Gridded, temporally referenced spatial information on soil organic carbon for Hungary DOI Creative Commons
Gábor Szatmári, Annamária Laborczi, János Mészáros

et al.

Scientific Data, Journal Year: 2024, Volume and Issue: 11(1)

Published: Dec. 2, 2024

Soil organic carbon (SOC), known as the most important soil attribute, affects various functions and services, essential for nutritious food clean drinking water. Since recognizing its key role in many environmental challenges, there has been an increasing demand spatial information on SOC. Our objective is to present results of a mapping activity aimed at producing spatially exhaustive SOC content, density, stock topsoils Hungary 1992 2000. A "time-for-space" digital approach was pursued predict map these properties, with associated uncertainty, resolution 100 × m. Particular attention paid validating accuracy maps reliability uncertainty quantifications. The published are recommended be used baseline Hungary. makes them suitable practical applications (e.g., GHG inventory, sustainable agriculture, sequestration). interest researchers, practitioners, policymakers, helping achieve scientifically sound informed decision-making.

Language: Английский

Soil Science-Informed Machine Learning DOI Creative Commons
Budiman Minasny, Toshiyuki Bandai, Teamrat A. Ghezzehei

et al.

Geoderma, Journal Year: 2024, Volume and Issue: 452, P. 117094 - 117094

Published: Nov. 14, 2024

Language: Английский

Citations

13
A China dataset of soil properties for land surface modelling (version 2, CSDLv2) DOI Creative Commons
Gaosong Shi,

Wenye Sun,

Wei Shangguan

et al.

Earth system science data, Journal Year: 2025, Volume and Issue: 17(2), P. 517 - 543

Published: Feb. 7, 2025

Abstract. Accurate and high-resolution spatial soil information is crucial for efficient sustainable land use, management, conservation. Since the establishment of digital mapping (DSM) GlobalSoilMap working group, significant advances have been made in terms availability quality globally. However, accurately predicting variation over large complex areas with limited samples remains a challenge, especially China, which has diverse landscapes. To address this we utilised 11 209 representative multi-source legacy profiles (including Second National Soil Survey World Information Service, First regional databases) soil-forming environment characterisation. Using advanced ensemble machine learning high-performance parallel-computing strategy, developed comprehensive maps 23 physical chemical properties at six standard depth layers from 0 to 2 m China 90 resolution (China dataset surface modelling version 2, CSDLv2). Data-splitting independent-sample validation strategies were employed evaluate accuracy predicted maps' quality. The results showed that significantly more accurate detailed compared traditional type linkage methods (i.e. CSDLv1, first dataset), SoilGrids 2.0, HWSD 2.0 products, effectively representing across China. prediction all intervals ranged good moderate, median model efficiency coefficients most ranging 0.29 0.70 during data-splitting 0.25 0.84 validation. wide range between 5 % lower 95 upper limits may indicate substantial room improvement current predictions. relative importance environmental covariates predictions varied property depth, indicating complexity interactions among multiple factors formation processes. As used study mainly originate conducted 1970s 1980s, they could provide new perspectives on changes, together existing based 2010s. findings make important contributions project can also be Earth system better represent role hydrological biogeochemical cycles This freely available https://www.scidb.cn/s/ZZJzAz (last access: 17 November 2024​​​​​​​) or https://doi.org/10.11888/Terre.tpdc.301235 (Shi Shangguan, 2024).

Language: Английский

Citations

1
Monitoring and Modeling the Soil‐Plant System Toward Understanding Soil Health DOI Creative Commons
Yijian Zeng, Anne Verhoef, Harry Vereecken

et al.

Reviews of Geophysics, Journal Year: 2025, Volume and Issue: 63(1)

Published: Jan. 25, 2025

Abstract The soil health assessment has evolved from focusing primarily on agricultural productivity to an integrated evaluation of biota and biotic processes that impact properties. Consequently, shifted a predominantly physicochemical approach incorporating ecological, biological molecular microbiology indicators. This shift enables comprehensive exploration microbial community properties their responses environmental changes arising climate change anthropogenic disturbances. Despite the increasing availability indicators (physical, chemical, biological) data, holistic mechanistic linkage not yet been fully established between functions across multiple spatiotemporal scales. article reviews state‐of‐the‐art monitoring, understanding how soil‐microbiome‐plant contribute feedback mechanisms causes in properties, as well these have functions. Furthermore, we survey opportunities afforded by soil‐plant digital twin approach, integrative framework amalgamates process‐based models, Earth Observation data assimilation, physics‐informed machine learning, achieve nuanced comprehension health. review delineates prospective trajectory for monitoring embracing systematically observe model system. We further identify gaps opportunities, provide perspectives future research enhanced intricate interplay hydrological processes, hydraulics, microbiome, landscape genomics.

Language: Английский

Citations

0
Using the phosphorus saturation degree as a guide for sustainable phosphorus management balancing crop production and water quality objectives DOI Creative Commons
Maarten van Doorn, Debby van Rotterdam, Gerard H. Ros

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 384, P. 125617 - 125617

Published: May 5, 2025

Incorporating environmental boundaries into P fertilizer recommendations is key to reconcile agronomic objectives and leaching risks ground- surface waters. Current soil quantity tests, used as the basis for recommendations, are poorly suited this purpose they provide no information on ortho-P concentration in solution which prone leach. Therefore, we converted test values equilibrium through corresponding saturation degree (PSD), using sorption capacity affinity of bind soil. We derived an PSD threshold compared with current target values. In Dutch agricultural soils, exceed 84 % 94 land area, respectively. Decreasing mining showed limited adverse effects crop yields, except areas being vulnerable losses because a low high hydrological connectivity. Here, cultivation less P-sensitive crops or provision other ecosystem services than food production may be more appropriate. Limited yield result from targets based achieving 99 maximum potato crop. Given livestock density excess manure Netherlands, reducing poses significant challenge.

Language: Английский

Citations

0
Four-dimensional modelling reveals decline in cropland soil pH during last four decades in China’s Mollisols region DOI Creative Commons
Chen Jian, Enze Xie, Yuxuan Peng

et al.

Geoderma, Journal Year: 2024, Volume and Issue: 453, P. 117135 - 117135

Published: Dec. 10, 2024

Language: Английский

Citations

2
Interpreting and evaluating digital soil mapping prediction uncertainty: A case study using texture from SoilGrids DOI Creative Commons
Linda Lilburne, Anatol Helfenstein, G.B.M. Heuvelink

et al.

Geoderma, Journal Year: 2024, Volume and Issue: 450, P. 117052 - 117052

Published: Oct. 1, 2024

Language: Английский

Citations

1
Fine-resolution baseline maps of soil nutrients in farmland of Jiangxi Province using digital soil mapping and interpretable machine learning DOI
Bifeng Hu, Yibo Geng,

Kejian Shi

et al.

CATENA, Journal Year: 2024, Volume and Issue: 249, P. 108635 - 108635

Published: Dec. 9, 2024

Language: Английский

Citations

1
Gridded, temporally referenced spatial information on soil organic carbon for Hungary DOI Creative Commons
Gábor Szatmári, Annamária Laborczi, János Mészáros

et al.

Scientific Data, Journal Year: 2024, Volume and Issue: 11(1)

Published: Dec. 2, 2024

Soil organic carbon (SOC), known as the most important soil attribute, affects various functions and services, essential for nutritious food clean drinking water. Since recognizing its key role in many environmental challenges, there has been an increasing demand spatial information on SOC. Our objective is to present results of a mapping activity aimed at producing spatially exhaustive SOC content, density, stock topsoils Hungary 1992 2000. A "time-for-space" digital approach was pursued predict map these properties, with associated uncertainty, resolution 100 × m. Particular attention paid validating accuracy maps reliability uncertainty quantifications. The published are recommended be used baseline Hungary. makes them suitable practical applications (e.g., GHG inventory, sustainable agriculture, sequestration). interest researchers, practitioners, policymakers, helping achieve scientifically sound informed decision-making.

Language: Английский

Citations

0