Soil-erosion and runoff prevention by plant covers in a mountainous area (se spain): Implications for sustainable agriculture

In the Mediterranean region the intensities and amounts of soil loss and runoff on sloping land are governed by rainfall pattern and vegetation cover. Over a two-year period (1998–1999), six wild species of aromatic and mellipherous plants (Thymus serpylloides subsp. Gadorensis, Thymus baeticus Boiss, Salvia lavandulifolia Vahl., Santolina rosmarinifolia L., Lavandula stoechas L. and Genista umbellata Poiret) were selected for erosion plots to determine their effectiveness in reducing water erosion on hillslopes of the Sierra Nevada Mountain (SE Spain). The erosion plots (including a bare-soil plot as control), located at 1,345 m in altitude, were 2 m² (2 m × 1 m) in area and had 13% incline. The lowest runoff and soil erosion rates, ranging from 9 to 26 mm yr⁻¹ and from 0.01 to 0.31 Mg ha⁻¹ yr⁻¹, respectively, over the entire study period, were measured under the Thymus serpylloides. Lavandula stoechas L. registered the highest rates among the plant covers tested, runoff ranging from 77 to 127 mm yr⁻¹ and erosion from 1.67 to 3.50 Mg ha⁻¹ yr⁻¹. In the bare-soil plot, runoff ranged from 154 to 210 mm yr⁻¹ and erosion from 4.45 to 7.82 Mg ha⁻¹ yr⁻¹. According to the results, the lowest-growing plant covers (Thymus serpylloides and Salvia lavandulifolia Vahl.) discouraged the soil erosion and runoff more effectively than did the taller and open medium-sized shrubs (Santolina rosmarinifolia L., Genista umbellata Poiret, Thymus baeticus Boiss and Lavandula stoechas L.). Monitoring allowed more direct linkage to be made between plant covers and the prevention of erosion, with implications for sustainable mountain agriculture and environmental protection.     

Development and Testing of a Physically Based Model of Streambank Erosion for Coupling with a Basin‐Scale Hydrologic Model SWAT

A comprehensive streambank erosion model based on excess shear stress has been developed and incorporated in the hydrological model Soil and Water Assessment Tool (SWAT). It takes into account processes such as weathering, vegetative cover, and channel meanders to adjust critical and effective stresses while estimating bank erosion. The streambank erosion model was tested for performance in the Cedar Creek watershed in north‐central Texas where streambank erosion rates are high. A Rapid Geomorphic field assessment (RAP‐M) of the Cedar Creek watershed was done adopting techniques developed by the Natural Resources Conservation Service (NRCS), and the stream segments were categorized into various severity classes. Based on the RAP‐M field assessment, erosion pin sites were established at seven locations within the severely eroding streambanks of the watershed. A Monte Carlo simulation was carried out to assess the sensitivity of different parameters that control streambank erosion such as critical shear stress, erodibility, weathering depth, and weathering duration. The sensitive parameters were adjusted and the model was calibrated based on the bank erosion severity category identified by the RAP‐M field assessment. The average observed erosion rates were in the range 25‐367 mm year^?1. The SWAT model was able to reasonably predict the bank erosion rates within the range of variability observed in the field (R² = 0.90; E = 0.78). Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Optimal spatial resolution for collection of ground data and multi-sensor image mapping of a soil erosion cover factor

Military training activities disturb ground and vegetation cover of landscapes and increases potential soil erosion. To monitor the dynamics of soil erosion, there is an important need for an optimal sampling design in which determining the optimal spatial resolutions in terms of size of sample plots used for the collection of ground data and the size of pixels for mapping. Given a sample size, an optimal spatial resolution should be cost-efficient in both sampling costs and map accuracy. This study presents a spatial variability-based method for that purpose and compared it with the traditional methods in a study area in which a soil erosion cover factor was sampled and mapped with multiple plot sizes and multi-sensor images. The results showed that the optimal spatial resolutions obtained using the spatial variability-based method were 12 and 20m for years 1999 and 2000, respectively, and were consistent with those using the traditional methods. Moreover, the most appropriate spatial resolutions using the high-resolution images were also consistent with those using ground sample data, which provides a potential to use the high-resolution images instead of ground data to determine the optimal spatial resolutions before sampling. The most appropriate spatial resolutions above were then verified in terms of cost-efficiency which was defined as the product of sampling cost and map error using ordinary kriging without images and sequential Gaussian co-simulation with images to generate maps.     

Developing a framework for integrating local and scientific knowledge in internationally funded environment management projects: case studies from Kien Giang Province,Vietnam

Local and scientific knowledge, when adequately and properly integrated, produces enormous benefits for natural resource management in comparison to a single knowledge system being used. Adequate and proper integration has major constraints that include ineffective use of the integrated knowledge, thoroughly inclusive processes, and true public participation. A six-stage framework is developed using the results and conclusions of two case studies regarding sustainable management of eroding mangrove-dominated muddy coasts in Vam Ray, Hon Dat district, Kien Giang Province, Vietnam. The framework does not stop with the creation of integrated knowledge, but should undergo a longer process. The new knowledge developed in this framework is the understanding gained and lessons learnt during the testing of products of multiple knowledge systems in a local context rather than products of integrated knowledge systems themselves. The Vam Ray framework promotes a high level of participation, effective use of products of multiple knowledge systems, maximum integration of local and scientific knowledge, local ownership, and sustainability. Therefore, the Vam Ray framework adds a new dimension to the literature in relation to integration of local and scientific knowledge in natural resource management.