This study aims to clarify the previously overlooked carbon sink associated with carbonate and silicate mineral dissolution in riverine suspended sediments, using the Yangtze River Basin as a case study. The main objectives of this study are: (1) to quantify the carbon sink potential (CSP), capacity (CSC), and flux (CSF) of sediment dissolution in the Yangtze River; (2) to identify carbon sink influencing factors in the Yangtze River Basin; and (3) to assess the contributions of carbon sink functions by sediment dissolution to both local and global carbon cycles. Mineral and chemical compositions of suspended sediments from the Yangtze River were analyzed alongside climatic, topographic, erosion, and lithological data. A major-cation-based carbon sink model was developed and a correction index was applied to reduce systematic errors. The CSP, CSC, and CSF were quantified by the model, while key influencing factors were identified by statistical analyses. Calcium, magnesium, sodium, and potassium compositions in the sediment decreased along the mainstream of the Yangtze River by 62.56

Sediment source fingerprinting can be an effective method for identifying sediment sources in wildfire-impacted areas, but the effects of tracer and model selection on robustness remain poorly understood. In this study, soil samples were collected from three potential sources, and artificial mixtures with known source proportions were created. Three types of tracers were tested for their sensitivity to wildfire. Ten composite fingerprints, generated through the traditional three-step procedure (TSP) as well as consensus ranking and the conservativeness index (CM) were used to assess the accuracy of two un-mixing models (FingerPro and MixSIAR). The results indicated that wildfire had substantial effects on most tracer properties. Among the ten composite fingerprints, the CM selection method performed best. While the TSP method could achieve a near-global optimum in some cases, it was the least stable among the ten tracer sets. Compared to FingerPro, MixSIAR delivered higher accuracy and precision for our case study.

The cover and management factor (C/B factor) in the Universal Soil Loss Equation (USLE) series models indicates the effects of vegetation cover and management practices on water erosion. Remote sensing technology provides abundant data and methods for the C/B factor estimation, but the applicability and accuracy of these methods can vary widely. More critically, they often overlook the impact of non-photosynthetic vegetation cover on soil erosion. This study aimed to evaluate and develop a more accurate and cost-effective method for calculating the C/B factor in the purple soil hilly region, focusing on typical small watersheds. A correlation analysis was conducted to compare four C/B factors derived from the remote sensing data, aiming to identify the most suitable method for the purple soil hilly region. Additionally, artificial rainfall simulation tests were performed to investigate the relationship between photosynthetic vegetation cover, non-photosynthetic vegetation cover, and soil erosion, leading to the development of a relational equation between integrated vegetation cover and C/B factors. The results indicate that the method from the technical regulations for dynamic monitoring of soil erosion is most suitable for calculating the C/B factor in purple soil hilly regions. On this basis, the integrated vegetation cover effectively accounted for the impact of non-photosynthetic vegetation on soil erosion, leading to a more comprehensive and precise estimation of the C/B factor. The newly developed method significantly improved the accuracy of the C/B factor calculation in the purple soil hilly region. This study provides a scientific and accurate algorithm for calculating the C/B factor in the purple soil hilly region, offering valuable insights and a methodological framework for similar studies in other areas.

The results of topographic factor computations are highly sensitive to the setting of contributing area thresholds when applied to soil erosion modeling to evaluate soil erosion; however, the existing choice of contributing area thresholds is highly arbitrary. Meanwhile, due to regional-scale limitations, lower-resolution DEM data are usually used to calculate topographic factors, and with the fragmentation of land parcels in hilly areas of purple soil, lower-resolution DEM data respond to very limited topographic information. This study focuses on solving the mentioned issues by selecting the Lizixi watershed in a hilly area of purple soil as the research subject. It establishes a relationship equation between the resolution of DEM data and the optimal contributing area threshold. This is achieved by investigating the change in the contributing area threshold with the resolution of DEM data, determining the optimal contributing area threshold for different resolutions of DEM data, and establishing the relationship equation between the resolution of DEM data and the optimal contributing area threshold. Meanwhile, to solve the key problem of fragmented land parcels in the purple soil area, where the low-resolution and medium-resolution DEM data cannot accurately reflect the topographic information, combined with the principle of histogram matching, the downscaling model between the topographic factors under the low-resolution DEM data and the topographic factors under the high-resolution DEM data is established. This study confirms that the scale transformation model developed has a strong simulation effect, and the findings can offer technical assistance for the precise computation of soil erosion in small watersheds in hilly areas of purple soil.

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Identifying sediment sources is a prerequisite for developing sediment management strategies. Erosion sediment derived from a small agriculture catchment is an important component of sediment inflow in the Three Gorges Reservoir Area. Paddy fields are one of the major land-use types in this region and can have both positive and negative effects on sediment. In this study, two different source group classification schemes were used to analyze the effect of paddy fields on the sediment in a typical small agriculture catchment in the Three Gorges Reservoir Region. A total of 32 soil source samples were collected from four kinds of land-use types (13 from dry land, 5 from orchards, 8 from paddy fields, and 6 from forest) in the Shipanqiu catchment. Moreover, the properties consisted of 41 elements and 12 element ratios were analyzed. Composite fingerprinting methodology was applied to discriminate and quantify the sediment source contributions. Additionally, element ratio was used as the fingerprint property in the fingerprinting application. The results showed that the element ratio was verified as an effective fingerprint property. Additionally, the relative sediment contributions of the potential land-use sources were 55.25% of dry land, 32.69% of orchards, and 12.06% of forest. Paddy fields played a role of sink rather than of source in this study. Accordingly, both forest and paddy fields are effective sediment management strategies. Particularly, paddy fields are a preferred choice for soil erosion control in mountainous and hilly areas. Furthermore, the proper management of paddy fields can help promote sediment retention and reduce soil erosion, which have positive effects on both the environment and agricultural productivity.

中国是世界山地大国，山地面积约为陆地国土面积的 2/3。近 10 年来，山地林草植被覆盖率增加8.2%，山地绿色覆盖指数均值达到 82.1%，植被覆盖率达到新中国成立以来最高水平，水土流失面积减少27.5×104km2，土壤年侵蚀量减少 27%。目前，中国山地生态安全屏障骨干体系基本形成，高效的山地灾害防控体系不断健全，山地灾害减灾成效显著；与此同时，山区脱贫攻坚战取得历史性胜利，山区产业结构得到显著优化，现代化进程稳步推进。

Soil stoichiometry is an essential tool for understanding soil nutrient balance and cycling. Previous studies have recognized that some relationships were observed between particle size and carbon and nitrogen parameters. This study attempted to evaluate nutrient element concentrations and their stoichiometric ratios of surface soil (0–10 cm) under different land use types (forest, sloping arable land, paddy fields, and orchards). and different particle sizes (<32 µm, <63 µm, and <125 µm) from a small typical hilly catchment (0.35 km2) in the Three Gorges Reservoir Region of China. The contents of soil organic carbon (SOC), total nitrogen (TN). and total phosphorus (TP) were measured, and the ratios of C:N, C:P, N:P were calculated. The results indicated that land use type and soil particle size have diverse impacts on the studied indexes (SOC, TN, TP, C:N, C:P, and N:P). Six indexes were significantly affected by land use type (p < 0.01), while only C:N ratio was statistically influenced by soil particle size (p < 0.05). Furthermore, several significant differences of studied parameters of four land use types grouped within three particle sizes were found. The concentrations of SOC (12.34~13.46 g kg−1), TN (1.27~1.59 g kg−1), and TP (0.71~0.92 g kg−1) in the study site were lower than the national average values of China. Moreover, the productivity in the study area was mainly limited by TN concentration. Additionally, the concentration of TP decreased obviously with the increase in particle size. Furthermore, various coupling relationships were validated by linear and nonlinear fitting among different indexes. At the small catchment scale, take forest as a reference, human activities have significant impact on C-N-P stoichiometry (p < 0.05). Especially, tillage may reduce SOC and TN contents, leading to a decline in soil quality. Overall, our findings can provide a basis for rational utilization and sustainable development of land resources.

The Three Gorges Reservoir (TGR) is an artificial riparian ecosystem and influenced on its soil erosion. However, the probability and magnitude of the erosion on upland adjacent to riparian zone and its impacts on the TGR are still unclear. In this research, we determined the relationship between minute-scale rainfall erosivity and soil erosion from three replicated upland bare plots (5 m x 20 m for each) in Zhong County, southwest of China, from 2017 to 2019 (short-term), and estimated the rainfall erosion based on the daily-scale rainfall erosivity from 1992 to 2015 (long-term). We performed generalized extreme value (GEV) modeling to quantify three risk elements (scenario, probability-magnitude relation, consequences) and predicted the erosion risks. The results indicated that, over the short-term, wet season increased the average runoff depth and soil loss by a factor of 1.6 (p < 0.01) and 1.4 (p < 0.01), respectively. Low and rare rainfall erosivity (5 years < return period <= 20 years) caused the erosion event with relative low occurrence probability (return period > 5 years) to dominantly contribute the total erosion (>65%) in dry season. Common and normal rainfall erosivity (return period = 5 years) caused the common erosion events (return period <= 2 years) to contribute nearly 50% of the total erosion in wet season. Over the long-term, extreme rainfall erosivity (1621 MJ.mm.ha(-1).h(-1)) in dry season was predicted to be more effective on upland erosion, but a uniform pattern of erosion contribution of incremental rainfall return periods was estimated in wet season. Our findings improve the understanding of the uncertainty of upland-surface hydrologic processes in the TGR, and could provide useful risk management or ecological restoration strategies for the soil and water conservationists.

指纹识别技术是量化流域侵蚀泥沙来源的有效手段,如何应用于火烧流域,仍有一些问题值得探讨.通过回顾相关文献,总结森林火灾通过植被、土壤和灰烬加剧土壤侵蚀的机制,介绍应用指纹技术研究火烧流域泥沙来源的案例,重点分析放射性核素、矿物磁性、物理性质、地球化学元素和有机组分等指纹因子在火烧迹地的含量和性质变化,论述各类指纹因子在火烧流域泥沙来源研究中的适用性,并提出未来应重点关注指纹技术的物理基础、火灾后土壤性质的时空变化规律、指纹因子稳定性验证、燃烧灰烬的影响以及大粒径泥沙的识别等问题.为促进火烧迹地指纹识别技术的研究、理解森林火灾对于流域产沙格局的影响、提升火灾流域水土保持和生态修复的有效性提供理论依据.

Sediment is the main carrier of pollutants in river channels. This study analyzed the distribution characteristics of precipitation, runoff, and sediment and their response characteristics in the Daning River basin. Based on daily precipitation (1979–2017), runoff (1989–2017), and sediment (1997–2017) time series, the Gini concentration index, precipitation concentration index (PCI), precipitation concentration degree (PCD), and precipitation concentration period were applied to assess the concentration characteristics of precipitation, runoff, and sediment on the daily, monthly, and seasonal scales. At each intensity level, precipitation was negatively correlated to the PCI and PCD. The normalized difference vegetation index (NDVI) values had strong negative correlations with rainy days with light precipitation (0.1–9.9 mm). The degrees of concentration were in the same order for the multiscale analysis: runoff < precipitation < sediment. Although the amount of daily precipitation of more than 25 mm displayed a significant increasing trend, suggesting an increased risk of flood and soil erosion, the significantly improved vegetation cover reduced the sediment-carrying capacity of the surface runoff, with significant decreases in the total amount and multiscale concentration degrees of sediment being observed. The results of the study provide a reference for the improvement of the potable water safety and ecological environment in the Three Gorges Reservoir region.

In this study, the temporal and spatial patterns of rainfall in the Longchuan River basin from 1977 to 2017 were analyzed, to assess the feature of precipitation. Based on the daily precipitation time series, the Lorenz curve, precipitation concentration index (PCI), precipitation concentration degree (PCD), and the precipitation concentration period (PCP) were used to evaluate the precipitation distribution characteristics. The PCI, PCD and PCP in five categories, defined by the fixed thresholds, were proposed to investigate the concentrations, and the average values indicated the higher concentrations in the higher intensities. The indices showed strong irregularity of daily and monthly precipitation distributions in this basin. The decrease in the PCD revealed an increase in the proportion of precipitation in the dry season. The rainy days of slight precipitation in the upper and lower basins with significant downward trends (−13.13 d/10 a, −7.78 d/10 a) led to longer dry spells and an increase in the risk of drought, even severe in the lower area. In the upper basin, the increase in rainfall erosivity was supported by the upward trend in the PCIw of heavy precipitation and the simple daily intensity index (SDII) of extreme precipitation. Moreover, the PCP of light precipitation, moderate precipitation, and heavy precipitation concentrated earlier at the end of July. The results of this study can provide beneficial reference information to water resource planning, reservoir operation, and agricultural production in the basin.

Quantitative assessment of soil erosion and deposition rates using fallout radionuclides, including Beryllium-7 (7Be), requires reliable reference inventory, a crucial parameter in the conversion models. However, little information is currently available on the microscale spatial variabilities of 7Be inventory at reference locations, producing less confidence in the accuracy of the estimated soil redistribution rates with 7Be measurements. To address this need, 44 soil cores were sampled extensively at 1 m intervals on a 5×12 m2 bare flat reference plot in each year of 2019 and 2021 in Southwestern China. Surface soil samples were collected using a stainless steel cylinder with an internal diameter of 10 cm and a height of 3 cm. The soils are purple soils characterised by a silt loam texture. 7Be activity concentrations in <2 mm particles were measured to explore potential variability of fallout inventory at the microscale within the reference area. To determine possible causes of 7Be variation in soils, physicochemical characteristics including organic matter content (OM), pH, cation exchange capacity (CEC) and grain size compositions were also analysed. In the case of 2019, 7Be mass activities in soil samples ranged from 2.5 to 10.9 Bq kg-1 and the areal activities ranged from 82.7 to 417.6 Bq m-2. The deposition of 7Be was higher in 2021, with mass activities ranged between 5.6 and 22.1 Bq kg-1 and the areal activities between 213.9 and 775.6 Bq m-2. The higher inventory of 7Be in 2021 (211.1 ± 66.2 Bq m-2, mean ± 1SD) than that of 2019 (456.1 ± 145.5 Bq m-2) can be explained by higher rainfall amounts of 384.0 mm in 2021 (January 1 - May 18) 2021, compared with 225.4 mm for 2019 (January 1 - May 15). The coefficient of variation (CV) analysis indicated that soil pH and CEC were the most stable properties at the study site with CVs ranged from 1.3 to 5.1%. In contrast, 7Be contents in soils, in terms of both mass and areal activities, exhibited almost the strongest variation with CVs around 30%. No significant correlations were noted between 7Be activities and the measured soil properties. The high degree of spatial viability in 7Be areal activities at the reference site indicates that the simple assumption of uniform distribution of 7Be across the reference site needs detailed examination. A spatially-integrated sampling design is recommended to improve the accuracy of reference inventory estimates and thus soil erosion assessment with 7Be technique.

Quantitative assessment of soil erosion and deposition rates using fallout radionuclides (FRNs), including Beryllium-7 (7Be), requires establishment of a reliable reference inventory i.e. the inventory of a non-eroding point. Little information, however, is currently available on the microscale spatial variability of 7Be inventory within reference sites. This is important information to inform sample design and replication, and in addition, to evaluate the uncertainty of derived soil redistribution data. In this study, soil samples were taken systematically at grid points on a 5 m x 12 m experimental reference plot with a bare soil surface, at two sampling occasions (2019 and 2021) in southwest China. 7Be activities were measured to explore the potential variability of 7Be inventory at the microscale. To determine possible causes of 7Be inventory variation, physicochemical charac-teristics including organic matter content (OM), pH, cation exchange capacity (CEC) and grain size compositions were analyzed at each sample location. 7Be inventories for the two periods were estimated at 211.1 +/- 20.0 and 456.1 +/- 43.8 Bq m- 2 (mean +/- 2 SEM, n = 44), with coefficients of variation of 31.4 and 31.9% for the 2019 and 2021 sampling cases, respectively. No significant correlations were observed between 7Be activity and the measured soil compositional properties, suggesting observed spatial variability is primarily a result of random variation due to rainsplash and other processes, although sampling and measuring processes may contribute some uncertainties. Using the traditional method, ca. 40 independent reference samples are required to estimate the mean 7Be inventory, i.e. to represent input across the site, with an allowable error of 10% at 95% confidence, while application of a bootstrap approach suggests that ca. 28 would be adequate under similar accuracy. Overall, results of this study emphasize that the simple assumption of uniform distribution of 7Be across the reference area needs detailed examination on a case-by-case basis, if this radionuclide is to be used effectively to assess patterns and rates of soil redistribution from field to hillslope scale.

Characterizing soil particle-size distribution is a key measure towards soil property. The purpose of this study was to evaluate the multifractal characteristics of soil particle-size distribution among different land-use from a purple soil catchment and to generalize the spatial variation trend of multifractal parameters across the catchment. A total of 84 soil samples were collected from four kinds of land use patterns (dry land, orchard, paddy, and forest) in an agricultural catchment in the Three Gorges Reservoir Region, China. The multifractal analysis method was applied to quantitatively characterize the soil particle size distribution. Six soil particle size distribution (PSD) multifractal parameters ( D (0), D (1), D (2), Δ α ( q ), Δ f [ α ( q )], α (0)) were computed. Additionally, a geostatistical analysis was employed to reveal the spatial differentiation and map the spatial distribution of these parameters. Evident multifractal characteristics were found. The trend of generalized dimension spectrum of four land use patterns was basically consistent with the range of 0.8 to 2.0. However, orchard showed the largest monotonic decline, while the forest demonstrated the smallest decrease. D (0) of the four land use patterns were ranked as: dry land < orchard < forest < paddy, the order of D (1) was: dry land < paddy < orchard < forest, D (2) presented a rand-size relationship as dry land < forest < paddy < orchard. Furthermore, all land-use patterns presented as Δ f [α( q )] < 0. The rand-size relationship of α (0) was same as D (0). The best-fitting model for D (0), D (1), D (2) and Δ f [ α ( q )] was spherical model, for Δ α ( q ) was gaussian model, and for α (0) was exponential model with structure variance ratio was 1.03%, 49.83%, 0.84%, 1.48%, 22.20% and 10.60%, respectively. The results showed that soil particles of each land use pattern were distributed unevenly. The multifractal parameters under different land use have significant differences, except for Δ α ( q ). Differences in the composition of soil particles lead to differences in the multifractal properties even though they belong to the same soil texture. Farming behavior may refine particles and enhance the heterogeneity of soil particle distribution. Our results provide an effective reference for quantifying the impact of human activities on soil system in the Three Gorges Reservoir region.

A sediment fingerprinting approach was applied to identify dominant sediment sources in an area where soil conservation measures (i.e. terracing) had been carried out on steep, intensively cultivated lands but the outcome was unknown. The wider purpose was to provide scientific evidence to inform decisions on where erosion control and sediment mitigation strategies could be further targeted. Geochemical fingerprints were used to quantify sediment contributions from three potential sources, i.e. surface soil under cropland and woodland land use, and channel banks, in a managed small catchment in the Upper Yangtze River basin in southwestern China. In parallel, artificial mixtures with known source proportions were evaluated to examine the effects of grain size selection (<125 mu m and < 63 mu m) on the accuracy of modeled source contributions. Source apportionment results suggest that materials originating from incised and actively eroding channel banks were the most important source of sediment, which contribute over 80% of sediment to the catchment outlet. Sediment inputs from cropland (10-20%) and woodland (<10%) areas as a result of surface erosion were less important, since effective soil conservation measures have been implemented in this catchment. Although apportionment of sampled sediment provided comparable results for both coarser (<125 mu m) and fine (<63 mu m) size fractions, the artificial mixture results indicated that unmixing the coarse fraction alone could yield poor agreement between modeled source contributions and actual source proportions. The mean absolute error (MAE) for the coarse fraction mixtures ranged between 8.8% and 19.6%, with a mean of 13.6%, compared to the values of 4.0-7.4%, with a mean of 5.2% for the fine fractions. The results of this study highlight that channel bank materials constitute a significant fraction of suspended sediment exports in a heavily managed agricultural catchment, suggesting that future conservation works should be focused on drivers of erosion from this particular source type. Herein, it is surmised that reworking of legacy valley fill deposits is tempering the downstream benefits (e.g. reduced siltation) of recent upslope soil conservation, an important message for policy makers. The findings of this work also emphasize the methodological need to take account of potential uncertainties associate with source apportionments when using specific particle size fractions in fingerprinting studies.

Accurate assessment of soil erosion is an important prerequisite for controlling soil erosion. The engineering-control (E) and tillage (T) factors are the keys for Chinese Soil Loss Equation (CSLE) to accurately evaluate water erosion in China. Besides, the E and T factors can reflect the water and soil conservation effects of engineering-control and tillage practices. But in the current full coverage of soil erosion surveys in China (such as soil erosion dynamic monitoring), for the same practice, the E or T factors are assigned the same value across the country. We selected 469 E and T factors data based on runoff plots from 73 publications, and they came from six soil and water conservation regions. Correlation analysis, regression analysis, and nonparametric tests were used to determine the comparability of the data, and it was proved that the runoff plots dimensions are consistent with the local topography. The results of one-way ANOVA and nonparametric tests for E and T factors in different regions showed that the engineering-control practices have good soil and water conservation effects and weaken the regional differences of other environmental factors, so there were no significant differences in E factors between different regions. However, there were significant differences in T factors between different regions, and the geodetector was applied to explore the intrinsic driving force of the spatial distribution of T factors. The results of the geodetector showed that the dominant driving forces of the spatial distribution of different types of tillage practices were not completely the same. When using CSLE to calculate water erosion, the E factor of the same practice can be used uniformly throughout the country, and the T factor needs to be considered and selected according to regional differences. At the same time, when choosing tillage practices in each water and soil conservation region, practices with better sediment reduction benefits should also be selected according to the regional environmental conditions.

金沙江下游地区侵蚀泥沙研究基础薄弱,实测资料较少,可靠的泥沙来源信息尤其是一系列国家重点水土保持工程如“长治”工程实施后流域泥沙的主要来源及贡献,对该区未来水土保持和生态环境建设以及不同治理措施效益评价具有重要意义.利用低频磁化率xlf和放射性核素210Pbex双指纹因子,开展了金沙江下游一“长治”工程治理小流域(元谋县凉山乡小流域)泥沙来源研究.结果 表明,坡耕地表土、林地表土和沟谷堆积物三种物源的xlf和210Pbex平均含量分别为(21.81±9.43) ×10-8 m3/kg和40.53±9.49 Bq/kg、(24.06+9.61)×10-8 m3/kg和119.35±22.81Bq/kg、(16.60±5.27) ×10-8 m3/kg和30.62±12.69 Bq/kg.流域出口泥沙的xlf和210Pbex平均含量分别为(17.69±2.87) ×10-8 m3/kg和33.63±6.17 Bq/kg.混合模型计算结果表明凉山乡小流域泥沙主要来源于沟谷堆积物,相对贡献率为79.6％;未经治理的陡坡耕地产沙贡献率为19.1％;林地面积占比最大但泥沙贡献极微,仅1.3％.基于xlf和210Pbex的双指纹泥沙来源判别结果与利用地球化学元素复合指纹分析结果一致.受地质地貌等自然因素主控,沟谷侵蚀是金沙江下游河流泥沙的主要来源;以坡改梯和植被恢复为主的小流域治理工程对坡面侵蚀泥沙减控具有积极作用.该区未来水土保持工作应重点加强流域沟谷治理,降低泥石流等泥沙灾害风险.

掌握四川省省级水土流失重点防治区水土流失情况、空间分异规律及其内在驱动因素对生态预警和土壤侵蚀治理等具有重要意义.应用中国土壤流失方程(CSLE)计算四川省省级水土流失重点防治区土壤侵蚀状况,通过不同土壤侵蚀敏感性评价方法识别中国土壤流失方程(CSLE)敏感因子,借助地理探测器探究重点防治区土壤侵蚀空间分异规律及其内在驱动力.结果表明:四川省省级水土流失重点防治区水土流失面积占比27.16％,平均土壤侵蚀模数为806.08 t/(km2·a),属于轻度侵蚀,但区内土壤侵蚀差异明显,局部存在严重水土流失;土壤侵蚀敏感性分析表明,生物措施因子B是中国土壤流失方程(CSLE)中最敏感的因子;不同水土保持分区土壤侵蚀定量归因表明,土地利用方式是土壤侵蚀空间异质性的主要驱动力,且影响因子两两交互均能增加对土壤侵蚀空间分布的解释能力,各因子在不同水土保持分区作用程度存在显著差异.因而,在应用中国土壤流失方程(CSLE)计算土壤侵蚀量时,基于不同研究区针对较为敏感因子建立区域化算法是提高计算精度的关键.