A high-resolution map of soil pH in China made by hybrid modelling of sparse soil data and environmental covariates and its implications for pollution

A - Papers appearing in refereed journals

Chen, S., Liang, Z., Webster, R., Zhang, G., Zhou, Y., Teng, H., Hi, B., Arrouays, D. and Shi, Z. 2019. A high-resolution map of soil pH in China made by hybrid modelling of sparse soil data and environmental covariates and its implications for pollution. Science of the Total Environment. 655, pp. 273-283. https://doi.org/10.1016/j.scitotenv.2018.11.230

AuthorsChen, S., Liang, Z., Webster, R., Zhang, G., Zhou, Y., Teng, H., Hi, B., Arrouays, D. and Shi, Z.
Abstract

The soil’s pH is the single most important indicator of the soil’s quality, whether for agriculture, pollution control or environmental health and ecosystem functioning. Well documented data on soil pH are sparse for the whole of China — data for only 4700 soil profiles were available from China’s Second National Soil Inventory. By combining those data, standardized for the topsoil (0–20cm), with 17 environmental covariates at a fine resolution (3 arc-second or 90m) we have predicted the soil’s pH at that resolution, that is at more than 10 9 points. We did so by parallel computing over tiles, each 100km×100km, with two machine learning techniques, namely Random Forest and XGBoost. The predictions for the tiles were then merged into a single map of soil pH for the whole of China. The quality of the predictions were assessed by cross-validation. The root mean squared error (RMSE) was an acceptable 0.71pH units per point, and Lin’s Concordance Correlation Coefficient was 0.84.The hybrid model revealed that climate(mean annual precipitation and mean annual temperature)and soil type were the main factors determining the soil’s pH. The pH map showed acid soil mainly in southern and north-eastern China, and alkaline soil dominant in northern and western China. This map can provide a benchmark against which to evaluate the impacts of changes in land use and climate on the soil’s pH, and it can guide advisors and agencies who make decisions on remediation and prevention of soil acidification, salinization and pollution by heavy metals, for which we provide examples for cadmium and mercury.

KeywordsSoil pH; Hybrid modelling; Environmental covariates; Digital soil mapping; Pollution potential
Year of Publication2019
JournalScience of the Total Environment
Journal citation655, pp. 273-283
Digital Object Identifier (DOI)https://doi.org/10.1016/j.scitotenv.2018.11.230
Web address (URL)https://doi.org/10.1016/j.scitotenv.2018.11.230
Open accessPublished as non-open access
FunderNational Key Research and Development Program of China
Output statusPublished
Publication dates
Online18 Nov 2018
Publication process dates
Accepted15 Nov 2018
PublisherElsevier Science Bv
Copyright licensePublisher copyright
ISSN0048-9697

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