Soil data harmonisation and geostatistical modelling efforts in support of improved studies of global sustainability Niels H. Batjes, Bas Kempen, Johan.

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Soil data harmonisation and geostatistical modelling efforts in support of improved studies of global sustainability Niels H. Batjes, Bas Kempen, Johan Leenaars and Rik van den Bosch Session 1105(b), ‘Quality and availability of data for global sustainability’ Our Common Future Under Climate Change Conference (7-10 July, UNESCO, Paris)

ISRIC mission: “To serve the international community with information about the world’s soil resources to help addressing major global issues”

Global web services Decision makers and managers must have access to the information they need, when they need it, and in a format they can use (GEO, 2010)

User needs vary at different scales ‘There is no magic single resolution that serves all purposes’ (HarvestChoice, 2011) Global assessments Soil monitoring National studies Scale 1: 5,000,000 1: 250,000 1: 5:000 1:1 Regional studies Spatial planning Precision farming

Global Soil Information Facility WoSIS & WorldGrids Data sources Soil information (maps) Modelling ‘GSIF - A framework for processing of soil data and information’ (Hengl et al.)

Digital Soil Mapping ‘DSM uses statistical models to predict soil functional properties at unobserved locations in the landscape’

Geo-DATA: Soil profile data -Draws on soil profile data provided by a wide range of international partners -Not all profile data are freely accessible due to inherited restrictions (licences) -Access rights and lineage are managed in WoSIS

WoSIS - World Soil Information Service Standardisation and harmonisation towards a global standard HARMONISATION STANDARD

Geo-DATA: Co-variate layers Represent soil forming factors (Jenny, 1941) : o Climate o Organisms (biology) o Relief (hydrology) o Parent material (rock etc.) o Time Managed in portal : o WorldGrids.org o Standardized format: 1 km resolution o So far ~ 80 layers

Model specifications: Fit model(s) ordinary kriging regression kriging c)c) (a) e)e) b)b) Soil profile measurements regression soil map only predictor other models co-variates run model(s) and (cross)validate against independent data sets

SoilGrids1km (30x30 arcsec) Hengl T. et al. (2014) SoilGrids1km — Global Soil Information Based on Automated Mapping. PLoS ONE 9(8): e105992PLoS ONE 9(8): e

-~10,000 profiles -linear regression (ISRIC, 2013) AfSoilGrids1km AfSoilGrids250m - ~ 25,000 profiles - Random forests and regression- kriging (Hengl et al., 2105) Updating SoilGrids: F rom 1km to 250m PLoS ONE 2015,10(6): e doi: /journal.pone Soil organic carbon 20 soil properties 9 soil properties

World Soil Profiles WoSIS & WorldGrids Earth system modelling, food security... Data sources Soil information (maps) POLICY / DECISION MAKING Use of soil information NEW DATA (crowd sourcing; Soilinfo App) Use of soil information Modelling

Use of soil information: Crop production potential Plant V Crop simulation models AaaAuxilliary database e + Soils + Slope Projected maize yield (t/ha) Land utilisation types

Use of soil information: Global organic carbon stocks (WISE30sec)  Some 30% of the global SOC stock to 2 m (2060 ± 215 Pg C) is held in the Northern Circumpolar Region  Potentially, large GHG emissions upon global warming  Earth system modelling Ton C ha -1 Batjes (2015, submitted) Ton C ha -1 * SOC stocks to 1 m depth

GSIF-Development team: More information: GSIF-Development team: More information: and many other experts and organisations