GeodermaPub Date : 2025-02-17DOI: 10.1016/j.geoderma.2025.117216
Jonne Pohjankukka , Timo A. Räsänen , Timo P. Pitkänen , Arttu Kivimäki , Ville Mäkinen , Tapio Väänänen , Jouni Lerssi , Aura Salmivaara , Maarit Middleton
{"title":"Digital mapping of peat thickness and extent in Finland using remote sensing and machine learning","authors":"Jonne Pohjankukka , Timo A. Räsänen , Timo P. Pitkänen , Arttu Kivimäki , Ville Mäkinen , Tapio Väänänen , Jouni Lerssi , Aura Salmivaara , Maarit Middleton","doi":"10.1016/j.geoderma.2025.117216","DOIUrl":"10.1016/j.geoderma.2025.117216","url":null,"abstract":"<div><div>Accurate data on peat extent and thickness is essential for managing drained peatlands and reducing greenhouse gas emissions. Machine learning-based digital soil mapping offers an effective approach for large-scale peat occurrence prediction. In this study, we present a workflow for producing peat occurrence maps for the whole of Finland. For this, we used random forest classification to map areas with peat thicknesses of ≥ 10 cm, ≥30 cm, ≥40 cm, and > 60 cm. The input data consisted of 3.5 million point observations and 188 feature rasters from various sources. We carefully split the reference data into training and test sets, allowing for independent and robust model validation. Feature selection included an initial screening for multicollinearity using correlation-based feature pruning, followed by final selection using a genetic algorithm. Feature importance was evaluated using permutation importance and SHAP values. The resulting models utilized 26–33 features, achieving overall accuracies and F1-scores between 86–95 % and 0.82–0.95, respectively. The most important features included soil wetness indices, terrain roughness indices, and natural gamma radiation. Additionally, we provided an approach for evaluating spatial prediction uncertainty based on the models’ internal prediction agreement. Compared to existing superficial deposit maps, our peat predictions significantly improve the spatial detail of peatlands at the national level, offering new opportunities for land use planning and emission mitigation. Our exceptionally comprehensive approach is broadly applicable, offering new insights into optimizing machine learning-based digital peatland mapping, particularly through refining feature selection to account for local conditions and enhance prediction accuracy.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"455 ","pages":"Article 117216"},"PeriodicalIF":5.6,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
GeodermaPub Date : 2025-02-16DOI: 10.1016/j.geoderma.2025.117207
Mingxi Zhang , Zefang Shen , Lewis Walden , Farid Sepanta , Zhongkui Luo , Lei Gao , Oscar Serrano , Raphael A. Viscarra Rossel
{"title":"Deep learning of the particulate and mineral-associated organic carbon fractions using a compositional transform and mid-infrared spectroscopy","authors":"Mingxi Zhang , Zefang Shen , Lewis Walden , Farid Sepanta , Zhongkui Luo , Lei Gao , Oscar Serrano , Raphael A. Viscarra Rossel","doi":"10.1016/j.geoderma.2025.117207","DOIUrl":"10.1016/j.geoderma.2025.117207","url":null,"abstract":"<div><div>We need soil organic carbon (SOC) and the SOC fractions, the particulate and mineral-associated organic carbon (POC, MAOC), to understand SOC dynamics. They have implications for soil management, carbon sequestration and climate change mitigation. However, conventional laboratory measurements of the SOC fractions, which involve physical or chemical separations, are elaborate, time-consuming and expensive. Mid-infrared (MIR) spectroscopy combined with multivariate modelling can alleviate these limitations because the method can estimate SOC and its fractions rapidly, cost-effectively and accurately. Previous spectroscopic modelling has mostly ignored the compositional nature of the SOC fractions (i.e. SOC = <span><math><mo>∑</mo></math></span>fractions), causing discrepancies in the estimation such that the sum of the fractions does not equal the total SOC. We recorded the MIR spectra (4000–450 cm<sup>−1</sup>) of 397 soil samples from across Australia and then performed a granulometric fractionation to derive three SOC fractions, the POC in the macroaggregates (250–<span><math><mrow><mn>2000</mn><mspace></mspace><mi>μ</mi><mi>m</mi></mrow></math></span>, POC<span><math><msub><mrow></mrow><mrow><mi>m</mi><mi>a</mi><mi>c</mi></mrow></msub></math></span>), POC in the micro-aggregates (50–<span><math><mrow><mn>250</mn><mspace></mspace><mi>μ</mi><mi>m</mi></mrow></math></span>, POC<span><math><msub><mrow></mrow><mrow><mi>m</mi><mi>i</mi><mi>c</mi></mrow></msub></math></span>), and MAOC (<span><math><mrow><mo><</mo><mn>50</mn><mspace></mspace><mi>μ</mi><mi>m</mi></mrow></math></span>). We used the centred log ratio (CLR) method to transform the data compositionally and then modelled POC<span><math><msub><mrow></mrow><mrow><mi>m</mi><mi>a</mi><mi>c</mi></mrow></msub></math></span>, POC<span><math><msub><mrow></mrow><mrow><mi>m</mi><mi>i</mi><mi>c</mi></mrow></msub></math></span>, POC (POC<span><math><msub><mrow></mrow><mrow><mi>m</mi><mi>a</mi><mi>c</mi></mrow></msub></math></span> + POC<span><math><msub><mrow></mrow><mrow><mi>m</mi><mi>i</mi><mi>c</mi></mrow></msub></math></span>), and MAOC with the spectra, using convolutional neural networks (CNN) and <span>cubist</span> for benchmarking. We interpreted the models using the SHapley Additive exPlanations (SHAP) values and a land use classification of the data. Modelling the CLR-transformed SOC fractions with CNN maintained the composition of the fractions and improved the accuracy of the estimates (Lin’s concordance correlation coefficient (<span><math><msub><mrow><mi>ρ</mi></mrow><mrow><mi>c</mi></mrow></msub></math></span>) of 0.58, 0.86, and 0.94 for the POC<span><math><msub><mrow></mrow><mrow><mi>m</mi><mi>a</mi><mi>c</mi></mrow></msub></math></span>, POC<span><math><msub><mrow></mrow><mrow><mi>m</mi><mi>i</mi><mi>c</mi></mrow></msub></math></span>, and MAOC), compared to CLR with <span>cubist</span> (<span><math><msub><mrow><mi>ρ</mi></mrow><mrow><mi>c</mi></mrow></msub></math></span","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"455 ","pages":"Article 117207"},"PeriodicalIF":5.6,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
GeodermaPub Date : 2025-02-16DOI: 10.1016/j.geoderma.2025.117210
Meijun Li , Wei Shao , Wenjun Yu , Ye Su , Qinghai Song , Yiping Zhang , Hongkai Gao , Yonggen Zhang , Jianzhi Dong
{"title":"Optimization of soil hydraulic parameters within a constrained sampling space","authors":"Meijun Li , Wei Shao , Wenjun Yu , Ye Su , Qinghai Song , Yiping Zhang , Hongkai Gao , Yonggen Zhang , Jianzhi Dong","doi":"10.1016/j.geoderma.2025.117210","DOIUrl":"10.1016/j.geoderma.2025.117210","url":null,"abstract":"<div><div>The direct optimization of soil hydraulic parameters (SHP) in unconstrained parameter space introduces significant uncertainties in ecohydrological modeling, particularly when addressing the complex model structure of Richards’ equation combined with Penman-Monteith equation. Pedotransfer functions (e.g., the latest version of Rosetta 3), which have been extensively trained using abundant soil hydraulic data, could potentially provide a physical constraint for sampling SHP. This study integrates optimization algorithms (Particle Swarm Optimization, PSO; Markov Chain Monte Carlo, MCMC; Sequential Monte Carlo, SMC; Generalized Likelihood Uncertainty Estimation, GLUE) with two sampling strategies − direct optimization of SHP and indirect optimization of SHP derived from soil particle composition (SPC) using Rosetta 3 − to evaluate their performance in ecohydrological modeling under predefined soil conditions. The results demonstrated that indirect optimization of SHP significantly enhances the accuracy in recovering predefined true parameters and states, and reduces the uncertainty of ecohydrological modeling compared to direct optimization of SHP. Specifically, the mean quartile deviation of biases in soil water content and evaporation were reduced from 0.0347 m<sup>3</sup>/m<sup>3</sup> and 0.0027 m/h to 0.0061 m<sup>3</sup>/m<sup>3</sup> and 0.0010 m/h, respectively. Furthermore, integration of the Rosetta 3 diminished the dimensionality of inverse modeling, thereby significantly enhancing algorithm convergence speed and precision. It is recommended to integrate Rosetta 3 with various optimization algorithms to enhance the accuracy of ecohydrological modeling.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"455 ","pages":"Article 117210"},"PeriodicalIF":5.6,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
GeodermaPub Date : 2025-02-16DOI: 10.1016/j.geoderma.2025.117219
Birhanu Iticha , Luke M. Mosley , Petra Marschner
{"title":"Water-extractable alkalinity to estimate the acid-neutralising capacity of organic amendments","authors":"Birhanu Iticha , Luke M. Mosley , Petra Marschner","doi":"10.1016/j.geoderma.2025.117219","DOIUrl":"10.1016/j.geoderma.2025.117219","url":null,"abstract":"<div><div>The effectiveness of amendments to increase the pH of an acidic soil can be expressed as acid-neutralizing capacity (ANC). The alkalinity measurement method, based on prolonged hydrolysis of organic amendments with acid, is widely used but may overestimate the ANC of the amendments. We developed methods for determining the filtered water-extractable alkalinity (WEA) and unfiltered WEA of organic amendments to provide more accurate estimation of their ANC. Filtered WEA indicates the alkalinity arising from water-soluble compounds, while unfiltered WEA relates to alkalinity originating from both surface adsorption of proton by particulate organic materials and water-soluble compounds. The methods were tested using organic materials differing in decomposability; readily decomposable wheat straw, faba bean straw, and more resistant blended poultry litter, biochar, and compost. Filtered WEA of the organic amendments obtained at equilibrium extraction time (12 h) ranged from 6.5 cmol H<sup>+</sup> kg<sup>−1</sup> (wheat straw) to 14.2 cmol H<sup>+</sup> kg<sup>−1</sup> (biochar), whereas the unfiltered WEA measured after 2 h of extraction with water and short acid treatment during titration ranged from 10.3 cmol H<sup>+</sup> kg<sup>−1</sup> (wheat straw) to 219.3 cmol H<sup>+</sup> kg<sup>−1</sup> (compost). Unfiltered WEA values were slightly lower than acid-extractable alkalinity in rapidly biodegradable materials, but significantly lower in resistant organic materials. This could be because the former materials breakdown readily in water to release organic alkalinity, whereas resistant materials decompose and release organic alkalinity slowly in water, compared to that induced by prolonged acid hydrolysis. The organic materials treated with HCl produced stronger FTIR absorption peaks at various bands than those treated with water. Hydrolysis in water did not cause significant changes in spectral peaks compared to the original organic materials. Rates of organic amendments or organic amendment-lime combinations calculated for acidic soil (pHw 4.8) based on unfiltered WEA results in a pHw closer to 6.5. We conclude that the unfiltered WEA method is suitable for determining the available alkalinity of organic materials that can be used for estimating amendment rates for amelioration of acidic soils.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"455 ","pages":"Article 117219"},"PeriodicalIF":5.6,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
GeodermaPub Date : 2025-02-13DOI: 10.1016/j.geoderma.2025.117209
Nelly S. Raymond , Peter M. Kopittke , Frederik J.T. van der Bom , Enli Wang , Michael J. Bell
{"title":"Phosphorus dynamics in P-depleted sub-surface of cropping soils in northeast Australia: Evaluating the potential of APSIM for simulation and the influence of soil properties","authors":"Nelly S. Raymond , Peter M. Kopittke , Frederik J.T. van der Bom , Enli Wang , Michael J. Bell","doi":"10.1016/j.geoderma.2025.117209","DOIUrl":"10.1016/j.geoderma.2025.117209","url":null,"abstract":"<div><div>Sub-surface (10–30 cm depths) phosphorus (P) depletion in Vertisols of northern Australia necessitates deeper placement of phosphate fertilisers to sustain rain-fed crop productivity. However, predicting crop P availability in these layers is challenging due to the variability in soil properties and seasonal rainfall. This study had two main objectives: (1) to determine which soil properties influence the decrease in extractable-P after the addition of different types of fertilisers and, (2) to evaluate the performance of the Agricultural Production Systems sIMulator (APSIM) model in simulating soil extractable-P dynamics within the labile-P pool (i.e., plant-available P pool in APSIM) in P-depleted sub-surface soils following mineral P fertiliser application. In an incubation study, monoammonium phosphate and diammonium phosphate were applied at a rate of 50 mg P kg<sup>−1</sup> to nine Vertisols and three contrasting soil types. Extractable-P was measured using Colwell-P (0.5 M NaHCO<sub>3</sub>, pH 8.5) and BSES-P (0.005 M H<sub>2</sub>SO<sub>4</sub>) at intervals of 10, 30, and 90 days, and extrapolated beyond 365 days of incubation. Extractable-P levels decreased rapidly, reaching equilibrium at 30 days, following an exponential decay model. The degree of P saturation, derived from the P Buffering Index (PBI) and highly correlated with the concentration of extractable amorphous aluminium and iron oxides, was identified as the most significant factor in determining fertiliser P availability. Using Colwell-P to initialise APSIM, the simulated labile-P pool reasonably captured the actual decline of Colwell-P over time by employing a specific loss rate coefficient “r” for each soil, which was related to the soil PBI. The study indicates that the degree of P saturation is crucial in determining the reduction in extractable-P following fertiliser application in these soils. Furthermore, the P module in the APSIM model shows potential for predicting long-term (>1 year) labile-P dynamics, although further testing on diverse soils, varying fertiliser application rates, and under field conditions is necessary to optimise the model’s parameterisation and user confidence.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"455 ","pages":"Article 117209"},"PeriodicalIF":5.6,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
GeodermaPub Date : 2025-02-13DOI: 10.1016/j.geoderma.2025.117212
W. Khairallah , D. Raclot , M. Annabi , G. Coulouma , B. Guenet , C. Rumpel , H. Bahri
{"title":"Evidence of high carbon biodegradability in the subsoil of Mediterranean croplands","authors":"W. Khairallah , D. Raclot , M. Annabi , G. Coulouma , B. Guenet , C. Rumpel , H. Bahri","doi":"10.1016/j.geoderma.2025.117212","DOIUrl":"10.1016/j.geoderma.2025.117212","url":null,"abstract":"<div><div>Although soil carbon is a key element for soil health and climate change mitigation, our understanding of its dynamics is still incomplete. Deep soil horizons are thought to contain mostly organic carbon stabilised at centennial or even millennia time scales. The present study aimed to investigate the common paradigm of high stability of soil carbon in deep soil horizons in semiarid Mediterranean cultivated environments. It was based on a combined assessment and analysis of soil organic carbon (SOC) contents, stocks, biodegradability, and radiocarbon age of eleven soil profiles in north-eastern Tunisia, in the context of soils developed on marine sedimentary parent material with very low to moderate soil inorganic carbon (SIC) content. SOC content and stocks were found to be typical of cultivated Mediterranean soils, with low SOC content (<2%), decreasing with depth and a predominant stock of SOC in subsoils (>30 cm). Our results first revealed high levels of carbon biodegradability for all the soils investigated, confirming that soil carbon in the Mediterranean context can be rapidly decomposed under optimal temperature and moisture conditions. They also showed that the biodegradability of carbon increased with depth, even in profiles with very low SIC contents, indicating that the organic fraction of subsoil carbon is likely to be less stable than that of topsoil carbon. The significant increase in SOC biodegradability with depth was supported by applying a literature-based correction for the contribution of SIC-derived CO<sub>2</sub> to soil respiration emissions. In addition, SOC biodegradability was strongly positively correlated with its radiocarbon age, implying that SOC stability decreases with increasing mean residence time. We explained these original results by a significant presence of very old and highly biodegradable organic carbon in the subsoil organic carbon pool, probably inherited from a Quaternary paleoenvironment and preserved since then due to the favourable preservation conditions associated with the semi-arid climate. Finally, this study highlights the great vulnerability of the millennia-old organic carbon pool stored in some deep horizons of Mediterranean soils, and the necessity to protect it from reconnection with the atmosphere. More broadly, it demonstrates the need to take greater account of the active role of old organic carbon in carbon cycle studies in these specific environments.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"455 ","pages":"Article 117212"},"PeriodicalIF":5.6,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
GeodermaPub Date : 2025-02-12DOI: 10.1016/j.geoderma.2025.117208
Caner Ferhatoglu , Wei Chen , Marshall D. McDaniel , Bradley A. Miller
{"title":"An optimal sample size index for updating spatial soil models","authors":"Caner Ferhatoglu , Wei Chen , Marshall D. McDaniel , Bradley A. Miller","doi":"10.1016/j.geoderma.2025.117208","DOIUrl":"10.1016/j.geoderma.2025.117208","url":null,"abstract":"<div><div>Soil map updates can be expensive due to soil sampling and analysis costs. This study introduces the Optimal Sample Size Index (OSSI), a flexible framework for digital soil mapping that balances model accuracy and sampling costs to update soil spatial models. OSSI determines optimal sample size from subsets of initially available training sets, accounting for different physiographies and model validation metrics with adjustable weights, including root-mean-square-error (RMSE) for cross-validation (CV) and RMSE for independent validation, the standard deviation of RMSE values from 10-fold CV, and relative sampling cost. Relative sampling cost represents the proportion of the number of samples used in modeling to the initially available sample size. We applied two OSSI scenarios to address limitations of the original approach, which prioritized cost reduction but occasionally resulted in unreliable models due to very small training sizes. By adjusting metrics and weights, the second scenario accounted for model uncertainty, producing more reliable models with sample sizes considerably lower than full training sets. Four soil properties (pH, clay, silt, and sand %) were spatially modeled for surface soils in three study areas in Iowa, USA, using random forest regressors. Both scenarios reduced relative sampling costs by up to 92 % compared to using all samples while maintaining similar or improved model performance. The second scenario further ensured model reliability, as shown by lower standard deviations of CV-RMSE values. Our results demonstrate OSSI’s flexibility to balance cost, accuracy, and reliability, offering a practical solution for optimizing soil sample sizes and updating soil survey maps.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"455 ","pages":"Article 117208"},"PeriodicalIF":5.6,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Nitrous oxide act as an alternative electron acceptor for microbial methane oxidation in oxygen-deficient microcosms","authors":"Fengqin Liu , Yu Zhang , Mingting Xie , Zhiliang Yuan , Zhongjun Jia , Yupeng Zhang","doi":"10.1016/j.geoderma.2025.117213","DOIUrl":"10.1016/j.geoderma.2025.117213","url":null,"abstract":"<div><div>Submerged paddy is a hotspot of nitrous oxide (N<sub>2</sub>O) and methane (CH<sub>4</sub>) emission, which is typically considered electron donor and acceptor for microbes, respectively. Theoretical calculations suggested the thermodynamic feasibility of anaerobic CH<sub>4</sub> oxidation coupled with N<sub>2</sub>O reduction (AMNR), and anaerobic methane oxidation and denitrification are typically coupled by certain anaerobic microbes, such as <em>Ca</em>. Methylomirabilis sinica from the NC10 phylum. However, the conventional aerobic methanotrophs underlying this novel greenhouse gas sink remain largely unclear. Four typical soil sample from different latitudes in China were used as inoculum. Enrichment reactors were constructed with continuous CH<sub>4</sub> and N<sub>2</sub>O supply for 400 days to cultivate aerobic methanotrophs capable of N<sub>2</sub>O reduction. This study revealed that conventional methanotrophs, such as species from the <em>Methylocystis</em> and <em>Methylobacterium</em> genera, are the key taxa catalyzing the AMNR process. Consistently high N<sub>2</sub>O reduction rate (5.37–6.24 μmol·g<sup>−1</sup>-dry soil·d<sup>−1</sup>) was observed in strong association with CO<sub>2</sub> formation, that was nearly matched with the expected stoichiometry (4:1). The N<sub>2</sub>O reduction process occurred in two distinct phases: a rapid reduction phase concurrent with CH<sub>4</sub> oxidation, followed by a slower reduction phase. N<sub>2</sub>O was directly reduced by conventional aerobic methanotrophs harboring the <em>nosZ</em> gene, such as <em>Methylocystis</em>, or by denitrifiers using the fermentative intermediates produced by methanotrophs as electron donors. This suggests that conventional methanotrophs, which typically perform aerobic methane oxidation, could also have denitrification potential, possibly facilitated by the presence of the <em>nosZ</em> gene. Although methanotrophs and denitrifiers are usually considered distinct groups, these results indicate that the AMNR process could allow for the simultaneous oxidation of CH<sub>4</sub> and reduction of N<sub>2</sub>O in paddy soils, thus enhancing the potential for greenhouse gas mitigation.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"455 ","pages":"Article 117213"},"PeriodicalIF":5.6,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
GeodermaPub Date : 2025-02-11DOI: 10.1016/j.geoderma.2025.117198
Youliang Peng , Liangjun Fei , Fangyuan Shen , Runqiao Zheng , Qian Wang , Qianwen Fan
{"title":"A green-Ampt model considering unsaturated zone and pore air pressure","authors":"Youliang Peng , Liangjun Fei , Fangyuan Shen , Runqiao Zheng , Qian Wang , Qianwen Fan","doi":"10.1016/j.geoderma.2025.117198","DOIUrl":"10.1016/j.geoderma.2025.117198","url":null,"abstract":"<div><div>The relationship between infiltration time and the depth of the wetting front can be solved using Darcy’s law. According to this, the infiltration rate is equal to the derivative of the infiltration amount regarding time. However, the traditional Green-Ampt model considers the infiltration amount on the basis of the complete saturation of the wetting regions while ignoring the effect of pore gas pressure. This limits the calculation accuracy of the relationship between infiltration time and wetting front depth. As a response to this problem, this paper analyses the effects of soil bulk density and surface water depth on soil moisture content and pore air pressure at varying depths during water infiltration. It then constructs models for the unsaturated regions and additional pore gas pressure as a means of adjusting the cumulative infiltration volume and infiltration time separately. The results demonstrate that as the bulk density of the soil increased, the infiltration rate decreased while the time required for the wetting front to reach the measurement point increased. As the surface water depth increased, the infiltration rate also increased. During the water infiltration process, the change in pore gas pressure was a continuous state, which can be divided into two phases: rapid change and slow change. The maximum and stable pore air pressure were positively correlated with the surface water depth and soil bulk density during the infiltration process. In comparison to the measured values, the accuracy of the infiltration amount that was calculated by the combination model was the highest, followed by the ellipse model and the original model was the worst. Of the three Green-Ampt models, the infiltration time that was calculated using the Green-Ampt model that considered the pore pressure and unsaturated regions was closer to the measured values. This was followed by the Green-Ampt model that considered the unsaturated regions and the traditional Green-Ampt model was the worst. In addition, the Green-Ampt correction model that considered soil bulk density and surface water depth rather than stable pore air pressure did not affect the accuracy of the experiment. The research results can provide theoretical reference for improving the application of the Green-Ampt model.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"455 ","pages":"Article 117198"},"PeriodicalIF":5.6,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
GeodermaPub Date : 2025-02-01DOI: 10.1016/j.geoderma.2024.117162
Geng Cui , Yan Liu , Xiaojie Li , Shan Wang , Xiangning Qu , Lei Wang , Shouzheng Tong , Mingye Zhang , Xiaofeng Li , Wenqiang Zhang
{"title":"Impacts of groundwater storage variability on soil salinization in a semi-arid agricultural plain","authors":"Geng Cui , Yan Liu , Xiaojie Li , Shan Wang , Xiangning Qu , Lei Wang , Shouzheng Tong , Mingye Zhang , Xiaofeng Li , Wenqiang Zhang","doi":"10.1016/j.geoderma.2024.117162","DOIUrl":"10.1016/j.geoderma.2024.117162","url":null,"abstract":"<div><div>Soil salinization, which is significantly influenced by groundwater storage dynamics, leads to reduced land productivity, loss of arable land, and degradation of vegetation, thereby posing a substantial threat to global food security and ecosystem functions. The western Songnen Plain (WSP) is one of the world’s three largest concentrations of soda saline-alkaline regions. However, the availability of observed data on groundwater storage dynamics in the WSP remains limited, potentially impeding the evaluation of their impacts on soil salinization processes. This study investigated the impact of groundwater storage variability on soil salinization in the WSP, utilizing multi-source satellite data, the Global Land Data Assimilation System hydrological model data, and ground observation data. Our results demonstrated that groundwater storage anomalies (GWSAs) exhibited cyclical fluctuations from 2002 to 2014, followed by a substantial decline of 13.215 cm equivalent water height from 2015 to 2021. GWSAs exhibited a significant positive relationship with the area of medium-salinized soils that comprised over 56 % of the total salinized soil area. Both the area and degree of soil salinization overall decreased in the WSP due to the decline in groundwater storage and the implementation of soil improvement policies. Our results suggest that targeting soil treatment projects on salinized soils that are less affected by groundwater conditions could potentially mitigate soil salinization in the WSP. This study assessed the potential impact of groundwater storage variability on soil salinization, enhancing mechanisms underlying salinization processes and offering valuable data to inform land and water resources management in salinization-prone regions.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"454 ","pages":"Article 117162"},"PeriodicalIF":5.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142935985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}