Soil simulation models

Knox JW, Matthews RB, Wassmann R. 2000. Using a crop/soil simulation model and GIS techniques to assess methane emissions from rice fields in Asia. III. Databases. Nutrient Cycling in Agroecosystems 58 179-199. 

One of the first complete, continuous simulation models was the pesticide mnoff transport model (PRT) (56). Improvements in the PRT modelled to the hydrologic simulation program—FORTRAN model (57). A number of other models have been developed (58,59). These models represent a compromise between the avadable data and the abiHty to encompass a wide range in soils, climates, and pesticides. These models have had mixed success when extended beyond the data with which they were caHbrated. No model has yet been developed that can be proven to give accurate predictions of... 

H. W. Hunt, J. A. E. Stewart, and C. V. Cole, Concepts of sulphur, carbon and nitrogen transformations in soil evaluation of simulating modeling. Bioj eochemis-try 2 163 (1986). 

P. de Willigen, Nitrogen turnover in the soil crop system—comparison of 14 simulation models. Feitil. Res. 27 141 (1991). 

L. Pages. M. D. Jourdan, and D. Picard, A simulation model of the three-dimensional architecture of the maize root system. Plant Soil II9 41 (1989). 

R. F. Grant, Simulation model of soil compaction and root growth I. Model development. Plant Soil 750 15 (1993). 

R. J. Ryel and M. M. Caldwell, Nutrient acquisition from soils with patchy nutrient di.stributions as a.ssessed with simulation models. Ecology 79 2725 (1998). 

Rao, P.S.C. and Jessup, R.E., Development and verification of simulation models for describing pesticides dynamics in soils, Ecol. Modeling, 16, 67-75, 1982. 

UNSAT-H simulates plant transpiration with a PET concept. The model partitions plants removal of soil-water between soil layers based on (1) distribution of plant roots within the soil profile for cheatgrass (an invading and weedy grass species found in dry regions of Washington State) or (2) the user may supply other functions. The user must enter soil-water parameters that describe the limits for plant extraction of water from each layer of soil. The model also uses the same daily value pattern for the LAI for each year. 

Without a solution, formulated mathematical systems (models) are of little value. Four solution procedures are mainly followed the analytical, the numerical (e.g., finite different, finite element), the statistical, and the iterative. Numerical techniques have been standard practice in soil quality modeling. Analytical techniques are usually employed for simplified and idealized situations. Statistical techniques have academic respect, and iterative solutions are developed for specialized cases. Both the simulation and the analytic models can employ numerical solution procedures for their equations. Although the above terminology is not standard in the literature, it has been used here as a means of outlining some of the concepts of modeling. 

Aldicarb residues leached deeper than one meter 6-9 months after application to a sandy Long Island soil (39) Based on a comparison of computer simulation modeling and ground water data, at least several percent of the aldicarh applied to certain Long Island fields leached to ground water (37). 

Ge, Z., Rubio, G., and Lynch, J. R (2000). The importance of root gravitropism for inter-root competition and phosphorus acquisition efficiency Results from a geometric simulation model. Plant Soil 218,159-171. 

Walker, S.R. and W.M. Blacklow (1994). Adsorption and degradation of triazine herbicides in soils used for lupin production in Western Australia Laboratory studies and a simulation model. Aust. J. Soil Res., 32 1189-1205. 

Dutt, G. R., Shaffer, M. J., and Moore, W. J. (1972). Computer simulation model of dynamic bio-physicochemical processes in soils. Ariz. Agric. Exp. Stn., Tech. Bull. 196. 

SVATs are simulated models that use parameters such as vegetation cover, soil texture, water-holding capacity of soils, surface roughness, and albedo, to make predictions on soil moisture, evapotranspiration, and runoff. 

Figure 8.7 Rates of fresh litter decomposition (y-1) in soils in the USA, using a simulation model based on evapotranspiration rates as a predictive variable. Contour lines represent loss rate (k) during an initial year of decay. (Modified from Meentemeyer, 1978.)...

Bronswijk, J. J, B. and J. E. Groenenberg 1993. SMASS A simulation model for acid sulfate soils. I. Basic principles. In D. Dent and M. E. F. van Mensvoort, Eds. Selected Paper, Saigon Symposium on Acid Sulfate Soils, Ho Chi Minh City, Vietnam, March 2-6 1992. ILRI Publication 52. Institute for Land Reclamation and Improvement, Wageningen, The Netherlands. 

THERdbASE contains two major modules, namely a Database Module and a Model Base Module. The Database Module relates information from exposure, dose and risk-related data files, and contains information about the following population distributions, location/activity patterns, food-consumption patterns, agent properties, agent sources (use patterns), environmental agent concentrations, food contamination, physiological parameters, risk parameters and miscellaneous data files. The Model Base Module provides access to exposure dose and risk-related models. The specific models included with the software are as follows Model 101, subsetting activity pattern data Model 102, location patterns (simulated) Model 103, source (time application) Model 104, source (instantaneous application) Model 105, indoor air (two zones) Model 106, indoor air (n zones) Model 107, inhalation exposure (BEAM) Model 108, inhalation exposure (multiple chemicals) Model 109, dermal dose (film thickness) Model 110, dose scenario (inhalation/dermal) Model 201, soil exposure (dose assessment). 

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