POLARIS: A 30-meter probabilistic soil series map of the contiguous United States

A newcomplete map of soil series probabilities has been produced for the contiguous United States at a 30mspatial resolution. This innovative database, named POLARIS, is constructed using available high-resolution geospatial environmental data and a state-of-the-art machine learning algorithm (DSMART-HPC) to remap the Soil Survey Geographic (SSURGO) database. This 9 billion grid cell database is possible using available high performance computing resources. POLARIS provides a spatially continuous, internally consistent, quantitative prediction of soil series. It offers potential solutions to the primary weaknesses in SSURGO: 1) unmapped areas are gap-filled using survey data from the surrounding regions, 2) the artificial discontinuities at political boundaries are removed, and 3) the use of high resolution environmental covariate data leads to a spatial disaggregation of the coarse polygons. The geospatial environmental covariates that have the largest role in assembling POLARIS over the contiguous United States (CONUS) are fine-scale (30 m) elevation data and coarse-scale (~2 km) estimates of the geographic distribution of uranium, thorium, and potassium. A preliminary validation of POLARIS using the NRCS National Soil Information System (NASIS) database shows variable performance over CONUS. In general, the best performance is obtained at grid cells where DSMART-HPC is most able to reduce the chance of misclassification. The important role of environmental covariates in limiting prediction uncertainty suggests including additional covariates is pivotal to improving POLARIS\u27 accuracy. This database has the potential to improve the modeling of biogeochemical, water, and energy cycles in environmental models; enhance availability of data for precision agriculture; and assist hydrologic monitoring and forecasting to ensure food and water security

Digital Soil Assessment: Beyond DSM

The scope of digital soil mapping is described, but it is not seen as an end in itself. It provides data and information for a new framework for soil assessment which we call digital soil assessment. Although still somewhat fluid, a procedural framework for digital soil mapping and assessment with its links and feedbacks are set out diagrammatically and discussed. Theoretically, the principal, but not the sole, advantage of DSM over conventional methods is the intended provision of estimates of predictor uncertainties. DSA comprises three main processes: (1) a soil attribute space inference system, (2) evaluation of soil functions and the threats to soils, and (3) risk assessment and the development of strategies for soil protection. Digital risk assessment consists of integrating political, social, economical parameters and general environmental threats for building, modelling and testing some scenarios about environmental perspectives. The procedure as a whole is illustrated by considering how to address potential questions such as, ‘are we able to provide all the soil data parameters for climate-change modelling at 200-m resolution?’JRC.H.7-Land management and natural hazard

The pesticide health risk index - An application to the world's countries

While the use of pesticides continues to rise worldwide, our understanding of the pervasiveness of associated contamination and the health risks humans may be exposed to remain limited to small samples size, and based on small geographic scales, the exposed population, or the pesticide types. Using our recent mapping of global pesticide use, we quantify three complementary health risk metrics for 92 active ingredients: (i) the pesticide hazard load (PHL); (ii) the population exposure (PE); and (iii) the human intake relative to the acceptable dose (INTR). We integrated these metrics into the pesticide health risk index (PHRI) to assess the standing of 133 nations against the global averages of PHL and PE and the acceptable levels of INTR using data of 2015 (PHRI > 1 indicates a concern). We found that some low-toxicity ingredients have PHL values equivalent to high-toxicity ones, and hence neglecting low-toxicity ingredients may cause biases in risk assessments. The geography of PHL, PE, and INTR show hotspots across the Americas, East and South Asia, and Europe, but with the EU27 countries generally showing lower PHL than other countries possibly due to strict governance on pesticide use. By our measure, about 1.7 billion people (24% of the world population) reside in close proximity to where pesticide applications are greater than 100 kg-a.i. km 1 indicates a concern). We found that some low-toxicity ingredients have PHL values equivalent to high-toxicity ones, and hence neglecting low-toxicity ingredients may cause biases in risk assessments. The geography of PHL, PE, and INTR show hotspots across the Americas, East and South Asia, and Europe, but with the EU27 countries generally showing lower PHL than other countries possibly due to strict governance on pesticide use. By our measure, about 1.7 billion people (24% of the world population) reside in close proximity to where pesticide applications are greater than 100 kg-a.i. km-2 year-1; about 2.3 billion people (32% of the world population) may exceed the acceptable pesticide intake and about 1.1 billion (15% of the world population) may exceed this by 10 fold. We identified 36 countries with PHRI > 1 and 6 countries with PHRI > 5; of these countries, 10 belong to lower-middle and low income economies. Our analyses show that proximity exposure to pesticides may be more widespread than revealed in occupational studies, and therefore assessments of potential health effects over wider scales may be needed. 1 and 6 countries with PHRI > 5; of these countries, 10 belong to lower-middle and low income economies. Our analyses show that proximity exposure to pesticides may be more widespread than revealed in occupational studies, and therefore assessments of potential health effects over wider scales may be needed. 5; of these countries, 10 belong to lower-middle and low income economies. Our analyses show that proximity exposure to pesticides may be more widespread than revealed in occupational studies, and therefore assessments of potential health effects over wider scales may be needed

Global Soil Organic Carbon Assessment

Soil carbon is a key component of functional ecosystems and crucial for food, soil, water and energy security. Climate change and altered land-use will have a great impact on soils. The influence of these factors will create a dynamic feedback between soil and the environment. There is a crucial need to evaluate the responses of soil to global environmental change at large scales that occur along natural environmental gradients over decadal timescales. This work provides a suite of new data on global soil change which will uniquely utilise the world’s prior investment in soil data infrastructure. Here we attempt a comprehensive global space-time assessment of soil carbon dynamics in different ecoregions of the world accounting for impacts of climate change and other environmental factors.JRC.H.5-Land Resources Managemen

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

A two-dimensional fuzzy random model of soil pore structure

A new conceptual model for soil pore-solid structure is formalized. Soil pore-solid structure is proposed to comprise spatially abutting elements each with a value which is its membership to the fuzzy set ''pore,'' termed porosity. These values have a range between zero (all solid) and unity (all pore). Images are used to represent structures in which the elements are pixels and the value of each is a porosity. Two-dimensional random fields are generated by allocating each pixel a porosity by independently sampling a statistical distribution. These random fields are reorganized into other pore-solid structural types by selecting parent points which have a specified local region of influence. Pixels of larger or smaller porosity are aggregated about the parent points and within the region of interest by controlled swapping of pixels in the image. This creates local regions of homogeneity within the random field. This is similar to the process known as simulated annealing. The resulting structures are characterized using one-and two-dimensional variograms and functions describing their connectivity. A variety of examples of structures created by the model is presented and compared. Extension to three dimensions presents no theoretical difficulties and is currently under development