Pub Date : 2025-07-03DOI: 10.1016/j.iswcr.2025.06.006
Cheng Tong , Xiaodong Deng , Yulin Shangguan , Baiyu Dong , Yurun Chen , Chenhao Huang , Luyao Zhu , Sinan Li , Yang Ye , Hongquan Wang
<div><div>Soil moisture (SM) is a pivotal component of the global water cycle and a critical environmental parameter in terrestrial carbon cycling, significantly influencing energy exchange, vegetation dynamics, and ecosystem productivity. Its spatial and temporal distribution offers critical insights for climate models and water resource management, particularly in predicting extreme weather events and optimizing agricultural practices. Passive microwave remote sensing, characterized by its all-weather capability, extensive coverage, and high efficiency, has emerged as the primary method for SM estimation. Over recent decades, significant progress in microwave SM retrieval has been driven by technological innovations and increased satellite data availability, resulting in the development and widespread adoption of passive microwave SM products. Notwithstanding the significant progress in microwave SM retrieval techniques, a comprehensive literature review on passive microwave SM, encompassing research advancements, retrieval methods, application hotspots, shortcomings, and future prospects, remains notably absent. To address this gap, this study undertakes a systematic and in-depth exploration of passive microwave SM research. Initially, the fundamental principles of passive microwave SM retrieval are introduced, establishing the groundwork for understanding the underlying mechanisms. Subsequently, the primary retrieval methods are reviewed, including physically-based radiative transfer models and machine learning algorithms, with a focus on their respective strengths and limitations. Additionally, the study introduces the current mainstream passive microwave SM products, detailing their specific attributes such as spatial resolution, temporal frequency, and available time. Following this, a thorough classification of the specific applications of existing passive microwave SM products is conducted through the VOS (Visualization of Similarities) viewer-based keyword co-occurrence technique. The findings indicate that these products are predominantly utilized in environmental science and ecology for applications such as data assimilation, drought monitoring, rainfall estimation, and flood forecasting. Moreover, passive microwave SM data are increasingly being applied in fields related to human activities, such as disaster early warning, military simulation, and vehicle speed modeling, underscoring their versatility and expanding relevance in both natural and anthropogenic contexts. Despite the notable progress in these areas, persistent challenges such as data gaps, lower spatial resolution, and degraded accuracy caused by external environmental factors continue to limit the full potential of passive microwave SM products across diverse application scenarios. In the end, this study offers a forward-looking perspective on passive microwave SM research, with the goal of addressing current challenges and advancing the development of microwave SM prod
{"title":"The passive microwave remote sensing in soil moisture retrieval: Products, models, applications and challenges","authors":"Cheng Tong , Xiaodong Deng , Yulin Shangguan , Baiyu Dong , Yurun Chen , Chenhao Huang , Luyao Zhu , Sinan Li , Yang Ye , Hongquan Wang","doi":"10.1016/j.iswcr.2025.06.006","DOIUrl":"10.1016/j.iswcr.2025.06.006","url":null,"abstract":"<div><div>Soil moisture (SM) is a pivotal component of the global water cycle and a critical environmental parameter in terrestrial carbon cycling, significantly influencing energy exchange, vegetation dynamics, and ecosystem productivity. Its spatial and temporal distribution offers critical insights for climate models and water resource management, particularly in predicting extreme weather events and optimizing agricultural practices. Passive microwave remote sensing, characterized by its all-weather capability, extensive coverage, and high efficiency, has emerged as the primary method for SM estimation. Over recent decades, significant progress in microwave SM retrieval has been driven by technological innovations and increased satellite data availability, resulting in the development and widespread adoption of passive microwave SM products. Notwithstanding the significant progress in microwave SM retrieval techniques, a comprehensive literature review on passive microwave SM, encompassing research advancements, retrieval methods, application hotspots, shortcomings, and future prospects, remains notably absent. To address this gap, this study undertakes a systematic and in-depth exploration of passive microwave SM research. Initially, the fundamental principles of passive microwave SM retrieval are introduced, establishing the groundwork for understanding the underlying mechanisms. Subsequently, the primary retrieval methods are reviewed, including physically-based radiative transfer models and machine learning algorithms, with a focus on their respective strengths and limitations. Additionally, the study introduces the current mainstream passive microwave SM products, detailing their specific attributes such as spatial resolution, temporal frequency, and available time. Following this, a thorough classification of the specific applications of existing passive microwave SM products is conducted through the VOS (Visualization of Similarities) viewer-based keyword co-occurrence technique. The findings indicate that these products are predominantly utilized in environmental science and ecology for applications such as data assimilation, drought monitoring, rainfall estimation, and flood forecasting. Moreover, passive microwave SM data are increasingly being applied in fields related to human activities, such as disaster early warning, military simulation, and vehicle speed modeling, underscoring their versatility and expanding relevance in both natural and anthropogenic contexts. Despite the notable progress in these areas, persistent challenges such as data gaps, lower spatial resolution, and degraded accuracy caused by external environmental factors continue to limit the full potential of passive microwave SM products across diverse application scenarios. In the end, this study offers a forward-looking perspective on passive microwave SM research, with the goal of addressing current challenges and advancing the development of microwave SM prod","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 843-859"},"PeriodicalIF":7.3,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183838","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 : 2025-07-01DOI: 10.1016/j.iswcr.2025.06.007
Jingjiang Li , Yingying Zhang , Hanyu Zhang , Xia Li , Wenjun Sun , Yajie Zhao , Yi Zhang , Aide Sun , Qianjin Liu , Nufang Fang
The rill erosion process in sloping farmland after straw incorporation is different from that under traditional tillage, including complex variations and hysteresis in runoff and sediment concentration. However, the hysteresis of original runoff and sediment concentration series is not enough to show the hidden multi-timescale information. Different straw incorporation strategies have varying degrees of change to the hysteresis on runoff and sediment content. The purpose of this study was to systematically identify the hysteresis characteristics and differences of runoff and sediment concentration in multi-timescales on rill erosion, and to reveal the effects of straw length, incorporation depth, and straw amount on hysteresis. In this study, scouring experiments were carried out in runoff plots for brown soil under nine maize straw incorporation treatments, i.e., two gradients of straw length (<3, 3−6 cm), incorporation depth (15, 20 cm), straw amount (4000, 8000 kg ha−1), and traditional tillage without straw (CK). The signal decomposition method was used to extract runoff and sediment concentration components at multi-timescales for rill erosion, and hysteresis loops and cross-correlation were applied to analyze the multi-timescale hysteresis relationship of runoff and sediment concentration. The results showed that increases in straw length and straw amount could reduce runoff and sediment and increase runoff start time. The CK had the hysteresis loop with anticlockwise type, and the runoff and sediment concentration had complex hysteresis phenomenon under straw incorporation. The <3 cm straw length treatments exhibited a tendency for clockwise hysteresis loops. This was attributed to the limited supply of sediment during the later erosion stages. In addition, multiscale cross-correlation showed more detailed hysteresis information than the hysteresis loop of the original series, and better explained the variation of sediment concentration. In the >0.3 high-frequency component, the CK exhibited sediment concentration leading runoff (1−3 min), while the 8000 kg ha−1 straw amount treatments intensified complex fluctuations in runoff and sediment, demonstrating variable leads or lags for the sediment concentration. At the sub-event scale, the 3−6 cm straw length treatments resulted in sediment concentration leading runoff, showing a hysteresis similar to that of the event scale. Clarifying the multi-timescale hysteresis of runoff and sediment helps improve understanding of runoff and sediment dynamics in rill erosion processes under straw incorporation for brown soil.
秸秆还田后坡耕地细沟侵蚀过程与传统耕作方式不同，径流和泥沙含量变化复杂，具有滞后性。但是，原始径流和泥沙浓度序列的滞后性不足以显示隐藏的多时间尺度信息。不同秸秆还田策略对径流和泥沙的滞后性有不同程度的影响。本研究旨在系统识别多时间尺度径流和泥沙浓度对细沟侵蚀的滞后特征和差异，揭示秸秆长度、入渗深度和秸秆用量对滞后的影响。本研究采用9种玉米秸秆还田处理，即秸秆长度（3、3 ~ 6 cm）、还田深度（15、20 cm）、秸秆用量（4000、8000 kg ha ~ 1）和传统无秸秆耕作（CK）两种梯度，对棕壤径流地块进行了冲刷试验。采用信号分解方法提取细沟侵蚀多时间尺度的流沙分量，利用滞回线和相互关系分析径流和泥沙的多时间尺度滞回关系。结果表明，增加秸秆长度和秸秆量可以减少径流和泥沙，延长径流启动时间。对照区存在逆时针型滞回环，秸秆还田条件下径流和泥沙浓度存在复杂的滞回现象。秸秆长度为3 cm的处理呈现顺时针迟滞回线的趋势。这是由于后期侵蚀阶段沉积物供应有限。此外，多尺度相互关比原始序列的滞回线显示出更详细的滞回信息，更好地解释了泥沙浓度的变化。在>；0.3高频分量中，CK表现出泥沙浓度主导径流（1 ~ 3 min），而8000 kg ha - 1秸秆量处理则加剧了径流和泥沙的复杂波动，对泥沙浓度表现出不同的领先或滞后。在次事件尺度上，3 ~ 6 cm秸秆长度处理导致泥沙浓度主导径流，表现出与事件尺度相似的滞后性。阐明径流泥沙的多时间尺度滞后性，有助于进一步认识秸秆还田条件下褐土细沟侵蚀过程的径流泥沙动力学。
{"title":"Straw incorporation regulates rill erosion processes: Revealing multi-timescale hysteresis between runoff and sediment concentration in brown soil","authors":"Jingjiang Li , Yingying Zhang , Hanyu Zhang , Xia Li , Wenjun Sun , Yajie Zhao , Yi Zhang , Aide Sun , Qianjin Liu , Nufang Fang","doi":"10.1016/j.iswcr.2025.06.007","DOIUrl":"10.1016/j.iswcr.2025.06.007","url":null,"abstract":"<div><div>The rill erosion process in sloping farmland after straw incorporation is different from that under traditional tillage, including complex variations and hysteresis in runoff and sediment concentration. However, the hysteresis of original runoff and sediment concentration series is not enough to show the hidden multi-timescale information. Different straw incorporation strategies have varying degrees of change to the hysteresis on runoff and sediment content. The purpose of this study was to systematically identify the hysteresis characteristics and differences of runoff and sediment concentration in multi-timescales on rill erosion, and to reveal the effects of straw length, incorporation depth, and straw amount on hysteresis. In this study, scouring experiments were carried out in runoff plots for brown soil under nine maize straw incorporation treatments, i.e., two gradients of straw length (<3, 3−6 cm), incorporation depth (15, 20 cm), straw amount (4000, 8000 kg ha<sup>−1</sup>), and traditional tillage without straw (CK). The signal decomposition method was used to extract runoff and sediment concentration components at multi-timescales for rill erosion, and hysteresis loops and cross-correlation were applied to analyze the multi-timescale hysteresis relationship of runoff and sediment concentration. The results showed that increases in straw length and straw amount could reduce runoff and sediment and increase runoff start time. The CK had the hysteresis loop with anticlockwise type, and the runoff and sediment concentration had complex hysteresis phenomenon under straw incorporation. The <3 cm straw length treatments exhibited a tendency for clockwise hysteresis loops. This was attributed to the limited supply of sediment during the later erosion stages. In addition, multiscale cross-correlation showed more detailed hysteresis information than the hysteresis loop of the original series, and better explained the variation of sediment concentration. In the >0.3 high-frequency component, the CK exhibited sediment concentration leading runoff (1−3 min), while the 8000 kg ha<sup>−1</sup> straw amount treatments intensified complex fluctuations in runoff and sediment, demonstrating variable leads or lags for the sediment concentration. At the sub-event scale, the 3−6 cm straw length treatments resulted in sediment concentration leading runoff, showing a hysteresis similar to that of the event scale. Clarifying the multi-timescale hysteresis of runoff and sediment helps improve understanding of runoff and sediment dynamics in rill erosion processes under straw incorporation for brown soil.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 909-921"},"PeriodicalIF":7.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183839","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 : 2025-06-25DOI: 10.1016/j.iswcr.2025.06.005
Dian Lin , Zhongbao Xin , Feng Lin , Jinhao Liu , Yanzhang Huang
Soil organic carbon (SOC) plays a critical role in the carbon cycle of alpine ecosystems; however, little is known about the dynamics of SOC governed by soil types and elevation gradients in these systems. In this study, soil properties, environmental conditions, and anthropogenic activities were identified along an 835 km east-west transect in the Yarlung Tsangpo River of the Tibetan Plateau region, which has an elevation range of 2800–5200 m. The information was used to investigate the effects of two soil types (dark felty soils and aeolian soils) and elevation gradients on SOC dynamics. The findings revealed that the average SOC content in dark felty soil (15.13 ± 5.78 g/kg) was significantly greater than that in aeolian soil (7.98 ± 2.76 g/kg). The SOC content of dark felty soil continuously increased with elevation, increasing by about 23.4 g/kg for every 1000 m increase in elevation. In contrast, owing to the high sand particle content and loose, porous structure of aeolian soil, the low SOC content did not vary with elevation. We found that mean annual precipitation (MAP), normalized difference vegetation index (NDVI), electrical conductivity (EC), and clay content (clay) were the primary factors influencing SOC accumulation in dark felty soils. As elevation increased, a more humid and cool water-thermal environment was formed, significantly improving vegetation (NDVI) and optimizing soil physicochemical properties (clay and EC). These factors interacted synergistically to promote significant SOC accumulation in dark felty soils. This study emphasized the importance of the effects of dark felty soil and aeolian soil on the SOC content and improved the understanding of the mechanism by which SOC accumulates in the alpine region of high elevation areas.
{"title":"Variability of soil organic carbon with elevation gradient in the Yarlung Tsangpo River Basin on the southeastern Tibetan Plateau","authors":"Dian Lin , Zhongbao Xin , Feng Lin , Jinhao Liu , Yanzhang Huang","doi":"10.1016/j.iswcr.2025.06.005","DOIUrl":"10.1016/j.iswcr.2025.06.005","url":null,"abstract":"<div><div>Soil organic carbon (SOC) plays a critical role in the carbon cycle of alpine ecosystems; however, little is known about the dynamics of SOC governed by soil types and elevation gradients in these systems. In this study, soil properties, environmental conditions, and anthropogenic activities were identified along an 835 km east-west transect in the Yarlung Tsangpo River of the Tibetan Plateau region, which has an elevation range of 2800–5200 m. The information was used to investigate the effects of two soil types (dark felty soils and aeolian soils) and elevation gradients on SOC dynamics. The findings revealed that the average SOC content in dark felty soil (15.13 ± 5.78 g/kg) was significantly greater than that in aeolian soil (7.98 ± 2.76 g/kg). The SOC content of dark felty soil continuously increased with elevation, increasing by about 23.4 g/kg for every 1000 m increase in elevation. In contrast, owing to the high sand particle content and loose, porous structure of aeolian soil, the low SOC content did not vary with elevation. We found that mean annual precipitation (MAP), normalized difference vegetation index (NDVI), electrical conductivity (EC), and clay content (clay) were the primary factors influencing SOC accumulation in dark felty soils. As elevation increased, a more humid and cool water-thermal environment was formed, significantly improving vegetation (NDVI) and optimizing soil physicochemical properties (clay and EC). These factors interacted synergistically to promote significant SOC accumulation in dark felty soils. This study emphasized the importance of the effects of dark felty soil and aeolian soil on the SOC content and improved the understanding of the mechanism by which SOC accumulates in the alpine region of high elevation areas.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 945-956"},"PeriodicalIF":7.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183920","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 : 2025-06-13DOI: 10.1016/j.iswcr.2025.06.004
Lixin Lin , Xixi Liu , Yuan Sun
Soil mapping using Landsat-8 provides potential for a real-time synoptic estimation of soil organic carbon (SOC) and soil total nitrogen (STN) stocks. However, the few relevant studies at global and European scales have shown relatively poor model accuracy because of the effects from buildings, water and vegetation. Here, we used independent variable fuzzy learning based on several building, water and vegetation indices to reduce the effects of these land covers on the SOC and STN models. We applied the models to predict the SOC and STN stocks at the pan-European scale. Measured SOC and STN stocks obtained from the Land Use/Cover Area frame statistical Survey 2018 dataset and spectral data from the corresponding Landsat-8 images were used in this study. The results indicated that the SOC and STN models after learning performed better than the models before learning (the SOC model: R2 = 0.56, mean absolute error (MAE) = 10.38 t C ha−1, root mean squared error (RMSE) = 13.72 t C ha−1, ratio of performance to interquartile range (RPIQ) = 2.02; the STN model: R2 = 0.52, MAE = 0.92 t N ha−1, RMSE = 1.20 t N ha−1, RPIQ = 1.45). The two models predicted the 0–20 cm SOC and STN stocks across Europe as 28.13 and 2.25 Gt, respectively. The uneven distributions were clearly reduced when compared with the maps before learning, especially our STN map and STN relative standard deviation (RSD) map. The results indicated that our study provided a valuable reference for reducing the effects of buildings, water, and vegetation during satellite SOC and STN mapping. Considering the importance of SOC and STN for future global policies, we will also pay attention to the effects of other soil properties, weathering and land covers in the future.
利用Landsat-8进行土壤制图为土壤有机碳（SOC）和土壤全氮（STN）储量的实时天气估计提供了可能。然而，在全球和欧洲尺度上的少数相关研究表明，由于建筑物、水和植被的影响，模式的准确性相对较差。本文采用基于建筑、水和植被指数的自变量模糊学习来降低这些土地覆盖对SOC和STN模型的影响。应用该模型对泛欧尺度上的碳储量和碳储量进行了预测。本研究使用了2018年土地利用/覆盖面积框架统计调查数据集和相应Landsat-8图像的光谱数据获得的实测SOC和STN储量。结果表明，学习后的SOC和STN模型表现优于学习前的模型(SOC模型：R2 = 0.56，平均绝对误差(MAE) = 10.38 t C ha−1，均方根误差(RMSE) = 13.72 t C ha−1，性能与四分位数间距之比(RPIQ) = 2.02；STN模型：R2 = 0.52, MAE = 0.92 t N ha−1,RMSE = 1.20 t N ha−1,RPIQ = 1.45)。两种模式预测欧洲0 ~ 20 cm的碳储量为28.13 Gt， STN储量为2.25 Gt。与学习前的地图相比，不均匀分布明显减少，特别是我们的STN地图和STN相对标准偏差（RSD）地图。研究结果为降低建筑物、水和植被对卫星SOC和STN的影响提供了有价值的参考。考虑到SOC和STN对未来全球政策的重要性，未来我们还将关注其他土壤性质、风化和土地覆盖的影响。
{"title":"Improving the Landsat-8 determinations of soil organic carbon and total nitrogen stocks through reducing the effects of buildings, water, and vegetation","authors":"Lixin Lin , Xixi Liu , Yuan Sun","doi":"10.1016/j.iswcr.2025.06.004","DOIUrl":"10.1016/j.iswcr.2025.06.004","url":null,"abstract":"<div><div>Soil mapping using Landsat-8 provides potential for a real-time synoptic estimation of soil organic carbon (SOC) and soil total nitrogen (STN) stocks. However, the few relevant studies at global and European scales have shown relatively poor model accuracy because of the effects from buildings, water and vegetation. Here, we used independent variable fuzzy learning based on several building, water and vegetation indices to reduce the effects of these land covers on the SOC and STN models. We applied the models to predict the SOC and STN stocks at the pan-European scale. Measured SOC and STN stocks obtained from the Land Use/Cover Area frame statistical Survey 2018 dataset and spectral data from the corresponding Landsat-8 images were used in this study. The results indicated that the SOC and STN models after learning performed better than the models before learning (the SOC model: <em>R</em><sup>2</sup> = 0.56, mean absolute error (MAE) = 10.38 t C ha<sup>−1</sup>, root mean squared error (RMSE) = 13.72 t C ha<sup>−1</sup>, ratio of performance to interquartile range (RPIQ) = 2.02; the STN model: <em>R</em><sup>2</sup> = 0.52, MAE = 0.92 t N ha<sup>−1</sup>, RMSE = 1.20 t N ha<sup>−1</sup>, RPIQ = 1.45). The two models predicted the 0–20 cm SOC and STN stocks across Europe as 28.13 and 2.25 Gt, respectively. The uneven distributions were clearly reduced when compared with the maps before learning, especially our STN map and STN relative standard deviation (RSD) map. The results indicated that our study provided a valuable reference for reducing the effects of buildings, water, and vegetation during satellite SOC and STN mapping. Considering the importance of SOC and STN for future global policies, we will also pay attention to the effects of other soil properties, weathering and land covers in the future.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 1032-1043"},"PeriodicalIF":7.3,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183842","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 : 2025-06-11DOI: 10.1016/j.iswcr.2025.06.001
Martín Francia , Pablo González Barrios , Antonella Celio , Carolina Munka , Guadalupe Tiscornia
Soil temperature (ST) is an important physical property that influences all soil processes; it is a relevant component of the climate system and impacts terrestrial ecological, hydrological and biogeochemical processes. Its variability presents challenges, limiting studies the spatiotemporal distribution and prediction of ST. This study describes the calibration of a model that uses land surface temperature (LST), the Normalized Difference Vegetation Index (NDVI), and daily solar declination (Ds), along with data from meteorological stations, to predict the covered soil temperature at depth of 5 cm (SMTc5cm) and 10 cm (SMTc10cm). Iterations were performed using combinations of 18 LST and 10 NDVI treatments derived from MODIS images, with the aim of selecting and applying validated models for the intra-annual characterization of SMTc5cm and SMTc10cm across Uruguay. The Results showed that the models for SMTc5cm and SMTc10cm had R2 values of 0.84 and 0.87-0.89, respectively, and RMSE values of 2.3 °C for SMTc5cm and 2.1-1.8 °C for SMTc10cm. Comparisons with observed SMTc5cm and SMTc10cm, and SMTc5cm with observed ST at 20 cm depth and uncovered soil, indicated that the models accurately predicted soil temperature and maintained phase shifts, with minor variations in the timing of profile intersections. Models that used averages of daytime and nighttime LST observations, along with filtered NDVI series, achieved better fits than those using the original data. Preliminary observations highlight the importance of further investigating the effects of forests, soil composition, and subsurface characteristics on soil temperature.
{"title":"Intra-annual characterization of soil mean temperature at 5 and 10 cm depths based on remote sensing data, at country scale","authors":"Martín Francia , Pablo González Barrios , Antonella Celio , Carolina Munka , Guadalupe Tiscornia","doi":"10.1016/j.iswcr.2025.06.001","DOIUrl":"10.1016/j.iswcr.2025.06.001","url":null,"abstract":"<div><div>Soil temperature (ST) is an important physical property that influences all soil processes; it is a relevant component of the climate system and impacts terrestrial ecological, hydrological and biogeochemical processes. Its variability presents challenges, limiting studies the spatiotemporal distribution and prediction of ST. This study describes the calibration of a model that uses land surface temperature (LST), the Normalized Difference Vegetation Index (NDVI), and daily solar declination (Ds), along with data from meteorological stations, to predict the covered soil temperature at depth of 5 cm (SMTc5cm) and 10 cm (SMTc10cm). Iterations were performed using combinations of 18 LST and 10 NDVI treatments derived from MODIS images, with the aim of selecting and applying validated models for the intra-annual characterization of SMTc5cm and SMTc10cm across Uruguay. The Results showed that the models for SMTc5cm and SMTc10cm had R<sup>2</sup> values of 0.84 and 0.87-0.89, respectively, and RMSE values of 2.3 °C for SMTc5cm and 2.1-1.8 °C for SMTc10cm. Comparisons with observed SMTc5cm and SMTc10cm, and SMTc5cm with observed ST at 20 cm depth and uncovered soil, indicated that the models accurately predicted soil temperature and maintained phase shifts, with minor variations in the timing of profile intersections. Models that used averages of daytime and nighttime LST observations, along with filtered NDVI series, achieved better fits than those using the original data. Preliminary observations highlight the importance of further investigating the effects of forests, soil composition, and subsurface characteristics on soil temperature.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 1019-1031"},"PeriodicalIF":7.3,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183926","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 : 2025-06-07DOI: 10.1016/j.iswcr.2025.06.002
Bastian Steinhoff-Knopp , Sebastian Neuenfeldt , Stefan Erasmi , Philipp Saggau
The crop cover and management factor (C factor) is crucial to assess the impact of management on soil erosion by water within the (R)USLE (Revised Universal Soil Loss Equation) modelling framework. Its derivation is challenging due to the need for spatiotemporal data on crop sequences. Therefore, the aim of this study is the generation of spatiotemporal detailed C factor datasets for Germany by integrating (a) crop composition data from agricultural statistics on the municipality level for six individual years from 1999 to 2020 and (b) high-resolution (10 × 10 m) crop sequence information for 2017 to 2023 derived from earth observation data in the C factor estimation. The results reveal an overall increase of 8.7 % in the mean C factor for German municipalities from 1999 to 2020, which can be attributed to policy-driven changes in crop composition. The comparison of the two C factor datasets emphasises the importance of multi-annual information on crops in (R)USLE-based erosion modelling as (i) high-resolution C factors based on single years show a weak agreement with crop sequence-derived C factors (RMSE of 0.062) and (ii) C factors based on crop composition data from agricultural statistics are 5.7 % lower compared to high-resolution crop sequence-derived C factors. As high-resolution crop type data from earth observation is updated yearly, the C factor maps presented here can be incorporated into German monitoring systems as agri-environmental indicators. Further research is needed to obtain more detailed information on cover crops and tillage practices to improve C factor derivation. These findings and the visible heterogenious patterns in the pixel-based multi-annual C factor data highlight that spatiotemporal high-resolution input data is key in C factor estimation.
{"title":"Spatiotemporal detailed crop cover and management factor maps as agri-environmental indicators for soil erosion in Germany","authors":"Bastian Steinhoff-Knopp , Sebastian Neuenfeldt , Stefan Erasmi , Philipp Saggau","doi":"10.1016/j.iswcr.2025.06.002","DOIUrl":"10.1016/j.iswcr.2025.06.002","url":null,"abstract":"<div><div>The crop cover and management factor (C factor) is crucial to assess the impact of management on soil erosion by water within the (R)USLE (Revised Universal Soil Loss Equation) modelling framework. Its derivation is challenging due to the need for spatiotemporal data on crop sequences. Therefore, the aim of this study is the generation of spatiotemporal detailed C factor datasets for Germany by integrating (a) crop composition data from agricultural statistics on the municipality level for six individual years from 1999 to 2020 and (b) high-resolution (10 × 10 m) crop sequence information for 2017 to 2023 derived from earth observation data in the C factor estimation. The results reveal an overall increase of 8.7 % in the mean C factor for German municipalities from 1999 to 2020, which can be attributed to policy-driven changes in crop composition. The comparison of the two C factor datasets emphasises the importance of multi-annual information on crops in (R)USLE-based erosion modelling as (i) high-resolution C factors based on single years show a weak agreement with crop sequence-derived C factors (RMSE of 0.062) and (ii) C factors based on crop composition data from agricultural statistics are 5.7 % lower compared to high-resolution crop sequence-derived C factors. As high-resolution crop type data from earth observation is updated yearly, the C factor maps presented here can be incorporated into German monitoring systems as agri-environmental indicators. Further research is needed to obtain more detailed information on cover crops and tillage practices to improve C factor derivation. These findings and the visible heterogenious patterns in the pixel-based multi-annual C factor data highlight that spatiotemporal high-resolution input data is key in C factor estimation.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 933-944"},"PeriodicalIF":7.3,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183872","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 : 2025-05-23DOI: 10.1016/j.iswcr.2025.05.009
Yao Xiao , Qunou Jiang , Weihang Zhao , Zuoxiao Wang , Rui Xiong , Jing Li , Linjuan He
The arid valley region in southeastern Tibet exemplifies an ecologically vulnerable area in southwestern China, where soil erosion has intensified in recent years as a consequence of socio-economic growth and infrastructure construction. This study aimed to elucidate the mechanism by which freeze-thaw cycles affect soil erosion processes on the bare slopes of this alpine arid valley region under artificial disturbances from engineering construction. Focusing on bare slopes with inclinations of 20° and 40°, we analyzed the impact of freeze-thaw cycles on flow and sand production through indoor artificial rainfall experiments. The findings indicated an approximately threefold increase in soil splattering following the freeze-thaw cycle compared to unfrozen slopes; cumulative flow production exhibited a declining trend, decreasing by 15.99 % and 37.42 % after the freeze-thaw cycle at slope angles of 20° and 40°, respectively; cumulative sand production increased by 2.29 % and 51.24 % after the freeze-thaw cycle at slope angles of 20° and 40°, respectively. On the freeze-thaw and unfrozen slopes, the sand production rates escalated swiftly following the initiation of flow production, reaching peaks of 1.34 g m−2·min−1 and 1.52 g m−2·min−1 in 10 min and 12 min, respectively. Post the freeze-thaw cycle, the rates stabilized, with the sand production rates on the freeze-thaw slopes exceeding those on the unfrozen slopes. These findings will serve as a significant reference for the management of bare ground surfaces and the conservation and restoration of biological environments following construction disturbances.
本研究旨在阐明冻融循环在工程建设人为干扰下对高寒干旱河谷裸露坡面土壤侵蚀过程的影响机制。以坡度为20°和40°的裸坡为研究对象，通过室内人工降雨试验，分析了冻融循环对径流和产沙的影响。研究结果表明，与未冻结的斜坡相比，冻融循环后土壤飞溅的数量增加了大约三倍；坡角为20°和40°时，冻融循环后累积产流量分别减少15.99%和37.42%；当坡角为20°和40°时，冻融循环后的累积出砂量分别增加了2.29%和51.24%。在冻融边坡和非冻融边坡上，产砂速率在产流开始后迅速上升，分别在10 min和12 min达到1.34 g m−2·min−1和1.52 g m−2·min−1的峰值。冻融循环后，产沙速率趋于稳定，冻融斜坡的产沙速率大于未冻融斜坡。这些研究结果将为裸地管理和建筑干扰后生物环境的保护和恢复提供重要参考。
{"title":"Disparity in soil erosion processes between freeze-thaw and unfrozen slopes under artificial rainfall conditions in high-altitude and dry valleys of the Southeast Tibet region","authors":"Yao Xiao , Qunou Jiang , Weihang Zhao , Zuoxiao Wang , Rui Xiong , Jing Li , Linjuan He","doi":"10.1016/j.iswcr.2025.05.009","DOIUrl":"10.1016/j.iswcr.2025.05.009","url":null,"abstract":"<div><div>The arid valley region in southeastern Tibet exemplifies an ecologically vulnerable area in southwestern China, where soil erosion has intensified in recent years as a consequence of socio-economic growth and infrastructure construction. This study aimed to elucidate the mechanism by which freeze-thaw cycles affect soil erosion processes on the bare slopes of this alpine arid valley region under artificial disturbances from engineering construction. Focusing on bare slopes with inclinations of 20° and 40°, we analyzed the impact of freeze-thaw cycles on flow and sand production through indoor artificial rainfall experiments. The findings indicated an approximately threefold increase in soil splattering following the freeze-thaw cycle compared to unfrozen slopes; cumulative flow production exhibited a declining trend, decreasing by 15.99 % and 37.42 % after the freeze-thaw cycle at slope angles of 20° and 40°, respectively; cumulative sand production increased by 2.29 % and 51.24 % after the freeze-thaw cycle at slope angles of 20° and 40°, respectively. On the freeze-thaw and unfrozen slopes, the sand production rates escalated swiftly following the initiation of flow production, reaching peaks of 1.34 g m<sup>−2</sup>·min<sup>−1</sup> and 1.52 g m<sup>−2</sup>·min<sup>−1</sup> in 10 min and 12 min, respectively. Post the freeze-thaw cycle, the rates stabilized, with the sand production rates on the freeze-thaw slopes exceeding those on the unfrozen slopes. These findings will serve as a significant reference for the management of bare ground surfaces and the conservation and restoration of biological environments following construction disturbances.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 828-842"},"PeriodicalIF":7.3,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183837","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 : 2025-05-22DOI: 10.1016/j.iswcr.2025.05.008
Wanbao Shi , Juanjuan Liu , Xiaomin Sun , Kuandi Zhang
The combined effects of freeze-thaw and water erosion significantly increase the risk of soil erosion in seasonally freeze-thaw regions. Although soil detachment capacity (SDC) is a critical parameter for evaluating soil erosion degree, the effect of freeze-thaw cycles (FTC) on SDC is not comprehensively understood. Therefore, experiments were conducted in a scouring flume under six freeze-thaw cycles (i.e., 0, 1, 5, 10, 15, and 20 FTC), five flow discharges (2−18 L min−1), and five soil types. The results showed that FTC caused varying degrees of degradation in soil properties, leading to variations in SDC. Under different initial moisture contents, SDC exhibited an increasing trend during the initial stages of FTC and stabilized after 10 FTC. Compared with unfrozen soil, under different freeze-thaw levels (1−20 FTC), the mean SDC of Wuzhong soil, Shenmu soil, Ansai soil, Dingxi soil, and Changwu soil increased by 27, 30, 25, 38, and 57 %, respectively. Apart from porosity, SDC showed notable inverse correlations with other soil properties, including cohesion, shear strength, internal friction angle, organic matter, and bulk density (p < 0.05). Stream power was identified as the ideal hydrodynamic parameter for characterizing SDC (R2 = 0.85). An SDC prediction model was established according to these key factors. The model effectively predicted the SDC under the synergistic action of flow and freeze-thaw (R2 = 0.90, RE = −9.02 %). Additional verification is necessary when applying the predictive model outside the conditions under which it was developed. The findings contribute novel understanding into the operational mechanism of soil detachment in freeze-thaw affected regions.
冻融和水侵蚀的共同作用显著增加了季节性冻融地区土壤侵蚀的风险。土壤剥离能力（SDC）是评价土壤侵蚀程度的重要参数，但冻融循环对土壤剥离能力的影响尚不全面。因此，在冲刷水槽中进行了6次冻融循环（即0、1、5、10、15和20 FTC）、5种流量（2 - 18 L min - 1）和5种土壤类型的实验。结果表明，FTC对土壤性质造成不同程度的退化，从而导致SDC的变化。不同初始含水率下，SDC在FTC初期呈上升趋势，在FTC 10后趋于稳定。在不同冻融水平（1 ~ 20 FTC）下，吴中土、神木土、安塞土、定西土和长武土的平均SDC分别比未冻融土高27%、30%、25%、38%和57%。除孔隙度外，SDC与土壤黏聚力、抗剪强度、内摩擦角、有机质、容重等其他性状呈显著负相关（p < 0.05）。水流功率被认为是表征SDC的理想水动力参数（R2 = 0.85）。根据这些关键因素建立了SDC预测模型。该模型有效预测了冻融与流动协同作用下的SDC （R2 = 0.90, RE =−9.02%）。在开发预测模型的条件之外应用预测模型时，需要进行额外的验证。研究结果有助于对冻融影响地区土壤分离的作用机制有新的认识。
{"title":"Response of soil detachment capacity to freeze‒thaw process for five loess soils from the Loess Plateau of China","authors":"Wanbao Shi , Juanjuan Liu , Xiaomin Sun , Kuandi Zhang","doi":"10.1016/j.iswcr.2025.05.008","DOIUrl":"10.1016/j.iswcr.2025.05.008","url":null,"abstract":"<div><div>The combined effects of freeze-thaw and water erosion significantly increase the risk of soil erosion in seasonally freeze-thaw regions. Although soil detachment capacity (SDC) is a critical parameter for evaluating soil erosion degree, the effect of freeze-thaw cycles (FTC) on SDC is not comprehensively understood. Therefore, experiments were conducted in a scouring flume under six freeze-thaw cycles (i.e., 0, 1, 5, 10, 15, and 20 FTC), five flow discharges (2−18 L min<sup>−1</sup>), and five soil types. The results showed that FTC caused varying degrees of degradation in soil properties, leading to variations in SDC. Under different initial moisture contents, SDC exhibited an increasing trend during the initial stages of FTC and stabilized after 10 FTC. Compared with unfrozen soil, under different freeze-thaw levels (1−20 FTC), the mean SDC of Wuzhong soil, Shenmu soil, Ansai soil, Dingxi soil, and Changwu soil increased by 27, 30, 25, 38, and 57 %, respectively. Apart from porosity, SDC showed notable inverse correlations with other soil properties, including cohesion, shear strength, internal friction angle, organic matter, and bulk density (<em>p</em> < 0.05). Stream power was identified as the ideal hydrodynamic parameter for characterizing SDC (<em>R</em><sup><em>2</em></sup> = 0.85). An SDC prediction model was established according to these key factors. The model effectively predicted the SDC under the synergistic action of flow and freeze-thaw (<em>R</em><sup><em>2</em></sup> = 0.90, <em>RE</em> = −9.02 %). Additional verification is necessary when applying the predictive model outside the conditions under which it was developed. The findings contribute novel understanding into the operational mechanism of soil detachment in freeze-thaw affected regions.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 808-827"},"PeriodicalIF":7.3,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183836","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 : 2025-05-21DOI: 10.1016/j.iswcr.2025.05.006
Boxiang Zhang , Yanfeng Jia , Haoming Fan , Chengjiu Guo , Fangli Su , Shuang Li , Juan Fu , Xi Zhang , Mingyao Yu , Mingchun Yang , Renming Ma
Soil erosion resulting from soil compaction and freeze-thaw action is a major global environmental issue in intensively mechanized agricultural and cold regions. Existing studies predominantly focus on the direct effects of freeze-thaw cycles on soil erosion, yet overlook the legacy effects of pre-freeze-thaw soil compaction. This study aimed to reveal the cross-temporal impact mechanisms of pre-freeze-thaw soil compaction on post-freeze-thaw soil erosion and how soil properties drive these effects. A comparative study was conducted in the Mollisol region of Northeast China by utilizing in situ field erosion experiments and soil property measurements under various compaction levels before and after the freeze-thaw period. Results showed that before the freeze-thaw period, compaction significantly increased total runoff and sediment mass (p < 0.05). After the freeze-thaw period, the sediment mass of compacted soil decreased by 1.84 %–57.73 % compared to before the freeze-thaw period, but still increased by 28.59 %–148.22 % compared to uncompacted soil. The structural equation model revealed that before the freeze-thaw period, the influence of soil properties on runoff was greater than their direct effect on sediment mass, and the sediment mass variation was mainly driven by runoff scouring due to soil compaction. After the freeze-thaw period, the decreased soil erosion resistance (aggregate stability and soil strength) and the increased runoff caused by the legacy effects of compaction were the primary reasons for higher sediment mass in compacted soil compared to uncompacted soil. This study highlights the crucial role of human activities before the freeze-thaw period in influencing subsequent erosion dynamics, providing essential insights for erosion control and soil restoration in vulnerable farmlands.
{"title":"Impact of soil compaction on the rill erosion of Mollisol by waterflow: A comparative analysis before and after the seasonal freezing and thawing","authors":"Boxiang Zhang , Yanfeng Jia , Haoming Fan , Chengjiu Guo , Fangli Su , Shuang Li , Juan Fu , Xi Zhang , Mingyao Yu , Mingchun Yang , Renming Ma","doi":"10.1016/j.iswcr.2025.05.006","DOIUrl":"10.1016/j.iswcr.2025.05.006","url":null,"abstract":"<div><div>Soil erosion resulting from soil compaction and freeze-thaw action is a major global environmental issue in intensively mechanized agricultural and cold regions. Existing studies predominantly focus on the direct effects of freeze-thaw cycles on soil erosion, yet overlook the legacy effects of pre-freeze-thaw soil compaction. This study aimed to reveal the cross-temporal impact mechanisms of pre-freeze-thaw soil compaction on post-freeze-thaw soil erosion and how soil properties drive these effects. A comparative study was conducted in the Mollisol region of Northeast China by utilizing in situ field erosion experiments and soil property measurements under various compaction levels before and after the freeze-thaw period. Results showed that before the freeze-thaw period, compaction significantly increased total runoff and sediment mass (p < 0.05). After the freeze-thaw period, the sediment mass of compacted soil decreased by 1.84 %–57.73 % compared to before the freeze-thaw period, but still increased by 28.59 %–148.22 % compared to uncompacted soil. The structural equation model revealed that before the freeze-thaw period, the influence of soil properties on runoff was greater than their direct effect on sediment mass, and the sediment mass variation was mainly driven by runoff scouring due to soil compaction. After the freeze-thaw period, the decreased soil erosion resistance (aggregate stability and soil strength) and the increased runoff caused by the legacy effects of compaction were the primary reasons for higher sediment mass in compacted soil compared to uncompacted soil. This study highlights the crucial role of human activities before the freeze-thaw period in influencing subsequent erosion dynamics, providing essential insights for erosion control and soil restoration in vulnerable farmlands.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 756-770"},"PeriodicalIF":7.3,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183833","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 : 2025-05-20DOI: 10.1016/j.iswcr.2025.05.007
Jiaqiong Zhang , Minfeng Yin , Kaizu Wu , Ruru Bai , Yueting Shang , Mingyi Yang , Yingge Xie
<div><div>Both the rare earth element (REE) tracing and the composite fingerprinting approaches are valuable for sediment source identification. However, few studies have compared the accuracy of sediment source determination based on these two approaches, particularly for coarse-textured soils. This study combined simulated rainfall experiments with artificial mixtures, providing validation data for sediment contribution estimation. Simulated rainfall experiments were conducted using lanthana (La<sub>2</sub>O<sub>3</sub>), yttria (Y<sub>2</sub>O<sub>3</sub>), and ceria (CeO<sub>2</sub>) separately tagged Acrisols, Chernozems, and Arenosols at 10°, 15°, and 20° slope gradients under a 120 mm h<sup>−1</sup> rainfall intensity. Sediment from different soils during 1-h (1 h) erosion process was continuously and separately collected within a 6-min time interval. Then, artificial mixtures were created using sediment from different soils over the same collection time. Sediment contributions were estimated using bulk samples (i.e., <1000 μm) for REE tracing, while they were estimated using a series of particle size ranges (i.e., <10, 10–63, 63–125, 125–250, 250–500, and 500–1000 μm) according to the composite fingerprinting for different source soil groups (i.e., Acrisols–Chernozems, Acrisols–Arenosols, Chernozems–Arenosols, and Acrisols–Chernozems–Arenosols). Here, we also analyzed the impacts of particle correction based on REE enrichment ratio (<em>ER</em>) within fine particles (<10, <63, and 10–63 μm). The results showed that sediment contribution accuracy based on the bulk samples was relatively high for both fine-textured and coarse-textured soils (RMSE<13.4%) on hillslopes, with or without adopting the particle correction factor. Whereas the accuracy of sediment contributions determined using different particle size ranges greatly varied for fine-textured source soils, while all the results presented significant (<em>p</em> < 0.05) differences compared to those obtained using the sediment weighting approach when coarse-textured source soil was included. Moreover, particle correction based on <em>ER</em> values of fine particle size fractions in which REEs were mainly enriched had no obvious effects on decreasing sediment contribution estimation bias. Additionally, particle correction had a high risk of decreasing estimation accuracy of sediment contributions using both REE tracing and the composite fingerprinting approaches. For the bulk samples, <em>ER</em>-corrected sediment contributions were significantly different (<em>p</em> < 0.05) from sediment weighting and uncorrected results when a coarse-textured soil (i.e., Arenosols) was included in the source soils. This was also the case for Acrisols and Chernozems, particularly on 15° hillslopes. Clearly, both REE tracing and composite fingerprinting are useful for sediment source determination, and sediment bulk samples normally provide robust results. Additionally, particl
稀土示踪法和复合指纹法在沉积物源识别中都具有重要的应用价值。然而，很少有研究比较基于这两种方法确定沉积物来源的准确性，特别是对于粗糙质地的土壤。本研究将模拟降雨试验与人工混合试验相结合，为泥沙贡献估算提供了验证数据。利用镧（La2O3）、钇（Y2O3）和铈（CeO2）分别标记Acrisols、Chernozems和Arenosols，在10°、15°和20°坡度下进行了模拟降雨实验，降雨强度为120 mm h - 1。在6 min的时间间隔内，连续收集不同土壤在1 h （1 h）侵蚀过程中的沉积物。然后，在相同的收集时间内，使用来自不同土壤的沉积物制成人工混合物。沉积物的贡献采用块状样品（即<；1000 μm）进行REE示踪，而根据不同源土组（即Acrisols-Chernozems、Acrisols-Arenosols、Chernozems-Arenosols、Acrisols-Arenosols和Acrisols-Chernozems - arenosols）的复合指纹图谱，采用一系列粒度范围（即<；10、10 - 63、63-125、125-250、250-500和500-1000 μm）进行估算。在此，我们还分析了基于细颗粒（<10, <；63和10 - 63 μm）内REE富集比（ER）的颗粒校正的影响。结果表明，无论是否采用颗粒校正因子，基于体样的细质土和粗质土沉积物贡献精度均较高（rmse13.4%）。而在细质源土中，不同粒度范围确定的泥沙贡献精度差异很大，而在粗质源土中，所有结果都与采用泥沙加权法获得的结果存在显著差异（p < 0.05）。此外，基于稀土元素富集的细粒度组分的ER值进行粒子校正对减小沉积物贡献估算偏差没有明显作用。此外，粒子校正有降低稀土示踪和复合指纹法估算沉积物贡献的精度的高风险。对于散装样品，当源土壤中包含粗质土壤（即砂硝土）时，er校正的沉积物贡献与沉积物加权和未校正的结果显著不同（p < 0.05）。Acrisols和Chernozems也是如此，特别是在15°山坡上。显然，稀土元素示踪和复合指纹图谱对于沉积物来源的确定都是有用的，沉积物样品通常提供可靠的结果。此外，当沉积物分选效果较弱时，不建议进行颗粒校正。
{"title":"Sediment source determination comparing rare earth element tracing and composite fingerprinting approaches on hillslopes","authors":"Jiaqiong Zhang , Minfeng Yin , Kaizu Wu , Ruru Bai , Yueting Shang , Mingyi Yang , Yingge Xie","doi":"10.1016/j.iswcr.2025.05.007","DOIUrl":"10.1016/j.iswcr.2025.05.007","url":null,"abstract":"<div><div>Both the rare earth element (REE) tracing and the composite fingerprinting approaches are valuable for sediment source identification. However, few studies have compared the accuracy of sediment source determination based on these two approaches, particularly for coarse-textured soils. This study combined simulated rainfall experiments with artificial mixtures, providing validation data for sediment contribution estimation. Simulated rainfall experiments were conducted using lanthana (La<sub>2</sub>O<sub>3</sub>), yttria (Y<sub>2</sub>O<sub>3</sub>), and ceria (CeO<sub>2</sub>) separately tagged Acrisols, Chernozems, and Arenosols at 10°, 15°, and 20° slope gradients under a 120 mm h<sup>−1</sup> rainfall intensity. Sediment from different soils during 1-h (1 h) erosion process was continuously and separately collected within a 6-min time interval. Then, artificial mixtures were created using sediment from different soils over the same collection time. Sediment contributions were estimated using bulk samples (i.e., <1000 μm) for REE tracing, while they were estimated using a series of particle size ranges (i.e., <10, 10–63, 63–125, 125–250, 250–500, and 500–1000 μm) according to the composite fingerprinting for different source soil groups (i.e., Acrisols–Chernozems, Acrisols–Arenosols, Chernozems–Arenosols, and Acrisols–Chernozems–Arenosols). Here, we also analyzed the impacts of particle correction based on REE enrichment ratio (<em>ER</em>) within fine particles (<10, <63, and 10–63 μm). The results showed that sediment contribution accuracy based on the bulk samples was relatively high for both fine-textured and coarse-textured soils (RMSE<13.4%) on hillslopes, with or without adopting the particle correction factor. Whereas the accuracy of sediment contributions determined using different particle size ranges greatly varied for fine-textured source soils, while all the results presented significant (<em>p</em> < 0.05) differences compared to those obtained using the sediment weighting approach when coarse-textured source soil was included. Moreover, particle correction based on <em>ER</em> values of fine particle size fractions in which REEs were mainly enriched had no obvious effects on decreasing sediment contribution estimation bias. Additionally, particle correction had a high risk of decreasing estimation accuracy of sediment contributions using both REE tracing and the composite fingerprinting approaches. For the bulk samples, <em>ER</em>-corrected sediment contributions were significantly different (<em>p</em> < 0.05) from sediment weighting and uncorrected results when a coarse-textured soil (i.e., Arenosols) was included in the source soils. This was also the case for Acrisols and Chernozems, particularly on 15° hillslopes. Clearly, both REE tracing and composite fingerprinting are useful for sediment source determination, and sediment bulk samples normally provide robust results. Additionally, particl","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 4","pages":"Pages 876-891"},"PeriodicalIF":7.3,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183840","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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