Land-use conversion can substantially modify the soil properties that control water erosion, yet its effects on soil erodibility across different soil classes remain poorly understood in tropical ecotones. This study evaluated how land-use conversion influences soil erodibility (K factor) in the Rio da Prata watershed, located in the Cerrado–Atlantic Forest ecotone, Brazil. Soil physical attributes, aggregate stability, and erodibility were evaluated in the 0.0–0.10 m layer under native vegetation, pasture, and cropland across multiple soil classes using univariate and multivariate statistical analyses. Soil erodibility ranged from 0.0172 to 0.0415 Mg ha-1 MJ-1 mm-1, with croplands exhibiting values up to 2.4 times higher than pastures within the same soil class. Native vegetation and pasture systems maintained a higher proportion of macroaggregates (>2 mm), greater aggregate stability, and lower erodibility, whereas cultivated soils showed reduced aggregation and increased erosion susceptibility. Recently converted cropland exhibited intermediate soil conditions, indicating that structural degradation begins shortly after land-use conversion. The results demonstrate that soil aggregation was the primary driver of erodibility and that vegetation cover and land management can modify K values within the same soil class, indicating that soil erodibility should be treated as a dynamic property rather than a fixed taxonomic characteristic. These findings provide a scientific basis for improving erosion-risk assessment, USLE/RUSLE parameterization, conservation agriculture, and land-use planning in tropical watersheds.
Desert ecosystems in China and Egypt—two regions increasingly impacted by climate extremes—are among the most vulnerable to the effects of prolonged drought. This review synthesizes current understanding of how extreme drought events, exacerbated by global climate change, disrupt the overall productivity of desert ecosystems in both countries—altering vegetation dynamics, soil microbial activity, nutrient cycling, and the balance of carbon and energy flows that sustain ecosystem function. It addresses key questions including how droughts alter vegetation dynamics and species composition, and how these changes affect long-term ecosystem function in Chinese and Egyptian deserts. Findings reveal that in both countries, prolonged water deficits reduce plant growth and overall ecosystem productivity, shift species dominance, and disrupt photosynthesis, leading to biodiversity loss and weakened ecosystem resilience. Soil quality and productivity declines as microbial biomass and enzyme activity are suppressed, accelerating nutrient depletion and land degradation. In both the Gobi and Taklamakan deserts of China and the Sahara and Sinai deserts of Egypt, carbon sequestration is significantly diminished, with soils increasingly acting as carbon sources. Case studies highlight distinct regional vulnerabilities shaped by climatic, ecological, and land-use differences. The review underscores the urgent need for country-specific and cross-border strategies—including drought-resilient vegetation restoration, water-efficient technologies, sustainable land-use practices, and international scientific collaboration—to restore productivity, enhance ecosystem resilience and secure ecosystem services critical for local communities in both China and Egypt.
Ecosystem water use efficiency (WUE) is a key indicator of terrestrial carbon–water coupling, yet the mechanisms governing drought sensitivity across heterogeneous climatic and vegetation regimes remain poorly understood. This study examines the spatial variability, environmental controls, drought memory, and post-drought resilience of WUE across the Nile River Basin (NRB) from 2000 to 2024, using satellite-derived gross primary productivity (GPP) and evapotranspiration (ET), together with multi-timescale Standardized Precipitation Evapotranspiration Index (SPEI) data. WUE exhibited a pronounced north–south gradient, with higher, more stable values in humid upstream regions and lower or declining values in arid downstream areas. Air temperature, solar radiation, wind speed, and vapor pressure deficit were the dominant environmental controls, whereas precipitation and soil moisture exerted weaker, largely indirect influences. The relative contributions of GPP and ET to drought-related WUE variability varied with drought intensity, vegetation type, and climatic conditions. Drought exhibited substantial memory effects, with cumulative responses affecting 68% of the basin and an average response timescale of approximately 4 months. Lagged responses averaged 5.52 months and were generally longer in humid and sub-humid regions, consistent with greater soil and subsurface water storage. Approximately 64% of the basin was classified as resilient, although recovery dynamics varied among ecosystems, with forests exhibiting stronger drought buffering but slower recovery. Overall, WUE dynamics across the NRB reflect interactions among climate, vegetation, drought memory, and hydrological controls, highlighting the importance of distinguishing between atmospheric drought and ecosystem water stress under increasing hydroclimatic variability.
High-resolution mapping of soil sand content across interregional scales is essential for characterizing the physical heterogeneity of black soil regions and supporting sustainable agricultural management. However, existing studies commonly rely on a single global modeling strategy, limiting their ability to capture pedogenetic differences among geographic units. This study focused on two typical black soil regions in the Northern Hemisphere: Northeast China (NEC) and the Mississippi River Basin in North America (MNA). Using long-term Landsat-8 composite imagery from 2020–2024 and multi-source environmental covariates, a cross-regional global model and a local model considering spatial nonstationarity were developed. On this basis, recursive feature elimination with cross-validation (RFECV) and SHapley Additive exPlanations (SHAP) were introduced for predictor optimization and model interpretation. The results showed that the local modeling strategy substantially improved adaptation to regional heterogeneity, and after RFECV-based optimization the optimal model achieved an R2 of 0.810 and an RMSE of 8.802%. SHAP analysis revealed clear regional differences in dominant drivers. In NEC, sand content was primarily governed by climatic factors such as temperature and precipitation, whereas in MNA, spectral variables and soil silt content were more influential. Furthermore, soil-type-based analyses confirmed clear regional contrasts: within the same soil classes, sand content in MNA was generally higher and more variable than in NEC. The final 30-m resolution products revealed a northeast-to-southwest increase in sand content across cultivated lands in NEC and a fragmented spatial pattern in MNA. Overall, this study provides a robust framework for high-resolution intercontinental soil texture mapping.
Slopes covered with both grass cover (GC) and biological soil crusts (BSC) play a critical role in influencing rainfall-runoff processes within semi-arid regions. However, the limited understanding of runoff mechanisms on slopes covered with both GC and BSC hinders the effective utilization of water resources. The SCS-CN model is limited by its neglect of hydrological connectivity, which reduces the accurate assessment of runoff processes over the complex slope surface. This study focused on slopes covered by combinations of GC and BSC. Simulated rainfall experiments were conducted in boxes (2 m×1 m) filled with loess soil, under a rainfall intensity of 90 mm h-1. Close-range photogrammetry was used to reconstruct microtopography and quantify multidimensional hydrological connectivity indicators. The results showed that GC and BSC affected runoff parameters differently, with GC promoting infiltration and BSC increasing surface roughness and shortening flow length (FL). Consequently, the combination of GC-BSC significantly affected hydrological connectivity, with the FL decreased by 14.38%-40.15% compared to the bare soil, the topographic wetness index stabilized at 1.95, and the runoff coefficient in simplified hydrographs remained stable between 0.55 and 0.6. The original SCS-CN model shows significant deviations in runoff simulation for slopes covered with GC-BSC. In this study, the FL and the runoff retention coefficient (k) were incorporated into the SCS-CN model to redefine the potential maximum retention (S), and a calculation equation was constructed as S=S0+kFL. The revised model improved NSE from -19.92 to 0.75 and reduced RMSE by 87.86% for the validation dataset. This study revealed the regulatory mechanism of runoff generation by the combination of GC-BSC and provided a reliable scientific tool for ecological restoration in semi-arid regions.
Conservation tillage reduces soil disturbance and improves soil health. Due to its systematic, scalable, and cost-effective nature, remote sensing offers an efficient means to monitor conservation tillage. Reliable monitoring of conservation tillage remains a significant challenge because it requires remote sensing data with high spatial and temporal resolution, while optical observations can be hindered by cloudy and rainy weather conditions as well as by green vegetation. This study in central Indiana (USA) combined Landsat 8 OLI's high spatial resolution with Moderate Resolution Imaging Spectroradiometer (MODIS)'s high temporal resolution to estimate the normalized difference tillage index (NDTI) using three spatiotemporal fusion algorithms: spatial and temporal adaptive reflectance fusion model (STARFM), enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM), and flexible spatiotemporal data fusion (FSDAF). Their performance was assessed in predicting NDTI and crop residue cover (CRC), validated with field data across subregions with different cropland ratios. Results showed that ESTARFM achieved the best overall performance for NDTI prediction, with coefficient of determination (R2) values of 0.56–0.70 and positive NSE values of 0.26–0.45, outperforming STARFM and FSDAF. The proportion of cultivated land was associated with model performance, but it was not the sole controlling factor. The 2015 spatial distribution of CRC revealed pronounced heterogeneity across croplands, with values ranging from 0 % to 98 % and higher values mainly concentrated in the northern part of the study area, demonstrating the method's ability to characterize continuous residue-cover patterns. The integration of multi-source remote sensing and ESTARFM offers a practical approach for large-scale residue-cover monitoring.
Intensive plastic mulch application has improved agricultural productivity. However, fragmentary microplastic residues accumulate in soils, potentially degrading surface soil hydraulic properties while being prone to overland transport. As soil surfaces act as dynamic pollutant sources for both overland and subsurface transport during erosive rainfall, both transport processes are mechanistically coupled and must be conjunctively understood to characterize microplastic fate. Accordingly, a flume experiment was conducted to simulate coupled overland and subsurface microplastic transport at two slopes (5°, 10°) under 1.5 mm min−1 rainfall intensity for 1 h. The uppermost 1 cm of soil was spiked with 0.025 % by weight microplastics, comprising a mixture of debris and particles, to simulate agricultural plastic mulch residues. Results showed that 4.8 % and 6.4 % of microplastics were transported overland at 5° and 10° slope, respectively. The overland transported microplastics occurred mostly within runoff, while a small proportion settled with the eroded soil sediments. The transport behavior of debris and particles differed substantially, including the sensitivities of the overland and subsurface fluxes to slope, temporal dynamics of concentration profiles within the runoff and eroded sediment, and mass distributions across runoff, sediment, and various soil depths. Therefore, microplastics are susceptible to overland transport due to low subsurface mobility, which may be most severe in arid croplands, where soil erosion, plastic mulching, and limited rainwater infiltration are prevalent. This study advances understanding of how rainfall-induced soil erosion may drive expanding shallow soil microplastic pollution, which is susceptible to further erosive rainfall, and distinct for microplastics of different characteristics.
Microbial necromass carbon (MNC), a critical component of the soil organic carbon (SOC) pool, constitutes a key component on global carbon cycling via the dynamic equilibrium between its formation and decomposition. In aquatic-terrestrial interfaces (e.g., river systems), hydrodynamic disturbances may critically regulate the fate of MNC during terrestrial-to-aquatic carbon transport. However, dynamic responses of MNC to hydrodynamic disturbances during lateral transport remain systematically underexplored. This study employed controlled experiments simulating lateral transport processes to unravel hydrodynamic disturbance-driven MNC depletion mechanisms. Results demonstrated that hydrodynamic disturbances significantly reduced the contribution of MNC to SOC (disturbance treatment: 46.65% vs. control: 55.17%; P < 0.001). In contrast, inundation alone (static water treatment: 59.32% vs. control: 55.17%; P > 0.05) exerted negligible influence. Path analysis revealed the core mechanisms of hydrodynamic suppression on MNC accumulation: (1) triggering positive “desorption-mineralization” feedback by destabilizing MNC occurrence forms and enhancing hydrolytic enzyme activity (path coefficient = 0.60, P < 0.05); (2) generating negative “re-synthesis” feedback through reduced microbial biomass inputs (path coefficient = -0.48, P < 0.05). Synergistic interactions between these coupled pathways ultimately suppressed MNC accumulation (standardized total effect = -0.39). These findings advance theoretical understanding of carbon cycling during lateral transport and provide critical insights for optimizing soil carbon conservation and ecological management strategies in erosion-prone regions.
Soil and water conservation practices (SWCPs) have been widely applied in the highlands of Ethiopia to combat land degradation, increase crop productivity, and enhance soil properties. However, information on these practices is limited for the lowlands, particularly for the Beles River Basin (BRB). This study aimed to evaluate the effects of SWCPs on crop productivity and selected soil properties in the warm, sub-humid lowlands of the middle BRB. The experiment was conducted using a randomized complete block design with three replications. Five treatments were evaluated: conventional practice (C), conservation agriculture (CA), vetiver grass strips (VGS), soil bund (SB), and Fanya juu (FJ). Finger millet, soybean, and maize were grown in consecutive years. Soil and agronomic data were collected from the plots. Results showed that soil attributes and crop productivity were significantly influenced by SWCP (p < 0.05). The highest values for soil moisture (22.3 %), soil organic carbon (2.55 %), total nitrogen (0.22 %), available phosphorus (2.22 mg/kg), and cation exchange capacity (23.3 cmol+/kg, and the lowest bulk density (1.11 g/cm) were observed under CA compared to C. Similarly, CA increased grain and biomass yield by 63.2 and 58.5 %, respectively. The use of CA decreased Striga infestation and significantly (p < 0.05) increased the days to maturity, thousand-seed weight, and grain and biomass yields of finger millet and maize. Partial least squares regression identified SOC, TN, and CEC as the most influential predictors of grain yield. Continued monitoring is recommended to assess the long-term impacts of physical SWC measures on crop productivity and soil quality.
The livelihoods of millions of people from five countries rely on the water resources of the transboundary Amudarya River basin, one of the most important freshwater systems in Central Asia. However, climate change (CC) and human activities (HA) have substantially altered the hydrological processes in the basin. This study provides one of the first comprehensive impact assessments of CC and HA on streamflow changes by analysing 90 years of simulated streamflow in this climate data-scarce region, using the hydrological modeling approach and climate elasticity. The data limitations were addressed by integrating multiple sources, including local and global datasets. The CC and HA's impacts were separately quantified at 29 sites across all the main Amudarya tributaries for 1951–2020 relative to 1931–1950. The results showed a substantial increase in temperature (0.51–0.83 °C) and precipitation (6–13 %) in the entire basin. Streamflow decreased by 54–77 % in the middle and lower reaches. Attribution analysis showed that human activities were the dominant driver of this decline, contributing 114–120 % of the net reduction, while climate change partly offset the decline by increasing streamflow by 14–20 %, mainly through increased precipitation. In the headwater region, streamflow decreased by 22 %, with human activities contributing 140 % of the net decline, offsetting the positive contribution from climate change. Major tributaries, including the Vakhsh, Kunduz, Kofirnihon, Surkhandarya, Zeravshan, and Qashqadarya, showed streamflow reductions of 4–34 %, primarily attributed to HA. Climate elasticity revealed precipitation as the most sensitive element in the region, with an elasticity of 1.25. These latest and comprehensive findings provide valuable insights for improving water resources planning and management in the region under changing climatic and anthropogenic pressures.
Climate change affects the quality, character and overall structure of the soil, which is a key factor to most ecosystems around the world. This study intends to systematically review the impacts of climate-change on soil-health. The analysis focuses on its implications for achieving Sustainable Development Goals (SDGs), particularly SDG 2, SDG 6, SDG 13, and SDG15. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines; 41 peer-reviewed articles were selected published between 2000-2024 from databases (Science-Direct, Springer, SAGE Publications, and Wiley Online-Library). This review found that droughts have reduced soil moisture by 25-35%. Decomposition processes have accelerated the loss of soil organic matter by 30-50%. Additionally, microbial biomass and diversity have declined by 20-45%. These changes affect nutrient cycling, carbon sequestration reduction up to 40% and crop productivity declined for 10-25% which affects Sustainable Development Goals (SDGs) 2, 6, 13 and 15. Technologically improved land management practices (conservation tillage, intensive fallows, and cover crops) increase the productivity of soil by up to 30%, while simultaneously increasing soil carbon sequestration by 15-20%, and reduction of greenhouse gas emissions by between 10-18%. There is uncertainty in modeling soil-climate connectivity, the effects of climatic shocks like intense rainfall which may lead to 60% enhancement of soil erosion, requiring further refinement. The findings emphasize the importance of integrated soil-conservation strategies; to enhance ecosystem-resilience, and mitigate climate-impacts, and stresses to support sustainable-development.
Agricultural runoff is a major source of water pollution, particularly in tile-drained landscapes where fields are engineered to move water rapidly off the land, enabling earlier spring field operations. At present, few tools help farmers and watershed managers identify the most suitable best management practices (BMPs) to mitigate this nonpoint source pollution. For example, the Agricultural Conservation Planning Framework (ACPF) effectively identifies potential BMPs. However, it does not rank field-specific options or incorporate regional stakeholder priorities. To address this gap, this study developed a field-specific BMP assignment framework that converts conservation opportunity maps into ranked BMP recommendations by integrating hydrogeomorphic suitability, conservation-need classes, feasibility constraints, and stakeholder-adjustable policy weights. The framework was applied to 627 agricultural fields in the Medway Creek watershed, southern Ontario, using ACPF-derived spatial datasets, field-survey information from 138 fields, hydrogeomorphic clustering, a Composite BMP Need Score (CBNS), and multi-criteria BMP analysis. Four hydrogeomorphic field typologies were identified, and repeated K-means testing showed high cluster stability. Under a balanced multi-criteria setting, controlled drainage was the most frequent top-ranked practice, recommended for 292 fields, followed by grassed waterways, water and sediment control basins, wetlands, and riparian buffers. Sensitivity analysis and field-record consistency assessment supported the BMP ranking logic, indicating that stakeholder inputs refined the rankings without dominating the biophysically relevant suggestions. The field-specific thematic maps developed in this study provide spatially explicit decision support for prioritizing the right BMP in the right place, while final implementation requires local verification, engineering design, cost assessment, and landowner consultation.
Understanding how reduced soil disturbance restructures aggregates and influences soil organic carbon content is critical for sustaining calcareous soils under intensive cropping. Using a 15-year field experiment in the eastern Indo-Gangetic Plains (IGP), this study examined how long-term conservation tillage and residue management regulate soil aggregation and carbon distribution in a calcareous rice–wheat system. Eight treatment combinations of tillage method, crop establishment and residue management were evaluated. Soils were sampled at 0-5, 5-15 and 15-30 cm depths. Zero tillage with residue retention consistently increased soil organic carbon across all depths while reducing soil inorganic carbon, indicating a shift in carbon distribution under reduced disturbance. Conservation tillage promoted aggregate restructuring by increasing the proportion of macro-aggregates, mean weight diameter, geometric mean diameter, and the fraction of water-stable aggregates larger than 0.25 mm. These changes were accompanied by lower fractal dimensions, reduced aggregate breakdown during wetting, and higher soil stability indices, which together indicate stronger and more coherent aggregate structures. In contrast, conventional tillage, particularly puddling for rice, intensified aggregate fragmentation, increased micro-aggregate dominance, and accelerated aggregate breakdown upon wetting. Aggregate stability and soil organic carbon concentrations declined with depth across all treatments, but conservation systems maintained clear structural advantages throughout the soil profile. Profile-scale analysis using a linear mixed-effects modelling framework confirmed that management-related differences in water-stable aggregate properties and soil organic carbon content were strongly depth-dependent, indicating that the benefits of conservation-based systems extend beyond surface layers. Overall, the results demonstrate that decadal conservation tillage is associated with higher soil organic carbon and more stable aggregates under reduced mechanical disturbance, highlighting its importance for restoring soil structural resilience and long-term sustainability in calcareous agroecosystems.
The efficacy of current soil and water conservation measures (SWCMs) in managing runoff and sediment has been confirmed at the plot scale. However, the effectiveness of conventional measures has been challenged by extreme rainfall and steep slopes, and systematic assessments of the benefits of combined measures are lacking. This study conducted a meta-analysis of 1399 runoff pairs and 1117 soil erosion pairs from 87 studies (2000–2025) to evaluate the effectiveness of various SWCMs and the moderating effects of slope and rainfall. SWCMs were categorized into single measures (biological measures [BMs], engineering measures [EMs], and soil management measures [SMs]) and combined measures (e.g., BMs + EMs). Findings indicate that SWCMs reduce runoff by 58.5 % and soil loss by 82.4 % on average. Runoff and sediment reduction benefits peak on 15–20° slopes when considering slope gradient, and under heavy rainfall when considering rainfall intensity; however, they generally decline under extreme rainfall. This suggests that the combination of steep slopes and extreme rainfall further reduces the protective benefits of these SWCMs. Under slope gradients of 15–20° and I30 < 60 mm/h, combined measures show noticeably greater benefits than single measures; the BMs + EMs approach performs the best. Overall, this study proposes a climate-adaptive “slope-measure” synergistic architecture to provide a scientific basis for optimizing SWCM structure and addressing extreme rainfall erosion risk intensified by steep slopes.
Over the past few decades, widespread vegetation greening has occurred globally, with China exhibiting the most pronounced increase. Integrating multi-source satellite vegetation indices and land-use data, this study employs RUSLE and trend analysis to characterize greening's impact on soil erosion in China. From 1982 to 2021, China exhibited a significant greening trend, with 68.1 % of its vegetated area showing significant increases in vegetation growth (p < 0.05), whereas only 2.5 % experienced significant browning trend. Over the past 40 years, vegetation greening has led to a reduction of soil erosion rate (SER) and soil erosion amount (SEA) by 35.9 % and 41.1 %, with an average decrease of 0.17 t ha−1 y−1 and 0.15 Pg y−1, respectively. However, these mitigation effects were spatially heterogeneous: significant erosion reduction was concentrated in key ecological project areas like the southwestern Karst region and the northwestern Loess plateau region. In contrast, mitigation was negligible in arid areas like the northern windy sand region. Nationally, the reduction of erosion by forestland (SER: 6.63 t ha−1 y−1; SEA: 4.09 Pg) was larger than cropland (SER: 1.51 t ha−1 y−1; SEA: 0.96 Pg) and grassland (SER: 1.37 t ha−1 y−1; SEA: 0.73 Pg), emphasizing the critical role of forests in erosion control. These findings provide a scientific basis for optimizing vegetation configuration in ecologically fragile regions and maintaining existing vegetation health to mitigate soil erosion.
Reducing river basin sediment loads is a common goal of erosion management programs, yet resources are limited. Research has focused on identifying sediment source areas and processes and defining erosion control practices. However, achieving targeted and efficient sediment management requires decision support systems based on cost-effectiveness. A method was developed to prospectively assess the cost-effectiveness of rehabilitating gully and streambank sites, being the cost to reduce future sediment yield by 1 tonne per year. Sediment reduction was calculated as the untreated yield multiplied by the effectiveness of erosion treatments, which ranged between 10 and 80 percent. The method was applied to 273 sites in river basins flowing to the Great Barrier Reef coast. Cost-effectiveness varied by 2 to 3 orders of magnitude, driven mainly by untreated sediment loads and treatment costs. Cost-effectiveness was better at sites with low unit-area treatment costs, large areas and high sediment connectivity to the basin outlet. Revegetation was more cost effective than structural treatments. Streambank sites were more cost-effective than gullies. Rapid erosion was more cost-effectively treated than slow erosion. Assessment during management planning helped to avoid sites with poor cost-effectiveness and to match treatment intensity to erosion severity. Despite these gains, material sediment reductions require large investments. The cost to reduce GBR sediment loads by 25% of current loads is at least AUD$1 billion. Concurrent land use intensification and climate change could potentially increase sediment loads. Better estimation of historical erosion rates and further monitoring of treatment effectiveness will reduce uncertainties in the approach.
Recognized for their exceptional fertility and agricultural productivity, Chernozems, Phaeozems, Kastanozems, and Mollisols have attracted sustained scientific attention over the past century. However, much of this work has focused on degradation, conservation, carbon sequestration, and agricultural impacts, whereas scientific classification and global pedogenic factors have received comparatively less attention. Referred to collectively as ‘black soils’ for their characteristic dark color, these soils are often grouped together in public and academic discourse, even though they may differ considerably in origin, environment, and detailed classification. Drawing on more than 150 studies worldwide, this review synthesizes current knowledge of how black soils form and evolve across different regions of the globe. Specifically, we examine: (1) research trends in publication records; (2) formation ages and chronological development based on literature data; (3) pedogenic conditions shaped by key environmental factors and representative soil profiles; (4) principal proxies and methodologies used to investigate black-soil genesis; and (5) disturbance regimes such as wildfire, volcanic activity, and permafrost thaw. The accumulated evidence highlights both the remarkable difficulty and the slow pace of black-soil accumulation, where the formation of even 1 mm may require centuries. These insights emphasize the urgent need for greater scientific attention and for immediate measures to preserve and restore these critical resources. Advances in understanding pedogenic mechanisms, including humus accumulation, carbonate dynamics, and horizon differentiation, provide an essential scientific basis for conservation strategies to mitigate erosion, nutrient depletion, and organic matter loss in black-soil regions.
Understanding the factors influencing soil erosion in agricultural catchments is crucial to reduce land degradation. This study investigated the benefit of disdrometer information beyond rain-gauge observations and the factors that explain the variability in event-scale suspended sediment load. The study seasonally assessed multi-year, high frequency observations of rain-gauge and disdrometer-based rainfall and suspended sediment load measurements in the 66 ha Hydrological Open Air Laboratory agricultural catchment in Austria. Hydrometric and land management information was combined to understand the factors controlling erosion. The results confirmed that the kinetic energy of rainfall and rainfall erosivity estimated by disdrometer and rain gauge data were comparable (r = 0.93 and 0.95, respectively). Rainfall erosivity alone did not fully explain the observed variability in SSL. Winter events with small kinetic energy caused large total event suspended sediment load because bare and saturated soils reinforced surface runoff. In the spring and summer months, the average size and velocity of the drops were the largest and events with larger number of drops in the most frequent velocity class were associated with larger total event suspended sediment load. In spring and summer, the sediment response to a given level of rainfall erosivity was modulated by land management state and antecedent soil moisture rather than by rainfall properties alone. This study demonstrated that instead of disdrometers rain gauge-based estimates can suffice to estimate the erosivity of rainfall events which can be linked to soil erosion. Still, the disdrometer data provided additional knowledge on detailed characteristics of the rainfall events.
As a key variable in soil erosion models, soil erodibility is strongly linked to alterations in vegetation and soil properties driven by land use and climate change. Thus, accurate quantification of the temporal variation among land use types is highly important for optimizing vegetation selection to meet the demand for dynamic changes in soil erosion. This study was aimed at quantifying the temporal variation in soil erodibility among land use types and elucidating the climate-vegetation-soil interaction mechanisms attributed to these variations in the Three Gorges Reservoir area (TGRA). Six typical land use types of slope farmland (SF), broadleaf forestland (BF), coniferous forestland (CF), economic fruit forestland (EF), shrubland (S), and grassland (G) were selected, and a comprehensive soil erodibility index (CSEI) derived from eight soil erodibility indicators was applied to assess soil erodibility. The results demonstrated that the temporal variation in CSEI differed among land use types. The CSEI of the SF fluctuated over time, whereas that of the other land use types first decreased but then gradually increased. Overall, compared with the CSEI of SF, the mean CSEIs of EF, G, S, CF, and BF decreased by 4.81%, 18.97%, 37.83%, 51.25%, and 51.59%, respectively. Temporal variation in the CSEI was comprehensively affected by alterations in vegetation characteristics and soil properties driven by vegetation growth and agricultural activities, but their influencing mechanisms varied with land use types. For SF and EF, temporal variation in the CSEI was primarily controlled by agricultural activities, whereas for other land use types, it was governed by vegetation. Nevertheless, compared with the land use types of CF, S, and G, the temporal variation in the CSEI of BF was influenced not only by the indirect effect of vegetation on improving soil structure but also by its direct mechanical stabilization function. These findings advance our understanding of the mechanism through which climate-vegetation-soil interactions influence soil erodibility, and they provide a practical basis for selecting optimal land use types to prevent soil and water loss in the TGRA.
Assessing the spatiotemporal variations and driving factors of sediment load (SL) in the Yellow River Basin (YRB) is fundamental for scientific governance and targeted management. This study quantifies the spatiotemporal dynamics of SL and sediment budgets across different sections of the YRB, utilizing observations from 110 gauging stations from the 1950s to 2021. A hybrid framework integrating machine learning with the LOADEST model was employed to reconstruct natural SL and distinguish the impacts of climate change and human activities. Annual SL declined consistently and significantly along the main stream and most tributaries, except in the source regions. The most pronounced reduction occurred in the middle and lower reaches of the YRB, where SL decreased by approximately 86–92 % during 2000–2021 relative to the 1950s–1968. The Lanzhou–Toudaoguai section underwent sediment deposition, whereas the Toudaoguai–Tongguan section exhibited a source-to-sink dynamic that facilitated downstream sediment flushing. The Water–Sediment Regulation Scheme, implemented by Sanmenxia and Xiaolangdi reservoirs, has significantly enhanced downstream flushing, resulting in substantial increases in sediment transport from Huayuankou to Lijin since 2002. Human activities, including reservoir construction and soil and water conservation measures, contributed approximately 77–83 % to SL reduction in the YRB during 2002–2021. Sustainable ecological restoration and sediment regulation strategies are essential for improving water use efficiency, maintaining or restoring ecosystem balance, and advancing the overall sustainable development of the YRB. These findings could offer valuable insights for the long-term ecological restoration and sediment management.
