Deriving a dataset for agriculturally relevant soils from the Soil Landscapes of Canada (SLC) database for use in Soil and Water Assessment Tool (SWAT) simulations

The Soil and Water Assessment Tool (SWAT) model has been commonly used in Canada for hydrological and water quality simulations. However, preprocessing of critical data such as soils information can be laborious and time-consuming. The objective of this work was to preprocess the Soil Landscapes of Canada (SLC) database to offer a country-level soils dataset in a format ready to be used in SWAT simulations. A two-level screening process was used to identify critical information required by SWAT and to remove records with information that could not be calculated or estimated. Out of the 14&thinsp;063 unique soil records in the SLC, 11&thinsp;838 records with complete information were included in the dataset presented here. Important variables for SWAT simulations that are not reported in the SLC database (e.g., hydrologic soils groups (HSGs) and erodibility factor (K)) were calculated from information contained within the SLC database. These calculations, in fact, represent a major contribution to enabling the present dataset to be used for hydrological simulations in Canada using SWAT and other comparable models. Analysis of those variables indicated that 21.3&thinsp;%, 24.6&thinsp;%, 39.0&thinsp;%, and 15.1&thinsp;% of the soil records in Canada belong to HSGs 1, 2, 3, and 4, respectively. This suggests that almost two-thirds of the soil records have a high (i.e., HSG 4) or relatively high (i.e., HSG 3) runoff generation potential. A spatial analysis indicated that 20.0&thinsp;%, 26.8&thinsp;%, 36.7&thinsp;%, and 16.5&thinsp;% of soil records belonged to HSG 1, HSG 2, HSG 3, and HSG 4, respectively. Erosion potential, which is inherently linked to the erodibility factor (K), was associated with runoff potential in important agricultural areas such as southern Ontario and Nova Scotia. However, contrary to initial expectations, low or moderate erosion potential was found in areas with high runoff potential, such as regions in southern Manitoba (e.g., Red River Valley) and British Columbia (e.g., Peace River watershed). This dataset will be a unique resource to a variety of research communities including hydrological, agricultural, and water quality modelers and is publicly available at https://doi.org/10.1594/PANGAEA.877298.</p

GlobalSoilMap: Toward a Fine-Resolution Global Grid of Soil Properties

Soil scientists are being challenged to provide assessments of soil condition from local through to global scales. A particular issue is the need for estimates of the stores and fluxes in soils of water, carbon, nutrients, and solutes. This review outlines progress in the development and testing of GlobalSoilMap—a digital soil map that aims to provide a fineresolution global grid of soil functional properties with estimates of their associated uncertainties. A range of methods can be used to generate the fine-resolution spatial estimates depending on the availability of existing soil surveys, environmental data, and point observations. The system has an explicit geometry for estimating point and block estimates of soil properties continuously down the soil profile. This geometry is necessary to ensure mass balance when stores and fluxes are computed. It also overcomes some limitations with existing systems for characterizing soil variation with depth. GlobalSoilMap has been designed to enable delivery of soil data via Web services. This review provides an overview of the system's technical specifications including the minimum data set. Examples from contrasting countries and environments are then presented to demonstrate the robustness of the technical specifications. GlobalSoilMap provides the means for supplying soil information in a format and resolution compatible with other fundamental data sets from remote sensing, terrain analysis, and other systems for mapping, monitoring, and forecasting biophysical processes. The initial research phase of the core project is nearing completion and attention is now shifting toward establishing the institutional and governance arrangements necessary to complete a full global coverage and maintaining the operational version of the GlobalSoilMap. This will be a grand and rewarding challenge for the soil science profession in the coming years.JRC.H.5-Land Resources Managemen

GlobalSoilMap for Soil Organic Carbon Mapping and Modeling

les auteurs : Dominique Arrouays, Budiman Minasny, Alex. B. McBratney, Mike Grundy, Neil McKenzie, James Thompson, Alessandro Gimona, Suk Young Hong, Scott Smith, Alfred Hartemink, Songchao Chen, Manuel P. Martin, Vera Leatitia Mulder, Anne C. Richer-de-Forges, Nicolas P.A. Saby, Inakwu Odeh, José Padarian, Glenn Lelyk, Laura Poggio, Igor Savin, Vladimir Stolbovoy, Yiyi Sulaeman, Dedi Nursyamsi, Gan-Lin Zhang, Mogens H. Greve, Zamir Libohova, Philippe Lagacherie, Pierre Roudier, Johan G.B. Leenaars, Gerard B.M. Heuvelink, Luca Montanarella, Panos Panagos, Jon HempelThe demand for information on functional soil properties is high and has increased over time. This isespecially true for soil organic carbon (SOC) in the framework of food security and climate change. TheGlobalSoilMap consortium was established in response to such a soaring demand for up-to-date andrelevant soil information. The majority of the data needed to produce GlobalSoilMap soil property mapswill, at least for the first generation, come mainly from archived soil legacy data, which could includepolygon soil maps and point pedon data, and from available co-variates such as climatic data, remotesensing information, geological data, and other forms of environmental information.Several countries have already released products according to the GlobalSoilMap specifications and theproject is rejuvenating soil survey and mapping in many parts of the world. Functional soil property mapshave been produced using digital soil mapping techniques and existing legacy information and madeavailable to the user community for application. In addition, uncertainty has been provided as a 90%prediction interval based on estimated upper and lower class limits. We believe that GlobalSoilMapconstitutes the best available framework and methodology to address global issues about SOC mapping.Main scientific challenges include time related and uncertainties issues

Soil legacy data rescue via GlobalSoilMap and other international and national initiatives

Legacy soil data have been produced over 70 years in nearly all countries of the world. Unfortunately, data, information and knowledge are still currently fragmented and at risk of getting lost if they remain in a paper format. To process this legacy data into consistent, spatially explicit and continuous global soil information, data are being rescued and compiled into databases. Thousands of soil survey reports and maps have been scanned and made available online. The soil profile data reported by these data sources have been captured and compiled into databases. The total number of soil profiles rescued in the selected countries is about 800,000. Currently, data for 117, 000 profiles are compiled and harmonized according to GlobalSoilMap specifications in a world level database (WoSIS). The results presented at the country level are likely to be an underestimate. The majority of soil data is still not rescued and this effort should be pursued. The data have been used to produce soil property maps. We discuss the pro and cons of top-down and bottom-up approaches to produce such maps and we stress their complementarity. We give examples of success stories. The first global soil property maps using rescued data were produced by a top-down approach and were released at a limited resolution of 1 km in 2014, followed by an update at a resolution of 250 m in 2017. By the end of 2020, we aim to deliver the first worldwide product that fully meets the GlobalSoilMap specifications

Soil legacy data rescue via GlobalSoilMap and other international and national initiatives

Legacy soil data have been produced over 70 years in nearly all countries of the world. Unfortunately, data, information and knowledge are still currently fragmented and at risk of getting lost if they remain in a paper format. To process this legacy data into consistent, spatially explicit and continuous global soil information, data are being rescued and compiled into databases. Thousands of soil survey reports and maps have been scanned and made available online. The soil profile data reported by these data sources have been captured and compiled into databases. The total number of soil profiles rescued in the selected countries is about 800,000. Currently, data for 117, 000 profiles are compiled and harmonized according to GlobalSoilMap specifications in a world level database (WoSIS). The results presented at the country level are likely to be an underestimate. The majority of soil data is still not rescued and this effort should be pursued. The data have been used to produce soil property maps. We discuss the pro and cons of top-down and bottom-up approaches to produce such maps and we stress their complementarity. We give examples of success stories. The first global soil property maps using rescued data were produced by a top-down approach and were released at a limited resolution of 1 km in 2014, followed by an update at a resolution of 250 m in 2017. By the end of 2020, we aim to deliver the first worldwide product that fully meets the GlobalSoilMap specifications. © 2017 Elsevier Lt