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High-resolution digital soil mapping of amorphous iron- and aluminium-(hydr)oxides to guide sustainable phosphorus and carbon management

Authors :
Maarten van Doorn
Anatol Helfenstein
Gerard H. Ros
Gerard B.M. Heuvelink
Debby A.M.D. van Rotterdam-Los
Sven E. Verweij
Wim de Vries
Source :
Geoderma, Vol 443, Iss , Pp 116838- (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

Amorphous iron- and aluminium-(hydr)oxides are key soil properties in controlling the dynamics of phosphorus availability and carbon storage. These oxides affect the potential of soils to retain phosphorus and carbon, thus affecting ecosystem services such as crop production, water quality and carbon sequestration. In this study, we spatially predicted oxalate-extractable Fe and Al (FeOX, AlOX) contents in the Netherlands at 25 m resolution across six soil depth layers between 0 and 200 cm and quantified the associated prediction uncertainty using quantile regression forest. For model training and validation, geo-referenced data of FeOX and AlOX contents were used including 12,110 wet-chemical observations and 102,393 NIR spectroscopy observations. Over 150 spatial covariates were selected that provide information about soil typology, climate, soil organisms, land use, relief, parent material and space (sampling depth and oblique coordinates). Map quality was assessed by comparing predictions with observations using an independent data set of 4841 soil samples from agricultural fields. Soil sample locations were selected by stratified random sampling, allowing us to assess map quality using design-based statistical inference. Map quality was evaluated using the metrics Model Efficiency Coefficient (MEC), Root Mean Square Error (RMSE) and Mean Error (ME). Map quality differed, depending on the target variable and soil depth, with MEC ranging from 0.19 to 0.80, RMSE from 13.5 to 56.9 mmol kg−1 and ME from −6.8 to 6.8 mmol kg−1. Overall, map quality was better for topsoil than for subsoil and better for AlOX contents than for FeOX contents. Prediction uncertainty quality was evaluated by calculating the Prediction Interval Coverage Probability of the 90 per cent Prediction Interval, which were close to 0.90 in all cases and slightly below 0.90 for AlOX. Thus, prediction uncertainties were generally reliable, though for AlOX contents uncertainty was slightly underpredicted. The maps are a valuable tool for site-specific manure and fertiliser management strategies aiming to balance crop production, water quality and carbon sequestration in agriculture.

Details

Language :
English
ISSN :
18726259
Volume :
443
Issue :
116838-
Database :
Directory of Open Access Journals
Journal :
Geoderma
Publication Type :
Academic Journal
Accession number :
edsdoj.4aa10cf360304c9fb4026d159896bda7
Document Type :
article
Full Text :
https://doi.org/10.1016/j.geoderma.2024.116838