Pub Date : 2025-09-01Epub Date: 2025-04-08DOI: 10.1016/j.iswcr.2025.03.007
Luping Ye , Rui Zhang , Xiaoyuan Lin , Kang Ji , Juan Zuo , Yong Zheng , Chuanqin Huang , Li Zhang , Wenfeng Tan
Soil inorganic carbon (SIC) is vital for terrestrial carbon reservoirs and the global carbon cycle. Understanding its spatial distribution is essential for environmental management and climate change mitigation. However, there remains a significant gap in predicting the spatial distribution of SIC content (SICC) and density (SICD), and our comprehension of the combined influences of natural factors and human activities on SIC is limited. This study in the Loess Plateau aimed to predict the spatial distribution of SIC content and density using data from 142 soil profiles and environmental covariates. We evaluated random forest (RF), support vector machine (SVM), and Cubist models for their predictive performance using metrics like coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). Landscape analysis revealed that land use significantly impacts both horizontal and vertical distributions of SICC and SICD, with leaching being a critical factor. Terrain attributes influenced these patterns by affecting sunlight exposure and hydrothermal conditions. Remote sensing technologies proved valuable for predictions. RF outperformed SVM and Cubist, yielding robust results for SICC (R2: 0.317–0.514, RMSE: 1.386–4.194 g/kg, and MAE: 1.045–2.940 g/kg) and SICD (R2: 0.282–0.490, RMSE: 0.220–1.069 kg m−2, and MAE: 0.174–0.772 kg m−2). RF was used to estimate total SIC stocks at 286.92 × 106 kg, with 49 % found in the 100–200 cm layer, underscoring the carbon sequestration potential of deeper soils. These insights are crucial for policymakers to understand SIC variability and inform sustainable land management strategies.
土壤无机碳（SIC）对陆地碳库和全球碳循环至关重要。了解其空间分布对环境管理和减缓气候变化至关重要。然而，在预测碳化硅含量（SICC）和密度（SICD）的空间分布方面仍存在较大差距，对自然因素和人类活动对碳化硅的综合影响认识有限。利用142个土壤剖面和环境协变量数据，对黄土高原土壤中碳化硅含量和密度的空间分布进行了预测。我们使用决定系数（R2）、均方根误差（RMSE）和平均绝对误差（MAE）等指标来评估随机森林（RF）、支持向量机（SVM）和立体主义模型的预测性能。景观分析结果表明，土地利用对土壤碳含量和土壤碳含量的水平和垂直分布均有显著影响，淋滤是影响土壤碳含量和土壤碳含量的关键因素。地形属性通过影响阳光照射和热液条件来影响这些模式。遥感技术证明对预测很有价值。RF优于SVM和Cubist，在SICC （R2: 0.317-0.514, RMSE: 1.384 - 4.194 g/kg, MAE: 1.045-2.940 g/kg）和SICD （R2: 0.282-0.490, RMSE: 0.220-1.069 kg m - 2, MAE: 0.174-0.772 kg m - 2）上产生了稳健的结果。利用RF估计，总碳化硅储量为286.92 × 106 kg，其中49%分布在100-200 cm土层，表明深层土壤具有固碳潜力。这些见解对于决策者理解SIC变异性并为可持续土地管理战略提供信息至关重要。
{"title":"Digital mapping of soil inorganic carbon content and density in soil profiles after ‘Grain for Green’ program","authors":"Luping Ye , Rui Zhang , Xiaoyuan Lin , Kang Ji , Juan Zuo , Yong Zheng , Chuanqin Huang , Li Zhang , Wenfeng Tan","doi":"10.1016/j.iswcr.2025.03.007","DOIUrl":"10.1016/j.iswcr.2025.03.007","url":null,"abstract":"<div><div>Soil inorganic carbon (SIC) is vital for terrestrial carbon reservoirs and the global carbon cycle. Understanding its spatial distribution is essential for environmental management and climate change mitigation. However, there remains a significant gap in predicting the spatial distribution of SIC content (SICC) and density (SICD), and our comprehension of the combined influences of natural factors and human activities on SIC is limited. This study in the Loess Plateau aimed to predict the spatial distribution of SIC content and density using data from 142 soil profiles and environmental covariates. We evaluated random forest (RF), support vector machine (SVM), and Cubist models for their predictive performance using metrics like coefficient of determination (R<sup>2</sup>), root mean square error (RMSE), and mean absolute error (MAE). Landscape analysis revealed that land use significantly impacts both horizontal and vertical distributions of SICC and SICD, with leaching being a critical factor. Terrain attributes influenced these patterns by affecting sunlight exposure and hydrothermal conditions. Remote sensing technologies proved valuable for predictions. RF outperformed SVM and Cubist, yielding robust results for SICC (R<sup>2</sup>: 0.317–0.514, RMSE: 1.386–4.194 g/kg, and MAE: 1.045–2.940 g/kg) and SICD (R<sup>2</sup>: 0.282–0.490, RMSE: 0.220–1.069 kg m<sup>−2</sup>, and MAE: 0.174–0.772 kg m<sup>−2</sup>). RF was used to estimate total SIC stocks at 286.92 × 10<sup>6</sup> kg, with 49 % found in the 100–200 cm layer, underscoring the carbon sequestration potential of deeper soils. These insights are crucial for policymakers to understand SIC variability and inform sustainable land management strategies.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 3","pages":"Pages 656-674"},"PeriodicalIF":7.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330085","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 : 2025-09-01Epub Date: 2025-03-04DOI: 10.1016/j.iswcr.2025.02.007
Zihan Qi , Yunqi Wang , Tong Li , Xiangjun Yan , Yue Lan , Xiaoming Zhang , Peng Li , Liqun Lyu
Soil macropores are key factors affecting slope hydrological processes and stability, particularly under heavy rainfall conditions. Although wildfires can lead to the decay and death of plant roots, leaving root channels, few studies have examined temporal variation in the distribution of soil macropores or their impact on slope stability. To address this, we examined the bacterial abundance, root distribution, and macropore characteristics of burnt forest at one week and 6 and 12 months post-fire. Numerical simulation was used to analyze the effects of macropore distribution on slope stability under extreme rainfall conditions (80 mm/d × 4 d) at each time-point. Soil macropores accelerated the propagation of water pressure, potentially triggering shallow-slope instability. In the simulation, following 1 d of rainfall, slope stability was lower, by 3.55% and 8.68%, respectively, at 6 and 12 months than at one week post-fire. Following 4 d of rainfall, slope stability was better at 6 and 12 months than at one week post-fire, by 1.87% and 2.81%, respectively, owing to the drainage effect of the macropores. Even more importantly, this study proposed a method for coupling the spatial heterogeneity of soil macropores with a numerical model of slope stability. These findings help to elucidate the temporal changes in vegetated slope hydrology and stability after a wildfire and provide a reference for the numerical simulation of the stability of heterogeneous slopes.
{"title":"Influence of post-fire root decay-induced soil macropores on slope stability: A new method for analyzing heterogeneous slope stability","authors":"Zihan Qi , Yunqi Wang , Tong Li , Xiangjun Yan , Yue Lan , Xiaoming Zhang , Peng Li , Liqun Lyu","doi":"10.1016/j.iswcr.2025.02.007","DOIUrl":"10.1016/j.iswcr.2025.02.007","url":null,"abstract":"<div><div>Soil macropores are key factors affecting slope hydrological processes and stability, particularly under heavy rainfall conditions. Although wildfires can lead to the decay and death of plant roots, leaving root channels, few studies have examined temporal variation in the distribution of soil macropores or their impact on slope stability. To address this, we examined the bacterial abundance, root distribution, and macropore characteristics of burnt forest at one week and 6 and 12 months post-fire. Numerical simulation was used to analyze the effects of macropore distribution on slope stability under extreme rainfall conditions (80 mm/d × 4 d) at each time-point. Soil macropores accelerated the propagation of water pressure, potentially triggering shallow-slope instability. In the simulation, following 1 d of rainfall, slope stability was lower, by 3.55% and 8.68%, respectively, at 6 and 12 months than at one week post-fire. Following 4 d of rainfall, slope stability was better at 6 and 12 months than at one week post-fire, by 1.87% and 2.81%, respectively, owing to the drainage effect of the macropores. Even more importantly, this study proposed a method for coupling the spatial heterogeneity of soil macropores with a numerical model of slope stability. These findings help to elucidate the temporal changes in vegetated slope hydrology and stability after a wildfire and provide a reference for the numerical simulation of the stability of heterogeneous slopes.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 3","pages":"Pages 702-715"},"PeriodicalIF":7.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330072","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 : 2025-09-01Epub Date: 2025-03-12DOI: 10.1016/j.iswcr.2025.03.001
Nicolas Francos , Eden Karasik , Matan Myers , Eyal Ben-Dor
Digital Soil Mapping (DSM) is an essential tool for understanding the complex relationship between soil and the environment. In this study, we digitized the soil map of Israel created by Ravikovitch in 1969 (that was based on a local classification system) and used Landsat 8 spectral data to predict soil classes across Israel using machine learning. We also made a similar analysis using a global USDA soil orders layer. This work is pioneering, and this is the first attempt to transfer the enormous and important work done by Ravikovitch to the digital level by combining this map with satellite observations of Landsat 8. Our study showed that the spectral-based predictions using Landsat 8 data in combination with the USDA soil orders data and machine learning techniques resulted in very accurate predictions of USDA soil orders in Israel (accuracy = 0.84) and in Cyprus (accuracy = 0.88). We also tested the transferability of the Israeli USDA soil orders model to Cyprus, a nearby country with a similar soil taxonomy, however, poor accuracies were obtained at this stage (accuracy = 0.13). The predictions on the digital map of Ravikovitch were intermediate (accuracy = 0.54) because so many classes were required to predict (24 classes). Our study highlights the importance of digitizing and updating existing soil maps, and demonstrates the potential of combining machine learning with satellite spectral data for accurate soil classification.
{"title":"Soil type classification using Landsat 8: A comparison between the USDA and a local system in Israel","authors":"Nicolas Francos , Eden Karasik , Matan Myers , Eyal Ben-Dor","doi":"10.1016/j.iswcr.2025.03.001","DOIUrl":"10.1016/j.iswcr.2025.03.001","url":null,"abstract":"<div><div>Digital Soil Mapping (DSM) is an essential tool for understanding the complex relationship between soil and the environment. In this study, we digitized the soil map of Israel created by Ravikovitch in 1969 (that was based on a local classification system) and used Landsat 8 spectral data to predict soil classes across Israel using machine learning. We also made a similar analysis using a global USDA soil orders layer. This work is pioneering, and this is the first attempt to transfer the enormous and important work done by Ravikovitch to the digital level by combining this map with satellite observations of Landsat 8. Our study showed that the spectral-based predictions using Landsat 8 data in combination with the USDA soil orders data and machine learning techniques resulted in very accurate predictions of USDA soil orders in Israel (accuracy = 0.84) and in Cyprus (accuracy = 0.88). We also tested the transferability of the Israeli USDA soil orders model to Cyprus, a nearby country with a similar soil taxonomy, however, poor accuracies were obtained at this stage (accuracy = 0.13). The predictions on the digital map of Ravikovitch were intermediate (accuracy = 0.54) because so many classes were required to predict (24 classes). Our study highlights the importance of digitizing and updating existing soil maps, and demonstrates the potential of combining machine learning with satellite spectral data for accurate soil classification.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 3","pages":"Pages 576-588"},"PeriodicalIF":7.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144329597","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 : 2025-09-01Epub Date: 2025-02-13DOI: 10.1016/j.iswcr.2025.02.003
Kai Wang , Gang Liu , Xiaokang Wang , Yingli Shen , Chengbo Shu , Qiong Zhang , Xiaolin Xia , Dandan Liu , Zhen Guo , Xining Zhao
A quantitative assessment of sediment sources is crucial for understanding soil erosion trends and enhancing soil erosion prevention and control measures. The environmental elements, such as vegetation, land use, and rainfall, etc., of the Chinese Loess Plateau (CLP) changed significantly after the implementation of “Grain for Green” (GFG) project. However, the response of sediment sources to the environmental changes in different periods remains unclear. In this study, sediment yields and sources were investigated by using the composite fingerprinting method. Forty flood couplets and their sediment yields corresponding to the 20-year period after the GFG project were established in Shagouba watershed, Shaanxi Province, China. Results showed that the thicker flood couplets, the higher percentage of silt and clay particles. Following the GFG project, the cumulative sediment yields during the first period (2000–2010) was 91,760 t, and in the second period (2011–2019) was 77,940 t. The sediment contributions changed from the first period that gully (48.73%) > shrub sandy land (28.82%) > sloping farmland (12.06%) > forestland and grassland (8.58%) > road (1.81%), to the second period that gully (47.33%) > shrub sandy land (26.40%) > forestland and grassland (10.27%) > road (9.02%) > sloping farmland (6.98%). The gully always contributes the most sediment, thus implementing measures such as safeguarding gully heads and constructing bio-valley mills in channels were recommended to mitigate gully erosion. This study provides a scientific basis for evaluating the effects of the GFG project on the CLP, and theoretical support for the scientific management of small watersheds.
{"title":"Dynamic change of watershed sediment sources during implementation of the “grain for green” project in the coarse sandy areas of the Chinese Loess Plateau","authors":"Kai Wang , Gang Liu , Xiaokang Wang , Yingli Shen , Chengbo Shu , Qiong Zhang , Xiaolin Xia , Dandan Liu , Zhen Guo , Xining Zhao","doi":"10.1016/j.iswcr.2025.02.003","DOIUrl":"10.1016/j.iswcr.2025.02.003","url":null,"abstract":"<div><div>A quantitative assessment of sediment sources is crucial for understanding soil erosion trends and enhancing soil erosion prevention and control measures. The environmental elements, such as vegetation, land use, and rainfall, etc., of the Chinese Loess Plateau (CLP) changed significantly after the implementation of “Grain for Green” (GFG) project. However, the response of sediment sources to the environmental changes in different periods remains unclear. In this study, sediment yields and sources were investigated by using the composite fingerprinting method. Forty flood couplets and their sediment yields corresponding to the 20-year period after the GFG project were established in Shagouba watershed, Shaanxi Province, China. Results showed that the thicker flood couplets, the higher percentage of silt and clay particles. Following the GFG project, the cumulative sediment yields during the first period (2000–2010) was 91,760 t, and in the second period (2011–2019) was 77,940 t. The sediment contributions changed from the first period that gully (48.73%) > shrub sandy land (28.82%) > sloping farmland (12.06%) > forestland and grassland (8.58%) > road (1.81%), to the second period that gully (47.33%) > shrub sandy land (26.40%) > forestland and grassland (10.27%) > road (9.02%) > sloping farmland (6.98%). The gully always contributes the most sediment, thus implementing measures such as safeguarding gully heads and constructing bio-valley mills in channels were recommended to mitigate gully erosion. This study provides a scientific basis for evaluating the effects of the GFG project on the <span>CLP</span>, and theoretical support for the scientific management of small watersheds.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 3","pages":"Pages 564-575"},"PeriodicalIF":7.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144329598","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 : 2025-09-01Epub Date: 2025-03-04DOI: 10.1016/j.iswcr.2025.02.012
Balázs Madarász , Éva Zsuzsanna Járási , Gergely Jakab , Zoltán Szalai , Márta Ladányi
There is considerable knowledge regarding the environmental benefits of conservation agriculture (CA). However, long-term profitability data are limited, despite their potential to drive CA adoption. This study analyses and compares the economic indicators of conservation reduced tillage (CT) widely practiced in Central Europe with those of conventional ploughing tillage (PT). This research investigated the costs and incomes under CT and assessed the impact of CT on crop yields and profitability over a 20-year period (2004–2023). The study covered 83 ha in 10 paired plots (from year 13 onwards, 76 ha in 9 paired plots), including extreme weather conditions and 6 crops. All annual data were adjusted to 2024 price levels to maintain consistency. Piecewise linear regression was applied to the data, revealing four distinct temporal phases. On the basis of profit, periods ‘Transitional’ (years 1–3), ‘Adapted 1’ (years 4–10), ‘Steady’ (years 11–17) and ‘Adapted 2’ (years 18–20) were separated. During the transitional period, profit under CT decreased by an average of 11.9% compared with PT, but subsequent periods indicated positive results. Therefore, the shift from year 7 onwards resulted in a profit increase. Over 20 years, material costs for CT plots were 1.9% higher and operating costs were 9.8% lower compared with PT. In addition, gross income increased by 2.3%, leading to a 13.0% higher profit on CT compared with PT plots, which could encourage wider adoption of CT by farmers.
{"title":"Economic comparison of conventional and conservation tillage in a long-term experiment: Is it worth shifting?","authors":"Balázs Madarász , Éva Zsuzsanna Járási , Gergely Jakab , Zoltán Szalai , Márta Ladányi","doi":"10.1016/j.iswcr.2025.02.012","DOIUrl":"10.1016/j.iswcr.2025.02.012","url":null,"abstract":"<div><div>There is considerable knowledge regarding the environmental benefits of conservation agriculture (CA). However, long-term profitability data are limited, despite their potential to drive CA adoption. This study analyses and compares the economic indicators of conservation reduced tillage (CT) widely practiced in Central Europe with those of conventional ploughing tillage (PT). This research investigated the costs and incomes under CT and assessed the impact of CT on crop yields and profitability over a 20-year period (2004–2023). The study covered 83 ha in 10 paired plots (from year 13 onwards, 76 ha in 9 paired plots), including extreme weather conditions and 6 crops. All annual data were adjusted to 2024 price levels to maintain consistency. Piecewise linear regression was applied to the data, revealing four distinct temporal phases. On the basis of profit, periods ‘Transitional’ (years 1–3), ‘Adapted 1’ (years 4–10), ‘Steady’ (years 11–17) and ‘Adapted 2’ (years 18–20) were separated. During the transitional period, profit under CT decreased by an average of 11.9% compared with PT, but subsequent periods indicated positive results. Therefore, the shift from year 7 onwards resulted in a profit increase. Over 20 years, material costs for CT plots were 1.9% higher and operating costs were 9.8% lower compared with PT. In addition, gross income increased by 2.3%, leading to a 13.0% higher profit on CT compared with PT plots, which could encourage wider adoption of CT by farmers.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 3","pages":"Pages 501-510"},"PeriodicalIF":7.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144329569","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 : 2025-09-01Epub Date: 2025-03-17DOI: 10.1016/j.iswcr.2025.03.003
Sinae Kim , Seung-Oh Hur , Jihye Kwak , Jihye Kim , Moon-Seong Kang
Soil erosion is a significant global problem that has far-reaching effects on agricultural productivity, environmental health, and ecosystem stability. The rainfall erosivity factor (R-factor) used in the Universal Soil Loss Equation (USLE) is a key parameter for predicting soil erosion. However, its accurate estimation is difficult owing to the complexities of high-resolution rainfall data and limitations of simplified models. This study addressed these challenges by introducing several key innovations. We developed a precise algorithm for calculating the R-factor using minute-interval rainfall data to effectively capture the necessary temporal resolution for assessing the impacts of extreme rainfall events. This advancement allows for accurate R-factor estimation, thereby overcoming the complexities associated with high-resolution data processing. In addition, we established a comprehensive rainfall erosivity database across South Korea based on 24 years of minute-interval rainfall data. We then derived an optimal regression model for estimating monthly rainfall erosivity from daily precipitation data, achieving high accuracy (R2 = 0.87) by effectively accounting for extreme rainfall events. These efforts culminated in the development of the Web-based Rainfall Erosivity Calculation (WREC) tool, which integrates a database, a rainfall erosivity calculation algorithm, and a simple estimation model. The user-friendly interface of the WREC tool offers a versatile platform for calculating rainfall erosivity, supporting practical applications, and assessing future climate change impacts. Expanding the WREC tool globally and adapting regression models to local contexts will enhance our ability to manage soil erosion and promote sustainable land and water management practices.
{"title":"Development of web-based decision support tool for rainfall erosivity estimation using both high-resolution rainfall data and simplified models","authors":"Sinae Kim , Seung-Oh Hur , Jihye Kwak , Jihye Kim , Moon-Seong Kang","doi":"10.1016/j.iswcr.2025.03.003","DOIUrl":"10.1016/j.iswcr.2025.03.003","url":null,"abstract":"<div><div>Soil erosion is a significant global problem that has far-reaching effects on agricultural productivity, environmental health, and ecosystem stability. The rainfall erosivity factor (R-factor) used in the Universal Soil Loss Equation (USLE) is a key parameter for predicting soil erosion. However, its accurate estimation is difficult owing to the complexities of high-resolution rainfall data and limitations of simplified models. This study addressed these challenges by introducing several key innovations. We developed a precise algorithm for calculating the R-factor using minute-interval rainfall data to effectively capture the necessary temporal resolution for assessing the impacts of extreme rainfall events. This advancement allows for accurate R-factor estimation, thereby overcoming the complexities associated with high-resolution data processing. In addition, we established a comprehensive rainfall erosivity database across South Korea based on 24 years of minute-interval rainfall data. We then derived an optimal regression model for estimating monthly rainfall erosivity from daily precipitation data, achieving high accuracy (R<sup>2</sup> = 0.87) by effectively accounting for extreme rainfall events. These efforts culminated in the development of the Web-based Rainfall Erosivity Calculation (WREC) tool, which integrates a database, a rainfall erosivity calculation algorithm, and a simple estimation model. The user-friendly interface of the WREC tool offers a versatile platform for calculating rainfall erosivity, supporting practical applications, and assessing future climate change impacts. Expanding the WREC tool globally and adapting regression models to local contexts will enhance our ability to manage soil erosion and promote sustainable land and water management practices.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 3","pages":"Pages 600-614"},"PeriodicalIF":7.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144329600","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 : 2025-09-01Epub Date: 2025-03-20DOI: 10.1016/j.iswcr.2025.03.004
Ziwei Zhang , Yaojun Liu , Yichun Ma , Gang Sun , Dengchun Wen , Siyuan Liu , Jian Duan , Xiaodong Nie , Zhongwu Li
The surface tillage layer structure of sloping farmland has a significant impact on rainfall-runoff distribution; however, the relationships between the Tillage Layer Depth (TLD) and surface-subsurface runoff, and the coupling effects of surface-subsurface runoff on soil erosion are still unclear. Thus, a set of laboratory experiments were conducted to reveal impacts of tillage layer depth (10, 20 and 30 cm) on surface-subsurface runoff relationships, eroded sediment processes, and soil erosion pattern evolution under the long-duration (180 min) rainfall simulation tests. A deeper TLD mitigated soil erosion. When the TLD increased from 10 to 30 cm, the average surface runoff decreased by 13 %, subsurface runoff increased by 5 %, and soil loss rate decreased by 19 g m−2 min−1. The interaction between surface runoff and subsurface runoff, influenced by the tillage layer depth, significantly impacts soil erosion. Both surface runoff and subsurface runoff promoted soil erosion at shallow tillage layer depths (10 and 20 cm). Conversely, at TLD 30, the diversion effect of subsurface runoff on surface runoff was enhanced, which played a role in alleviating soil erosion. With the increase of TLD, the soil erosion pattern changed from rill erosion to sheet or splash erosion. During the interill erosion stage, soil loss primarily occurred in the early stage, wherein the Variation Ratio (VR) of soil loss rate and surface runoff coefficient ranged from 2.16 to 4.99. At the rill erosion stage, the VR was approximately 1.0, and the soil loss rate was 2.7- to 6.3- fold greater than that in the interrill erosion stage. These results increase understanding of the effects of TLD on the coupling relationship of surface-subsurface runoff, which is of great significance for alleviating slope farmland erosion.
{"title":"Effect of tillage layer depth on erosion driven by surface-subsurface runoff coupling under rainfall simulation conditions","authors":"Ziwei Zhang , Yaojun Liu , Yichun Ma , Gang Sun , Dengchun Wen , Siyuan Liu , Jian Duan , Xiaodong Nie , Zhongwu Li","doi":"10.1016/j.iswcr.2025.03.004","DOIUrl":"10.1016/j.iswcr.2025.03.004","url":null,"abstract":"<div><div>The surface tillage layer structure of sloping farmland has a significant impact on rainfall-runoff distribution; however, the relationships between the Tillage Layer Depth (TLD) and surface-subsurface runoff, and the coupling effects of surface-subsurface runoff on soil erosion are still unclear. Thus, a set of laboratory experiments were conducted to reveal impacts of tillage layer depth (10, 20 and 30 cm) on surface-subsurface runoff relationships, eroded sediment processes, and soil erosion pattern evolution under the long-duration (180 min) rainfall simulation tests. A deeper TLD mitigated soil erosion. When the TLD increased from 10 to 30 cm, the average surface runoff decreased by 13 %, subsurface runoff increased by 5 %, and soil loss rate decreased by 19 g m<sup>−2</sup> min<sup>−1</sup>. The interaction between surface runoff and subsurface runoff, influenced by the tillage layer depth, significantly impacts soil erosion. Both surface runoff and subsurface runoff promoted soil erosion at shallow tillage layer depths (10 and 20 cm). Conversely, at TLD 30, the diversion effect of subsurface runoff on surface runoff was enhanced, which played a role in alleviating soil erosion. With the increase of TLD, the soil erosion pattern changed from rill erosion to sheet or splash erosion. During the interill erosion stage, soil loss primarily occurred in the early stage, wherein the Variation Ratio (VR) of soil loss rate and surface runoff coefficient ranged from 2.16 to 4.99. At the rill erosion stage, the VR was approximately 1.0, and the soil loss rate was 2.7- to 6.3- fold greater than that in the interrill erosion stage. These results increase understanding of the effects of TLD on the coupling relationship of surface-subsurface runoff, which is of great significance for alleviating slope farmland erosion.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 3","pages":"Pages 615-626"},"PeriodicalIF":7.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144329601","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 : 2025-09-01Epub Date: 2025-04-05DOI: 10.1016/j.iswcr.2025.04.001
Xiaojin Xu , Youjin Yan , Quanhou Dai , Fengling Gan , Sherif S.M. Ghoneim
In Karst regions, the impact of widespread bedrock outcrops on soil erosion processes is crucial and cannot be overlooked. These bedrock outcrops not only change the flow of surface runoff, but also have a significant influence on rainfall and sediment redistribution processes driven by runoff. This study aims to utilize simulation experiments and rare earth elements (REE) tracer technology to uncover the underlying effects of exposed bedrock outcrops on the soil erosion process, and the sediment transport patterns on slopes in karst regions during both dry and rainy seasons. The results demonstrate that the REE tracer technique holds considerable practical value for studying soil erosion processes on karst bedrock outcrop slopes. Seasonal variations in soil erosion rates are evident, with distinct differences between dry and rainy seasons due to rainfall flushing effects. Sediment migration on slopes shows both upward and downward movement, with predominant downward migration and deposition. Bedrock outcrops play a significant role in soil redistribution on karst slopes, hindering sediment transport and causing abrupt changes in rare earth element concentrations nearby. Monitoring and predicting soil erosion risk during the rainy season remains crucial for erosion prevention in karst regions. The impact of bedrock outcrops on soil erosion processes and spatial distribution in karst landscapes should be carefully considered when designing control measures. These findings offer a solid scientific foundation for understanding slope soil erosion mechanisms in karst regions and developing effective control strategies.
{"title":"Tracing soil erosion processes in Karst regions using rare earth elements: The role of bedrock outcrops and seasonal impacts","authors":"Xiaojin Xu , Youjin Yan , Quanhou Dai , Fengling Gan , Sherif S.M. Ghoneim","doi":"10.1016/j.iswcr.2025.04.001","DOIUrl":"10.1016/j.iswcr.2025.04.001","url":null,"abstract":"<div><div>In Karst regions, the impact of widespread bedrock outcrops on soil erosion processes is crucial and cannot be overlooked. These bedrock outcrops not only change the flow of surface runoff, but also have a significant influence on rainfall and sediment redistribution processes driven by runoff. This study aims to utilize simulation experiments and rare earth elements (REE) tracer technology to uncover the underlying effects of exposed bedrock outcrops on the soil erosion process, and the sediment transport patterns on slopes in karst regions during both dry and rainy seasons. The results demonstrate that the REE tracer technique holds considerable practical value for studying soil erosion processes on karst bedrock outcrop slopes. Seasonal variations in soil erosion rates are evident, with distinct differences between dry and rainy seasons due to rainfall flushing effects. Sediment migration on slopes shows both upward and downward movement, with predominant downward migration and deposition. Bedrock outcrops play a significant role in soil redistribution on karst slopes, hindering sediment transport and causing abrupt changes in rare earth element concentrations nearby. Monitoring and predicting soil erosion risk during the rainy season remains crucial for erosion prevention in karst regions. The impact of bedrock outcrops on soil erosion processes and spatial distribution in karst landscapes should be carefully considered when designing control measures. These findings offer a solid scientific foundation for understanding slope soil erosion mechanisms in karst regions and developing effective control strategies.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 3","pages":"Pages 675-686"},"PeriodicalIF":7.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330086","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 : 2025-09-01Epub Date: 2025-04-02DOI: 10.1016/j.iswcr.2025.03.006
Xinmei Zhao , Tianyang Li , Hongye Zhu , Chi Wang , Hui Yan , Lan Song , Yonghao Li , Binghui He
Hedgerow-grass ditch systems combine the advantages of contour planting and ecological grass ditches and have better soil and water conservation (SWC) benefits; however, there is a lack of a comprehensive understanding of their combined effects on sediment yield (SY) and N loss with surface runoff. To study the efficient management of hedgerow-ditch system runoff and nutrient loss in sloping farmland, an adjustable slope with a gradient of 15° and a drainage ditch with a gradient of 16° were used under typical erosive rainfall of 60 mm h−1. Four treatments, including control check (CK), bare slope (a slope without hedgerow and ditch system); T1, hedgerow slope (a hedgerow slope without a ditch system); T2, bare slope-soil ditch system (a bare slope with a soil ditch system); and T3, hedgerow-grass ditch system (a slope with hedgerow and a grass ditch system), were used to assess their impacts on runoff depth (RD), infiltration rate, sediment yield, and the concentration and loss quantities of total nitrogen (TN), dissolved nitrogen (DN), and particulate nitrogen (PN) and DN/TN in runoff. The results indicated that, compared with CK, the RD under T1, T2, and T3 were significantly decreased by 16.6 %, 14.4 %, and 54 %, respectively. The infiltration amounts under T1, T2, and T3 were significantly increased by 52.9 %, 45.7 %, and 171.9 %, respectively. The sediment concentration and SY rate were significantly reduced by 69.9 % and 94.9 %, and 22.1 % and 93.3 % under T1 and T3, respectively, but increased by 43.9 % and 274.7 % under T2 relative to CK. The diverse forms nitrogen (TN, DN, and PN) concentrations and losses under T3 were significantly reduced by 21 %, 10.4 %, 30.2 %, and 64.6 %, 57.6 %, and 67.1 %, respectively. The runoff DN/TN ratio was 53 %, revealing that DN was the primary type of N loss. Regression analysis showed that the RD exerted a more pronounced influence on TN loss across the four treatments, and a power function (R2 > 0.98, p < 0.01) of the cumulative RD could be used to predict TN, DN, and PN losses. Principal component analysis demonstrated that the hedgerow-grass ditch system affected slope nitrogen loss by changing the infiltration rate and DN/TN ratio. Our study demonstrates that the hedgerow-grass ditch system effectively reduced the sediment yield and N loss and could be used as an effective means of N control on sloping farmlands.
植物篱-草沟系统结合了等高线种植和生态草沟的优点，具有较好的水土保持效益；然而，对它们对地表径流产沙量（SY）和氮损失的综合影响缺乏全面的认识。为研究坡耕地篱沟系统径流和养分流失的有效管理，在典型侵蚀降雨量为60 mm h−1的条件下，采用坡度为15°的可调坡道和坡度为16°的排水沟。4种处理，包括控制检查（CK）、裸坡（没有树篱和沟渠系统的斜坡）；T1，篱坡（无沟渠系统的篱坡）；T2，裸坡-土沟系统（带土沟系统的裸坡）；以植物篱-草沟系统T3（有植物篱和草沟系统的坡面）为研究对象，评价其对径流深度（RD）、入渗速率、产沙量以及径流中总氮（TN）、溶解氮（DN）、颗粒氮（PN）和DN/TN的浓度和损失量的影响。结果表明，与对照相比，T1、T2和T3处理下的RD分别显著降低了16.6%、14.4%和54%。T1、T2和T3下的入渗量分别显著增加了52.9%、45.7%和171.9%。与对照相比，T1和T3处理显著降低了含沙量69.9%和94.9%，显著降低了22.1%和93.3%，而T2处理则显著增加了43.9%和274.7%。不同形态氮素（TN、DN和PN）浓度和损失在T3处理下分别显著降低了21%、10.4%、30.2%、64.6%、57.6%和67.1%。径流DN/TN比值为53%，表明DN是主要的N损失类型。回归分析表明，在4个处理中，RD对全氮损失的影响更为显著，呈幂函数(R2 >；0.98, p <；累积RD的0.01)可用于预测TN、DN和PN的损失。主成分分析表明，植物篱-草沟系统通过改变入渗速率和DN/TN比影响坡面氮素损失。研究表明，篱草沟渠系统能有效降低坡耕地的产沙量和氮素损失，可作为坡耕地氮素控制的有效手段。
{"title":"Hedgerow-grass ditch system effectively reduces sediment yield and nitrogen loss with surface runoff during simulated rainfall","authors":"Xinmei Zhao , Tianyang Li , Hongye Zhu , Chi Wang , Hui Yan , Lan Song , Yonghao Li , Binghui He","doi":"10.1016/j.iswcr.2025.03.006","DOIUrl":"10.1016/j.iswcr.2025.03.006","url":null,"abstract":"<div><div>Hedgerow-grass ditch systems combine the advantages of contour planting and ecological grass ditches and have better soil and water conservation (SWC) benefits; however, there is a lack of a comprehensive understanding of their combined effects on sediment yield (SY) and N loss with surface runoff. To study the efficient management of hedgerow-ditch system runoff and nutrient loss in sloping farmland, an adjustable slope with a gradient of 15° and a drainage ditch with a gradient of 16° were used under typical erosive rainfall of 60 mm h<sup>−1</sup>. Four treatments, including control check (CK), bare slope (a slope without hedgerow and ditch system); T1, hedgerow slope (a hedgerow slope without a ditch system); T2, bare slope-soil ditch system (a bare slope with a soil ditch system); and T3, hedgerow-grass ditch system (a slope with hedgerow and a grass ditch system), were used to assess their impacts on runoff depth (RD), infiltration rate, sediment yield, and the concentration and loss quantities of total nitrogen (TN), dissolved nitrogen (DN), and particulate nitrogen (PN) and DN/TN in runoff. The results indicated that, compared with CK, the RD under T1, T2, and T3 were significantly decreased by 16.6 %, 14.4 %, and 54 %, respectively. The infiltration amounts under T1, T2, and T3 were significantly increased by 52.9 %, 45.7 %, and 171.9 %, respectively. The sediment concentration and SY rate were significantly reduced by 69.9 % and 94.9 %, and 22.1 % and 93.3 % under T1 and T3, respectively, but increased by 43.9 % and 274.7 % under T2 relative to CK. The diverse forms nitrogen (TN, DN, and PN) concentrations and losses under T3 were significantly reduced by 21 %, 10.4 %, 30.2 %, and 64.6 %, 57.6 %, and 67.1 %, respectively. The runoff DN/TN ratio was 53 %, revealing that DN was the primary type of N loss. Regression analysis showed that the RD exerted a more pronounced influence on TN loss across the four treatments, and a power function (<em>R</em><sup>2</sup> > 0.98, <em>p</em> < 0.01) of the cumulative RD could be used to predict TN, DN, and PN losses. Principal component analysis demonstrated that the hedgerow-grass ditch system affected slope nitrogen loss by changing the infiltration rate and DN/TN ratio. Our study demonstrates that the hedgerow-grass ditch system effectively reduced the sediment yield and N loss and could be used as an effective means of N control on sloping farmlands.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 3","pages":"Pages 644-655"},"PeriodicalIF":7.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330071","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 : 2025-09-01Epub Date: 2025-04-17DOI: 10.1016/j.iswcr.2025.04.002
Yuanyuan Li , Jiayan Yang , Mingyi Yang , Bing Wang , Fengbao Zhang
Variation of soil properties induced by biochar amendments affects soil detachment capacity (Dc). However, the long-term effects of biochar on Dc have remained unexplored. This study assessed the variation of Dc with the rates and elapsed time since apple branch-derived biochar application, and quantified the relationship of Dc with hydrodynamic parameters and soil physicochemical properties in a three-year field experiment. Undisturbed soil samples to 20 cm depth were collected by using steel rings from field plots treated with biochar at 0, 24, 60, 96, 132, and 168 t ha−1 after biochar application for 1, 2 and 3 years. The Dc of these samples was evaluated through a flume experiment, with scouring soil samples under three flow discharge rates (0.00025, 0.00045, and 0.00065 m3 s−1) and five slope gradients (5.24, 8.75, 17.63, 26.79, and 40.40 %). Results revealed that, compared with no biochar treatment, the application of 24∼96 t ha−1 biochar after 1–2 years generally resulted in a reduction of Dc ranging from 6 %∼80 %, with a mean of 36 %. Conversely, 132 and 168 t ha−1 biochar application increased Dc by 59 % and 45 %. All biochar treatments after 3 years resulted in a 48 % reduction in Dc relative to bare soil. The Dc generally decreased with an increasing of rates and elapsed time since biochar application. The mean weight diameter of soil aggregates (MWD) and cohesion (COH) were the key indices influencing Dc in the first two years, while total organic carbon (TOC) started to significantly affect Dc in the last year. Shear stress (τ) emerged as the optimal hydrodynamic parameter for simulating Dc. Power function equations well estimated Dc using τ, MWD, COH, and TOC under biochar application. These results demonstrate that applying biochar with sufficient elapsed time since application and low rates, rather than minimal elapsed time since application and high rates leads to a greater enhancement of soil erosion resistance for loess soils, with potential to control rill erosion for degraded or degrading sloping farmland at risk of erosion on the Loess Plateau.
生物炭改性引起的土壤性质变化影响土壤剥离能力（Dc）。然而，生物炭对Dc的长期影响仍未得到探索。本研究通过3年的田间试验，评估了苹果枝源生物炭施用后土壤中直流电含量随施用速率和施用时间的变化，并定量分析了直流电含量与水动力参数和土壤理化性质的关系。在施用生物炭1、2和3年后，分别在0、24、60、96、132和168 t ha - 1处理过的地块上，采用钢环收集20 cm深度的原状土壤样品。在3种流量（0.00025、0.00045和0.00065 m3 s−1）和5种坡度（5.24、8.75、17.63、26.79和40.40%）条件下，通过水槽试验评估了冲刷土样品的Dc。结果表明，与没有生物炭处理相比，1 - 2年后施用24 ~ 96 tha - 1生物炭通常导致Dc降低6% ~ 80%，平均为36%。相反，施用132和168 t ha - 1生物炭可使Dc分别增加59%和45%。3年后，所有的生物炭处理导致Dc相对于裸土减少48%。自生物炭施用以来，Dc一般随速率和时间的增加而降低。土壤团聚体平均重径（MWD）和黏聚力（COH）是前2年影响土壤水分流变性的关键指标，而总有机碳（TOC）从去年开始显著影响土壤水分流变性。剪切应力（τ）是模拟直流的最佳水动力参数。在生物炭应用下，幂函数方程利用τ、MWD、COH和TOC很好地估计了Dc。这些结果表明，施用生物炭后，施用足够的时间和较低的施用量，而不是施用最短的时间和较高的施用量，可以更大程度地增强黄土土壤的抗侵蚀能力，并有可能控制黄土高原有侵蚀风险的退化或退化坡耕地的细沟侵蚀。
{"title":"Biochar application reduces soil detachment capacity by overland flow under a continuous three-year field experiment on the Loess Plateau of China","authors":"Yuanyuan Li , Jiayan Yang , Mingyi Yang , Bing Wang , Fengbao Zhang","doi":"10.1016/j.iswcr.2025.04.002","DOIUrl":"10.1016/j.iswcr.2025.04.002","url":null,"abstract":"<div><div>Variation of soil properties induced by biochar amendments affects soil detachment capacity (D<sub><em>c</em></sub>). However, the long-term effects of biochar on D<sub><em>c</em></sub> have remained unexplored. This study assessed the variation of D<sub><em>c</em></sub> with the rates and elapsed time since apple branch-derived biochar application, and quantified the relationship of D<sub><em>c</em></sub> with hydrodynamic parameters and soil physicochemical properties in a three-year field experiment. Undisturbed soil samples to 20 cm depth were collected by using steel rings from field plots treated with biochar at 0, 24, 60, 96, 132, and 168 t ha<sup>−1</sup> after biochar application for 1, 2 and 3 years. The D<sub><em>c</em></sub> of these samples was evaluated through a flume experiment, with scouring soil samples under three flow discharge rates (0.00025, 0.00045, and 0.00065 m<sup>3</sup> s<sup>−1</sup>) and five slope gradients (5.24, 8.75, 17.63, 26.79, and 40.40 %). Results revealed that, compared with no biochar treatment, the application of 24∼96 t ha<sup>−1</sup> biochar after 1–2 years generally resulted in a reduction of D<sub><em>c</em></sub> ranging from 6 %∼80 %, with a mean of 36 %. Conversely, 132 and 168 t ha<sup>−1</sup> biochar application increased D<sub><em>c</em></sub> by 59 % and 45 %. All biochar treatments after 3 years resulted in a 48 % reduction in D<sub><em>c</em></sub> relative to bare soil. The D<sub><em>c</em></sub> generally decreased with an increasing of rates and elapsed time since biochar application. The mean weight diameter of soil aggregates (MWD) and cohesion (COH) were the key indices influencing D<sub><em>c</em></sub> in the first two years, while total organic carbon (TOC) started to significantly affect D<sub><em>c</em></sub> in the last year. Shear stress (<em>τ</em>) emerged as the optimal hydrodynamic parameter for simulating D<sub><em>c</em></sub>. Power function equations well estimated D<sub><em>c</em></sub> using <em>τ</em>, MWD, COH, and TOC under biochar application. These results demonstrate that applying biochar with sufficient elapsed time since application and low rates, rather than minimal elapsed time since application and high rates leads to a greater enhancement of soil erosion resistance for loess soils, with potential to control rill erosion for degraded or degrading sloping farmland at risk of erosion on the Loess Plateau.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 3","pages":"Pages 687-701"},"PeriodicalIF":7.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330634","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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