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Given the potential role of vegetation in controlling water pollution by trapping clay particles in the landscape, changes are also made to the way the model deals with sediment deposition and to allow the model to incorporate particle-size selectivity in the processes of erosion, transport and deposition. Vegetation effects are described in relation to percentage canopy cover, percentage ground cover, plant height, effective hydrological depth, density of plant stems and stem diameter. Deposition is modelled through a particle fall number, which takes account of particle settling velocity, flow velocity, flow depth and slope length. The detachment, transport and deposition of soil particles are simulated separately for clay, silt and sand. Average linear sensitivity analysis shows that the revised model behaves rationally. For bare soil conditions soil loss predictions are most sensitive to changes in rainfall and soil parameters, but with a vegetation cover plant parameters become more important than soil parameters. Tests with the model using field measurements under a range of slope, soil and crop covers from Bedfordshire and Cambridgeshire, UK, give good predictions of mean annual soil loss. Regression analysis of predicted against observed values yields an intercept value close to zero and a line slope close to 1\u00b70, with a coefficient of efficiency of 0\u00b781 over a range of values from zero to 38\u00b76 t ha\u22121. Copyright \u00a9 2007 John Wiley & Sons, Ltd.", "formats": [{"name": "R package"}], "keywords": ["Global", "model", "Crop"], "contacts": [{"name": "R. P. C. Morgan, J. H. 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An international team of scientists developed a decision support system for agrotechnology transfer (DSSAT) to estimate production, resource use, and risks associated with different crop production practices. The DSSAT is a microcomputer software package that contains crop-soil simulation models, data bases for weather, soil, and crops, and strategy evaluation programs integrated with a \u2018shell\u2019 program which is the main user interface. In this paper, an overview of the DSSAT is given along with rationale for its design and its main limitations. Concepts for using the DSSAT in spatial decision support systems (for site-specific farming, farm planning, and regional policy) are presented. DSSAT provides a framework for scientific cooperation through research to enhance its capabilities and apply it to research questions. It also has considerable potential to help decision makers by reducing the time and human resources required for analyzing complex alternative decisions.", "formats": [{"name": "Website"}, {"name": "Git repository"}], "keywords": ["Global", "models", "decision support system", "DSSAT", "sustainability", "technology transfer", "risk management", "Crop"], "contacts": [{"name": "J. W. Jones, G. Y. Tsuji, G. Hoogenboom, L. A. Hunt, P. K. Thornton, P. W. Wilkens, D. T. Imamura, W. T. Bowen & U. Singh", "organization": "Department of Agricultural and Biological Engineering, University of Florida", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": null}], "addresses": [{"deliveryPoint": ["P.O. 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The model is currently being utilized in several large area projects by EPA, NOAA, NRCS and others to estimate the off-site impacts of climate and management on water use, non-point source loadings, and pesticide contamination. Model development, operation, limitations, and assumptions are discussed and components of the model are described. In Part II, a GIS input/output interface is presented along with model validation on three basins within the Upper Trinity basin in Texas.", "formats": [{"name": "Website"}, {"name": "Git repository"}], "keywords": ["Global", "Crop"], "contacts": [{"name": "J. G. Arnold, R. Srinivasan, R. S. Muttiah, J. R. 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At the start of yield formation period, HI increases linearly with time after a lag phase, until near physiological maturity. Other than for the yield, there is no biomass partitioning into the various organs. Crop responses to water deficits are simulated with four modifiers that are functions of fractional available soil water modulated by evaporative demand, based on the differential sensitivity to water stress of four key plant processes: canopy expansion, stomatal control of transpiration, canopy senescence, and HI. The HI can be modified negatively or positively, depending on stress level, timing, and canopy duration. AquaCrop uses a relatively small number of parameters (explicit and mostly intuitive) and attempts to balance simplicity, accuracy, and robustness. 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