Hand-feel soil texture observations to evaluate the accuracy of digital soil maps for local prediction of particle size distribution. A case study in central France

Authors: RICHER-DE-FORGES, ANNE - INRAE; ARROUAYS, DOMINIQUE - INRAE; POGGIO, LAURA - ISRIC - WORLD SOIL INFORMATION; CHEN, SONGCHAO - ZHEJIANG SCI-TECH UNIVERSITY; LACOSTE, MARINE - INRAE; MINASNY, BUDIMAN - UNIVERSITY OF SYDNEY; Libohova, Zamir; ROUDIER, PIERRE - MANAAKI WHENUA LANDCARE RESEARCH; MULDER, VERA - ISRIC - WORLD SOIL INFORMATION; NEDELEC, HERVE - CEMAGREF(CENTRE FOR AGRICULTURAL AND ENVIRONMENTAL ENGINEERING RESEARCH); MARTELET, GUILLAUME - INRAE; LEMERCIER, BLANDINE - INRAE; LAGACHERIE, PHILIPPE - INRAE; BOURENNANE, HOCINE - INRAE

Submitted to: Pedosphere
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/28/2022
Publication Date: 10/1/2023
Citation: Richer-De-Forges, A.C., Arrouays, D., Poggio, L., Chen, S., Lacoste, M., Minasny, B., Libohova, Z., Roudier, P., Mulder, V.L., Nedelec, H., Martelet, G., Lemercier, B., Lagacherie, P., Bourennane, H. 2023. Hand-feel soil texture observations to evaluate the accuracy of digital soil maps for local prediction of particle size distribution. A case study in central France. Pedosphere. 33(5):731-743. https://doi.org/10.1016/j.pedsph.2022.07.009.
DOI: https://doi.org/10.1016/j.pedsph.2022.07.009

Interpretive Summary: There is a considerable amount of soil texture data estimated in the field that is greater than the soil textures determined in the laboratory. The soil texture determined by the laboratory is also expensive and time consuming. There is a need to increase the density of points with measured data for improving soil texture maps that are important for many agricultural practices. Using hand-feel soil texture data that are more abundant and less expensive to collect, we tested their usability for evaluating and improving the accuracy of soil texture maps that are generated by different soil mapping methods and at different level of detail. The use of hand-feel soil texture reduced the cost of evaluating the accuracy of soil texture maps and identified areas where there is a need for more samples to increase the accuracy of maps, especially at field and farm levels. Identifying the areas with needs for more sampling would increase the efficiency of field sampling and reduce cost while improving the accuracy of soil maps that would in turn support precision agriculture at farm and field levels.

Technical Abstract: Gridded maps of soil properties are now widely available. End-users now can access several DSM products of soil properties, produced using different models, calibration/training data, covariates and at various spatial scales from global to local. Therefore, there is an urgent need to provide easy-to-understand tools to communicate map uncertainty and help end-users assess the reliability of DSM products for use at local scales. In this study, we used a large number of hand-feel soil texture data (HFST) to assess the performance of various published DSM products on the prediction of particle-size distribution in Central France. We tested four DSM products of texture prediction developed at various scales (Global, continental, national, and sub-national) by comparing their predictions with ca 3,200 HFST observations realized on a 1:50,000 soil survey conducted after the release of these DSM products. We used both visual comparisons and quantitative indicators of matching DSM predictions and HFST. The comparison between low-cost observed HFST and DSM predictions clearly shows the applicability of various DSM products, with prediction accuracy increasing from global to sub-national predictions. This simple evaluation can decide which products that can be used at local scale and if more accurate DSM products are required.