (N. Fodor).
(Kova´cs et al., 1995). 4M inherited all these characteristics. Although we were acquainted with the MS Windows version of CERES (Caldwell, 2000), we aimed at developing a crop model package with additional subroutines that CERES originally did not include. Our first goal was to incorporate a routine to model the water balance of soil profiles affected by shallow water table. In 2001, a small group of Hungarian crop modellers started to develop 4M. The Fortran source code of CERES 3.5 was translated into Delphi. A user-friendly interface was created to handle inputs, outputs and procedures, and several new procedures/modules were incorporated. During the spring semesters of 2001 and 2002 versions 1.0 and 1.5, respectively, were tested at the Debrecen University with positive results.
1161-0301/02/$ - see front matter # 2002 Elsevier Science B.V. All rights reserved. PII: S 1 1 6 1 - 0 3 0 1 ( 0 2 ) 0 0 1 2 6 - 0
390
N. Fodor et al. / Europ. J. Agronomy 18 (2003) 389 /393
2. Software description The main idea behind 4M was to initiate the creation of a system that enables the user to build up his or her own model by selecting procedures made available by the software for each process of the described soil-plant-atmosphere system. The procedures that have been taken over from CERES (source code) are marked, in the following list, with an ‘ ’. The procedures that were developed by the 4M team are marked with a ‘/’. Other scientists have developed the unmarked routines. Their algorithms have been incorporated into 4M (see points 1, 2, 3 below). Since every model needs input data that sometimes (or often) are either missing, incomplete or difficult to measure, a great emphasis is placed on input data estimation (see points 5, 6 below). Since user-friendliness is one of the main goals of the software development, an easy-to-handle interface has been created (see points 13, 14, 15,16 below). Therefore, 4M has the following characteristics: 1)
Optional procedures for different processes are as follows: a) Water balance routines include a capacitive (Ritchie, 1981) and a conductive one (van Dam et al., 1997; Simunek et al., 1998). b) Potential evapotranspiration routines are as follows: Priestley and Taylor (1972) , Sza´sz (1973) , and FAO-24 Penman (Doorenbos and Pruitt, 1977) . c) Canopy growth routines for maize can be selected, either a ‘one leaf’ type (Jones and Kiniry, 1986) or a ‘leaf by leaf’ type (Kova´cs et al., 1989). d) Leaf appearance rate routines can be chosen from Tollenaar et al. (1979), Jones and Kiniry (1986) ; and Jame et al. (1999). e) Routines for describing preferential flow of soil water can be selected for bypass flow in cracked shrinking-swelling soils (Feddes et al., 1988; Fodor, 2002); or bypass flow using bimodal
2)
3)
4) 5)
6)
7)
retention curves (Mohanty et al., 1997 modified by Fodor, 2002). The conductive water balance routine implements a numerical solution of the Richards equation. It uses the Brooks-Corey or the van Genuchten function for describing the retention curve (Brooks and Corey, 1964; van Genuchten, 1980) combined with Mualem’s concept for describing the condictivityhead relationship (Mualem, 1976). 4M is able to describe the water balance of soils that have bimodal porosity by using bimodal retention function and unsaturated hydraulic conductivity function. 4M includes a procedure for describing hysteresis (Kool and Parker, 1987). 4M includes several procedures for estimating soil-related input data. These routines use data, that are easy to measure, such as: bulk density, organic matter content, clay content, etc. a) One can select from two pedotransfer functions for calculating hydraulic conductivity (Campbell, 1985; Wo¨sten et al., 1999). b) Three sets of pedotransfer functions are available for calculating the parameters of the van Genuchten type of retention curve (Rajkai, 1987 ; Wo¨sten et al., 1999; Fodor, 2002 ). c) Two sets of pedotransfer functions can be used for calculating the saturated water content, field capacity and wilting point (Rajkai, 1987; Ritchie et al., 1999). 4M includes two procedures for estimating daily global solar radiation: a) The procedure of Sza´sz (1968) uses sunshine hours. b) The incorporated Fodor-Ritchie’ method (Fodor et al., 2001) is similar to the Bristow and Campbell method (1984) and uses the daily minimum and maximum temperatures. (However, it applies different equations for days with and without precipitation.) 4M includes a module for curve fitting. The Brooks and Corey (1964) and van Genuch-
N. Fodor et al. / Europ. J. Agronomy 18 (2003) 389 /393
8)
9)
10)
11) 12) 13) 14) 15)
16)
ten (1980) types of retention curves can be fitted on the measured pF data using the Levenberg-Marquardt method (Marquardt, 1963). This module is able to fit bimodal retention curves, as well. 4M is able to describe the effect of irrigation, and the effects of inorganic and organic fertilization on crop growth and development. 4M is able to handle 100 year long runs (with crop rotation). The final conditions of the system after crop harvest are used as initial conditions for the following crop. Three crops (maize, wheat, barley) can be simulated in the current version (Ritchie et al., 1998). Weather scenarios can be produced for climate change studies. Potential yield can be simulated by switching off the effect of water and nitrogen stresses. All of the input data are easy to access, change, and save through the user interface. Large weather filed can be imported from Excel. 4M includes a graphical tool that can present two output variables of five runs at the same time. Two dialogue languages are available, Hungarian and English. The German version is under development.
3. Illustrative results 4M (with its new conductive water balance module) was compared to UNSATCHEM (Simunek et al., 1996) and LEACHM (Hutson and Wagenet, 1992), using data collected at two sites in Hungary both were affected by their high water tables (To´th and Jozefaciuk, 2002). The root mean square errors (RMSE) between the simulated and measured soil water contents (m3 m 3) (at 0 /0.3 m depth) are: RMSE /0.142, 0.146, AND 0.147 for UNSATCHEM, LEACHM and 4M, respectively. The capacitive and conductive water balance modules of 4M were compared using the data collected on a site (two profiles, 2 years) having
391
deep water table. Both of the modules simulated the water contents of the profiles within the error of the measurement. This is a notable result, since it is much easier to determine the input data of the capacitive modules. Simulation studies were carried out for a selected profile of the Hungarian Soil Database (Rajkai et al., 1981; Va´rallyay, 1987) having horizons with bimodal porosity. Simulations were made, and the results were compared using two different soil input files, first, with (the parameters of) unimodal retention curves for all of the horizons of the profile, and second, with bimodal retention curves for the horizons having bimodal porosity. Significant differences (/0.10 m3 m 3, Fig. 1.) were observed between the simulated water contents (especially in rainy years: Fig. 1) and 0.3 /22.2% differences were found (depending on the weather) considering the simulated yield. Three kinds of model runs were carried out while testing the preferential flow module of 4M, first, without using the preferential flow module, second, using the module with equally distributed daily rainfall (simulation models often use this assumption), third, using the module supposing that during the summer time, the bigger rainfall events (/20 mm) last for 15 /20 min (rainstorms), something that happens very frequently in Hungary. An example, of the results, is presented on Fig. 2. The incorporated solar radiation estimators have been tested only on Hungarian data sets, so
Fig. 1. Simulated water contents of a soil layer (depth: 0.55 / 0.70 m, Mezo¨tu´r, Hungary, 1987) characterised by bimodal porosity.
392
N. Fodor et al. / Europ. J. Agronomy 18 (2003) 389 /393
References
Fig. 2. Simulated water contents of a soil layer of a profile (depth: 0.50 /0.70 m, Nyiro¨lapos, Hungary, 1999) with shrinking /swelling characteristics.
far. The average error (AE) was calculated for two sites, comparing the measured and predicted (obtained by the Fodor-Ritchie method) solar radiation. For Budapest (1968-1987), AE /2.20 MJ m 2, R2 /0.87 and for Debrecen (1970-1974): AE /2.47 MJ m 2, R2 /0.84. The Sza´sz method, using sunshine hours, gave even better results for Budapest (R2 /0.94).
4. System requirements 4M ver. 1.5 runs under WIN95/98/NT/ME/XP. The software requires (at least) 4MB free disk space, 16MB memory, PI processor, and 800 /600 screen resolution. 4M ver. 1.5 can be downloaded from: http:// www.taki.iif.hu/english/agrok/fodor/.
5. Final remarks The 4M group developed a pea model, that is planned to be included in the next version, together with a sunflower and a generic plant model. The group is working on incorporating a weather generator and a module for carrying out economical analysis. In the next phase of development, 4M (point model) will be linked with a digital terrain model in order to handle field conditions more realistically. This research work has been supported by OTKA (T 029217 and T 032768).
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