نوع مقاله : مقاله پژوهشی
نویسندگان
1 گروه مطالعات محیطی، پژوهشکده تحقیق و توسعه علوم انسانی (سمت)، تهران، ایران
2 گروه ارزیابی و مخاطرات محیطزیست، پژوهشکده محیط زیست و توسعه پایدار، تهران، ایران.
3 گروه نوآوری و پایداری، دانشکده حکمرانی، دانشگاه تهران، تهران، ایران
4 گروه اقتصاد محیطزیست، پژوهشکده محیط زیست و توسعه پایدار، تهران، ایران.
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Objectives
The primary objectives of this research were: 1) To conduct a spatial assessment and mapping of the sediment retention ecosystem service in the watersheds of Zanjan Province by quantifying avoided soil erosion and avoided sediment export. 2) To identify and delineate priority management areas at the watershed level and provide spatial strategies for enhancing the sediment retention service. The overarching goal was to bridge the gap between detailed biophysical evaluations and practical, location-specific decision-making for sustainable watershed management.
Methodology
The methodological core of this study was the Sediment Delivery Ratio (SDR) model implemented in the InVEST software suite. The process began with estimating soil erosion potential for each pixel using the RUSLE, which synthesizes data layers for rainfall erosivity (R), soil erodibility (K), the topographic length-slope factor (LS) derived from a 30m Digital Elevation Model (DEM), land cover (C), and conservation practices (P). Subsequently, the SDR for each pixel was calculated based on a hydrological connectivity index, balancing upslope resistance and downslope flow path factors. The sediment export from each pixel was then derived as the product of its USLE erosion potential and its SDR. Finally, the ecosystem services of "avoided erosion" (soil loss prevented at source by vegetation) and "avoided sediment export" (sediment prevented from entering streams) were quantified. All spatial data, including land use/land cover from Landsat 8 imagery, were standardized within a GIS environment to a consistent coordinate system and raster resolution for model execution.
Results
The application of the model across Zanjan Province revealed a highly heterogeneous spatial pattern of erosion and sediment dynamics. The total annual soil erosion potential and sediment export for the province were estimated, confirming the severity of the process. More importantly, the existing vegetative cover was quantified as providing a crucial ecosystem service by preventing a vastly greater amount of soil loss and sediment delivery to watercourses annually. Spatial aggregation of pixel-level results to the watershed scale enabled clear prioritization. Watershed 1 was identified as "Critical," contributing the dominant share to both total erosion potential and sediment export. watersheds 7 and 5 were categorized as "High Priority," while the remaining watersheds (2, 3, 4, 6) were classified as "Moderate to Low Priority." This stratification effectively pinpoints areas where management interventions would yield the highest return in terms of reducing sediment loads to vital water reservoirs.
Conclusion
This study successfully moved beyond conventional erosion modeling by translating complex biophysical assessments into operational, priority-ranked maps at a management-relevant scale. By integrating the RUSLE and SDR models within the InVEST framework, it provided a scientifically robust and spatially explicit basis for optimizing the allocation of limited conservation resources. The proposed spatial prioritization enables a shift from uniform, dispersed management approaches to a targeted, evidence-based strategy focused on critical intervention areas. The methodology and findings not only offer a direct and practical tool for watershed managers in Zanjan Province but also establish a replicable framework for adaptive and intelligent decision-making in other watersheds across Iran. Ultimately, this approach supports the development of a dynamic, integrated spatial information system for the national-scale protection of fundamental soil and water resources.
کلیدواژهها [English]