Search Results (1,185)

Post-fire soil and vegetation changes can intensify erosion and sediment yield by altering the factors controlling the runoff–infiltration balance. Erosion barriers (EBs) are widely used in hydrological and forest restoration to mitigate erosion, reduce sediment transport, and promote vegetation recovery. However, precise spatial assessments of their effectiveness remain scarce, requiring validation through operational methodologies. This study evaluates the impact of EB on post-fire vegetation recovery at two temporal and spatial scales: (1) Remotely Piloted Aircraft System (RPAS) imagery, acquired at high spatial resolution but limited to a single acquisition date coinciding with the field flight. These data were captured using a MicaSense RedEdge-MX multispectral camera and an RGB optical sensor (SODA), from which NDVI and vegetation height were derived through aerial photogrammetry and digital surface models (DSMs). (2) Sentinel-2 satellite imagery, offering coarser spatial resolution but enabling multi-temporal analysis, through NDVI time series spanning four consecutive years. The study was conducted in the area of the Luna Fire (northern Spain), which burned in July 2015. A paired sampling design compared upstream and downstream areas of burned wood stacks and control sites using NDVI values and vegetation height. Results showed slightly higher NDVI values (0.45) upstream of the EB (p < 0.05), while vegetation height was, on average, ~8 cm lower than in control sites (p > 0.05). Sentinel-2 analysis revealed significant differences in NDVI distributions between treatments (p < 0.05), although mean values were similar (~0.32), both showing positive trends over four years. This study offers indirect insight into the functioning and effectiveness of EB in post-fire recovery. The findings highlight the need for continued monitoring of treated areas to better understand environmental responses over time and to inform more effective land management strategies. Full article

Preventing soil degradation caused by water erosion is essential for sustainable agriculture and long-term agroecological development. The objective of this study was to evaluate the effectiveness of an ethylene-vinyl acetate (EVA) polymer-based soil conditioner in mitigating soil erosion, a key driver of soil degradation. Laboratory experiments and simulations employing the Water Erosion Prediction Project (WEPP) model were conducted to assess soil erodibility parameters and sediment yield of two soil types from Okinawa, Japan. A key contribution of this work is the integration of these experimentally determined erodibility parameters into the WEPP model for robust validation. Interrill and rill erosion processes were analyzed under different soil conditioner application rates. Laboratory results showed that applying the soil conditioner reduced interrill erodibility by 59 to 99% and rill erodibility by 65 to 100%, while increasing critical shear stress and water infiltration rate. The effectiveness varied between the two soil types due to differences in particle-size distribution and inherent erodibility. The soil conditioner exhibited a more pronounced impact on rill erosion. WEPP simulations confirmed sediment yield reductions of 73% to 99%, primarily influenced by changes in rill erodibility and critical shear stress. While its practical application will be subject to various field conditions, our findings confirm the significant potential of this soil conditioner as a strategy for preserving topsoil resources. Full article

Soil erosion is an increasingly severe problem and a global focus. As one of the countries facing relatively serious soil erosion, China encounters significant ecological challenges. This study focuses on the carbon sink benefits of comprehensive soil and water conservation management in the red soil erosion area of southern China, conducting an in-depth analysis using the Ziyang small watershed in Shangyou County, Jiangxi Province, as a typical case. Research methods involved constructing an integrated monitoring approach combining basic data, measured data, and remote sensing data. Changes in soil and vegetation carbon storage in the Ziyang small watershed across different years were determined by establishing a baseline scenario and applying inverse distance spatial interpolation, quadrat calculation, feature extraction, and screening. The results indicate that from 2002 to 2023, after 21 years of continuous implementation of various soil and water conservation measures under comprehensive watershed management, the carbon storage of the Ziyang small watershed increased significantly, yielding a net carbon sink of 54,537.28 tC. Tending and Management of Coniferous and Broad-leaved Mixed Forest, Low-efficiency Forest Improvement, and Thinning and Tending contributed substantially to the carbon sink, accounting for 72.72% collectively. Furthermore, the carbon sink capacity of the small watershed exhibited spatial variation influenced by management measures: areas with high carbon density were primarily concentrated within zones of Tending and Management of Coniferous and Broad-leaved Mixed Forest, while areas with low carbon density were mainly found within zones of Bamboo Forest Tending and Reclamation. The increase in watershed carbon storage was attributed to contributions from both vegetation and soil carbon pools. Comprehensive management of soil erosion demonstrates a significant carbon accumulation effect. The annual growth rate of vegetation carbon storage was higher than that of soil carbon storage, yet the proportion of soil carbon storage increased yearly. This study provides a theoretical basis and data foundation for the comprehensive management of soil and water conservation in small watersheds in the southern red soil erosion region of China and can offer technical and methodological support for other soil and water conservation carbon sink projects in this area. Full article

Multi-centennial C budgets in forested watersheds require information on forest growth, detritus turnover, and disturbances, as well as the transfer to and fate of terrestrial C in aquatics systems. Here, a sediment gravity core was collected from a drinking water reservoir in Canada, and analyzed for temporal changes in charcoal, magnetic susceptibility, carbon, and nitrogen. These indicators were used to assess disturbance history and terrestrial C sequestration in sediments. During the reservoir development period from 1910 to 2012, charcoal flux and magnetic susceptibility increased ca. 10 years after nearby fire and forest-clearing events associated with reservoir expansion. Total C and δ¹³C gradually declined during the development period, likely due to increased inputs of mineral soil from human activity. Concurrently, total terrestrial C sequestered in sediments, estimated using three or eight marker compounds, ranged between 3557 and 5145 Mg C/100 yrs, accounting for 11%–17% of DOC exports to the reservoir (30,640 Mg C/100 yrs), as estimated from a previously developed terrestrial carbon budget model. In comparison, mixed-severity fires burned around the reservoir during the pre-development period (pre-1910), as evidenced by stand ages and/or increases in charcoal flux. In general, decreased terrestrial C flux was associated with higher-severity fires that burned between 1870 and 1890 and perhaps around 1790. Further, comparisons show that soil erosion was up to 3× greater in the development versus the pre-development period. Overall, this investigation revealed the impact of land use change and fire on watershed carbon budgets and advanced a previously developed pyGC-MS methodology that demonstrated the amount of terrestrial and aquatic C being buried in sediment. It also identified the fraction of terrestrial C that was exported from the forest to the reservoir and sequestered in the sediment, uncommon data that could inform current and future landscape C budget modelling studies in this region. Full article

Gully erosion, driven by the interplay of natural processes and human activities, results in severe soil degradation and landscape alteration, yet approaches for accurately quantifying erosion triggered by extreme precipitation using multi-source high-resolution remote sensing remain limited. This study first extracted digital surface models (DSM) for the years 2014 and 2024 using Ziyuan-3 and GaoFen-7 satellite stereo imagery, respectively. Subsequently, the DSM was calibrated using high-resolution unmanned aerial vehicle photogrammetry data to enhance elevation accuracy. Based on the corrected DSMs, gully erosion depths from 2014 to 2024 were quantified. Erosion patches were identified through a deep learning framework applied to GaoFen-1 and GaoFen-2 imagery. The analysis further explored the influences of natural processes and anthropogenic activities on elevation changes within the gully erosion watershed. Topographic monitoring in the Sandu River watershed revealed a net elevation loss of 2.6 m over 2014–2024, with erosion depths up to 8 m in some sub-watersheds. Elevation changes are primarily driven by extreme precipitation-induced erosion alongside human activities, resulting in substantial spatial variability in surface lowering across the watershed. This approach provides a refined assessment of the spatial and temporal evolution of gully erosion, offering valuable insights for soil conservation and sustainable land management strategies in the Loess Plateau region. Full article

Snowmelt runoff is a major soil erosion trigger in mid-to-high latitude and altitude regions. Through runoff plot observations and simulations in the northeastern black soil region, this study reveals the key regulatory mechanism of water migration on snowmelt erosion. Results demonstrate that the interaction between thawed upper and frozen lower soil layers creates a significant hydraulic gradient during snowmelt. Impermeability of the frozen layer causes meltwater accumulation and moisture supersaturation (>47%, exceeding field capacity) in the upper layer. Freeze–thaw action accelerates vertical moisture migration and redistributes shallow moisture by increasing porosity. This process causes soils with high initial moisture to reach supersaturation faster, triggering earlier and more frequent erosion. Gray correlation analysis shows that soil moisture migration’s contribution to erosion intensity is layered: migration in shallow soil (0–10 cm) correlates most strongly with surface erosion; migration in deep soil (10–15 cm) exhibits a U-shaped contribution due to freeze–thaw front boundary effects. A regression model identified key controlling factors (VIP > 1.0): changes in bulk density, porosity, and permeability of deep soil significantly regulate erosion intensity. The nonlinear relationship between erosion intensity and moisture content (R² = 0.82) confirms supersaturation dominance. Physical structure and mechanical properties of unfrozen layers regulate erosion dynamics via moisture migration. These findings clarify the key mechanism of moisture migration governing snowmelt erosion, providing a critical scientific foundation for developing targeted soil conservation strategies and advancing regional prediction models essential for sustainable land management under changing winter climates. Full article

The Yellow River Basin (YRB), a pivotal ecoregion in China, has long been plagued by a range of ecological problems, including water loss, soil erosion, and ecological degradation. Despite previous reports on the ecological environment of YRB, systematic studies on the multi-factor driving mechanism and the coupling between the ecological and hydrological systems remain scarce. In this study, with multi-source remote-sensing imagery and measured hydrological data, the random forest (RF) model and the geographical detector (GD) technique were employed to quantify the dynamic spatiotemporal changes in the ecological environment of YRB in 2000–2024 and identify the driving factors. The variables analyzed in this study included gross primary productivity (GPP), fractional vegetation cover (FVC), land use and cover change (LUCC), meteorological statistics, as well as runoff and sediment data measured at hydrological stations in YRB. The main findings are as follows: first, the GPP and FVC increased significantly by 37.9% and 18.0%, respectively, in YRB in 2000–2024; second, LUCC was the strongest driver of spatiotemporal changes in the ecological environment of YRB; third, precipitation and runoff contributed positively to vegetation growth, whereas the sediment played a contrary role, and the response of ecological variables to the hydrological processes exhibited a time lag of 1–2 years. This study is expected to provide scientific insights into ecological conservation and water resources management in YRB, and offer a decision-making basis for the design of sustainability policies and eco-restoration initiatives. Full article

In recent years, under the dual pressures of climate change and human activities, wetlands in Liaoning Province, China, are increasingly threatened, raising concerns about regional ecological security. To better understand these changes, we developed a vulnerability assessment framework integrating a 30 m wetland dataset (2000–2020) with multi-source environmental and socio-economic data. Using the XGBoost–SHAP model, we analyzed wetland spatiotemporal evolution, driving mechanisms, and ecological vulnerability. Results show the following: (1) ecosystem service functions exhibited significant spatiotemporal differentiation; carbon storage has generally increased, water conservation capacity has significantly improved in the northern region, while wind erosion control and soil retention functions have declined due to urban expansion and agricultural development; (2) driving factors had evolved dynamically, shifting from population density in the early period to increasing influences of precipitation, vegetation index, GDP, and wetland area in later years; (3) ecologically vulnerable areas demonstrated a pattern of fragmented patches coexisting with zonal distribution, forming a three-level spatial gradient of ecological vulnerability—high in the north, moderate in the central region, and low in the southeast. These findings demonstrate the cascading effects of natural and human drivers on wetland ecosystems, and provide a sound scientific basis for targeted conservation, ecological restoration, and adaptive management in Liaoning Province. Full article

Farmland shelterbelts are vital ecological infrastructure for sustaining agriculture in arid regions, where high winds, soil erosion, and water scarcity severely constrain productivity. While their protective functions—reducing wind speed, controlling erosion, moderating microclimates, and enhancing yields—are well documented, previous studies have largely examined individual structural elements in isolation, leaving their interactive effects and trade-offs poorly understood. This review synthesizes current research on the structural optimization of shelterbelts, emphasizing the critical relationship between their physical and biological attributes and their protective functions. Key structural parameters—such as optical porosity, height, width, orientation, and species composition—are examined for their individual and interactive impacts on shelterbelt performance. Empirical and modeling studies indicate that moderate porosity maximizes wind reduction efficiency and extends the leeward protection zone, while multi-row, multi-species configurations effectively suppress soil erosion and improve microclimate conditions. Sheltered areas experience reduced evapotranspiration, increased humidity, and moderated temperatures, collectively enhancing crop water use efficiency and yielding significant improvements in crop production. Advanced methodologies, including field monitoring, wind tunnel testing, computational fluid dynamics, and remote sensing, are employed to quantify benefits and refine designs. A multi-objective optimization framework is essential to balance competing goals: maximizing wind reduction, minimizing water consumption, enhancing biodiversity, and ensuring economic viability. Future challenges involve adapting designs to climate change, integrating water-efficient and native species, leveraging artificial intelligence for predictive modeling, and addressing socio-economic barriers to implementation. Building on this evidence, we propose a multi-objective optimization framework to balance competing goals: maximizing wind protection, minimizing water use, enhancing biodiversity, and ensuring economic viability. We identify key research gaps including unresolved porosity thresholds, the climate resilience of alternative species compositions, and the limited application of optimization algorithms and outline future priorities such as region-specific design guidelines, AI-driven predictive models, and policy incentives. This review offers a novel, trade-off–aware synthesis to guide next-generation shelterbelt design in arid agriculture. Full article

Drought is an extremely terrifying environmental calamity, causing declining agricultural production, escalating food prices, water scarcity, soil erosion, increased wildfire risks, and changes in ecosystem. Drought data is noisy and poses challenges to accurate forecasts due to it being nonstationary and non-linear. This research aims to construct a contemporary and novel approach termed as TVFEMD-GPR, crossbreeding time varying filter-based empirical mode decomposition (TVFEMD) and gaussian process regression (GPR), to model multi-scaler standardized precipitation index (SPI) to forecast droughts. At first, the statistically significant lags at (t − 1) were computed via partial auto-correlation function (PACF). In the second step, the TVFEMD splits the (t − 1) lag into several factors named as intrinsic mode functions (IMFs) and residual components. The third step is the final step, where the GPR model took the IMFs and residual as input predictors to forecast one-month SPI (SPI1), three-months SPI (SPI3), six-months SPI (SPI6), and twelve-months SPI1 (SPI12) for Mackay and Springfield stations in Australia. To benchmark the new TVFEMD-GPR model, the long short-term memory (LSTM), boosted regression tree (BRT), and cascaded forward neural network (CFNN) were also developed to assess their accuracy in drought forecasting. Moreover, the TVFEMD was integrated to create TVFEMD-LSTM, TVFEMD-BRT, and TVFEMD-CFNN models to forecast multi-scaler SPI where the TVFEMD-GPR surpassed all comparable models in both stations. The outcomes proved that the TVFEMD-GPR outperformed comparable models by acquiring ENS = 0.5054, IA = 0.8082, U95% = 1.8943 (SPI1), ENS = 0.6564, IA = 0.8893, U95% = 1.5745(SPI3), ENS = 0.8237, IA = 0.9502, U95% = 1.1123 (SPI6), and ENS = 0.9285, IA = 0.9813, U95% = 0.7228 (SPI12) for Mackay Station. For Station 2 (Springfield), the TVFEMD-GPR obtained these metrics as ENS = 0.5192, IA = 0.8182, U95% = 1.9100 (SPI1), ENS = 0.6716, IA = 0.8953, U95% = 1.5163 (SPI3), ENS = 0.8289, IA = 0.9534, U95% = 1.1296 (SPI6), and ENS = 0.9311, IA = 0.9829, and U95% = 0.7695 (SPI12). The research exhibits the practicality of the TVFEMD-GPR model to anticipate drought events, minimize their impacts, and implement timely mitigation strategies. Moreover, the TVFEMD-GPR can assist in early warning systems, better water management, and reducing economic losses. Full article

This research presents a comprehensive spatiotemporal assessment of the effects of climate change and anthropogenic pressures on the water surface area and quality of the Sidi Salem Dam, the largest reservoir in Northern Tunisia. Located within a sub-humid to Mediterranean humid bioclimatic zone, the dam plays a vital role in regional water supply, irrigation, and flood control. Utilizing a 40-year dataset (1985–2025), this study integrates multi-temporal satellite imagery and geospatial analysis using Geographic Information System (GIS) and remote sensing (RS) techniques. The temporal variability of the dam’s surface water extent was monitored through indices such as the Normalized Difference Water Index (NDWI). The analysis was further supported by climate data, including records of precipitation, temperature, and evapotranspiration, to assess correlations with observed hydrological changes. The findings revealed a significant reduction in the dam’s surface area, from approximately 37.8 km² in 1985 to 19.8 km² in 2025, indicating a net loss of 18 km² (47.6%). The Mann–Kendall trend test confirmed a significant long-term increase in annual precipitation, while annual temperature showed no significant trend. Nevertheless, recent observations indicate a decline in precipitation during the most recent period. Furthermore, Pearson correlation analysis revealed a significant negative relationship between precipitation and temperature, suggesting that wet years are generally associated with cooler conditions, whereas dry years coincide with warmer conditions. This hydroclimatic interplay underscores the complex dynamics driving reservoir fluctuations. Simultaneously, land use changes in the catchment area, particularly the expansion of agriculture, urban development, and deforestation have led to increased surface runoff and soil erosion, intensifying sediment deposition in the reservoir. This has progressively reduced the dam’s storage capacity, further diminishing its water storage efficiency. This study also investigates the degradation of water quality associated with declining water levels and climatic stress. Indicators such as turbidity and salinity were evaluated, showing clear signs of deterioration resulting from both natural and human-induced processes. Increased salinity and pollutant concentrations are primarily linked to reduced dilution capacity, intensified evaporation, and agrochemical runoff containing fertilizers and other contaminants. Full article

In South Korea, reclaimed coastal tidelands (RTLs) are generally used for rice cultivation rather than upland cultivation; however, there is growing social pressure to change the use of RTLs to upland crop production to increase the self-sufficiency rate regarding grain. However, RTLs are not suitable for cultivating upland crops due to their high salinity, poor drainage, and shallow groundwater levels. Therefore, it is necessary to develop a cost-effective drainage method, such as surface drainage. This study investigated the effects of slope construction on surface drainage and on the growth and yield of soybean (Glycine max (L.) Merr.) in poorly drained fields at the Saemangeum RTL, which is the largest RTL district in South Korea. Slopes were constructed at angles of 0°, 3°, and 5°; soybean was sown in June 2023 (wet season) and May 2024 (dry season); and growth of soybean was monitored at the flowering, pod-filling, and harvest stages. Soil pH, electrical conductivity (EC), and mineral nitrogen (NH₄⁺ and NO₃⁻) were measured monthly, while daily changes in soil water content were measured using soil sensors. As expected, slope construction enhanced surface runoff from the upper to lower slope areas under heavy rainfall, but soil erosion was also increased. Soybean growth and yield were higher in the upper sites for the wet-season conditions mainly due to lowered moisture stress. For the dry-season, there was no significant differences in soybean growth and yield across the slopes due to drought and high temperatures during flowering and pod-filling stages. Soybean growth and yield parameters were negatively correlated with both soil water content and pH. Slope construction improves surface drainage but does not consistently translate into higher soybean yields, highlighting its limited agronomic and economic value when used alone. Instead, integrated management practices combining drainage improvement, supplemental irrigation, and soil erosion reduction need to be implemented to support sustainable upland cropping in coastal RTLs. Full article

By 2023, deforestation in the Cerrado biome surpassed 50% of its original area, primarily due to the conversion of native vegetation to pasture and agricultural land. In addition to anthropogenic pressure, climate change has intensified hydrological stress by reducing precipitation and decreasing river flows, thereby threatening water security, quality, and availability in that biome. The Annual Water Yield (AWY) model from the InVEST platform provides a tool to assess ecosystem services by estimating the balance between precipitation and evapotranspiration (ET). In this study, we applied the AWY model to the Urucuia River Basin, analyzing water yield trends from 1991 to 2020. We evaluated climate variables, land use dynamics, and river discharge data and validated the model validation using observed stream flow data. Although the model exhibited low performance in simulating observed streamflow (NSE = −0.14), scenario analyses under reduced precipitation and increased evapotranspiration (ET) revealed consistent water yield responses to climatic variability, supporting the model’s heuristic value for assessing the relative impacts of land use and climate change. The effects of deforestation on estimated water yield were limited, as land use changes resulted in only moderate shifts in basin-wide ET. This was primarily due to the offsetting effects of land conversion: while the replacement of savannas with pasture reduced ET, the expansion of agricultural areas increased it, leading to a net balancing effect. Nevertheless, other ecosystem services—such as water quality, soil erosion, and hydrological regulation—may have been affected, threatening long-term regional sustainability. Trend analysis showed a significant decline in river discharge, likely driven by the expansion of irrigated agriculture, particularly center pivot systems, despite the absence of significant trends in precipitation or ET. Full article

Urban green hearts provide essential ecosystem services, including carbon sequestration, water purification, and hydrological regulation. The Green Heart Area of the Chang-Zhu-Tan Urban Agglomeration in Hunan Province, China, is the largest globally, and plays a critical role in regional water management. These functions are increasingly threatened by intensive land-use, while soil, as the foundational ecosystem component, mediates water retention, nutrient cycling, and erosion resistance. This study examined the effects of four land-use types—cropland, plantation, arbor woodland, and other woodland—on soil particle composition and key nutrients (organic carbon, total nitrogen, and total phosphorus). Statistical comparisons among land-use types were performed. Results indicated that silt was the dominant soil fraction across all land-uses (64–72%). Arbor woodland exhibited significantly higher sand content (29%) compared to cropland (19%; p < 0.05), suggesting improved water permeability and erosion resistance. Cropland showed elevated nutrient levels, with TN (1450.32 mg·kg⁻¹) and TP (718.86 mg·kg⁻¹) exceeding both national averages and those in arbor woodland. Coupled with acidic soil conditions (pH 5.23) and lower stoichiometric ratios (C/N: 10.82; C/P: 35.67; N/P: 3.29), these traits indicate an increased risk of nutrient leaching in croplands. In contrast, arbor woodland displayed more balanced C:N:P ratios (C/N: 12.21; C/P: 48.05; N/P: 3.84), supporting greater nutrient retention and aggregate stability. These findings underscore the significant influence of land-use type on soil ecological functions, including water infiltration, runoff reduction, and climate adaptability. The study highlights the importance of adopting conservation-oriented practices such as reduced tillage and targeted phosphorus management in croplands, alongside reforestation with native species, to improve soil structure and promote long-term ecological sustainability. Full article

Radionuclide tracer technology, as a state-of-the-art tool for quantifying and monitoring soil erosion processes, has attracted much attention in global sustainable land management research in recent years. However, existing studies are fragmented in methodological applications, lack systematic knowledge integration and interdisciplinary perspectives, and lack global research trends and dynamic evolution of key themes. This study integrates Bibliometrix, VOSviewer, and CiteSpace to conduct bibliometric and knowledge mapping analysis of 1692 documents (2000–2023) in the Web of Science Core Collection, focusing on the overall developmental trends, thematic evolution, and progress of convergence and innovation. The main findings of the study are as follows: (1) China, the United States, and the United Kingdom are in a “three-legged race” at the national level, with China focusing on technological application innovation, the United States on theoretical breakthroughs, and the United Kingdom contributing significantly to methodological research; (2) “soil erosion” and “¹³⁷Cs” continue to be the core themes, while “climate change” and “human impact” on soil erosion and its reflection in radionuclide tracing became the focus of attention; and (3) multi-scale radionuclide tracing (watershed, slope), multi-method synergy (radionuclide tracing combined with RS, GIS, AI), and the integration of advanced measurement and control technologies (PGS, ARS) have become cutting-edge trends in soil erosion monitoring and control. This study provides three prospective research directions—the construction of a global soil erosion database, the policy transformation mechanism of the SDG interface, and the iterative optimization of multi-radionuclide tracer technology, which will provide scientific guidance for the realization of the sustainable management of soil erosion and the goal of zero growth of land degradation globally. Full article