Pub Date : 2025-07-28DOI: 10.1016/j.iswcr.2025.07.012
Elise Van Eynde, Arthur Nicolaus Fendrich, Felipe Yunta, Arwyn Jones, Panos Panagos
The European Union (EU) is one of the largest cereal producers in the world, with wheat covering around one-third of its agricultural area. Sustainable soil management has been put as a key point of EU Green Deal policies, with concrete measures to reduce fertilizer application by 2030. However, uncertainty still exists about the expected impact of such a reduction on wheat yield across the EU. In this work, we construct a regression model to evaluate the possible impacts of fertilizer reduction and climate change on wheat yields by 2050. The regression model quantifies the effects of soil properties, soil management, and climate on wheat yields at the EU scale. In addition, we simulate two scenarios, one based on the EU fertilizer targets only and the other focusing on climate change impact (+4 °C). The results show an important effect of soil phosphorus, nitrogen, and potassium content, soil carbon-to-nitrogen ratio, and nitrogen inputs on the variation in wheat yields across the EU, next to climate. The scenario analysis suggests that reducing N and P inputs by 20 % leads to wheat yield losses of up to 5 %, an effect that can rise to 50 % yield reduction by 2050 under climate change. Fertilizer reduction leads to most significant yield decreases in France, Germany and Northern Italy, while climate change reduces yields mostly in Southern Europe. Beyond highlighting relevant regional patterns, our results show how EU fertilizer reduction targets are expected to have a small impact on wheat production compared to climate change.
{"title":"A data-driven impact evaluation of nutrient input reduction on wheat yields across Europe","authors":"Elise Van Eynde, Arthur Nicolaus Fendrich, Felipe Yunta, Arwyn Jones, Panos Panagos","doi":"10.1016/j.iswcr.2025.07.012","DOIUrl":"10.1016/j.iswcr.2025.07.012","url":null,"abstract":"<div><div>The European Union (EU) is one of the largest cereal producers in the world, with wheat covering around one-third of its agricultural area. Sustainable soil management has been put as a key point of EU Green Deal policies, with concrete measures to reduce fertilizer application by 2030. However, uncertainty still exists about the expected impact of such a reduction on wheat yield across the EU. In this work, we construct a regression model to evaluate the possible impacts of fertilizer reduction and climate change on wheat yields by 2050. The regression model quantifies the effects of soil properties, soil management, and climate on wheat yields at the EU scale. In addition, we simulate two scenarios, one based on the EU fertilizer targets only and the other focusing on climate change impact (+4 °C). The results show an important effect of soil phosphorus, nitrogen, and potassium content, soil carbon-to-nitrogen ratio, and nitrogen inputs on the variation in wheat yields across the EU, next to climate. The scenario analysis suggests that reducing N and P inputs by 20 % leads to wheat yield losses of up to 5 %, an effect that can rise to 50 % yield reduction by 2050 under climate change. Fertilizer reduction leads to most significant yield decreases in France, Germany and Northern Italy, while climate change reduces yields mostly in Southern Europe. Beyond highlighting relevant regional patterns, our results show how EU fertilizer reduction targets are expected to have a small impact on wheat production compared to climate change.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 733-743"},"PeriodicalIF":7.3,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183845","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 : 2025-07-25DOI: 10.1016/j.iswcr.2025.07.011
Yonghui Yang , Hao Liu , Yunhong Zhang , Cuimin Gao , Weifeng Han , Xiaoying Pan , Fang He , Darrell W.S. Tang
Subsoil tillage (S) improves the stability and quality of soil organic carbon (SOC) and soil structure. Combining straw mulching with subsoil tillage (SS) may further improve soil physical and biogeochemical properties, whilst enabling abundant straw resources to be productively and sustainably recycled. To address knowledge gaps regarding these treatments’ effects under long-term application and at deeper soil layers, we conducted a 14-year field experiment and analyzed changes to SOC, soil aggregate characteristics, SOC associated with various soil aggregate sizes, and soil structural stability indicators at high spatial resolution down to 1 m depth. Results indicate that SS increased the proportion of 0.5–2.0 mm soil aggregates throughout much of the soil profile, but decreased the proportion of smaller <0.25 mm aggregates at 0–20 cm depth. SS increased the total organic carbon (TOC) at 0–20 cm, TOC and labile organic carbon (LOC) content of various aggregate sizes at various depths, the relative contribution of 0.5–2.0 mm aggregates to TOC at 0–40 cm, and multiple soil structure stability indices at 0–20 cm. Although both S and SS improved soil properties, the spatial and quantitative extents of the improvements are greater under SS. Correlation analyses indicate that improvements in SOC, soil stability, and aggregate properties are positively correlated, implying minimal trade-offs in prioritizing SS over S. These findings highlight long-term synergistic interactions: subsoiling mixes decomposed straw mulch applied in previous years into deeper soil, reinforcing the interdependent processes of aggregate formation and stabilization, along with SOC generation and protection, across more extensive soil depths.
{"title":"Subsoil tillage and straw mulching are synergistic for long-term improvement of soil carbon and structural characteristics","authors":"Yonghui Yang , Hao Liu , Yunhong Zhang , Cuimin Gao , Weifeng Han , Xiaoying Pan , Fang He , Darrell W.S. Tang","doi":"10.1016/j.iswcr.2025.07.011","DOIUrl":"10.1016/j.iswcr.2025.07.011","url":null,"abstract":"<div><div>Subsoil tillage (S) improves the stability and quality of soil organic carbon (SOC) and soil structure. Combining straw mulching with subsoil tillage (SS) may further improve soil physical and biogeochemical properties, whilst enabling abundant straw resources to be productively and sustainably recycled. To address knowledge gaps regarding these treatments’ effects under long-term application and at deeper soil layers, we conducted a 14-year field experiment and analyzed changes to SOC, soil aggregate characteristics, SOC associated with various soil aggregate sizes, and soil structural stability indicators at high spatial resolution down to 1 m depth. Results indicate that SS increased the proportion of 0.5–2.0 mm soil aggregates throughout much of the soil profile, but decreased the proportion of smaller <0.25 mm aggregates at 0–20 cm depth. SS increased the total organic carbon (TOC) at 0–20 cm, TOC and labile organic carbon (LOC) content of various aggregate sizes at various depths, the relative contribution of 0.5–2.0 mm aggregates to TOC at 0–40 cm, and multiple soil structure stability indices at 0–20 cm. Although both S and SS improved soil properties, the spatial and quantitative extents of the improvements are greater under SS. Correlation analyses indicate that improvements in SOC, soil stability, and aggregate properties are positively correlated, implying minimal trade-offs in prioritizing SS over S. These findings highlight long-term synergistic interactions: subsoiling mixes decomposed straw mulch applied in previous years into deeper soil, reinforcing the interdependent processes of aggregate formation and stabilization, along with SOC generation and protection, across more extensive soil depths.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 1008-1018"},"PeriodicalIF":7.3,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183925","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 : 2025-07-23DOI: 10.1016/j.iswcr.2025.07.008
Xiaolan Wang , Sixiao Li , Xiuguang Bai , José A. Gómez , Tianjun Liu , Jundi Liu
Soil remediation practices by farmers are crucial for improving soil quality and ensuring stable agricultural production. To analyze the factors influencing these practices, we surveyed 403 farmers in the Loess Plateau of Shaanxi and Shanxi, China. Using an ordered Probit model and moderation effect analysis, we investigated the direct effects of government regulations—specifically subsidies and technical training and the moderating role of farmers' ecological cognition on technology adoption. Our findings indicate: (1) Farmers generally accept and implement soil remediation technologies, with deep plowing being the most prevalent; (2) Government regulations, particularly subsidies and training, significantly enhance farmers' soil restoration efforts; (3) Farmers' green ecological cognition positively influences their restoration practices and moderates the impact of government regulation; (4) The influence of government regulation and cognition varies among farmers types, with subsidies being more crucial for smallholder, while training benefits larger operations more. These insights offer a new perspective for refining soil remediation policies and examining the global applicability of government regulation and farmers' cognition.
{"title":"Effect of government regulation on promotion of soil restoration practices among farmers in the Loess plateau: Unveiling the role of green ecological cognition","authors":"Xiaolan Wang , Sixiao Li , Xiuguang Bai , José A. Gómez , Tianjun Liu , Jundi Liu","doi":"10.1016/j.iswcr.2025.07.008","DOIUrl":"10.1016/j.iswcr.2025.07.008","url":null,"abstract":"<div><div>Soil remediation practices by farmers are crucial for improving soil quality and ensuring stable agricultural production. To analyze the factors influencing these practices, we surveyed 403 farmers in the Loess Plateau of Shaanxi and Shanxi, China. Using an ordered Probit model and moderation effect analysis, we investigated the direct effects of government regulations—specifically subsidies and technical training and the moderating role of farmers' ecological cognition on technology adoption. Our findings indicate: (1) Farmers generally accept and implement soil remediation technologies, with deep plowing being the most prevalent; (2) Government regulations, particularly subsidies and training, significantly enhance farmers' soil restoration efforts; (3) Farmers' green ecological cognition positively influences their restoration practices and moderates the impact of government regulation; (4) The influence of government regulation and cognition varies among farmers types, with subsidies being more crucial for smallholder, while training benefits larger operations more. These insights offer a new perspective for refining soil remediation policies and examining the global applicability of government regulation and farmers' cognition.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 979-991"},"PeriodicalIF":7.3,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183923","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 : 2025-07-21DOI: 10.1016/j.iswcr.2025.07.010
Peter M. Kopittke , Stephen M. Harper , Luz G. Asio , Victor B. Asio , Juanito T. Batalon , April Mae T. Batuigas , Apolinario B. Gonzaga Jr. , Nelda R. Gonzaga , Maria Teresa L. de Guzman , Deejay M. Lumanao , Brigid A. McKenna , Gennie B. Soyon , Joana Rose M. Vergara , Pearl B. Sanchez
Soil plays a critical role in seven existential challenges that threaten sustainable development of human society. However, despite this integrative role, humans generally focus on the use of soil to produce the 98.8 % of calories that the growing human population demands while failing to appreciate the less tangible role of soil in other existential challenges such as climate change abatement. Our current agricultural management approaches are causing ongoing soil degradation, manifested as the loss of soil organic matter, acidification, over-application of fertilizers, erosion, salinization, contamination, and biodiversity loss. However, to develop workable, sustainable, and equitable solutions, these proximate causes of degradation need to be considered in combination with the socio-economic factors that are the underlying drivers of this soil degradation, including the economic drivers, land pressure, poverty, security of land tenure, the differences between on-site and off-site impacts of degradation, and the impact of policies. Consideration must also be given to the importance of both intergenerational and developmental equity, whereby the current generation considers future generations, and where developed countries consider those that are still developing. Through this approach, we present a novel, integrated framework for soil degradation that bridges biophysical and socio-economic dimensions of soil degradation, with this providing an approach for advancing global soil security as required to maintain planetary hospitability, both now and into the future.
{"title":"Soil degradation: An integrated model of the causes and drivers","authors":"Peter M. Kopittke , Stephen M. Harper , Luz G. Asio , Victor B. Asio , Juanito T. Batalon , April Mae T. Batuigas , Apolinario B. Gonzaga Jr. , Nelda R. Gonzaga , Maria Teresa L. de Guzman , Deejay M. Lumanao , Brigid A. McKenna , Gennie B. Soyon , Joana Rose M. Vergara , Pearl B. Sanchez","doi":"10.1016/j.iswcr.2025.07.010","DOIUrl":"10.1016/j.iswcr.2025.07.010","url":null,"abstract":"<div><div>Soil plays a critical role in seven existential challenges that threaten sustainable development of human society. However, despite this integrative role, humans generally focus on the use of soil to produce the 98.8 % of calories that the growing human population demands while failing to appreciate the less tangible role of soil in other existential challenges such as climate change abatement. Our current agricultural management approaches are causing ongoing soil degradation, manifested as the loss of soil organic matter, acidification, over-application of fertilizers, erosion, salinization, contamination, and biodiversity loss. However, to develop workable, sustainable, and equitable solutions, these proximate causes of degradation need to be considered in combination with the socio-economic factors that are the underlying drivers of this soil degradation, including the economic drivers, land pressure, poverty, security of land tenure, the differences between on-site and off-site impacts of degradation, and the impact of policies. Consideration must also be given to the importance of both intergenerational and developmental equity, whereby the current generation considers future generations, and where developed countries consider those that are still developing. Through this approach, we present a novel, integrated framework for soil degradation that bridges biophysical and socio-economic dimensions of soil degradation, with this providing an approach for advancing global soil security as required to maintain planetary hospitability, both now and into the future.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 744-755"},"PeriodicalIF":7.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183847","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}
Projections of global population growth underscore the urgent need to restore degraded saline-sodic soils to meet rising demands for food, feed, and fiber. This study evaluated the individual and combined effects of gypsum (G), elemental sulfur (S), vermicompost (VC), biochar (B), and microbial inoculation on soil remediation. A comprehensive soil degradation index (CSDI) was developed with total (CSDI-T) and minimum datasets (CSDI-M) using 13 soil properties. All treatments significantly improved soil health (p < 0.05), with G + VC and S + VC combinations reducing CSDI-T by 84–85 % and 65–71 % and CSDI-M by 84–87 % and 66–70 %, respectively. Soil remediation rates correlated directly with crop yield, with CSDI models explaining 29–87 % of the variance in wheat yield. These findings highlight G/S + VC treatments as cost-effective, environmentally sustainable solutions for soil restoration and productivity enhancement, with CSDI models offering robust tools for evaluating amendment strategies.
{"title":"Integrated organochemical – Microbial solutions remediate degraded saline-sodic soils","authors":"Salar Rezapour , Amin Nouri , Farrokh Asadzadeh , Ruijun Qin , Günay Erpul","doi":"10.1016/j.iswcr.2025.07.009","DOIUrl":"10.1016/j.iswcr.2025.07.009","url":null,"abstract":"<div><div>Projections of global population growth underscore the urgent need to restore degraded saline-sodic soils to meet rising demands for food, feed, and fiber. This study evaluated the individual and combined effects of gypsum (G), elemental sulfur (S), vermicompost (VC), biochar (B), and microbial inoculation on soil remediation. A comprehensive soil degradation index (CSDI) was developed with total (CSDI-T) and minimum datasets (CSDI-M) using 13 soil properties. All treatments significantly improved soil health (<em>p</em> < 0.05), with G + VC and S + VC combinations reducing CSDI-T by 84–85 % and 65–71 % and CSDI-M by 84–87 % and 66–70 %, respectively. Soil remediation rates correlated directly with crop yield, with CSDI models explaining 29–87 % of the variance in wheat yield. These findings highlight G/S + VC treatments as cost-effective, environmentally sustainable solutions for soil restoration and productivity enhancement, with CSDI models offering robust tools for evaluating amendment strategies.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 992-1007"},"PeriodicalIF":7.3,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183924","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 : 2025-07-16DOI: 10.1016/j.iswcr.2025.07.006
Runze Yang , Tianjiao Feng , Bin Wang , Wenzhao Guo , Fenzhong Wang , Zuoxiao Wang , Xiaoyu Liang , Zekun Zhao , Shilei Wang , Saskia Keesstra , Artemi Cerdà
Soil erosion and non-point source pollution are critical global environmental issues, with profound implications for ecosystems, agricultural productivity, and water quality. These problems are especially exacerbated in regions subjected to intense rainfall, where their impacts can be particularly severe. In China, the suburban areas of Beijing have experienced considerable challenges associated with both soil erosion and non-point source pollution. Under different rainfall types, the impact mechanisms of rainfall, vegetation, and land preparation on soil erosion and non-point source pollution are highly complex and have not yet been fully understood. This study is based on soil erosion (runoff, sediment yield) and non-point source pollution (TN, Total nitrogen; TP, Total phosphorus; COD, Chemical Oxygen Demand) data from 130 erosive rainfall events (Classified as light, moderate, heavy and extreme rainfall based on 24-h precipitation) across 16 runoff plots from 2010 to 2023. The runoff plots consist of different vegetation and land preparation measures. The characteristics of soil erosion and non-point source pollution under four different rainfall types and different soil conservation measures were compared. Additionally, the impacts of rainfall, vegetation, and land preparation on soil erosion and non-point source pollution under different rainfall types were explored. The results indicate that the frequency of extreme rainfall events accounts for only 16.9 % of erosive rainfall, yet the runoff, sediment yield, TN, TP, and COD they generate account for 40.7 %, 35.0 %, 37.9 %, 33.4 %, and 41.9 % of the total, respectively. Vegetation and land preparation measures have a significant effect on reducing runoff, sediment yield, TN, TP, and COD. The primary factor influencing runoff, TN, TP, and COD was maximum 30-min rainfall intensity (I30), with correlation coefficients of 0.33, 0.20, 0.30, and 0.28, respectively (p < 0.01). As rainfall intensity increases, the contribution of vegetation to soil erosion and non-point source pollution increases from 0.7 % under light rainfall to 41.1 % under extreme rainfall. The combined effect of vegetation and land preparation increases from 1.7 % to 14.4 % under extreme rainfall. Under the same rainfall conditions, the contribution of vegetation and land preparation to soil erosion is significantly higher than that to non-point source pollution. The study identifies the mechanisms by which rainfall, vegetation, and land preparation influence soil erosion and non-point source pollution under varying rainfall conditions. These findings offer valuable insights for soil conservation and non-point source pollution management, particularly in areas experiencing extreme rainfall events.
{"title":"Response of soil erosion and non-point source pollution to different rainfall, vegetation and land preparation measures in Miyun reservoir area during 2010–2023","authors":"Runze Yang , Tianjiao Feng , Bin Wang , Wenzhao Guo , Fenzhong Wang , Zuoxiao Wang , Xiaoyu Liang , Zekun Zhao , Shilei Wang , Saskia Keesstra , Artemi Cerdà","doi":"10.1016/j.iswcr.2025.07.006","DOIUrl":"10.1016/j.iswcr.2025.07.006","url":null,"abstract":"<div><div>Soil erosion and non-point source pollution are critical global environmental issues, with profound implications for ecosystems, agricultural productivity, and water quality. These problems are especially exacerbated in regions subjected to intense rainfall, where their impacts can be particularly severe. In China, the suburban areas of Beijing have experienced considerable challenges associated with both soil erosion and non-point source pollution. Under different rainfall types, the impact mechanisms of rainfall, vegetation, and land preparation on soil erosion and non-point source pollution are highly complex and have not yet been fully understood. This study is based on soil erosion (runoff, sediment yield) and non-point source pollution (TN, Total nitrogen; TP, Total phosphorus; COD, Chemical Oxygen Demand) data from 130 erosive rainfall events (Classified as light, moderate, heavy and extreme rainfall based on 24-h precipitation) across 16 runoff plots from 2010 to 2023. The runoff plots consist of different vegetation and land preparation measures. The characteristics of soil erosion and non-point source pollution under four different rainfall types and different soil conservation measures were compared. Additionally, the impacts of rainfall, vegetation, and land preparation on soil erosion and non-point source pollution under different rainfall types were explored. The results indicate that the frequency of extreme rainfall events accounts for only 16.9 % of erosive rainfall, yet the runoff, sediment yield, TN, TP, and COD they generate account for 40.7 %, 35.0 %, 37.9 %, 33.4 %, and 41.9 % of the total, respectively. Vegetation and land preparation measures have a significant effect on reducing runoff, sediment yield, TN, TP, and COD. The primary factor influencing runoff, TN, TP, and COD was maximum 30-min rainfall intensity (I<sub>30</sub>), with correlation coefficients of 0.33, 0.20, 0.30, and 0.28, respectively (<em>p</em> < 0.01). As rainfall intensity increases, the contribution of vegetation to soil erosion and non-point source pollution increases from 0.7 % under light rainfall to 41.1 % under extreme rainfall. The combined effect of vegetation and land preparation increases from 1.7 % to 14.4 % under extreme rainfall. Under the same rainfall conditions, the contribution of vegetation and land preparation to soil erosion is significantly higher than that to non-point source pollution. The study identifies the mechanisms by which rainfall, vegetation, and land preparation influence soil erosion and non-point source pollution under varying rainfall conditions. These findings offer valuable insights for soil conservation and non-point source pollution management, particularly in areas experiencing extreme rainfall events.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 892-908"},"PeriodicalIF":7.3,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183843","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 : 2025-07-09DOI: 10.1016/j.iswcr.2025.07.005
Qiang Tang , Fangxin Chen , Guangyu Zhu , Xiubin He , Jie Wei , Yusheng Zhang , Hari Ram Upadhayay , Adrian Joynes , Adrian L. Collins
Fingerprinting generates reliable sediment provenance information which supports devising policy or practical strategies for soil conservation and sediment management, but it remains challenging in areas with fragmented landscapes and diverse land use practices. This study evaluated the seasonality of biomarker signatures and their variability among particle size fractions, and apportioned target time-integrated suspended sediment to land use-based sources in an intensive agricultural watershed with mosaic land use patch configurations and crop-specific farming practices. Source materials (i.e., topsoil) from dry croplands, paddy fields and citrus orchards were sampled, and target time-integrated suspended sediment samples were collected at the watershed outlet. The content and compound-specific δ13C of long-chain saturated n-alkanes (C23-C33) were determined for two particle size fractions (i.e., <25 μm, 25–63 μm). The δ13C of monomeric n-alkanes displayed insignificant variabilities between particle size fractions and temporal variability across the sampling period. The MixSIAR Bayesian model was employed to quantify sediment source contributions. Due to land disturbance by tillage and crop plantation, our results revealed that paddy fields act as an important temporary secondary sediment source despite such fields conventionally being recognized as sediment sinks. Regardless, dry farmland remains the largest contributor to watershed sediment loss. A range of measures such as soil virginization, returning straw to fields, and pasture cultures in orchards are recommended for precision sediment management at watershed scale.
{"title":"Fingerprinting using compound-specific δ13C of n-alkanes reveals the temporary role of paddy fields as a secondary source for watershed sediment loss","authors":"Qiang Tang , Fangxin Chen , Guangyu Zhu , Xiubin He , Jie Wei , Yusheng Zhang , Hari Ram Upadhayay , Adrian Joynes , Adrian L. Collins","doi":"10.1016/j.iswcr.2025.07.005","DOIUrl":"10.1016/j.iswcr.2025.07.005","url":null,"abstract":"<div><div>Fingerprinting generates reliable sediment provenance information which supports devising policy or practical strategies for soil conservation and sediment management, but it remains challenging in areas with fragmented landscapes and diverse land use practices. This study evaluated the seasonality of biomarker signatures and their variability among particle size fractions, and apportioned target time-integrated suspended sediment to land use-based sources in an intensive agricultural watershed with mosaic land use patch configurations and crop-specific farming practices. Source materials (i.e., topsoil) from dry croplands, paddy fields and citrus orchards were sampled, and target time-integrated suspended sediment samples were collected at the watershed outlet. The content and compound-specific δ<sup>13</sup>C of long-chain saturated n-alkanes (C<sub>23</sub>-C<sub>33</sub>) were determined for two particle size fractions (i.e., <25 μm, 25–63 μm). The δ<sup>13</sup>C of monomeric n-alkanes displayed insignificant variabilities between particle size fractions and temporal variability across the sampling period. The MixSIAR Bayesian model was employed to quantify sediment source contributions. Due to land disturbance by tillage and crop plantation, our results revealed that paddy fields act as an important temporary secondary sediment source despite such fields conventionally being recognized as sediment sinks. Regardless, dry farmland remains the largest contributor to watershed sediment loss. A range of measures such as soil virginization, returning straw to fields, and pasture cultures in orchards are recommended for precision sediment management at watershed scale.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 795-807"},"PeriodicalIF":7.3,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183835","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 : 2025-07-09DOI: 10.1016/j.iswcr.2025.07.004
Rui Li , Linlv Xiao , Feiyang Cai , Jiayong Gao , Maolin He , Jun Jing
The Revised Universal Soil Loss Equation (RUSLE) is the most widely used soil erosion modeling method worldwide. The karst regions, influenced by geological conditions and human activities, feature extensive exposure of carbonate rocks on the surface, which presents challenges for the application of the RUSLE model in these areas. This study introduces the rocky desertification factor (D) to characterize the influence of exposed surface rock on soil loss. The relationship between rock exposure rate and soil erosion was incorporated into the RUSLE model to develop a RUSLE-D model. We compared the performance of the RUSLE and RUSLE-D models using long-term high-frequency hydrological signals from two typical karst catchments to validate the applicability of the RUSLE-D model in karst areas. The results indicated that under natural rainfall conditions, soil erosion decreased as the rock exposure rate increased, showing a negative exponential relationship. The RUSLE-D model estimated the multi-year average soil erosion rates for the SBT and GC catchments to be 8.99 and 14.63 t ha−2·yr−1, respectively. The R2 values for the RUSLE and RUSLE-D models in the SBT catchment were 0.34 and 0.78, respectively, with NSE values of −0.03 and 0.55, and PBIAS values of −81.39 % and 13.87 %; for the GC catchment, the R2 values were 0.14 and 0.68, with NSE values of −13.82 and 0.43, and PBIAS values of −182.85 % and −24.27 %. The MCI indices for the SBT and GC catchments were 0.56 and 0.96, respectively. The RUSLE-D model significantly improved the accuracy of soil erosion simulation in typical karst watersheds. This study underscores the importance of incorporating the rocky desertification factor in soil erosion assessments within karst areas. The newly developed RUSLE-D model contributes to further developing the USLE/RUSLE series of models, enhancing their applicability in karst areas.
修正通用土壤流失方程（RUSLE）是目前国际上应用最广泛的土壤侵蚀模型方法。岩溶地区受地质条件和人类活动的影响，地表大量暴露碳酸盐岩，这给RUSLE模型在岩溶地区的应用带来了挑战。本文引入石漠化因子(D)来表征地表裸露岩石对土壤流失的影响。将岩石暴露率与土壤侵蚀的关系纳入RUSLE模型，建立RUSLE- d模型。利用两个典型喀斯特流域的长期高频水文信号，对比RUSLE和RUSLE- d模型的性能，验证RUSLE- d模型在喀斯特地区的适用性。结果表明：在自然降雨条件下，土壤侵蚀随岩石暴露率的增加而减小，呈负指数关系；RUSLE-D模型估计SBT和GC流域的多年平均土壤侵蚀速率分别为8.99和14.63 t ha - 2·yr - 1。SBT流域RUSLE和RUSLE- d模型的R2分别为0.34和0.78，NSE分别为- 0.03和0.55，PBIAS分别为- 81.39%和13.87%；GC流域的R2分别为0.14和0.68，NSE分别为- 13.82和0.43，PBIAS分别为- 182.85%和- 24.27%。SBT流域和GC流域的MCI指数分别为0.56和0.96。RUSLE-D模型显著提高了典型喀斯特流域土壤侵蚀模拟的精度。本研究强调了将石漠化因素纳入喀斯特地区土壤侵蚀评价的重要性。新建立的RUSLE- d模型有助于进一步发展USLE/RUSLE系列模型，增强其在喀斯特地区的适用性。
{"title":"Incorporating rocky desertification characteristic into soil erosion modeling in karst regions aligns better with regional conditions","authors":"Rui Li , Linlv Xiao , Feiyang Cai , Jiayong Gao , Maolin He , Jun Jing","doi":"10.1016/j.iswcr.2025.07.004","DOIUrl":"10.1016/j.iswcr.2025.07.004","url":null,"abstract":"<div><div>The Revised Universal Soil Loss Equation (RUSLE) is the most widely used soil erosion modeling method worldwide. The karst regions, influenced by geological conditions and human activities, feature extensive exposure of carbonate rocks on the surface, which presents challenges for the application of the RUSLE model in these areas. This study introduces the rocky desertification factor (D) to characterize the influence of exposed surface rock on soil loss. The relationship between rock exposure rate and soil erosion was incorporated into the RUSLE model to develop a RUSLE-D model. We compared the performance of the RUSLE and RUSLE-D models using long-term high-frequency hydrological signals from two typical karst catchments to validate the applicability of the RUSLE-D model in karst areas. The results indicated that under natural rainfall conditions, soil erosion decreased as the rock exposure rate increased, showing a negative exponential relationship. The RUSLE-D model estimated the multi-year average soil erosion rates for the SBT and GC catchments to be 8.99 and 14.63 t ha<sup>−2</sup>·yr<sup>−1</sup>, respectively. The <em>R</em><sup>2</sup> values for the RUSLE and RUSLE-D models in the SBT catchment were 0.34 and 0.78, respectively, with NSE values of −0.03 and 0.55, and PBIAS values of −81.39 % and 13.87 %; for the GC catchment, the <em>R</em><sup>2</sup> values were 0.14 and 0.68, with NSE values of −13.82 and 0.43, and PBIAS values of −182.85 % and −24.27 %. The MCI indices for the SBT and GC catchments were 0.56 and 0.96, respectively. The RUSLE-D model significantly improved the accuracy of soil erosion simulation in typical karst watersheds. This study underscores the importance of incorporating the rocky desertification factor in soil erosion assessments within karst areas. The newly developed RUSLE-D model contributes to further developing the USLE/RUSLE series of models, enhancing their applicability in karst areas.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 957-970"},"PeriodicalIF":7.3,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183921","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 : 2025-07-05DOI: 10.1016/j.iswcr.2025.07.002
Anilkumar Hunakunti, Alex B. McBratney, Budiman Minasny, Damien J. Field
Soil water erosion is a major threat to long-term soil sustainability. However, challenges remain in capturing how both natural and human-induced erosion processes interact over space and time to influence soil degradation. Current assessment methods often overlook how erosion simultaneously weakens the soil's inherent resistance (capacity) and degrades its current state (condition)-key drivers of long-term vulnerability and two core dimensions of soil security. To address this, we present a Capacity-Condition (CCF) framework, which quantifies erosion vulnerability using the erosion risk capability metric, which captures the gap between a soil's inherent resistance to erosion (capacity) and its erosion-altered state (condition). The framework employs the pedogeonon concept, identifying unique landscape units where the same soil-forming factors operate over time. Within each pedogeonon, two soil states are compared: genosoil (conditions influenced by natural erosion) and phenosoil (present state shaped by both natural and human-accelerated erosion). Capacity is assessed using genosoil indicators (clay ratio and topsoil thickness), and condition is evaluated using the phenosoil/genosoil ratio for the same indicators. Utility functions standardize these indicators on a 0–1 scale, enabling their aggregation into composite scores. When applied to New South Wales (NSW), Australia, the framework identified regions most vulnerable to erosion. Coastal areas and the upper northwest, characterized by intensive dry cropping and grazing on modified pastures, exhibited the highest risk values, indicating a lower capability to withstand future erosion. Conversely, regions with mixed land use-including grazing on native vegetation, intensive horticulture, and irrigated cropping-showed moderate risk, demonstrating the framework's utility for targeted, spatially explicit soil conservation and land management planning.
{"title":"Assessing soil erosion vulnerability using a novel capacity–condition framework (CCF): A case study from New South Wales, Australia","authors":"Anilkumar Hunakunti, Alex B. McBratney, Budiman Minasny, Damien J. Field","doi":"10.1016/j.iswcr.2025.07.002","DOIUrl":"10.1016/j.iswcr.2025.07.002","url":null,"abstract":"<div><div>Soil water erosion is a major threat to long-term soil sustainability. However, challenges remain in capturing how both natural and human-induced erosion processes interact over space and time to influence soil degradation. Current assessment methods often overlook how erosion simultaneously weakens the soil's inherent resistance (capacity) and degrades its current state (condition)-key drivers of long-term vulnerability and two core dimensions of soil security. To address this, we present a Capacity-Condition (CCF) framework, which quantifies erosion vulnerability using the erosion risk capability metric, which captures the gap between a soil's inherent resistance to erosion (capacity) and its erosion-altered state (condition). The framework employs the pedogeonon concept, identifying unique landscape units where the same soil-forming factors operate over time. Within each pedogeonon, two soil states are compared: genosoil (conditions influenced by natural erosion) and phenosoil (present state shaped by both natural and human-accelerated erosion). Capacity is assessed using genosoil indicators (clay ratio and topsoil thickness), and condition is evaluated using the phenosoil/genosoil ratio for the same indicators. Utility functions standardize these indicators on a 0–1 scale, enabling their aggregation into composite scores. When applied to New South Wales (NSW), Australia, the framework identified regions most vulnerable to erosion. Coastal areas and the upper northwest, characterized by intensive dry cropping and grazing on modified pastures, exhibited the highest risk values, indicating a lower capability to withstand future erosion. Conversely, regions with mixed land use-including grazing on native vegetation, intensive horticulture, and irrigated cropping-showed moderate risk, demonstrating the framework's utility for targeted, spatially explicit soil conservation and land management planning.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 771-794"},"PeriodicalIF":7.3,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183834","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 : 2025-07-04DOI: 10.1016/j.iswcr.2025.07.001
Haiyan Wei , Viktor Polyakov , David Goodrich , Morin Efrat , Phillip David Guertin , Shmuel Assouline , Phil Heilman , Carl Unkrich , Yuval Shmilovich , Francesco Marra
K2-RHEM, a recently integrated event-based rangeland watershed model, represents one of the few process-based models available for rangeland applications. However, to gain wider acceptance and demonstrate its reliability, comprehensive evaluation results are essential. In this study, K2-RHEM was evaluated in five small semi-arid watersheds within the USDA-ARS Walnut Gulch Experimental Watershed. Using extensive runoff and sediment data, along with field surveys on channel heads, soil textures, and channel cross-sections, the model showed strong performance in predicting hydrology metrics without calibration: NS ranged from 0.53 to 0.87 and KGE from 0.54 to 0.88 for runoff; NS from 0.59 to 0.85 and KGE from 0.69 to 0.90 for runoff peak; and NS from 0.98 to 0.99 and KGE from 0.94 to 0.98 for time to peak. Sediment yield predictions were particularly accurate in watersheds with significant channel incisions, with NS of 0.65 and KGE of 0.79. Good sediment yield calibration and validation results were achieved in three watersheds, and reasonable results achieved in the smallest watershed. Sediment yield and runoff peak were found to be sensitive to level of watershed discretization. Improved model performance was seen with additional rain gauges even in small watersheds. These findings demonstrate the potential of K2-RHEM as a reliable tool for the prediction of hydrology and erosion for small-scale rangeland watershed management and highlight the importance of both proper watershed discretization and rainfall data resolution in model applications.
{"title":"Modeling runoff and sediment yield at the event scale in semiarid watersheds","authors":"Haiyan Wei , Viktor Polyakov , David Goodrich , Morin Efrat , Phillip David Guertin , Shmuel Assouline , Phil Heilman , Carl Unkrich , Yuval Shmilovich , Francesco Marra","doi":"10.1016/j.iswcr.2025.07.001","DOIUrl":"10.1016/j.iswcr.2025.07.001","url":null,"abstract":"<div><div>K2-RHEM, a recently integrated event-based rangeland watershed model, represents one of the few process-based models available for rangeland applications. However, to gain wider acceptance and demonstrate its reliability, comprehensive evaluation results are essential. In this study, K2-RHEM was evaluated in five small semi-arid watersheds within the USDA-ARS Walnut Gulch Experimental Watershed. Using extensive runoff and sediment data, along with field surveys on channel heads, soil textures, and channel cross-sections, the model showed strong performance in predicting hydrology metrics without calibration: NS ranged from 0.53 to 0.87 and KGE from 0.54 to 0.88 for runoff; NS from 0.59 to 0.85 and KGE from 0.69 to 0.90 for runoff peak; and NS from 0.98 to 0.99 and KGE from 0.94 to 0.98 for time to peak. Sediment yield predictions were particularly accurate in watersheds with significant channel incisions, with NS of 0.65 and KGE of 0.79. Good sediment yield calibration and validation results were achieved in three watersheds, and reasonable results achieved in the smallest watershed. Sediment yield and runoff peak were found to be sensitive to level of watershed discretization. Improved model performance was seen with additional rain gauges even in small watersheds. These findings demonstrate the potential of K2-RHEM as a reliable tool for the prediction of hydrology and erosion for small-scale rangeland watershed management and highlight the importance of both proper watershed discretization and rainfall data resolution in model applications.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 860-875"},"PeriodicalIF":7.3,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183846","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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