International Soil and Water Conservation Research最新文献

{"title":"The evolution of large gullies in association with long-term rainfall in the Tsitsa River Catchment, Eastern Cape, South Africa","authors":"Ryan Leigh Anderson ,&nbsp;Jay le Roux ,&nbsp;Kate Rowntree","doi":"10.1016/j.iswcr.2025.02.004","DOIUrl":"10.1016/j.iswcr.2025.02.004","url":null,"abstract":"<div><div>Large gullies exist as permanent features in the landscape that impact the surrounding environment and communities. The effect of rainfall on long-term gully evolution is still understudied, especially for large gully systems. The extent of the growth of the gullies of four large gullies in the Eastern Cape Province (South Africa) is explored over a 70-year period (1950–2020) in relation to rainfall. The extent of these gullies was mapped by manually digitizing the gully edges using aerial surveys and SPOT images captured during the study period. Daily rainfall depths were assessed to examine intense rainfall and rainfall erosivity values using the modified Fournier index. The results reveal an exponential trend of the evolution of the gully in which two phases of development of the gully occurred, according to the type of erosion processes that occurred. The first phase (1950–2004) was mainly characterised by the linear lengthening of the gully systems. The second phase (2004–2020) is mainly characterised by the initiation and growth of side branches in the gullies, with greater increases in extent. Both phases recorded highly erosive rainfall. It is postulated that gully expansion accelerated in Phase 2 due to land degradation resulting from increased livestock in the area. This study highlights that intense rainfall, while acting as a driver for gully expansion, is influenced by interconnected factors, including vegetation cover removal and topography. The findings of this study have implications for the results of control measures in large gully systems with dispersive soils.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 2","pages":"Pages 290-300"},"PeriodicalIF":7.3,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic change of watershed sediment sources during implementation of the “grain for green” project in the coarse sandy areas of the Chinese Loess Plateau","authors":"Kai Wang ,&nbsp;Gang Liu ,&nbsp;Xiaokang Wang ,&nbsp;Yingli Shen ,&nbsp;Chengbo Shu ,&nbsp;Qiong Zhang ,&nbsp;Xiaolin Xia ,&nbsp;Dandan Liu ,&nbsp;Zhen Guo ,&nbsp;Xining Zhao","doi":"10.1016/j.iswcr.2025.02.003","DOIUrl":"10.1016/j.iswcr.2025.02.003","url":null,"abstract":"<div><div>A quantitative assessment of sediment sources is crucial for understanding soil erosion trends and enhancing soil erosion prevention and control measures. The environmental elements, such as vegetation, land use, and rainfall, etc., of the Chinese Loess Plateau (CLP) changed significantly after the implementation of “Grain for Green” (GFG) project. However, the response of sediment sources to the environmental changes in different periods remains unclear. In this study, sediment yields and sources were investigated by using the composite fingerprinting method. Forty flood couplets and their sediment yields corresponding to the 20-year period after the GFG project were established in Shagouba watershed, Shaanxi Province, China. Results showed that the thicker flood couplets, the higher percentage of silt and clay particles. Following the GFG project, the cumulative sediment yields during the first period (2000–2010) was 91,760 t, and in the second period (2011–2019) was 77,940 t. The sediment contributions changed from the first period that gully (48.73%) &gt; shrub sandy land (28.82%) &gt; sloping farmland (12.06%) &gt; forestland and grassland (8.58%) &gt; road (1.81%), to the second period that gully (47.33%) &gt; shrub sandy land (26.40%) &gt; forestland and grassland (10.27%) &gt; road (9.02%) &gt; sloping farmland (6.98%). The gully always contributes the most sediment, thus implementing measures such as safeguarding gully heads and constructing bio-valley mills in channels were recommended to mitigate gully erosion. This study provides a scientific basis for evaluating the effects of the GFG project on the <span>CLP</span>, and theoretical support for the scientific management of small watersheds.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 3","pages":"Pages 564-575"},"PeriodicalIF":7.3,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144329598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling land use changes impacts on the silting of small agricultural water harvesting reservoirs","authors":"Elia Degli Innocenti ,&nbsp;Giulio Castelli ,&nbsp;Simone Pozzolini ,&nbsp;Federico Preti ,&nbsp;Elena Bresci ,&nbsp;Enrica Caporali","doi":"10.1016/j.iswcr.2025.02.001","DOIUrl":"10.1016/j.iswcr.2025.02.001","url":null,"abstract":"<div><div>Water harvesting with Small Agricultural Reservoirs (SmAR) represents a solution for sustainable water management in different contexts. However, many technical challenges are still open despite its widespread application. One of the most relevant, for the sustainable management of SmAR, is represented by the loss of storage volume caused by the inflow of sediments, but the analysis of the dynamics of sedimentation for such small structures has received relatively little interest so far. This study aims to implement a validated model simulating the hydrology and erosion dynamics of the catchment upstream of a SmAR in the Mediterranean basin, specifically in the hilly area of Crete Senesi, Tuscany Region (Italy). Here, wine production is particularly developed, but not within the catchment of study, where the cultivation of cereals and forage is practiced. Our analysis aimed at estimating how much the rate of sediment accumulation in the reservoir would vary with the replacement of currently arable land with vineyards. A model was implemented on the HEC-HMS software, maximizing the value of existent low-cost data (Google Earth imagery and regional erosion maps) for its validation. The validated model was then used to test alternative land use scenarios in the upstream catchment, showing its flexibility for supporting decision-making over SmAR management. The model performed with an error always below 5% on the SmAR area detected by satellite. Erosion values calculated with HEC-HMS were in line, but lower than the estimation made by the Tuscany region with a GIS-based procedure. The scenario analysis showed that the simulated land use change led to a high value of annual sediment accumulation in the reservoir (216% of the original value of erosion obtained with cereals and other crops), showing the indirect cost of changing the cropping patterns to vineyard production. The approach can be replicated at the local scale in all other contexts where similar, and relatively easy-to-get, data are available. Further development of the present approach can include the replication of similar low-cost methodologies on other case studies, refinement of the erosion modelling and sensitivity analysis.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 2","pages":"Pages 422-435"},"PeriodicalIF":7.3,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictive performance and uncertainty analysis of ensemble models in gully erosion susceptibility assessment","authors":"Congtan Liu ,&nbsp;Haoming Fan ,&nbsp;Yixuan Wang","doi":"10.1016/j.iswcr.2025.01.004","DOIUrl":"10.1016/j.iswcr.2025.01.004","url":null,"abstract":"<div><div>Gully erosion, as a significant natural process in geomorphological evolution, poses serious threats to natural environments and socio-economic stability. In response, Gully Erosion Susceptibility Maps (GESMs) have become essential references for effective watershed management. This study aims to identify the optimal feature datasets and to quantify the uncertainty associated with gully erosion prediction models by developing a novel methodological framework based on ensembles of the three machine learning models: Random Forest (RF), Convolutional Neural Network (CNN), and Transformer models. This study area is the Tuquan watershed in Inner Mongolia, China. A total of 25 Geo-Environmental Factors (GEFs) were selected to build datasets, supplemented by a gully inventory map comprising 823 gullies, resulting in 12,946 samples of both gully and non-gully occurrences. 3 ensemble methods including probability mean (PM), Probability Weighted Mean (PWM), and Probability Empirical Weighted Mean (PEWM) were used. Subsequently, the datasets underwent multi-collinearity testing before model computations. The optimal feature datasets S₇ included factors such as the Convergence Index (CI), Topographic Wetness Index (TWI), Terrain Ruggedness Index (TRI), distance from river, annual rainfall, distance from road, drainage density, elevation, Normalized Difference Vegetation Index NDVI, slope, and Slope Length (LS). The ensemble model Transformer-RF-CNN employing PEWM demonstrated superior performance, validated by 10-fold cross-validation and 8 metrics: Efficiency (E), True Positive Rate (TPR), False Positive Rate (FPR), True Skill Statistics (TSS), Kappa coefficient (K), Area Under the receiver operating characteristic Curve (AUC), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The uncertainty associated with GESMs was quantified using the Coefficient of Variation (CV) map, resulting in a confidence map that classified 20 zones, with 75.976% of gullies located in high-susceptibility and low-uncertainty areas. This study provides critical insights for regulators and decision-makers, facilitating more informed planning for gully erosion prevention and control.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 2","pages":"Pages 319-333"},"PeriodicalIF":7.3,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving SOC estimation in low-relief farmlands using time-series crop spectral variables and harmonic component variables based on minimum sample size","authors":"Chenjie Lin ,&nbsp;Ling Zhang ,&nbsp;Nan Zhong","doi":"10.1016/j.iswcr.2025.01.005","DOIUrl":"10.1016/j.iswcr.2025.01.005","url":null,"abstract":"<div><div>Efficiently monitoring Soil Organic Carbon (SOC) in farmlands is crucial for environmental and agricultural sustainability. Currently, crop spectral variables are primarily employed to estimate SOC in low-relief farmlands. To enhance SOC estimation, further crop information needs to be excavated. Additionally, few studies have considered the sample size in modeling SOC estimation, which may lead to precision loss and cost waste. Therefore, this study proposed a novel method to improve SOC estimation in low-relief farmlands. This method considers more information on crop growth and minimum sample size. The results showed that: (1) time-series NDVI was established as the characteristic crop spectral variables, based on crop spectral variables extracted from eight-day time-series reflectance products. (2) Seventeen harmonic component variables were derived from time-series NDVI via Fourier transformation. (3) Six crop spectral variables and seven harmonic component variables were determined as the optimal SOC estimators. (4) The convolutional neural network model provided higher SOC estimation accuracy (R² = 0.81, NRMSE = 7.09%) than the random forest model and the back propagation neural network model. And the minimum sample size based on the optimal model was determined to be 250. (5) The proposed method improved SOC estimation at the regional scale, achieving a 2.54% reduction in NRMSE compared to the NDVI-based model. These findings suggest that the proposed method holds the potential for efficient SOC estimation in low-relief farmlands.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 2","pages":"Pages 395-409"},"PeriodicalIF":7.3,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Morphology evolution of vegetation-covered loess gully heads induced by hydraulic and gravitational erosion","authors":"Hongliang Kang ,&nbsp;Wenlong Wang ,&nbsp;Liangna Li ,&nbsp;Lei Han","doi":"10.1016/j.iswcr.2025.01.003","DOIUrl":"10.1016/j.iswcr.2025.01.003","url":null,"abstract":"<div><div>Gully heads suffer hydraulic and gravitational erosion triggered by rainstorms. However, how hydraulic and gravitational erosion affect the morphology evolution of the vegetation-covered loess gully heads is unclear. Field flow scouring and separation experiments were conducted to simulate the runoff and erosion processes of vegetation-covered gully heads subjected to concentrated flow on the Loess Plateau. The results show that the gully heads experienced early simplex hydraulic erosion and subsequent compound hydraulic and gravitational erosion under concentrated flow, resulting in the initiation, development, shrinkage, and reformation of the scour hole and plunge pool. In the early period, the rates of the scour hole widening and deepening had significant linear relationships with the on-wall flow rate (<em>P</em> &lt; 0.01); moreover, among the hydraulic parameters of jet flow, the cumulative width and stable depth of the plunge pool had the highest significant correlations with the kinetic energy of the jet flow into the plunge pool (<em>P</em> &lt; 0.01). Gravitational erosion contributed 26–50% and 0–26% to the maximum width and depth of the scour hole, respectively, and hydraulic erosion played a dominant role in scour hole development. Nevertheless, an overhanging mass collapse could reduce the depth and width of the plunge pool by 56–87% and 77–93%, respectively. The gully head retreated as a cyclic process of scour hole development, scour hole collapse (scour hole enlargement), overhanging mass collapse (scour hole shrinkage), and scour hole redevelopment. The mutual promotion of hydraulic erosion and gravitational erosion resulted in the sustained retreat of the vegetation-covered gully heads.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 2","pages":"Pages 447-462"},"PeriodicalIF":7.3,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How does shrub stem coverage affect the hydraulic properties of concentrated flow and sediment yield during gully bed erosion?","authors":"Lin Liu ,&nbsp;Donghong Xiong ,&nbsp;Baojun Zhang ,&nbsp;Dan Yang ,&nbsp;Yong Yuan ,&nbsp;Binyan Zhang ,&nbsp;Wenduo Zhang ,&nbsp;Liangtao Shi ,&nbsp;Xiaodan Wang","doi":"10.1016/j.iswcr.2025.01.002","DOIUrl":"10.1016/j.iswcr.2025.01.002","url":null,"abstract":"<div><div>Vegetation plays a critical role in influencing runoff processes and soil loss during gully bed erosion. However, it is still unclear how the stem coverage affects gully bed erosion processes by altering the runoff hydraulics and soil sedimentation. A series of in situ scouring experiments were conducted to investigate the influence of shrub stem coverage on the concentrated flow pathway characteristics, hydrodynamic parameters, and sediment concentration during gully bed erosion processes. The Flow pathway characteristics expressed by the Number of flow pathways (FN), total Flow path Width (FW), Tortuosity Ratio (TR), and Fractal Dimension (FD) were quantified by analyzing photographs of the gully bed surface taken during experimental periods. Structural equation model was used to analyze the comprehensive effect of stem coverage on hydraulic erosion of gully beds. The results showed that FN, FW, and TR increased linearly, and FD increased exponentially as stem coverage increased. Compared with the bare gully bed, the flow velocity and shear stress of gully beds with shrub stem covers decreased by 17.47%–25.19% and 4.75%–11.42%, respectively, while the Darcy-Weisbach friction factor increased by 35.94%–68.71%. The sediment concentration of stem-covered gully beds decreased by 11.82%–26.93%. The increasing stem coverage promoted concentrated flow branching and significantly increased FW, which in turn altered hydraulic parameters, particularly reducing flow velocity, and ultimately reducing sediment concentrations indirectly. These results contribute to partially explaining the differences in flow hydraulics and soil loss of vegetated gully beds in previous studies that failed to account for changes in flow pathways.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 2","pages":"Pages 334-347"},"PeriodicalIF":7.3,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring best soil conservation practices using the tolerable soil loss limit in central highland of Ethiopia: A case study of Andit Tid watershed","authors":"Tilahun Getachew Abebe ,&nbsp;Tesfaye Mebrate Lemma ,&nbsp;Tesfa Worku Meshesha","doi":"10.1016/j.iswcr.2025.01.001","DOIUrl":"10.1016/j.iswcr.2025.01.001","url":null,"abstract":"<div><div>Soil erosion is a major issue in Ethiopia, prompting ongoing watershed development campaigns. This study contributes to exploring Best Soil Conservation practices (BSCPs) to reduce erosion rates to/or below Tolerable Soil Loss Limits (TSLLs). To achieve these the study used the SWAT model, coupled with the SWAT Calibration and Uncertainty Procedures (SWAT-CUP), for simulation, sensitivity analysis, calibration, and validation using streamflow and sediment yield data. The calibrated SWAT model was used to assess soil erosion hotspot areas and evaluate the effectiveness of the selected BSCPs: Soil and/or Stone Bund (SSB), Grass strip (GT), reforestation (RF), Soil and/or Stone Bund and grass strip (SSB and GT) and Soil and/or Stone Bund and Reforestation (SSB and RF). The results revealed that 22.9% of the area showed soil loss rates below the TSLL. Furthermore, varying degrees of erosion above the TSLL was observed, with sub-watershed SW-12 experiencing the highest erosion rate (47 t ha⁻¹yr⁻¹) and sub-watershed SW-2 experiencing the lowest (7.8 t ha⁻¹yr⁻¹). Among the evaluated BSCPs, SSB + RF demonstrated the greatest erosion reduction effectiveness at 76.6%, followed by SSB + GT, SSB, RF, and GT, with erosion reduction effectiveness values of 61.7%, 60.0%, 43.3%, and 13.9%, respectively. Based on these findings, SSB + RF is recommended for erosion reduction to or below the TSLL, with implementation priority given to sub-watersheds SW-12, SW-10, SW-3, SW-2, and SW-5, ranked in descending order of erosion rate severity. During implementation, emphasis should be placed on reforestation of plant species of high ecological importance.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 2","pages":"Pages 348-361"},"PeriodicalIF":7.3,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction and mapping of soil organic carbon in the Bosten Lake oasis based on Sentinel-2 data and environmental variables","authors":"Shaotian Li ,&nbsp;Xinguo Li ,&nbsp;Xiangyu Ge","doi":"10.1016/j.iswcr.2024.12.002","DOIUrl":"10.1016/j.iswcr.2024.12.002","url":null,"abstract":"<div><div>Soil is the largest carbon pool on the Earth's surface. With the application of remote sensing technology, Soil Organic Carbon (SOC) estimation has become a hot topic in digital soil mapping. However, the heterogeneity of geomorphology can affect the performance of remote sensing in determining soil organic carbon. In the Bosten Lake Watershed in northwestern China, we collected 116 soil samples from farm land, uncultivated land, and woodland. To establish an SOC prediction model, we produced 16 optical remote sensing variables and 9 environmental covariates. Three types of land use were studied: farm land, uncultivated land, and woodland. Five machine learning models were used for these land use types: gradient Tree (ET), Support Vector Machine (SVM), Random Forest (RF), Adaptive gradient Boosting (AdaBoost), and extreme Gradient Boosting (XGBoost). The main driving variables for changes in organic carbon content across the entire sample area were Enhanced Vegetation Index (EVI), Enhanced Vegetation Index 2 (EVI2), Soil-Adjusted Vegetation Index (SAVI); for farm land, it was Clay Index (CI2); for farm land and woodland, it was Color Index (CI). The results showed that in terms of prediction accuracy, RF and XGBoost outperformed SVM. In terms of simulation precision, the ET model's woodland model (R² = 0.86, RMSE = 7.72), the ET model's farm land model (R² = 0.82, RMSE = 6.66), and the uncultivated land model of the RF model (R² = 0.81, RMSE = 1.09) performed best. Compared to global modeling, establishing SOC estimation models based on different land use types yielded more ideal results in this study. These findings provide new insights into high-precision estimation of organic carbon content.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 2","pages":"Pages 436-446"},"PeriodicalIF":7.3,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soil erosion elasticity initiative for prioritizing sub-watersheds","authors":"Mostafa Zabihi Silabi,&nbsp;Seyed Hamidreza Sadeghi,&nbsp;Mehdi Vafakhah","doi":"10.1016/j.iswcr.2024.12.001","DOIUrl":"10.1016/j.iswcr.2024.12.001","url":null,"abstract":"<div><div>Quantitative evaluation of soil erosion is necessary to analyze the destructive effects of soil erosion and to identify priority sub-watersheds in different climatic and environmental conditions. The variability of soil erosion thresholds introduced as Erosion elasticity (Ee) can be used to develop reliable management strategies in various temporal and spatial scales. Ee is a potential degree of soil erosion in an area representing the magnitude between maximum and minimum erosion rates. However, the comprehensive prioritization of sub-watersheds according to environmental changes and the concept of Ee is yet to be done. Therefore, the present study introduced the Ee-based approach based on the watershed's maximum and minimum soil erosion capability. The prioritization of the sub-watersheds of the Shazand Watershed of Iran has been exemplified, and the associated results were compared to those of conventional annual soil erosion zoning. Towards that, the mean annual soil erosion and corresponding changes of the study watershed were estimated according to the dynamic changes of vegetation cover and rainfall erosivity. Prioritizing 24-study sub-watersheds was then comparatively conducted using mean annual soil erosion and erosion elasticity approaches. The results of the RUSLE application showed that the soil erosion of the Shazand Watershed varied between 0 and 72 t ha⁻¹ year⁻¹ with a mean annual erosion of 14.35 t ha⁻¹ year⁻¹. The results further revealed that the worst and the best combination of soil erosion factors cause +151% and −62% changes in mean annual soil erosion of the Shazand Watershed. Based on the amount of soil erosion method, sub-watersheds 11, 14, and 23 were placed in the highest priorities, and sub-watersheds 5, 6, 16, and 17 are the lowest priority for management measures. In addition, the results of the Ee approach showed that 28% of the study sub-watersheds were placed in high and relatively high priorities, respectively, and sub-watersheds 9, 13, 18, 19, and 23 stand in the lowest priority. The Ee approach effectively identified the critical sub-watersheds to reduce their tendency to destructive conditions and take appropriate measures to reduce their soil erosion and move them towards ideal conditions. The results can help planners and managers implement the best management measures in priority sub-watersheds, saving time and cost.</div></div>","PeriodicalId":48622,"journal":{"name":"International Soil and Water Conservation Research","volume":"13 2","pages":"Pages 277-289"},"PeriodicalIF":7.3,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}