Soil Conservation Research Articles

In order to study the effect of different vegetation types on ecosystem water and soil conservation function, an area was selected as the research object, and the evaluation method of ecosystem water and soil conservation function under the application of different plant measures was designed based on ENVI and ArcGIS software. Delineate five types of vegetation in the study area. The experimental results showed that in the evaluation of water conservation function, the water conservation capacity of the five types of vegetation and the water conservation amount per unit area are ranked from large to small, i.e. grassland, shrub grassland, woodland, woodland and shrub mixed areas, cultivated land, in the evaluation of soil water conservation function, the potential and actual soil erosion of cultivated land are much greater than those of the other four vegetation types. Among the remaining four vegetation types, shrubs > mixed area of shrubs and forest land > forest land > grassland. In the order of soil conservation per unit area, cultivated land is far less than other vegetation types, and the other orders are grassland > forest land > mixed area of forest land and shrub > shrub. It can be seen that among the five vegetation types, grassland has the strongest effect on soil and water conservation, and cultivated land is the worst. Bangladesh J. Bot. 54(3): 797-804, 2025 (September) Special

In Latin America, the expansion of land for Extensive Cattle Ranching (ECR) is the leading driver of deforestation causing unsustainable levels of environmental degradation and social vulnerability to climate change extremes of drought or flood. Silvopastoral Systems (SPS) are a promising agroecological alternative to ECR. SPS combines trees and shrubs with forage grasses to enhance cattle production and landscape heterogeneity in this region. Despite strong evidence of SPS benefits (e.g., soil protection and recovery, increased cattle productivity and benefits to biodiversity), its adoption remains low. Previous work on how to scale out this practice has considered adoption as a binary option, without examining levels of adoption based on the amount (area) of SPS and types of practices adopted. This research aimed to assess how SPS can be scaled out by exploring the factors that influenced the number of hectares and component practices of SPS adopted by individual farmers to understand enablers and barriers. We used mixed effects linear models to analyze socio-economic survey data from 2,900 farms in Colombia collected over 9 years under the Sustainable Cattle Ranching (SCR) project (organized by The Nature Conservancy, CIPAV, FEDEGAN and Fondo Acción) combined with open access environmental information (8 spatial layers). The factors that had a positive significant effect on adoption were Payments for Ecosystem Services (PES), distance to closest SCR farm, presence of forest or watershed on the farm, and high levels of soil erosion. Water demand and hydric vulnerability (i.e., susceptibility to drought and flood) had a negative effect on adoption. These findings enhance knowledge of enablers and barriers for SPS adoption, including environmental constraints, thereby improving our understanding of pathways for scaling out agricultural transformation and shifting ECR to more sustainable alternatives.

Abstract The variability of raindrop size distribution (DSD) across terrain gradients plays a critical role in regulating rainfall microphysics and kinetic energy (KE), yet this variability remains under-explored in semi-arid regions. This study utilized six summers (2019–2024) of 92 disdrometer observations across Shaanxi Province, China, to demonstrate the pronounced south-north DSD gradient across terrains: while the site-averaged mass-weighted mean diameter ( D m ) increased, the normalized intercept parameter (log10 N w ) decreased rapidly from mountains to plateaus. The humid Qinling-Daba Mountains exhibits higher seasonal rainfall (>800 mm) dominated by a high concentration of small raindrops, while the semi-arid Loess Plateau shows frequent occurrences of large raindrops. This DSD shift drives higher KE in the Loess Plateau (25/28 stations >20 J m −2 mm −1 ) than in the Qinling-Daba Mountains (only 2/25 stations >20 J m −2 mm −1 ), thus amplifying soil erosion risks due to vulnerable loessal substrates. Despite the spatial heterogeneity, the site-averaged D m −log 10 N w pairs demonstrate consistent evolution throughout Shaanxi along with the increase in rain rate. We further establish D m as a universal microphysical constraint, deriving robust estimators for KE, accretion/evaporation rates, and mass-weighted terminal velocity of DSD. These relationships overcome the limitations of traditional methods by encoding terrain-mediated DSD heterogeneity through D m parameter. Consequently, they are practical for facilitating high-accuracy estimation of key microphysical quantities and process rates without full DSD resolution. Our findings offer critical semi-arid DSD benchmarks for improving model microphysics parameterization, advancing remote sensing-based KE retrievals, and designing targeted soil conservation strategies for erosion hotspots.

ABSTRACT Transitional drylands are anthropogenically fragile and climate‐susceptible land surfaces situated across sub‐humid, arid and semi‐arid ecosystems worldwide. Understanding land use dynamics is essential for food security and soil conservation, particularly in ecologically vulnerable ecosystems such as transitional drylands. Maintaining optimal soil nitrogen (N) fertility is a major challenge in intensive land use scenarios on these drylands. At the same time, understanding how soil N and associated soil functions respond to different land‐use changes is crucial for developing sustainable nitrogen management strategies. This study investigates the changes in soil N fertility and associated key ecosystem functions in topsoil (0–15 cm) and subsoil (15–30 cm) by comparing three land‐use systems along 5‐, 10‐ and 18‐year chronosequences: (i) groundnut (native land use), (ii) olive without cover crop (olive − CC) and (iii) olive with cover crop (olive + CC). Our results showed that long‐term integration of olive + CC, particularly after 18 years, led to the most noticeable decrease in soil pH and bulk density (BD). In contrast, we observed significantly higher water extractable organic carbon (WEOC), pentose (plant derived‐C), hexose (microbe derived‐C) and soil enzyme activities (i.e., dehydrogenase, urease and protease) in olive + CC compared to either groundnut or olive − CC. For total N stocks, the olive − CC showed a consistent decline (≈30% in topsoil; 27% in subsoil from 5 to 18 years), indicating progressive N depletion without organic inputs. In contrast, olive + CC restored soil N fertility with the highest N stocks after 18 years, including total N (131.58 kg N ha −1 in topsoil; 222.10 kg N ha −1 in subsoil), greater soil NO 3 ‐N and NH 4 + ‐N stocks at all depths, and a significant increase in organic N and microbial biomass nitrogen (MBN), especially in subsoil after 18 years. Regardless of soil depth, the mineral N stock under olive + CC increased steadily over 18 years, whereas changes under olive − CC were not significant. Furthermore, the regressions highlight the importance of both the quantity and quality of WEOC, which decisively influence soil N multifunctionality, especially through the additive effects of olive + CC. Overall, our study provides empirical evidence that long‐term diversification of olive orchards with cover crops is a practical, time‐dependent strategy to restore and improve soil nitrogen fertility in transitional drylands.

The Grain for Green Program (GGP), one of the world’s largest soil and water conservation initiatives, has been implemented in China as a representative payment for environmental service program. This study aims to evaluate the ecosystem service value (ESV) of forests established under the GGP in five representative provinces (Hebei, Liaoning, Hubei, Yunnan, Gansu), using a systematic methodology that integrates ecologic and economic dimensions for large-scale ecological projects. Between 1999 and 2013, a total of 717.67 × 104 ha of forests were established. Barren land served as the primary land source, with ecological forest being the dominant forest type within the program. The ESV assessment encompassed key services, including water conservation, soil conservation, carbon sequestration, nutrient retention, air quality improvements, and biodiversity improvements. Based on our estimates, the total annual ESV of the afforested areas under GGP in the five representative provinces is 3604.99 × 108 Yuan, with water conservation representing the largest share among all ecosystem services. Moreover, the cumulative ESV generated by these forests over the 14-year period exceeded the total payments made by the central government to farmers. To ensure the long-term success and sustainability of the GGP, a more equitable cost–benefit sharing mechanism is recommended.

To enhance ecosystem services (ESs) benefits and promote ecological–economic–sociologic sustainability in highly urbanized regions such as the Beijing–Tianjin–Hebei (BTH) region, it is essential to assess the dynamic changes in ESs within these regions from a functional zoning perspective and to explore the interactions between ESs. This research delved into how ESs change over space and time, using land-use projections for 2035 based on Natural Development (ND), Ecological Protection (EP), Economic Construction (EC) scenarios. This study also took a close look at the interplay of these ESs across BTH and its five distinct functional zones: the Bashang Plateau Ecological Protection Zone (BS), the Northwestern Ecological Conservation Zone (ST), the Central Core Functional Zone (HX), the Southern Functional Expansion Zone (TZ), and the Eastern Coastal Development Zone (BH). We utilize the Multiple Ecosystem Service Landscape Index (MESLI) to assess the capacity to supply multiple ESs. Key results include the following: (1) Projected land-use changes for 2035 scenarios consistently show cropland and grassland declining, while forest and urbanland expand, though the magnitude of change varies by scenario. (2) Habitat quality, carbon storage, and soil conservation displayed a “high northwest–low southeast” gradient, opposite to water yield. The average MESLI value declined in all scenarios relative to 2020, with the highest value under the EP scenario. (3) Synergies prevailed between habitat quality, carbon storage, and soil conservation, while trade-offs occurred with water yield. These relationships varied spatially—for instance, habitat quality and soil conservation were weakly synergistic in the BS but showed weak trade-offs in the HX. These insights can inform management strategies in other rapidly urbanizing regions.

Scenario-based simulation of ecosystem service supply and demand in China's Yangtze River Economic Belt.

Evaluating the effectiveness of four representative land uses in soil and water conservation on a typical rainfed Mediterranean agricultural landscape in La Rioja (Spain)

Synergistically enhanced black soil conservation by Paenarthrobacter sp. KN0901 under straw amendment: dual promotion of atrazine degradation and nutrient retention.

Structural and water stability characteristics of surface soil over shallow-buried coal seams: Spatial variability and co-inertia analysis.

Increased soil organic carbon density in karst areas compared to non-karst areas in a mountainous city since the 1980s.

Rapid urbanization and climate change are critical processes that affect groundwater resources, particularly in urban areas. This study investigates the long-term impacts of both processes on the potential natural groundwater recharge from precipitation across the period 1986-2100 under SSP2-4.5 and SSP5-8.5 pathways. The approach used in this study combines three models, including (1) a Cellular Automata-Artificial Neural Network (CA-ANN)-based modeling for the continuous mapping of future spatiotemporal land use-land cover (LULC) distributions, (2) climate change modeling using CMIP6 GM, and (3) hydrological modeling using the Soil Conservation Service-Curve Number method (SCS-CN). The findings indicate that the urban area is anticipated to increase from 18.2% of the total area in 1986 to 86.5% by 2100 at the expense of other land cover. Moreover, projected climate change indicators derived from precipitation exhibit declining trends in yearly precipitation and extreme event frequency and intensity against an increasing dry conditions trend during the period 2017-2100. The analysis reveals a fluctuating future potential natural groundwater recharge with decreasing trends under both climate change pathways. The regression analysis shows that 27.5% (R2 = 0.8199) and 24.7% (R2 = 0.7867) of precipitation contribute to natural recharge under SSP2 and SSP5, respectively, highlighting a strong linear correlation between them. In comparison to a high emission pathway, these slopes indicate that achieving a moderate emission pathway will increase the potential recharge by 2.8%. In addition, the outcomes demonstrate that future groundwater recharge patterns are more sensitive to changes in climatic conditions than to urbanization. This study underscores the importance of integrating urban planning and water resources management strategies to ensure the long-term groundwater sustainability in urban cities.

Loss of soil from river basins by water is a concerning issue for India which is an agricultural country. The particular distribution of quantitated soil erosion must be obtained to propose effective soil conservation practices. Revised Universal Soil Loss Equation (RUSLE) is a tool to estimate soil erosion distribution spatially. The properties of Vembanad lake that supports large biodiversity and ecosystem is altered by the sediments of Muvattupuzha River. The river, originating from the Western Ghats drains into Vembanad lake, has undergone many changes. In this work, an attempt has been made to determine the soil erosion in the Muvattupuha River basin through the years. Annual sediment loss from the basin is obtained for three consecutive decades. Maps of soil yield, sediment delivery ratio and sediment transportation index of the basin for 2021 are also developed.

Ecosystem services play a crucial role in maintaining ecological balance and supporting socio-economic development. However, long-term human activities and climate change have led to severe ecosystem degradation and exacerbated soil erosion on the Loess Plateau. This study takes the Loess Plateau as a case study and using key models such as Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) to analyze the spatiotemporal variations of five ecosystem services—water yield, habitat quality, windbreak and sand fixation, soil conservation, and net primary productivity (NPP)—from 2000 to 2020. Based on the land use types projected by the Patch-generating Land Use Simulation (PLUS) model for 2025 and 2030 under natural development, ecological protection, and cropland protection scenarios, the study simulates these five ecosystem services and the comprehensive ecosystem service index for the Loess Plateau in 2025 and 2030. Finally, an ecological risk assessment model based on the inverse transformation of ecosystem services is constructed to identify key ecological restoration areas on the Loess Plateau by 2030. The results indicate: (1) From 2000 to 2020, water yield, soil conservation services, and NPP on the Loess Plateau showed a significant increasing trend, The unit area sand fixation capacity displayed a spatial pattern of higher values in the Northwest and lower values in the Southeast, while soil conservation and NPP exhibited the opposite trend, with higher values in the Southeast and lower values in the Northwest. Water yield decreased from the Southeast to the Northwest. During this period, the comprehensive ecosystem service index of the Loess Plateau generally declines, but the balance and synchronicity of ecosystem services improve, with a reduction in regional disparities. (2) Different future scenarios have different effects on the regional pattern of ecosystem services and restoration. Among future scenarios, the ecological protection scenario is most conducive to enhancing comprehensive ecosystem services, reducing the proportion of medium- and high-priority restoration zones. The cropland protection scenario has the lowest proportion of general restoration zones, but local ecological risks increase. The findings of this study can provide a scientific basis for ecological restoration and land-use planning on the Loess Plateau, promoting the long-term stability and sustainable development of ecosystem services.

Climate change and biodiversity loss are interrelated global environmental challenges. Climate change is a long-term change in temperature and weather patterns over a very long period of time. The form of climate change is related to changes in weather patterns or changes in the distribution of weather events. The main cause of climate change is global warming. Biodiversity is defined as the diversity or variety of life on earth, including types of plants, animals, and microorganisms living in various ecosystems. In the relationship between climate change and biodiversity where climate change can cause species extinction, habitat changes, and ecosystem disruption. While the role of biodiversity is to overcome climate change, where ecosystems play an important role in absorbing carbon dioxide from the atmosphere and supporting resilience to the impacts of climate change. Efforts to integrate these two issues in national legislation through a comprehensive approach. Integrated regulations combine the objectives of protecting biodiversity and addressing the challenges of climate change with mitigation actions, namely reducing greenhouse gas emissions toward renewable energy such as solar, wind and hydro; increasing energy efficiency in homes, industry, and sustainable transportation; protecting forests as carbon sinks and reforestation; and reducing greenhouse gas emissions by managing waste to reduce methane emissions as well as energy-efficient building and environmental management. In addition, adapting actions to reduce vulnerabilities impacting existing climate change, such as urban planning based on climate and agricultural practices, adaptive, conservation, and habitat restoration and protection of vulnerable species. Identifying challenges and opportunities, including shifts in plant and pollinator phenology due to climate change. The main challenge is the mismatch in phenology between plants and pollinators, which can disrupt the pollination process, impact crop production, and create plant pests because rain patterns or droughts cause a decrease in crop yields, which can have an impact on economic value. While for sustainable agriculture, the government can provide incentives in the form of subsidies, taxes, and technical assistance to farmers, such as crop rotation, use of organic fertilizers, and soil conservation. To increase awareness and more integrated and effective legal action in protecting the planet, comprehensive efforts are needed, including strong regulations, stricter law enforcement, increased public awareness, and active involvement from various parties. These steps must complement each other to achieve the goal of sustainable environmental conservation.

Abstract To get a better understanding of potentially harmful contaminant emissions from soils or materials into the environment, politics demand practical and holistic sampling concepts for environmental samples such as leachates containing polycyclic aromatic hydrocarbons (PAH) or heavy metals, and hazardous particulate matter like microplastics (MP). Of particular concern are MP emissions from artificial turf sports pitches. So far, there has been only very limited data on MP mass emissions from artificial turf potentially posing a risk to the groundwater and no sampling device that allowed simultaneous sampling for dissolved and particulate contaminants. In this study, a novel integrative microplastics eluate lysimeter was developed to determine contaminant emissions from three artificial turf systems at different ageing states (fabric-new, artificially aged, real-time aged). For the accelerated ageing, all environmental simulation parameters were based on Central German conditions and simulated outdoor stress during the turf service lifespan of 15 years. MP masses from eluates were analysed using thermal extraction desorption-gas chromatography/mass spectrometry, PAH concentrations using gas chromatography/mass spectrometry and heavy metals using inductively coupled plasma-optical emission spectroscopy. Results showed that no PAH or heavy metal concentrations from the seepage water were above German legal limits for alternative granular construction materials considering soil and groundwater protection. Furthermore, it was found that only minimal MP emissions were released from new turf systems into the seepage water (< 1 mg/m 2 ). Ageing of the artificial turf increased MP formation, especially from rubber infill and grass fibres, which are then carried into the seepage water. The highest total MP emissions over a simulated turf lifespan of 15 years were detected in two real-time aged turf systems ranging from 136.4–252.5 mg/m 2 . Considerably less total MP emissions were detected in accelerated aged artificial turf systems, one of which contained a synthetic rubber infill (5.4–8.0 mg/m 2 ) and one without rubber infill (0.2–5.3 mg/m 2 ). In summary, it was demonstrated that the newly developed MEL generated reliable and reproducible data and has thus proven itself as an integrated, straightforward and automated sampling device for simultaneous monitoring of particulate and dissolved pollutant emissions from simple soil matrices.

Abstract Sustainable agriculture depends heavily on precise LULC classification to support soil conservation, water resource planning, and environmentally conscious land use. This study proposes a hybrid deep learning system integrating VGG16 and EfficientNetB7 models with a Random Forest (RF) classifier to classify agricultural and other LULC types in Najran, Saudi Arabia, utilizing digital elevation models (DEMs) and Indian Remote Sensing Advanced Wide Field Sensor satellite data from 2020. A stereo-derived DEM was used to extract topographical features, which, combined with multi-temporal imagery, were processed through VGG16 and EfficientNetB7 for spatial feature extraction. The Grasshopper Optimization Algorithm was applied to select the most essential features and remove the unimportant and redundant ones. The features were then fed into an RF classifier to classify the Najran terrain map efficiently. Evaluation of the hybrid system showed promising results for classifying the Najran terrain map, achieving an accuracy of 94.2%, precision of 79.88%, recall of 79.22%, F 1-score of 79.53%, and specificity of 96.01%. The system demonstrated robust performance in differentiating agricultural lands from urban and natural terrains, enabling efficient monitoring of land use patterns. This approach supports sustainable agricultural practices and environmental stewardship by providing decision-makers with high-resolution, automatically classified land maps for strategic planning in arid regions, such as Najran.

The composition elements of the earthwork allocation system (excavation project, filling project, transfer yard, waste disposal yard, and material yard) and the relationship between material flow were analyzed. Based on the construction of calculation models for soil and water conservation fees, landscape restoration fees, and road transportation intensity, a joint optimization model was constructed with the objectives of minimizing the total allocation cost and minimizing the peak transportation intensity of the road. By dynamically adjusting the volatility, setting penalty factors, and vectorizing NumPy arrays, the ant colony algorithm is improved and the optimization model is solved. Case analysis shows that considering the intensity of road transportation, the peak transportation intensity significantly decreases, and the proportion of directly filled earthwork increases to over 88% without exceeding the capacity of the intermediate transfer site. The total cost only increases by 0.91%, and the allocation plan is more in line with actual construction needs.

A GIS-based Soil Conservation Service Curve Number (SCS-CN) approach was used to estimate surface-runoff potential in Yemen’s arid Abyan Delta (∼1,237 km2). Sentinel-2 (10 m) imagery was classified into major land-cover types and combined with hydrologic soil groups (HYSOGs) to assign CN values under Antecedent Moisture Condition II. The composite CN map (67–100; mean = 91.8) indicates limited infiltration across large areas of bare or impervious surfaces on clayey soils. Using the standard SCS-CN equations, event runoff was simulated for representative storm depths of 74, 124, and 174 mm. The model produced direct-runoff depths of ∼52, 100, and 150 mm, corresponding to runoff coefficients of ∼71%, 81%, and 86%, and basin-wide volumes of 0.65, 1.24, and 1.85 × 108 m3, respectively. Spatial attribution shows that high-CN zones (notably barren HSG-C/D units and built-up/roads) generate most of the runoff despite covering a smaller fraction of the delta. The results identify priority areas for spate-irrigation, retention, and recharge interventions, and provide a reproducible baseline for flood-risk reduction and water-harvesting planning in data-scarce drylands. The workflow can be readily updated with improved soils, land-use, or climate inputs to support adaptive management.

Subalpine meadow soil is widespread in the steep valleys of the eastern Tibetan Plateau. Owing to its unique structure and climatic conditions, rainfall can trigger extensive ecohydrological disaster, characterized by soil disintegration and shallow landsliding. This phenomenon leads to significant soil erosion and degradation of meadow ecosystems, highlighting the ecological vulnerability of the region. Field investigations have identified porewater pressure from infiltrated rainwater and gravitational pressure on saturated meadow soil as the primary drivers of the landsliding. Building on this understanding, efforts were made to assess the risk of subalpine meadow soil erosion induced by extreme rainfall near Xinduqiao County using the TRIGRS model and the coupled TRIGRS-TOPMODEL (TOP-TRIGRS). Validation of the simulated results against observed erosion events revealed that TOP-TRIGRS tends to predict unstable areas more accurately, particularly in the lower to mid-sections of slopes with gentler gradients, in line with theoretical models of shallow landslide. Specifically, while TRIGRS identified 50.31% of actual shallow landslides, TOP-TRIGRS reached 80.35%. Moreover, the AUC values for TRIGRS and TOP-TRIGRS were 0.787 and 0.896, respectively, indicating the superior predictive performance of TOP-TRIGRS. Accurate prediction of shallow landslides in subalpine meadow soil is vital for informing ecological management regulations and advancing soil and water conservation efforts in the eastern Tibetan Plateau.