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The system is applicable to well \ndrained, deep soils, that have a pH(H20) in the range 4.5\u20137.0, and values for organic carbon, \nP-Olsen and exchangeable potassium below 70 g/kg, 30 mg/kg and 30 mmol/kg, respectively (0\u201320 cm). \nSoil fertility is interpreted as the capacity of a soil to provide plants with nitrogen, phosphorus \nand potassium, but the methodology allows for including other nutrients.", "formats": ["R package", "Git Repository", "Website", "canonical"], "keywords": ["model", "Global", "Crop"], "providers": [{"name": "Bert Janssen, Mink Zijlstra", "organization": "WUR", "positionName": null, "roles": [{"name": "pointOfContact"}], "contactInfo": {"phone": {"work": null}, "email": {"work": "mink.zijlstra@wur.nl"}, "address": {"work": {"deliveryPoint": null, "city": null, "administrativeArea": null, "postalCode": null, "country": null}}, "url": {"url": "None", "protocol": null, "name": null, "description": null, "function": null}}}]}, "links": [{"href": "https://CRAN.R-project.org/package=Rquefts", "name": "CRAN R package", "description": null, "type": "R package", "rel": null}, {"href": "https://github.com/cropmodels/Rquefts", "name": "Sources", "description": null, "type": "Git Repository", "rel": null}, {"href": "https://models.pps.wur.nl/index.php/original-version-3", "name": "Releases", "description": null, "type": "Website", "rel": null}, {"href": "https://github.com/lsc-hubs/kenya-catalogue/tree/main/portals/Global/models/quefts.yml", "name": "Source of the record", "description": null, "type": "canonical", "rel": "canonical"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016-0016-7061(90)90021-Z", "name": "item", "description": "10.1016-0016-7061(90)90021-Z", "href": "https://kenya.lsc-hubs.org/cat/collections/metadata:main/items/10.1016-0016-7061(90)90021-Z"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://kenya.lsc-hubs.org/cat/collections/metadata:main"}]}, {"id": "10.1002-esp.1530", "type": "Feature", "geometry": null, "time": "2023-07-07", "properties": {"themes": [{"scheme": "https://inspire.ec.europa.eu/metadata-codelist/SpatialScope", "concepts": []}, {"scheme": "https://lsc-hubs.org/categories/", "concepts": []}], "updated": "2023-07-07", "type": "model", "language": "english", "externalIds": [{"value": "https://doi.org/10.1002/esp.1530"}], "title": "Modified MMF (Morgan\u2013Morgan\u2013Finney) model for evaluating effects of crops and vegetation cover on soil erosion", "description": "Modifications are made to the revised Morgan\u2013Morgan\u2013Finney erosion prediction model to enable the effects of vegetation cover to be expressed through measurable plant parameters. 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": ["R package", "canonical"], "keywords": ["model", "Global", "Crop"], "providers": [{"name": "R. P. C. Morgan, J. H. Duzant", "organization": null, "positionName": null, "roles": [{"name": "pointOfContact"}], "contactInfo": {"phone": {"work": null}, "email": {"work": null}, "address": {"work": {"deliveryPoint": null, "city": null, "administrativeArea": null, "postalCode": null, "country": null}}, "url": {"url": "None", "protocol": null, "name": null, "description": null, "function": null}}}]}, "links": [{"href": "https://CRAN.R-project.org/package=DMMF", "name": "CRAN R Package", "description": null, "type": "R package", "rel": null}, {"href": "https://github.com/lsc-hubs/kenya-catalogue/tree/main/portals/Global/models/mmf.yml", "name": "Source of the record", "description": null, "type": "canonical", "rel": "canonical"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002-esp.1530", "name": "item", "description": "10.1002-esp.1530", "href": "https://kenya.lsc-hubs.org/cat/collections/metadata:main/items/10.1002-esp.1530"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://kenya.lsc-hubs.org/cat/collections/metadata:main"}]}, {"id": "10.1007-978-94-017-3624-4_8", "type": "Feature", "geometry": null, "time": ["2016-01-01", "2018-12-31"], "properties": {"themes": [{"scheme": "https://inspire.ec.europa.eu/metadata-codelist/SpatialScope", "concepts": []}, {"scheme": "https://lsc-hubs.org/categories/", "concepts": []}], "updated": "2023-07-07", "type": "model", "language": "english", "externalIds": [{"value": "https://doi.org/10.1007/978-94-017-3624-4_8"}], "title": "Decision support system for agrotechnology transfer (DSSAT v3)", "description": "Agricultural decision makers at all levels need an increasing amount of information to better understand the possible outcomes of their decisions to help them develop plans and policies that meet their goals. 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": ["Website", "Git repository", "canonical"], "keywords": ["models", "decision support system", "DSSAT", "sustainability", "technology transfer", "risk management", "Global", "Crop"], "providers": [{"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", "positionName": null, "roles": [{"name": "author"}], "contactInfo": {"phone": {"work": null}, "email": {"work": null}, "address": {"work": {"deliveryPoint": "P.O. Box 110570", "city": "Gainesville", "administrativeArea": null, "postalCode": "FL326II-0570", "country": "USA"}}, "url": {"url": null, "protocol": null, "name": null, "description": null, "function": null}}}]}, "links": [{"href": "https://dssat.net/main-download/", "name": "Releases", "description": null, "type": "Website", "rel": null}, {"href": "https://github.com/DSSAT/dssat-csm-os", "name": "Sources", "description": null, "type": "Git repository", "rel": null}, {"href": "https://github.com/lsc-hubs/kenya-catalogue/tree/main/portals/Global/models/dssat.yml", "name": "Source of the record", "description": null, "type": "canonical", "rel": "canonical"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007-978-94-017-3624-4_8", "name": "item", "description": "10.1007-978-94-017-3624-4_8", "href": "https://kenya.lsc-hubs.org/cat/collections/metadata:main/items/10.1007-978-94-017-3624-4_8"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://kenya.lsc-hubs.org/cat/collections/metadata:main"}]}, {"id": "10.1016-j.ecolind.2021.108386", "type": "Feature", "geometry": null, "time": "2024-02-05", "properties": {"themes": [{"scheme": "https://inspire.ec.europa.eu/metadata-codelist/SpatialScope", "concepts": []}], "updated": "2024-02-05", "type": "model", "language": "en", "externalIds": [{"value": "https://doi.org/10.1016/j.ecolind.2021.108386"}], "title": "Land Productivity Dynamics R package (lpdynr)", "description": "The Land Productivity sub-indicator (LP) refers to the total above-ground Net Primary Production and reflects changes in health and productive capacity of the land. Its declining trends can be usually understood as land degradation. LP is calculated using the Land Productivity Dynamics (LPD) approach, first developed by Ivits and Cherlet (2013). The LPD approach uses phenological and productivity variables derived from time series of remote sensed imagery, particularly the normalized difference vegetation index (NDVI), to estimate ecosystem dynamics and change. LPD is the methodological basis of the LPDynR package. It is based on a combined assessment of two sources of information, as seen in Figure 1. On the one hand, the first layer is the Long Term Change Map and, in general terms, it shows the tendency of change of land productivity (positive or negative) and the effect that this tendency might have had on a particular original point after a certain period of time. On the other hand, the second layer is the Current Status Map, which provides information on the current efficiency levels of vegetation on the productivity or, in other words, the current level of land productivity in relation to its potential. Further explanations for both branches can be found in this paper. The final result of the indicator is a categorical map with 5 classes of land productivity dynamics, ranging from declining to increasing productivity.", "formats": ["sourcecode", "canonical"], "keywords": ["Global"], "providers": [{"name": "Xavier Rotllan-Puig, Eva Ivits, Michael Cherlet", "organization": "Joint Research Center", "positionName": null, "roles": [{"name": "pointOfContact"}], "contactInfo": {"phone": {"work": null}, "email": {"work": null}, "address": {"work": {"deliveryPoint": null, "city": "Ispra", "administrativeArea": null, "postalCode": null, "country": "Italy"}}, "url": {"url": "https://joint-research-centre.ec.europa.eu/", "protocol": null, "name": null, "description": null, "function": null}}}]}, "links": [{"href": "https://github.com/xavi-rp/LPDynR", "name": "github", "description": null, "type": "sourcecode", "rel": null}, {"href": "https://github.com/lsc-hubs/kenya-catalogue/tree/main/portals/Global/models/lpdynr.yml", "name": "Source of the record", "description": null, "type": "canonical", "rel": "canonical"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016-j.ecolind.2021.108386", "name": "item", "description": "10.1016-j.ecolind.2021.108386", "href": "https://kenya.lsc-hubs.org/cat/collections/metadata:main/items/10.1016-j.ecolind.2021.108386"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://kenya.lsc-hubs.org/cat/collections/metadata:main"}]}, {"id": "10.1111-j.1752-1688.1998.tb05961.x", "type": "Feature", "geometry": null, "time": "2023-07-07", "properties": {"themes": [{"scheme": "https://inspire.ec.europa.eu/metadata-codelist/SpatialScope", "concepts": []}, {"scheme": "https://lsc-hubs.org/categories/", "concepts": []}], "updated": "2023-07-07", "type": "model", "language": "english", "externalIds": [{"value": "https://doi.org/10.1111/j.1752-1688.1998.tb05961.x"}], "title": "SWAT (Soil and Water Assessment Tool)", "description": "A conceptual, continuous time model called SWAT (Soil and Water Assessment Tool) was developed to assist water resource managers in assessing the impact of management on water supplies and nonpoint source pollution in watersheds and large river basins. 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": ["Website", "Git repository", "canonical"], "keywords": ["Global", "Crop"], "providers": [{"name": "J. G. Arnold, R. Srinivasan, R. S. Muttiah, J. R. Williams", "organization": null, "positionName": null, "roles": [{"name": "pointOfContact"}], "contactInfo": {"phone": {"work": null}, "email": {"work": null}, "address": {"work": {"deliveryPoint": null, "city": null, "administrativeArea": null, "postalCode": null, "country": null}}, "url": {"url": "None", "protocol": null, "name": null, "description": null, "function": null}}}]}, "links": [{"href": "https://swat.tamu.edu/software/swat-executables/", "name": "Releases", "description": null, "type": "Website", "rel": null}, {"href": "https://bitbucket.org/blacklandgrasslandmodels/swat_development", "name": "Sources", "description": null, "type": "Git repository", "rel": null}, {"href": "https://github.com/lsc-hubs/kenya-catalogue/tree/main/portals/Global/models/swat.yml", "name": "Source of the record", "description": null, "type": "canonical", "rel": "canonical"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111-j.1752-1688.1998.tb05961.x", "name": "item", "description": "10.1111-j.1752-1688.1998.tb05961.x", "href": "https://kenya.lsc-hubs.org/cat/collections/metadata:main/items/10.1111-j.1752-1688.1998.tb05961.x"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://kenya.lsc-hubs.org/cat/collections/metadata:main"}]}, {"id": "10.1111-j.1475-2743.1989.tb00755.x", "type": "Feature", "geometry": null, "time": "1989-03-01", "properties": {"themes": [{"scheme": "https://inspire.ec.europa.eu/metadata-codelist/SpatialScope", "concepts": []}, {"scheme": "https://lsc-hubs.org/categories/", "concepts": []}], "updated": "1989-03-01", "type": "model", "language": "english", "externalIds": [{"value": "https://doi.org/10.1111/j.1475-2743.1989.tb00755.x"}], "title": "WOFOST, a simulation model of crop production", "description": "The WOFOST simulation model is a tool for analysing the growth and production of field crops under a wide range of weather and soil conditions. Such an analysis is important first to assess to what extent crop production is limited by the factors of light, moisture and macro-nutrients, and second to estimate what improvements are possible. The theoretical concept of a production situation, as modelled by WOFOST, is explained, as is the hierarchy of potential production and water-limited and nutrient-limited production situations in the analysis. The organization of the computer files in the model, the structure of the FORTRAN source program and the available standard sets of data are described briefly.", "formats": ["Git repository", "Website", "Microsoft Windows installer", "canonical"], "keywords": ["model", "Global", "Crop"], "providers": [{"name": "C.A. van Diepen, J. Wolf, H. van Keulen, C. 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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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