A new method to quantify the impacts of human activity on soil conservation service.

Human activities and climate change impact ecosystem services, thereby affecting economic and social sustainable development. Measuring the heterogeneity in space and time of how human activities affect ecosystem services poses a challenge for the sustainable management of land resources. Based on "human appropriation of net primary production (HANPP) - Fractional Vegetation Cover (FVC) - Soil Conservation Service (SCS)" cascading effect, first, a geographically and temporally weighted regression (GTWR) model was employed to assess the impact of HANPP in percent of potential NPP (hereafter HANPP%) on the FVC; second, changes in the FVC caused by human activities were quantified; and third, the potential soil conservation service (SCSp) and actual soil conservation service (SCSa) were estimated using the Revised Universal Soil Loss Equation (RUSLE) model, and the difference between them represented the changes in soil conservation service caused by human activities (SCSh). Taking the Qinghai-Tibet Plateau as a case study, we found that the GTWR model was well suited for analyzing the relationship between the HANPP% and the FVC (R2 = 0.897). The HANPP resulted in a decrease in the FVC from 0.222 in 2001 to 0.199 in 2019 and correspondingly resulted in a decrease in the ratio of SCSh to SCSp from 8.95% to 7.24%. This study provides a quantitative method that allows quantifying the influence of human activity on ecosystem services closely related to the FVC.

Non-trade-off Changes in Soil Conservation Service and Soil Loss on the Tibetan Plateau Underlying the Impacts of Climate Change and human activities.

Climate change and human activities have significantly influenced soil loss and the soil conservation service, posed threats to regional ecological sustainability. However, the relationships and underlying driving forces between potential soil loss, actual soil loss, and soil conservation service have not been well understood. Utilizing the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, we evaluated the soil conservation service on the Tibetan plateau from 1990 to 2020. We analyzed the spatial and temporal trends and examined the driving factors using linear regression, Pearson correlation, and random forest regression. The soil conservation service exhibited a complex pattern of increase followed by a decrease, with a turning point around 2010. Soil conservation service and soil loss demonstrated non-trade-off changes. The potential soil loss dominated the spatiotemporal patterns of soil conservation service on the Tibetan Plateau. Climatic factors significantly influenced the spatiotemporal patterns of soil conservation service, with annual precipitation emerging as the dominant driving factor, contributing approximately 20%. However, the impacts of human activities became more pronounced since 2010, and the contribution of vegetation to changes in soil conservation service was increased. The impact of the Normalized Difference Vegetation Index (NDVI) on soil conservation service for the grades I, II, and III increased by 13.19%, 3.08%, and 3.41%, respectively. Conversely, in northern Tibet before 2010 and eastern Three-River-Source after 2010, soil conservation service exhibited an increasing trend driven by both climate factors and human activities. Which indicates that the implementation of ecological restoration measures facilitated vegetation improvement and subsequently reduced actual soil loss. This study provides a scientific basis for resource management, land development strategies, and the formulation of ecological restoration measures on the Tibetan Plateau.

Environmental vulnerability applied to the territorial planning of a tropical semiarid basin.

Tropical semiarid regions are naturally prone to environmental damage. Human activity can worsen this situation. To understand how human actions affect the ecosystem, plan land use effectively, and establish targeted management practices, assessing environmental vulnerability is crucial. This study focuses on a sub-basin receiving water transfers from the São Francisco River in Brazil's semiarid region. Here, we map and evaluate how land use and occupation alter natural vulnerability. We also propose zoning strategies to support water resource management and implement sustainable development policies in the region. To achieve this, we conducted an integrated analysis of physical factors (soil types, geology, climate, vegetation, and landforms) and spatial land-use data using geographic information systems (GIS) and map algebra techniques. Map algebra allowed us to combine these various datasets within the GIS environment, enabling the creation of maps that synthesize both natural and environmental vulnerability across the study area. Following analysis of these vulnerability maps, our findings reveal a high level of vulnerability. The areas with high to very high degrees of natural vulnerability coincide with the places that have high slopes, high altitudes, Lithic Neosols, and thick vegetation. Furthermore, the interaction between environmental factors and human activity exacerbates vulnerability. Based on the environmental vulnerability assessment, we defined four environmental management zones. These zones require distinct protection measures and management approaches. As a method to potentially improve the basin's vulnerability scenario, soil conservation measures are recommended. This approach is highly relevant for managing land in tropical semiarid regions and, with adaptations to specific regional factors, can be applied globally.

Optimizing payment for ecosystem services in a drinking water source watershed by quantifying the supply and demand of soil retention service.

Payment for ecosystem services (PES) plays a vital role in coordinating the relationship between ecosystem services supply and demand sides in watersheds. The upstream soil retention service brings significant off-site benefits to the downstream stakeholders. To fill gaps in the supply and demand of soil retention services for PES, we developed an approach that combined long-term observation data, hydrological model, and cost-benefit analysis. We applied and demonstrated the approach in a typical drinking water source watershed. By constructing the relationship between water clarity and the demanded trophic state, we identified the demand for soil retention as the suspended sediment concentration ≤4.4 mg L-1 at a transboundary station. Then, a well-calibrated hydrological model was applied to simulate the downstream sediment reduction under 36 upstream reforestation scenarios. Results showed that cropland reforestation effectively reduced downstream sediment loads by up to 37.8%. However, the efficiency of cropland reforestation for soil retention supply was influenced by its area, slope, and location. The cost-benefit analysis revealed that the feasible sediment reduction was 11,000 t per year, and the market-equilibrium price was 5800 CNY (Chinese Yuan, 7 CNY equaled 1 USD in 2020) per ton. The downstream side should pay 64 million CNY annually for soil retention provided by reforesting at upstream sloping cropland of 8° or above. This study suggested that the approach was helpful for integrating soil retention service supply and demand at a watershed scale to support PES decision-making.

Soil erosion in diverse agroecological regions of India: a comprehensive review of USLE-based modelling.

Soil erosion caused by water refers to the removal of topsoil by rainfall and runoff. Proper selection of an assessment method is crucial for quantifying the spatial variance of soil erosion. The Universal Soil Loss Equation (USLE) and its revised version (RUSLE) are widely used for modelling soil erosion. This study aimed to evaluate the effectiveness of the USLE-based soil erosion modelling in different agroecological regions of India, identify potential issues, and provide suggestions for future applications. The review revealed that little attention has been given to estimate soil erosion in high-priority land degradation regions of India. Additionally, many studies failed to thoroughly verify the authenticity of stated soil loss rates in their research regions either by overestimating or underestimating at least one of the five soil loss parameters. Furthermore, flaws in the application of methods to calculate these parameters leading to erroneous values were identified and suggestions for improvement were made. The USLE-based soil erosion modelling is an effective tool for quantifying soil erosion risk, but researchers should put emphasis on thoroughly verifying the methodologies adopted, unit conversions, and data availability for the estimation of soil loss parameters to improve the accuracy of their final results. This paper provides valuable insights to assist researchers in implementing USLE-based erosion models in diverse agroecological regions in India and elsewhere. However, for effective soil conservation and sustainable agriculture, further research is necessary to develop efficient techniques for using USLE-based soil erosion modelling to achieve a comprehensive understanding of erosion risk across different agroecological regions.

Evaluating the impacts of sustainable land management practices on water quality in an agricultural catchment in Lower Austria using SWAT.

Managing agricultural watersheds in an environmentally friendly manner necessitate the strategic implementation of well-targeted sustainable land management (SLM) practices that limit soil and nonpoint source pollution losses and translocation. Watershed-scale SLM-scenario modeling has the potential to identify efficient and effective management strategies from the field to the integrated landscape level. In a case study targeting a 66-hectare watershed in Petzenkirchen, Lower Austria, the Soil and Water Assessment Tool (SWAT) was utilized to evaluate a variety of locally adoptable SLM practices. SWAT was calibrated and validated (monthly) at the catchment outlet for flow, sediment, nitrate-nitrogen (NO3-N), ammonium nitrogen (NH4-N), and mineralized phosphorus (PO4-P) using SWATplusR. Considering the locally existing agricultural practices and socioeconomic and environmental factors of the research area, four conservation practices were evaluated: baseline scenario, contour farming (CF), winter cover crops (CC), and a combination of no-till and cover crops (NT + CC). The NT + CC SLM practice was found to be the most effective soil conservation practice in reducing soil loss by around 80%, whereas CF obtained the best results for decreasing the nutrient loads of NO3-N and PO4-P by 11% and 35%, respectively. The findings of this study imply that the setup SWAT model can serve the context-specific performance assessment and eventual promotion of SLM interventions that mitigate on-site land degradation and the consequential off-site environmental pollution resulting from agricultural nonpoint sources.

Spatial and temporal differences in the response of water conservation and soil conservation to ecosystem fragmentation: evidence from Qilian Mountain National Park of China.

Using spatial autocorrelation methods, we explored the spatial and temporal differences in the response of soil conservation (SC) and water conservation (WC) to ecosystem fragmentation during 1990 to 2019 in Qilian Mountain National Park (QMNP) of China. We found that the degree of ecosystem fragmentation decreased over the past 30 years, improving the WC and SC capacity of the ecosystems. However, the relationship among them varied temporally and exhibited a variety of spatial patterns. The correlation between fragmentation and WC increases year by year, and the correlation with SC weakens. There is a mismatch between park-level and regional autocorrelation between fragmentation and WC and SC. The spatial relationships between fragmentation and WC and SC in the QMNP show "high-high" and "low-low" patterns in its eastern and western sections, respectively. This heterogeneity is related to the differences in ecosystem composition, especially in ecosystem WC and SC capacity, and the characteristics of ecosystem fragmentation in the east-west direction of the QMNP.

Driving factors of ecosystem services and their spatiotemporal change assessment based on land use types in the Loess Plateau.

A clear understanding of the driving factors for different ecosystem services (ESs) is quite essential for sustainable ecosystem management. It is important to strengthen research in ESs and social sustainable development to identify the main driving factors of different ESs. This study assessed carbon sequestration (CS), water yield (WY) and soil conservation (SC) from 2000 to 2018 in the Loess Plateau using CASA (The Carnegie-AmesStanford Approach), InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) and RUSLE (Revised Universal Soil Loss Equation) models. The spatial heterogeneity, trade-offs and synergies and driving factors were explored in the whole Loess Plateau. The results showed that the WY, CS and SC had increased from 2000 to 2018. The spatial relationships between WY and SC, SC and CS, and WY and CS were mainly synergistic. Annual mean precipitation (MAP) was the dominant driving factor of WY, while normalized difference vegetation index (NDVI) and slope (SL) had the strongest explanatory power for CS and SC. The LU was the most critical factor affecting the ESs in the different climatic zones. These results could act as a reference for decision-makers on how to control various influencing factors of ESs to improve the local ecology under local conditions.

Conservation of complementary habitat types and small-scale spatial heterogeneity enhance soil arthropod diversity.

Humanity relies on soil fauna for important ecosystem services, as such our soils need sustainable management to ensure long-term biotic viability. However, environmental factors influencing the distribution and diversity of soil fauna are poorly understood, which limits effective conservation management. To address this issue, we assessed the influence of variables at different spatial scales (site, soil, and landscape) in different biotopes (natural forest patches and grasslands) in two contrasting geographical regions (inland Midlands and coastal Zululand, South Africa) on ant and springtail diversity in large-scale conservation corridors among commercial plantations. Midlands sites, with complex topography and nutrient-rich and deep soils, had higher soil arthropod diversity than sandy, shallow Zululand soils. Indigenous forest and grassland supported complementary arthropod assemblages. The responses of arthropod diversity and assemblage composition to local environmental variables varied greatly among biotopes, taxa, and regions, but responses were more pronounced in the Midlands than in Zululand, and arthropods were more responsive to site- and soil-related variables than to landscape variables. Lower soil biodiversity in Zululand compared to the Midlands emphasizes that management efforts to limit further homogenization from inappropriate management is particularly important in this sandy region. Lack of common drivers of soil arthropod diversity suggests that conservation strategies need to be tailored to different locations. Nonetheless, the conservation of both indigenous forest and grassland, together with promotion of small-scale spatial heterogeneity, will maximally benefit the widest range of soil-inhabiting organisms.

Have anthropogenic factors mitigated or intensified soil erosion over the past three decades in South China?

As a form of land degradation, soil erosion directly threatens the sustainability of natural resources and the environment. The impacts of humans on soil erosion are profound and complex, especially in the areas with frequent human activities. Moreover, the great variability of human activities at the spatial and time scales precludes a comprehensive understanding of how humans affect regional erosion. This study evaluated soil erosion by water from 1985 to 2015 occurring in South China, which is densely populated and has been intensively exploited, based on the Chinese Soil Loss Equation (CSLE) and multisource data including remote sensing images, meteorological station information and geographic data. A quantitative method combining traceability thinking and residual trend approach was employed to distinguish the relative contributions of climate change and human activities. The results showed that the average amount of soil erosion exhibited a significant decreasing trend from 1985 to 2015, which was consistent with the national water census data and previous studies. Anthropogenic factors played a more vital role than natural variables in the evolution of soil erosion, the multiyear average contribution of which was 63.90%. The area in which anthropogenic factors alleviated soil erosion covered approximately 83.70% of the study area. These results indicate that soil and water conservation practices have made outstanding contributions to the reduction of soil erosion in South China. However, the impacts of the expansion of building land and the development of plantations on aggravating soil erosion cannot be ignored. For future soil erosion control, we observed the diminishing marginal effect of investments in soil and water conservation, and a higher governance potential in the severely eroded regions, which made the severely eroded poor land a primary for comprehensive ecological management. This study aims to provide valuable insights for decision makers in South China to better understand the impacts of humans on the evolution of soil erosion and could provide scientific support for reducing regional soil loss and enhancing the sustainable development of the ecological environment.

Integrating future grassland degradation risk to improve the spatial targeting efficiency of payment for ecosystem services.

Spatial targeting plays a key role in improving the efficiency of payment for ecosystem services (PES). However, the risk of grassland degradation after implementing PES increases uncertainty about the efficiency of PES. Here, we identified the spatial heterogeneity of grassland degradation risk using Future Land Use Simulation (FLUS) model, then incorporated grassland degradation risk as a criterion into PES spatial targeting using cost-benefit analysis and ranking optimization. The framework was applied to a case study of the Three-River-Source National Park, China. We found that grasslands in the study area continued to degrade between 2015 and 2025, and the area of degraded grasslands increased by 26%. Compared with spatial targeting of PES without considering grassland degradation risk, PES spatial targeting that considered grassland degradation risk was significantly different (the overlap area accounted for only 75%, 82%, and 94% of the PES area within 25%, 50%, and 75% of the total protection cost budget). When the grassland degradation risk was considered as a targeting criterion, PES efficiency increased by 154%, 116%, 124%, and 99%, respectively, within 25%, 50%, 75%, and 100% of the total protection cost budget. Our results demonstrate that considering grassland degradation risk in the spatial targeting of PES increases efficiency because it helps to target areas with greater environmental benefits.

Assessing soil system changes under climate-smart agriculture via farmers' observations and conventional soil testing.

Soil degradation remains a challenge in African highlands, where land management lacks a strong context-specific evidence base. We investigated the impacts of recently implemented soil and water conservation (SWC) practices-farmyard manure addition, incorporation of crop residues in soil and fanya juu terracing under an agroforestry system on soil health indicators in the East Usambara Mountains of Tanzania. Farmers' observations of soil changes were combined with conventional soil testing to assess the initial impacts of SWC practices relative to conventional non-SWC practice. Majority of farmers (66%-83%) reported that combining fanya juu terracing with organic amendments led to soil colour change from red to black and an increase in crop yield. Despite the observed darkening of the soil, there was no significant increase in soil organic carbon stock and the contents of N, P, K. There were important changes in soil physical properties, including greater aggregate stability (mean weight diameter of 1.51-1.71 mm) in the SWC plots, a greater volume of transmission pores (>60 µm) and coarse storage pores (10-60 µm) in the surface soil layer (0-15 cm), and greater volume of fine storage pores (0.2-10 µm) and residual pores (0.2 µm) in the sub-surface layer (15-30 cm) of the SWC plots compared with the conventional plots. These changes indicate that SWC rapidly enhances infiltration and retention of water within the root zone, which are important for increasing crop yields and improving the resilience of the agro-ecosystem to environmental stress. Combining SWC with effective soil fertility management is needed for sustainable highland agriculture.

Evaluation of different boosting ensemble machine learning models and novel deep learning and boosting framework for head-cut gully erosion susceptibility.

The objective of this study is to assess the gully head-cut erosion susceptibility and identify gully erosion prone areas in the Meimand watershed, Iran. In recent years, this study area has been greatly influenced by several head-cut gullies due to unusual climatic factors and human induced activity. The present study is therefore intended to address this issue by developing head-cut gully erosion prediction maps using boosting ensemble machine learning algorithms, namely Boosted Tree (BT), Boosted Generalized Linear Models (BGLM), Boosted Regression Tree (BRT), Extreme Gradient Boosting (XGB), and Deep Boost (DB). Initially, we produced a gully erosion inventory map using a variety of resources, including published reports, Google Earth images, and field records of the Global Positioning System (GPS). Subsequently, we distributed this information randomly and choose 70% (102) of the test gullies and the remaining 30% (43) for validation. The methodology was designed using morphometric and thematic determinants, including 14 head-cut gully erosion conditioning features. We have also investigated the following: (a) Multi-collinearity analysis to determine the linearity of the independent variables, (b) Predictive capability of piping models using train and test dataset and (c) Variables importance affecting head-cut gully erosion. The study reveals that altitude, land use, distances from road and soil characteristics influenced the method with the greatest impact on head-cut gully erosion susceptibility. We presented five head-cut gully erosion susceptibility maps and investigated their predictive accuracy through area under curve (AUC). The AUC test reveals that the DB machine learning method demonstrated significantly higher accuracy (AUC = 0.95) than the BT (AUC = 0.93), BGLM (AUC = 0.91), BRT (AUC = 0.94) and XGB (AUC = 0.92) approaches. The predicted head-cut gully erosion susceptibility maps can be used by policy makers and local authorities for soil conservation and to prevent threats to human activities.

Enhancing the application of organic fertilisers by members of agricultural cooperatives.

Scientific literature has reported that participation in agricultural cooperatives has positive effects on small farmers' preference for organic fertilisers over chemical fertilisers. However, there is limited focus on enhancing the voluntary use of organic fertilisers by small farmers who have joined an agricultural cooperative. This paper describes an agent-based model for simulating small farmers' decision-making with regard to fertiliser selection. Ninety six farmers (members) of one of the largest strawberry production cooperatives in China were assessed to understand their willingness to use different fertilisers and their socioeconomic characteristics. Simulation results showed that for farmers belonging to the agricultural cooperative who earn higher marginal profits, variations in the prices of the agricultural produce had no significant effect on their behaviour in terms of the use of organic fertilisers. The number of farmers using organic fertilisers at the beginning of the first year has a positive relationship with the increase in the rate at which farmers use organic fertilisers. However, the count does not alter the final number of farmers who use organic fertilisers after several years. Moreover, farmers' willingness to use organic fertilisers enhances the increasing speed and final number of farmers using organic fertilisers simultaneously. The design of strategies (increasing the number of farmers using organic fertilisers at the beginning of the first year and enhancing farmers' willingness to use organic fertilisers) has a significant effect on the promotion of organic fertiliser application by agricultural cooperatives in China.

Optimizing the soil conservation service curve number model by accounting for rainfall characteristics: a case study of surface water sources in Beijing.

The upper catchment of the Miyun reservoir is an important drinking water source in Beijing. In recent years, researchers have used the soil conservation service curve number (SCS-CN) model to calculate surface runoff for the district. Although the runoff forecasting accuracy was unsatisfactory, the lack of understanding of rainfall processes and their influence on runoff may explain the observed deviations. Our study sought to optimize and assess the SCS-CN model simulation accuracy for the district by proposing an SCS-CN calculation method for each runoff event (CNt) based on observation data for 253 rainfall and runoff events from 7 plots in the Miyun Shixia watershed. This study elucidated a significant positive correlation between the ratio of CNt and the average SCS-CN (CN1), as well as the ratio of the maximum X-minute rainfall amount (PX) to the total rainfall amount for each rainfall event (P). Furthermore, a calculation method involving power function equations between CNt/CN1 and PX/P was proposed for CNt. When X = 5 min and the initial abstraction ratio (λ) = 0.01, the simulation performance of the optimized model was the highest, with a Nash-Sutcliffe efficiency coefficient of 0.791, which was significantly higher than that of the non-optimized SCS-CN model. The simulation performance for bare and cultivated land was higher than that of other land uses, with Ef values of 0.831 and 0.828, respectively. Future research should focus on improving the prediction accuracy of runoff events resulting from high-intensity and short-duration rainfall events.

Flow accumulation based method for the identification of erosion risk points in unpaved roads.

The unsuitable construction of unpaved roads has been causing problems related to the formation of erosive processes, sediments in watersheds, bogs, flooding, and holes. Presuming that the areas where flow accumulation intersects unpaved roads represent risk points, our objectives are (1) to develop a qualitative method based on the GIS software management tool (FlowAccRoad) for the identification of the intersection points between flow accumulation and roads and (2) to verify the discrepancy between the points of intersection produced by digital elevation models (DEM) accounting for different spatial resolutions. In the GIS environment, we used the Shuttle Radar Topography Mission (SRTM) and Goiania (GOI) digital elevation models for the modeling of flow accumulation and vectorization of the unpaved roads, both of which are based on the Bandeira Stream Watershed in Goiania, Goiás, Brazil. This highlights that 54 points of intersection between the flow accumulation and unpaved roads present problems related to erosive processes and quagmires, among others. The FlowAccRoad method identified the principal critical points observed in the field, using both the DEM of 30.4 m of spatial resolution (SRTM) and also of 4.8 m of spatial resolution (GOI). From the FlowAccRoad method, we observed that 91% of the risk points identified through the GOI DEM were located less than 20 m from valid points in the field by using GPS. Analyzing the SRTM DEM, only 45% of the critical risk points identified by the method were located less than 20 m from valid points in the field.

Changes to soil conservation in the Three Gorges Reservoir Area between 1982 and 2015.

Soil erosion is a major threat in the Three Gorges Reservoir Area (TGRA) of China. Since 1990, the Chinese government has launched a series of ecological restoration projects to promote soil conservation in the TGRA. To understand the effects of ecological restoration on soil conservation in the TGRA, we used the abrupt change analysis of soil mass from 1982 to 2015 and its drivers; soil mass was obtained with the universal soil loss equation at continental scale. We found that soil conservation and annual rainfall decreased in the TGRA over the study period. Abrupt change points of soil conservation occurred in 1984 and 2007. Soil conservation in the TGRA showed a dramatic decrease before 1984, a slow increase after 1984 as a result of climate, and a rapid increase after 2007 due to an increase in vegetation cover. From 1982 to 2015, climate change played a primary role in soil conservation changes and was more influential than topography and vegetation. However, ecological restoration was an important factor affecting soil conservation in the TGRA, and it needs to be promoted.

Agricultural implications of providing soil-based constraints on urban expansion: Land use forecasts to 2050.

Urbanization onto adjacent farmlands directly reduces the agricultural area available to meet the resource needs of a growing society. Soil conservation is a common objective in urban planning, but little focus has been placed on targeting soil value as a metric for conservation. This study assigns commodity and water storage values to the agricultural soils across all of the watersheds in Michigan's Lower Peninsula to evaluate how cities might respond to a soil conservation-based urbanization strategy. Land Transformation Model (LTM) simulations representing both traditional and soil conservation-based urbanization, are used to forecast urban area growth from 2010 to 2050 at five year intervals. The expansion of urban areas onto adjacent farmland is then evaluated to quantify the conservation effects of soil-based development. Results indicate that a soil-based protection strategy significantly conserves total farmland, especially more fertile soils within each soil type. In terms of revenue, ∼$88 million (in current dollars) would be conserved in 2050 using soil-based constraints, with the projected savings from 2011 to 2050 totaling more than $1.5 billion. Soil-based urbanization also increased urban density for each major metropolitan area. For example, there were 94,640 more acres directly adjacent to urban land by 2050 under traditional development compared to the soil-based urbanization strategy, indicating that urban sprawl was more tightly contained when including soil value as a metric to guide development. This study indicates that implementing a soil-based urbanization strategy would better satisfy future agricultural resource needs than traditional urban planning.

Identification and classification of structural soil conservation measures based on very high resolution stereo satellite data.

Land degradation affects large areas of land around the globe, with grave consequences for those living off the land. Major efforts are being made to implement soil and water conservation measures that counteract soil erosion and help secure vital ecosystem services. However, where and to what extent such measures have been implemented is often not well documented. Knowledge about this could help to identify areas where soil and water conservation measures are successfully supporting sustainable land management, as well as areas requiring urgent rehabilitation of conservation structures such as terraces and bunds. This study explores the potential of the latest satellite-based remote sensing technology for use in assessing and monitoring the extent of existing soil and water conservation structures. We used a set of very high resolution stereo Geoeye-1 satellite data, from which we derived a detailed digital surface model as well as a set of other spectral, terrain, texture, and filtered information layers. We developed and applied an object-based classification approach, working on two segmentation levels. On the coarser level, the aim was to delimit certain landscape zones. Information about these landscape zones is useful in distinguishing different types of soil and water conservation structures, as each zone contains certain specific types of structures. On the finer level, the goal was to extract and identify different types of linear soil and water conservation structures. The classification rules were based mainly on spectral, textural, shape, and topographic properties, and included object relationships. This approach enabled us to identify and separate from other classes the majority (78.5%) of terraces and bunds, as well as most hillside terraces (81.25%). Omission and commission errors are similar to those obtained by the few existing studies focusing on the same research objective but using different types of remotely sensed data. Based on our results, we estimate that the construction of the conservation structures in our study area in Eritrea required over 300,000 person-days of work, which underlines the huge efforts involved in soil and water conservation.

Effectiveness of Conservation Measures in Reducing Runoff and Soil Loss Under Different Magnitude-Frequency Storms at Plot and Catchment Scales in the Semi-arid Agricultural Landscape.

In this study, multi-year stormflow data collected at both catchment and plot scales on an event basis were used to evaluate the efficiency of conservation. At the catchment scale, soil loss from YDG, an agricultural catchment with no conservation measures, was compared with that from CZG, an agricultural catchment with an implementation of a range of conservation measures. With an increase of storm recurrence intervals in the order of <1, 1-2, 2-5, 5-10, 10-20, and >20 years, the mean event sediment yield was 639, 1721, 5779, 15191, 19627, and 47924 t/km(2) in YDG, and was 244, 767, 3077, 4679, 8388, and 15868 t/km(2) in CZG, which represented a reduction effectiveness of 61.8, 55.4, 46.7, 69.2, 57.2, and 66.8 %, respectively. Storm events with recurrence intervals greater than 2 years contributed about two-thirds of the total runoff and sediment in both YDG and CZG catchments. At the plot scale, soil loss from one cultivated slopeland was compared with that from five conservation plots. The mean event soil loss was 1622 t/km(2) on the cultivated slopeland, in comparison to 27.7 t/km(2) on the woodland plot, 213 t/km(2) on the grassland plot, 467 t/km(2) on the alfalfa plot, 236 t/km(2) on the terraceland plot, and 642 t/km(2) on the earthbank plot. Soil loss per unit area from all the plots was significantly less than that from the catchments for storms of all categories of recurrence intervals.