Pub Date : 2026-01-12DOI: 10.1016/j.catena.2026.109822
Gustavo Vieira Veloso , Danilo César de Mello , Lucas Vieira Silva , Elpídio Inácio Fernandes-Filho , Jorge Tadeu Fim Rosas , Fellipe Alcantara de Oliveira Mello , José João Lelis Leal de Souza , Márcio Rocha Francelino , Sara Ramos dos Santos , Francis Henrique Tenório Firmino , Nícolas Augusto Rosin , Gabriel Pimenta Barbosa de Sousa , Tiago Osório Ferreira , Arnaldo Barros e Souza , José A.M. Demattê
<div><div>Pedology, the study of pedogenesis, includes soil classification and mapping. Digital soil mapping (DSM) has evolved from traditional methods to creating comprehensive spatial soil information systems. This advancement is achieved by integrating field and laboratory data with environmental covariates and incorporating new geotechnologies such as geophysical techniques and remote sensing data, alongside machine learning approaches. This integration in DSM provides novel insights into soil survey and mapping, offering detailed information on soil variability both vertically and laterally. It also raises new research questions that traditional pedology may not have addressed. In this study, we proposed and compared three strategies for DSM in Brazil, creating predictive pedological mapping. These strategies integrate data from three geophysical sensors, remote sensing data, relief, and lithology as input in a machine learning approach testing five algorithms. The four proposed strategies were: <em>i)</em> the combined use of geophysical variables and remote sensing data (G + RS + DEM); <em>ii)</em> the use of remote sensing data only (RS + DEM); <em>iii)</em> the use of geophysical variables only (G + DEM) and; iv) relief data (DEM). Lithology and relief were used as common input data in the predictive pedological mapping modeling process for all four strategies. We conducted a statistical analysis to evaluate the models' performance employing the Kruskal-Walli's test, the F1-score, Kappa, Accuracy, Sensitivity, and Specificity. Additionally, the best strategy was chosen based on the Kruskal-Walli's test and Overall Agreement and Disagreement statistical validation method, utilizing the reference map generated by an expert pedologist. Results revealed that the Random Forest algorithm presented the best performance for modeling predictive pedological mapping in all proposed strategies. Among the predictor variables, the Synthetic Soil Image (a synthetic multi-temporal soil image created by selecting and integrating bare soil observations from satellite data to capture key soil properties for mapping and analysis), relief, and geophysical data had the most significant contributions. While variables associated with remote sensing displayed stronger correlations with surface pedological attributes, geophysical variables demonstrated stronger associations with subsurface pedological attributes and diagnostic horizons. The most effective strategies for predictive digital pedological mapping were the G + RS, while the least effective was DEM. The individual performances of G and RS were comparable. The final predictive digital pedological map had a strong correlation with the traditional one, considering the Agreement/Disagreement validation method. The most significant prediction errors occurred in the transitional zones between pedological and lithological classes. Within the predicted classes, the most substantial errors were observed in class
{"title":"Strategies for predictive digital soil mapping by geophysical, remote sensing and machine learning approaches","authors":"Gustavo Vieira Veloso , Danilo César de Mello , Lucas Vieira Silva , Elpídio Inácio Fernandes-Filho , Jorge Tadeu Fim Rosas , Fellipe Alcantara de Oliveira Mello , José João Lelis Leal de Souza , Márcio Rocha Francelino , Sara Ramos dos Santos , Francis Henrique Tenório Firmino , Nícolas Augusto Rosin , Gabriel Pimenta Barbosa de Sousa , Tiago Osório Ferreira , Arnaldo Barros e Souza , José A.M. Demattê","doi":"10.1016/j.catena.2026.109822","DOIUrl":"10.1016/j.catena.2026.109822","url":null,"abstract":"<div><div>Pedology, the study of pedogenesis, includes soil classification and mapping. Digital soil mapping (DSM) has evolved from traditional methods to creating comprehensive spatial soil information systems. This advancement is achieved by integrating field and laboratory data with environmental covariates and incorporating new geotechnologies such as geophysical techniques and remote sensing data, alongside machine learning approaches. This integration in DSM provides novel insights into soil survey and mapping, offering detailed information on soil variability both vertically and laterally. It also raises new research questions that traditional pedology may not have addressed. In this study, we proposed and compared three strategies for DSM in Brazil, creating predictive pedological mapping. These strategies integrate data from three geophysical sensors, remote sensing data, relief, and lithology as input in a machine learning approach testing five algorithms. The four proposed strategies were: <em>i)</em> the combined use of geophysical variables and remote sensing data (G + RS + DEM); <em>ii)</em> the use of remote sensing data only (RS + DEM); <em>iii)</em> the use of geophysical variables only (G + DEM) and; iv) relief data (DEM). Lithology and relief were used as common input data in the predictive pedological mapping modeling process for all four strategies. We conducted a statistical analysis to evaluate the models' performance employing the Kruskal-Walli's test, the F1-score, Kappa, Accuracy, Sensitivity, and Specificity. Additionally, the best strategy was chosen based on the Kruskal-Walli's test and Overall Agreement and Disagreement statistical validation method, utilizing the reference map generated by an expert pedologist. Results revealed that the Random Forest algorithm presented the best performance for modeling predictive pedological mapping in all proposed strategies. Among the predictor variables, the Synthetic Soil Image (a synthetic multi-temporal soil image created by selecting and integrating bare soil observations from satellite data to capture key soil properties for mapping and analysis), relief, and geophysical data had the most significant contributions. While variables associated with remote sensing displayed stronger correlations with surface pedological attributes, geophysical variables demonstrated stronger associations with subsurface pedological attributes and diagnostic horizons. The most effective strategies for predictive digital pedological mapping were the G + RS, while the least effective was DEM. The individual performances of G and RS were comparable. The final predictive digital pedological map had a strong correlation with the traditional one, considering the Agreement/Disagreement validation method. The most significant prediction errors occurred in the transitional zones between pedological and lithological classes. Within the predicted classes, the most substantial errors were observed in class","PeriodicalId":9801,"journal":{"name":"Catena","volume":"264 ","pages":"Article 109822"},"PeriodicalIF":5.7,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145973916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-12DOI: 10.1016/j.catena.2025.109746
Antonio Ganga , Ludmila Ribeiro Roder , Iraê Amaral Guerrini , Rafael Barroca Silva , Emmanuele Farris , Alfredo Maccioni , Gian Franco Capra
Soil plays a pivotal role in the processes and behavior of the global carbon cycle, with soil organic carbon stocks (SOCs) representing the largest terrestrial carbon (C) pool. Mediterranean areas are among the world's biodiversity hotspots for conservation priorities. The island of Sardinia (southern Italy), due to the rare convergence of environmental and historical land use factors, is characterized by extremely peculiar soil conditions. This study investigated SOCs and their behavior in two contrasting Mediterranean pedosystems: Cambisols developed on granite (the most common pedosystem) vs Luvisols on limestone (one of the rarest), featuring different land covers with a gradient varying from agricultural (vineyard at different ages) to more natural areas (remnants of natural potential vegetation cover). Several soil physico-chemical features were assessed. An ANOVA was conducted to determine significant differences (p < 0.05) between and among investigated horizons and land uses. The variability and complex multiple relationships were analyzed by factor (FA) and principal component analysis (PCA). Results revealed that areas with natural or near-natural features exhibited significantly higher SOCs compared to more intensively managed and human-influenced land covers. Interestingly, the two investigated pedosystems, originating from diverse substrates and thus contributing to different soil formation processes, are characterized by significantly different SOC amounts and behaviors. Overall, soil features have a greater influence on SOCs than usually expected and previously reported. Consequently, this study suggests that SOC investigations, if not conducted in conjunction with a thorough soil analysis, may lead to inaccurate or misleading outcomes and subsequent conclusions.
{"title":"The influence of soil physico-chemical properties and land uses on organic carbon stocks in contrasting Mediterranean pedosystems","authors":"Antonio Ganga , Ludmila Ribeiro Roder , Iraê Amaral Guerrini , Rafael Barroca Silva , Emmanuele Farris , Alfredo Maccioni , Gian Franco Capra","doi":"10.1016/j.catena.2025.109746","DOIUrl":"10.1016/j.catena.2025.109746","url":null,"abstract":"<div><div>Soil plays a pivotal role in the processes and behavior of the global carbon cycle, with soil organic carbon stocks (SOCs) representing the largest terrestrial carbon (C) pool. Mediterranean areas are among the world's biodiversity hotspots for conservation priorities. The island of Sardinia (southern Italy), due to the rare convergence of environmental and historical land use factors, is characterized by extremely peculiar soil conditions. This study investigated SOCs and their behavior in two contrasting Mediterranean pedosystems: Cambisols developed on granite (the most common pedosystem) <em>vs</em> Luvisols on limestone (one of the rarest), featuring different land covers with a gradient varying from agricultural (vineyard at different ages) to more natural areas (remnants of natural potential vegetation cover). Several soil physico-chemical features were assessed. An ANOVA was conducted to determine significant differences (<em>p</em> < 0.05) between and among investigated horizons and land uses. The variability and complex multiple relationships were analyzed by factor (FA) and principal component analysis (PCA). Results revealed that areas with natural or near-natural features exhibited significantly higher SOCs compared to more intensively managed and human-influenced land covers. Interestingly, the two investigated pedosystems, originating from diverse substrates and thus contributing to different soil formation processes, are characterized by significantly different SOC amounts and behaviors. Overall, soil features have a greater influence on SOCs than usually expected and previously reported. Consequently, this study suggests that SOC investigations, if not conducted in conjunction with a thorough soil analysis, may lead to inaccurate or misleading outcomes and subsequent conclusions.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"264 ","pages":"Article 109746"},"PeriodicalIF":5.7,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145973917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-12DOI: 10.1016/j.catena.2025.109788
Hamond Motsi , Catherine E. Clarke , Ailsa G. Hardie , Michele L. Francis , Alastair J. Potts
Soils beneath Portulacaria afra (spekboom) within the evergreen Albany Subtropical Thicket of South Africa contain unusually high soil organic carbon concentrations despite the biome's semi-arid climate. Fractionation of soil organic matter (SOM) into particulate organic matter (POM) and mineral-associated organic matter (MAOM) provide insights into the mechanisms of soil carbon (C) accumulation. Conventionally, sodium polytungstate (SPT) is used in density fractionation, but its high-cost limits sample numbers. Cheaper, reliable alternatives to SPT are therefore required to understand the C dynamics of spekboom and other high-C soils. Particle size (PS) sieving has been proposed as cheaper alternative to density fractionation, but its application in spekboom soils is unknown. This study compared SPT with PS fractionation and density fractionation using cheaper, highly soluble salts: sodium iodide (NaI), potassium iodide (KI), and calcium chloride (CaCl2). The relationship between permanganate oxidizable carbon (POXC) and POM-C was also explored. High C (>5 %) topsoils with a range of POM:MAOM ratios from the spekboom thicket, a pine forest, a wetland, and a grassland were evaluated. Results demonstrated that fractionation methods significantly affected (p < 0.05) fractions in each soil. NaI showed similar performance to SPT in SOM fractionation followed by KI. The PS method used in this study compared poorly to SPT, underestimating POM-C (34–39 %) and overestimating MAOM-C (39–51 %) in high POM soils (spekboom and pine forest soils) with the opposite effect in lower POM soils (wetland and grassland). The CaCl2 method was also not ideal due to salt entrainment. Some soils did not conform to the expected linear relationship between POM-C and POXC demonstrating that POXC method is not always suitable. Thus, NaI is proposed as a cheaper alternative to replace SPT in density fractionation of spekboom soils. Findings from this study have significant implications in appropriate method selection for SOM fractionation of high C soils.
{"title":"Comparison of alternative chemical density and physical methods for isolating soil organic matter fractions in high carbon soils","authors":"Hamond Motsi , Catherine E. Clarke , Ailsa G. Hardie , Michele L. Francis , Alastair J. Potts","doi":"10.1016/j.catena.2025.109788","DOIUrl":"10.1016/j.catena.2025.109788","url":null,"abstract":"<div><div>Soils beneath <em>Portulacaria afra</em> (spekboom) within the evergreen Albany Subtropical Thicket of South Africa contain unusually high soil organic carbon concentrations despite the biome's semi-arid climate. Fractionation of soil organic matter (SOM) into particulate organic matter (POM) and mineral-associated organic matter (MAOM) provide insights into the mechanisms of soil carbon (C) accumulation. Conventionally, sodium polytungstate (SPT) is used in density fractionation, but its high-cost limits sample numbers. Cheaper, reliable alternatives to SPT are therefore required to understand the C dynamics of spekboom and other high-C soils. Particle size (PS) sieving has been proposed as cheaper alternative to density fractionation, but its application in spekboom soils is unknown. This study compared SPT with PS fractionation and density fractionation using cheaper, highly soluble salts: sodium iodide (NaI), potassium iodide (KI), and calcium chloride (CaCl<sub>2</sub>). The relationship between permanganate oxidizable carbon (POXC) and POM-C was also explored. High C (>5 %) topsoils with a range of POM:MAOM ratios from the spekboom thicket, a pine forest, a wetland, and a grassland were evaluated. Results demonstrated that fractionation methods significantly affected (<em>p</em> < 0.05) fractions in each soil. NaI showed similar performance to SPT in SOM fractionation followed by KI. The PS method used in this study compared poorly to SPT, underestimating POM-C (34–39 %) and overestimating MAOM-C (39–51 %) in high POM soils (spekboom and pine forest soils) with the opposite effect in lower POM soils (wetland and grassland). The CaCl<sub>2</sub> method was also not ideal due to salt entrainment. Some soils did not conform to the expected linear relationship between POM-C and POXC demonstrating that POXC method is not always suitable. Thus, NaI is proposed as a cheaper alternative to replace SPT in density fractionation of spekboom soils. Findings from this study have significant implications in appropriate method selection for SOM fractionation of high C soils.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"264 ","pages":"Article 109788"},"PeriodicalIF":5.7,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145973835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-12DOI: 10.1016/j.catena.2026.109811
Ang Lu , Peng Tian , Guangju Zhao , Xingmin Mu , Xiaojing Tian , Chaojun Gu , Lin Yang , Junjian Fan
Soil erosion models are efficient tools for quantifying regional soil erosion, estimating long-term soil erosion rates, and assessing the effects of land surface changes on soil erosion and sediment yield. These models offer significant advantages over costly and geographically limited field monitoring. These models are crucial for understanding hydrological and sediment dynamic on the Loess Plateau, which is highly vulnerable to soil erosion due to its complex topography, high erodible loess and frequent storms. To address the need of event-based simulations that can capture the impacts of widespread conservation practices, this study developed a novel distributed hydrology and soil erosion model. The model couples the Vertical Mixed Runoff Model (VMM) with the Morgan-Morgan-Finney (MMF) erosion model and integrates a specialized module to explicitly simulate the interception effects of terraces, which are a key soil and water conservation measure in the region. This integrated model simulates three key components at the flood-event scale, including runoff generation, soil erosion, and sediment transport. The model was calibrated and validated using data from nine flood events in the Xichuanhe catchment, a typical tributary of the Yanhe River on the Loess Plateau. The results demonstrate a high level of accuracy in runoff simulation, achieving Nash-Sutcliffe Efficiency (NSE) coefficients of 0.82 and 0.67 for the calibration and validation periods, respectively. Relative Peak Errors (RPE) were consistently below 23%, indicating a close match between simulated and observed hydrographs. For sediment simulation, the model effectively captured the overall dynamics with an average NSE of 0.80 and RPE between 2.3% and 18.7% during calibration periods, though with some discrepancies during validation periods. The model confirms the significant role of terraces in reducing runoff and sediment yield. On average, terraces could reduce total runoff volume by 12.1% and sediment yield by 17.2% during flood events. These findings demonstrated the model's effectiveness for hydrological and soil erosion simulation and its potential in evaluating soil and water conservation measures on the Loess Plateau. The model can offer a valuable tool for quantitatively assessing the effectiveness of soil and water conservation measures in this critical region and similar semi-arid environments.
{"title":"Development and application of a distributed hydrology and soil erosion model in a semi-arid catchment, China","authors":"Ang Lu , Peng Tian , Guangju Zhao , Xingmin Mu , Xiaojing Tian , Chaojun Gu , Lin Yang , Junjian Fan","doi":"10.1016/j.catena.2026.109811","DOIUrl":"10.1016/j.catena.2026.109811","url":null,"abstract":"<div><div>Soil erosion models are efficient tools for quantifying regional soil erosion, estimating long-term soil erosion rates, and assessing the effects of land surface changes on soil erosion and sediment yield. These models offer significant advantages over costly and geographically limited field monitoring. These models are crucial for understanding hydrological and sediment dynamic on the Loess Plateau, which is highly vulnerable to soil erosion due to its complex topography, high erodible loess and frequent storms. To address the need of event-based simulations that can capture the impacts of widespread conservation practices, this study developed a novel distributed hydrology and soil erosion model. The model couples the Vertical Mixed Runoff Model (VMM) with the Morgan-Morgan-Finney (MMF) erosion model and integrates a specialized module to explicitly simulate the interception effects of terraces, which are a key soil and water conservation measure in the region. This integrated model simulates three key components at the flood-event scale, including runoff generation, soil erosion, and sediment transport. The model was calibrated and validated using data from nine flood events in the Xichuanhe catchment, a typical tributary of the Yanhe River on the Loess Plateau. The results demonstrate a high level of accuracy in runoff simulation, achieving Nash-Sutcliffe Efficiency (NSE) coefficients of 0.82 and 0.67 for the calibration and validation periods, respectively. Relative Peak Errors (RPE) were consistently below 23%, indicating a close match between simulated and observed hydrographs. For sediment simulation, the model effectively captured the overall dynamics with an average NSE of 0.80 and RPE between 2.3% and 18.7% during calibration periods, though with some discrepancies during validation periods. The model confirms the significant role of terraces in reducing runoff and sediment yield. On average, terraces could reduce total runoff volume by 12.1% and sediment yield by 17.2% during flood events. These findings demonstrated the model's effectiveness for hydrological and soil erosion simulation and its potential in evaluating soil and water conservation measures on the Loess Plateau. The model can offer a valuable tool for quantitatively assessing the effectiveness of soil and water conservation measures in this critical region and similar semi-arid environments.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"264 ","pages":"Article 109811"},"PeriodicalIF":5.7,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145973918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-12DOI: 10.1016/j.catena.2025.109765
Wei Tang, Xiurong Wang, Rong Zou, Bingyang Shi, Jiaqi Chen
While trampling disturbance affects soils, its impact on urban park soil carbon cycling remains unclear. This study elucidates the mechanisms by which varying trampling intensities influence urban park soil carbon pools, thereby providing theoretical foundations for soil restoration and park management. Four gradient sampling plots (0-3 m, 3-6 m, 6-9 m, 9-12 m) were established along park trail edges. Soil samples were collected using a five-point sampling method, with trampling intensities (heavy, moderate, light) classified based on changes in soil bulk density (compared to control) using the Jenks Natural Breaks method. Results indicated that heavy trampling reduced the >2 mm aggregate proportion by 30.95 %, mean weight diameter by 11.62 %, and geometric mean diameter by 16.62 %, thereby decreasing soil stability. Heavy trampling decreased total soil organic carbon by 34.45 % while increasing the <0.053 mm aggregate contribution by 40.58 %, facilitating carbon migration from >2 mm to <0.053 mm aggregates. Heavy trampling transiently increased labile organic carbon but decreased recalcitrant and inert fractions, while suppressing microbial biomass carbon. Structural equation modeling confirmed that trampling directly (P < 0.05) and indirectly (via reduced aggregate stability and carbon activity, P < 0.01) affected carbon dynamics. Trampling disturbance significantly compromises soil carbon pool stability and sequestration capacity through multiple mechanisms: disrupting aggregate stability, reducing organic carbon content, altering carbon fraction composition, and suppressing microbial activity. Compared to simply increasing carbon inputs, minimizing physical disturbance proves more effective for maintaining soil carbon sink functionality, providing a scientific basis for urban park carbon management.
{"title":"Trampling disturbance affects the stability of soil carbon pools in urban park green spaces by disrupting soil aggregates and altering the composition of organic carbon components","authors":"Wei Tang, Xiurong Wang, Rong Zou, Bingyang Shi, Jiaqi Chen","doi":"10.1016/j.catena.2025.109765","DOIUrl":"10.1016/j.catena.2025.109765","url":null,"abstract":"<div><div>While trampling disturbance affects soils, its impact on urban park soil carbon cycling remains unclear. This study elucidates the mechanisms by which varying trampling intensities influence urban park soil carbon pools, thereby providing theoretical foundations for soil restoration and park management. Four gradient sampling plots (0-3 m, 3-6 m, 6-9 m, 9-12 m) were established along park trail edges. Soil samples were collected using a five-point sampling method, with trampling intensities (heavy, moderate, light) classified based on changes in soil bulk density (compared to control) using the Jenks Natural Breaks method. Results indicated that heavy trampling reduced the >2 mm aggregate proportion by 30.95 %, mean weight diameter by 11.62 %, and geometric mean diameter by 16.62 %, thereby decreasing soil stability. Heavy trampling decreased total soil organic carbon by 34.45 % while increasing the <0.053 mm aggregate contribution by 40.58 %, facilitating carbon migration from >2 mm to <0.053 mm aggregates. Heavy trampling transiently increased labile organic carbon but decreased recalcitrant and inert fractions, while suppressing microbial biomass carbon. Structural equation modeling confirmed that trampling directly (<em>P</em> < 0.05) and indirectly (via reduced aggregate stability and carbon activity, <em>P</em> < 0.01) affected carbon dynamics. Trampling disturbance significantly compromises soil carbon pool stability and sequestration capacity through multiple mechanisms: disrupting aggregate stability, reducing organic carbon content, altering carbon fraction composition, and suppressing microbial activity. Compared to simply increasing carbon inputs, minimizing physical disturbance proves more effective for maintaining soil carbon sink functionality, providing a scientific basis for urban park carbon management.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"264 ","pages":"Article 109765"},"PeriodicalIF":5.7,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145973834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the context of global change and human activities, the increasing frequency of heavy rainfall and drought events due to uneven precipitation distribution poses significant challenges to ecosystem hydrology. Forest and grass ecosystems can exhibit distinct hydrological responses to climate extremes, yet their short- and long-term reactions across multiple temporal scales remain inadequately quantified. Using field standard runoff plots and vertically-distributed soil moisture monitoring systems over 13 years, this study investigated the effects of extreme rainfall events on P (precipitation), R (runoff), ET (evapotranspiration), and SWC (soil water content) in forest and grass ecosystems within a rocky mountainous area of Beijing. At the event scale, NG (natural grass) showed faster and more pronounced hydrological responses in shallow soil layers compared to SF (secondary forest). Storm events induced significant water transport in deep soils across both NG and SF. Deep water movement was regulated by root systems and pre-storm SWC, with SF demonstrating greater soil water retention capacity. At the annual scale, the primary water output was ET, accounting for 75.42% ∼ 107.69% of NG and 78.68% ∼ 121.55% of SF. Multi-year R was markedly higher in NG than in SF, although mean annual R accounted for only 6.74% to 12.97% of annual P. Deep SWC was significantly greater in extremely wet years compared to extremely dry years, highlighting the role of extreme precipitation in deep soil water recharge and retention. Both ecosystems exhibited multi-year soil water deficits, although heavy rainfall at the end of the growing season occasionally resulted in annual water surplus. These findings provide new insights into the hydrological dynamics of rocky mountain ecosystems under increasing climate variability.
{"title":"Response of hydrological processes to event- and annual-scale precipitation extremes in a rocky mountainous area of northern China","authors":"Yuxin Wu , Xinxiao Yu , Guodong Jia , Zihe Liu , Honghong Rao","doi":"10.1016/j.catena.2026.109803","DOIUrl":"10.1016/j.catena.2026.109803","url":null,"abstract":"<div><div>In the context of global change and human activities, the increasing frequency of heavy rainfall and drought events due to uneven precipitation distribution poses significant challenges to ecosystem hydrology. Forest and grass ecosystems can exhibit distinct hydrological responses to climate extremes, yet their short- and long-term reactions across multiple temporal scales remain inadequately quantified. Using field standard runoff plots and vertically-distributed soil moisture monitoring systems over 13 years, this study investigated the effects of extreme rainfall events on P (precipitation), R (runoff), ET (evapotranspiration), and SWC (soil water content) in forest and grass ecosystems within a rocky mountainous area of Beijing. At the event scale, NG (natural grass) showed faster and more pronounced hydrological responses in shallow soil layers compared to SF (secondary forest). Storm events induced significant water transport in deep soils across both NG and SF. Deep water movement was regulated by root systems and pre-storm SWC, with SF demonstrating greater soil water retention capacity. At the annual scale, the primary water output was ET, accounting for 75.42% ∼ 107.69% of NG and 78.68% ∼ 121.55% of SF. Multi-year R was markedly higher in NG than in SF, although mean annual R accounted for only 6.74% to 12.97% of annual P. Deep SWC was significantly greater in extremely wet years compared to extremely dry years, highlighting the role of extreme precipitation in deep soil water recharge and retention. Both ecosystems exhibited multi-year soil water deficits, although heavy rainfall at the end of the growing season occasionally resulted in annual water surplus. These findings provide new insights into the hydrological dynamics of rocky mountain ecosystems under increasing climate variability.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"264 ","pages":"Article 109803"},"PeriodicalIF":5.7,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145973915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-12DOI: 10.1016/j.catena.2026.109799
Xuan Luo , Xuan Ji , Yi Zou , Siqi Wang , Xinbei Liu , Xiaodong Wu , Jianxing Li , Yungang Li
Hydrological drought (HD) propagation and recovery dynamics exhibit spatiotemporal heterogeneity, which is driven by coupled climate-catchment interactions. However, the relative contributions and role of these drivers remain poorly quantified. This study developed an attribution approach integrating process-based modeling and machine learning to disentangle multi-factor controls on HD propagation and recovery in the Lancang-Mekong River Basin. By employing a Variable Infiltration Capacity model to reconstruct natural runoff, we quantified meteorological-to-hydrological drought propagation time (PT) and recovery lag time (RT) through event-based analysis. A multi-stage predictor selection strategy, combined with Optimal Parameter-based Geodetector (OPGD), Recursive Feature Elimination (RFE), and Extreme Gradient Boosting (XGBoost) algorithms, addressed spatial heterogeneity and multicollinearity among driver factors while retaining predictive power. Finally, SHapley Additive exPlanations (SHAP) were incorporated to quantify feature contributions and support the interpretation of nonlinear driver-response relationships. Results revealed that RT (mean: 3.45 months) consistently exceeded PT (mean: 1.12 months) across all sub-basins, with drought duration and severity amplifying PT and RT. The hybrid OPGD-RFE-XGBoost model achieved higher R2 (50% increase for PT and 42% increase for RT) using only 18% and 35% of the original features compared to XGBoost model. SHAP analysis identified climate as the primary controlling factor for both PT (contribution: 45.5%) and RT (51.8%). Catchment and morphological characteristics exhibited subordinate influence on PT (41.3%) and RT (32.7%). By integrating spatially structured predictors and explainable machine learning, this study establishes an analytical framework to decouple climate-catchment interactions in drought cascades, highlighting the role of underlying characteristics in drought propagation and recovery.
{"title":"Disentangling the impacts of climate, catchment, and morphological characteristics on hydrological drought propagation and recovery","authors":"Xuan Luo , Xuan Ji , Yi Zou , Siqi Wang , Xinbei Liu , Xiaodong Wu , Jianxing Li , Yungang Li","doi":"10.1016/j.catena.2026.109799","DOIUrl":"10.1016/j.catena.2026.109799","url":null,"abstract":"<div><div>Hydrological drought (HD) propagation and recovery dynamics exhibit spatiotemporal heterogeneity, which is driven by coupled climate-catchment interactions. However, the relative contributions and role of these drivers remain poorly quantified. This study developed an attribution approach integrating process-based modeling and machine learning to disentangle multi-factor controls on HD propagation and recovery in the Lancang-Mekong River Basin. By employing a Variable Infiltration Capacity model to reconstruct natural runoff, we quantified meteorological-to-hydrological drought propagation time (PT) and recovery lag time (RT) through event-based analysis. A multi-stage predictor selection strategy, combined with Optimal Parameter-based Geodetector (OPGD), Recursive Feature Elimination (RFE), and Extreme Gradient Boosting (XGBoost) algorithms, addressed spatial heterogeneity and multicollinearity among driver factors while retaining predictive power. Finally, SHapley Additive exPlanations (SHAP) were incorporated to quantify feature contributions and support the interpretation of nonlinear driver-response relationships. Results revealed that RT (mean: 3.45 months) consistently exceeded PT (mean: 1.12 months) across all sub-basins, with drought duration and severity amplifying PT and RT. The hybrid OPGD-RFE-XGBoost model achieved higher R<sup>2</sup> (50% increase for PT and 42% increase for RT) using only 18% and 35% of the original features compared to XGBoost model. SHAP analysis identified climate as the primary controlling factor for both PT (contribution: 45.5%) and RT (51.8%). Catchment and morphological characteristics exhibited subordinate influence on PT (41.3%) and RT (32.7%). By integrating spatially structured predictors and explainable machine learning, this study establishes an analytical framework to decouple climate-catchment interactions in drought cascades, highlighting the role of underlying characteristics in drought propagation and recovery.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"264 ","pages":"Article 109799"},"PeriodicalIF":5.7,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145973919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-10DOI: 10.1016/j.catena.2025.109783
Estêvão Botura Stefanuto , Cenira Maria Lupinacci , Higor Lourenzoni Bonzanini , Danilo Marques de Magalhães , Filipe Carvalho , Estela Nadal-Romero , Melina Fushimi , Fabiano Tomazini da Conceição , Archimedes Perez Filho
It is crucial to distinguish between gully erosion responses derived from the inherent fragility of the environment and those induced by human activities. This study examines gully sidewall erosion in relation to soil physical variables and land use, with particular attention to livestock farming. Sidewall data were collected and analysed during both wet and dry seasons, including grain size, soil resistance to penetration, and infiltration. Land use data were also compiled before and after the implementation of a restoration technique. These data were compared with three years of erosion monitoring on the gully sidewall. The results indicate that tropical environments with two well-defined seasons (summer and winter) also require careful consideration of transitional periods (spring and fall), as soil drying and crack formation increase erosion risk. Sandy fractions demonstrate high susceptibility to erosion; however, the role of finer fractions, especially silt, is equally critical, since their presence, together with higher soil penetration resistance during dry periods, indicates areas with high erosive potential. Infiltration measured under field conditions shows high variability, which complicates the assessment of its contribution to gully development. The adoption of simple measures, such as fencing off eroded areas, proved effective in reducing soil loss from gullies in pastures under livestock farming. Overall, the findings underline that the combined effect of environmental fragility and grazing pressure constitutes a major driver of gully erosion in tropical regions. Recognising these interactions is fundamental for designing appropriate soil conservation strategies in livestock-dominated landscapes.
{"title":"Natural susceptibility and human intervention in gullies sidewalls in tropical environments of southeastern Brazil","authors":"Estêvão Botura Stefanuto , Cenira Maria Lupinacci , Higor Lourenzoni Bonzanini , Danilo Marques de Magalhães , Filipe Carvalho , Estela Nadal-Romero , Melina Fushimi , Fabiano Tomazini da Conceição , Archimedes Perez Filho","doi":"10.1016/j.catena.2025.109783","DOIUrl":"10.1016/j.catena.2025.109783","url":null,"abstract":"<div><div>It is crucial to distinguish between gully erosion responses derived from the inherent fragility of the environment and those induced by human activities. This study examines gully sidewall erosion in relation to soil physical variables and land use, with particular attention to livestock farming. Sidewall data were collected and analysed during both wet and dry seasons, including grain size, soil resistance to penetration, and infiltration. Land use data were also compiled before and after the implementation of a restoration technique. These data were compared with three years of erosion monitoring on the gully sidewall. The results indicate that tropical environments with two well-defined seasons (summer and winter) also require careful consideration of transitional periods (spring and fall), as soil drying and crack formation increase erosion risk. Sandy fractions demonstrate high susceptibility to erosion; however, the role of finer fractions, especially silt, is equally critical, since their presence, together with higher soil penetration resistance during dry periods, indicates areas with high erosive potential. Infiltration measured under field conditions shows high variability, which complicates the assessment of its contribution to gully development. The adoption of simple measures, such as fencing off eroded areas, proved effective in reducing soil loss from gullies in pastures under livestock farming. Overall, the findings underline that the combined effect of environmental fragility and grazing pressure constitutes a major driver of gully erosion in tropical regions. Recognising these interactions is fundamental for designing appropriate soil conservation strategies in livestock-dominated landscapes.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"264 ","pages":"Article 109783"},"PeriodicalIF":5.7,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145973833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-10DOI: 10.1016/j.catena.2026.109793
Tom Avikasis Cohen , Gabriel Cotlier , Ioannis Daliakopoulos , Pandi Zdruli , Shahar Baram , Anna Brook
Topsoil organic matter content (OMC), particularly within the upper 30 cm, is critical for soil fertility, ecosystem functioning, and resilience. In Mediterranean environments, OMC is highly vulnerable to soil water erosion (SWE), a process intensified by increasingly frequent and intense rainfall. While SWE research has largely focused on mineral soil loss, its effects on OMC, especially the balance between depletion in source areas and accumulation in depositional zones, remain poorly quantified at regional scales. This study applies advanced analytical approaches, including multilevel meta-analytic models, to examine the spatial dynamics of OMC redistribution under SWE and to evaluate how scale and methodology influence reported outcomes. A meta-analysis was conducted using data from 71 studies across Mediterranean landscapes. Due to the limited availability of land-use-specific studies, the analysis adopts a broad regional perspective rather than stratification by management type. Results reveal extremely high heterogeneity, driven primarily by methodological differences, spatial scale, and timing. Mean effects varied by study type: field experiments showed a weakly negative association between SWE and OMC (β = −0.0421, k = 68), rainfall-based studies showed a positive relationship (β = 0.7209, k = 66), and simulation studies indicated a mild positive trend (β = 0.0835, k = 14), all with high heterogeneity (I2 > 90 %). Overall, the findings demonstrate that SWE does not uniformly result in OMC loss but often reflects spatial translocation. These results highlight the need for improved methodological consistency and ecologically grounded frameworks to interpret OMC dynamics in Mediterranean erosion-prone landscapes.
表层土壤有机质含量（OMC）对土壤肥力、生态系统功能和恢复力至关重要。在地中海环境中，OMC极易受到水土流失（SWE）的影响，而日益频繁和强烈的降雨加剧了这一过程。虽然SWE研究主要集中在矿质土壤流失上，但其对OMC的影响，特别是对源区耗损与沉积带积累之间平衡的影响，在区域尺度上仍然缺乏量化。本研究采用先进的分析方法，包括多层次元分析模型，来研究SWE下OMC再分配的空间动态，并评估规模和方法如何影响报告的结果。对地中海地区71项研究的数据进行了荟萃分析。由于具体土地用途的研究有限，分析采用了广泛的区域观点，而不是按管理类型分层。结果显示了极高的异质性，主要是由方法差异、空间尺度和时间驱动的。平均效应因研究类型而异：田间试验显示SWE与OMC呈弱负相关（β = - 0.0421, k = 68），基于降雨量的研究显示正相关（β = 0.7209, k = 66），模拟研究显示轻度正相关（β = 0.0835, k = 14），均具有高度异质性（I2 > 90%）。总的来说，研究结果表明SWE并不是均匀地导致OMC损失，而是经常反映空间易位。这些结果强调需要改进方法一致性和生态基础框架来解释地中海易侵蚀景观中的OMC动态。
{"title":"Methodological advancements in soil erosion: a meta-analysis of organic matter content and erosion in the Mediterranean region","authors":"Tom Avikasis Cohen , Gabriel Cotlier , Ioannis Daliakopoulos , Pandi Zdruli , Shahar Baram , Anna Brook","doi":"10.1016/j.catena.2026.109793","DOIUrl":"10.1016/j.catena.2026.109793","url":null,"abstract":"<div><div>Topsoil organic matter content (OMC), particularly within the upper 30 cm, is critical for soil fertility, ecosystem functioning, and resilience. In Mediterranean environments, OMC is highly vulnerable to soil water erosion (SWE), a process intensified by increasingly frequent and intense rainfall. While SWE research has largely focused on mineral soil loss, its effects on OMC, especially the balance between depletion in source areas and accumulation in depositional zones, remain poorly quantified at regional scales. This study applies advanced analytical approaches, including multilevel meta-analytic models, to examine the spatial dynamics of OMC redistribution under SWE and to evaluate how scale and methodology influence reported outcomes. A meta-analysis was conducted using data from 71 studies across Mediterranean landscapes. Due to the limited availability of land-use-specific studies, the analysis adopts a broad regional perspective rather than stratification by management type. Results reveal extremely high heterogeneity, driven primarily by methodological differences, spatial scale, and timing. Mean effects varied by study type: field experiments showed a weakly negative association between SWE and OMC (β = −0.0421, k = 68), rainfall-based studies showed a positive relationship (β = 0.7209, k = 66), and simulation studies indicated a mild positive trend (β = 0.0835, k = 14), all with high heterogeneity (I<sup>2</sup> > 90 %). Overall, the findings demonstrate that SWE does not uniformly result in OMC loss but often reflects spatial translocation. These results highlight the need for improved methodological consistency and ecologically grounded frameworks to interpret OMC dynamics in Mediterranean erosion-prone landscapes.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"264 ","pages":"Article 109793"},"PeriodicalIF":5.7,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145973832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-10DOI: 10.1016/j.catena.2026.109818
Xinmeng You , Xiaodong Yang , Lu Gong , Yihu Niu , Xue Wu , Xiaochen Li , Qian Guo
In desert dune ecosystems, climate change-and human disturbance-induced ecological processes have exacerbated the expansion risk of mobile dunes, substantially impairing soil functions maintenance and performance. As key biological functional groups in the dune ecosystem, ephemeral plants and soil microorganisms play crucial roles in regulating soil multifunctionality (SMF). However, the ecological mechanisms underlying this regulation remain unclear. To address this gap, we conducted a study on typical mobile dunes at the southern margin of the Gurbantunggut Desert. We established plots across four dune slope orientations to investigate the structure and diversity of ephemeral plant communities, employed high-throughput sequencing to analyze soil microbial community composition, and comprehensively evaluated SMF and its driving mechanisms. Results showed that SMF was significantly higher at the dune bottom than on the middle positions. Biodiversity and single functional indicators varied among different slope orientations. Piecewise structural equation modeling (SEM) analysis revealed that microbial diversity (bacterial ACE and fungal ACE) exerted a direct and significant positive effect on SMF. In contrast, plant diversity (Shannon and MNTD) imposed significant negative impacts through the dominant-species effect and their interactions with microorganisms. Our findings indicated that slope orientation, as a key environmental filtering factor, regulated soil physicochemical factors such as soil moisture, electrical conductivity, and pH. This regulation indirectly affected the structure and interaction of plant and microbial communities, which in turn modulated SMF. Collectively, slope orientation-driven environmental heterogeneity, microbial functional complementarity, and the dominant-species effect govern the spatial differentiation of SMF in arid desert dune ecosystems.
{"title":"Slope orientation regulates the joint influence of ephemeral plants and microorganisms on the soil multifunctionality of the mobile sand dunes","authors":"Xinmeng You , Xiaodong Yang , Lu Gong , Yihu Niu , Xue Wu , Xiaochen Li , Qian Guo","doi":"10.1016/j.catena.2026.109818","DOIUrl":"10.1016/j.catena.2026.109818","url":null,"abstract":"<div><div>In desert dune ecosystems, climate change-and human disturbance-induced ecological processes have exacerbated the expansion risk of mobile dunes, substantially impairing soil functions maintenance and performance. As key biological functional groups in the dune ecosystem, ephemeral plants and soil microorganisms play crucial roles in regulating soil multifunctionality (SMF). However, the ecological mechanisms underlying this regulation remain unclear. To address this gap, we conducted a study on typical mobile dunes at the southern margin of the Gurbantunggut Desert. We established plots across four dune slope orientations to investigate the structure and diversity of ephemeral plant communities, employed high-throughput sequencing to analyze soil microbial community composition, and comprehensively evaluated SMF and its driving mechanisms. Results showed that SMF was significantly higher at the dune bottom than on the middle positions. Biodiversity and single functional indicators varied among different slope orientations. Piecewise structural equation modeling (SEM) analysis revealed that microbial diversity (bacterial ACE and fungal ACE) exerted a direct and significant positive effect on SMF. In contrast, plant diversity (Shannon and MNTD) imposed significant negative impacts through the dominant-species effect and their interactions with microorganisms. Our findings indicated that slope orientation, as a key environmental filtering factor, regulated soil physicochemical factors such as soil moisture, electrical conductivity, and pH. This regulation indirectly affected the structure and interaction of plant and microbial communities, which in turn modulated SMF. Collectively, slope orientation-driven environmental heterogeneity, microbial functional complementarity, and the dominant-species effect govern the spatial differentiation of SMF in arid desert dune ecosystems.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"264 ","pages":"Article 109818"},"PeriodicalIF":5.7,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145974283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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