We compiled an extensive database of erosion and runoff measurements on erosion plots under natural rainfall in China. We used this database to analyse how soil loss by sheet and rill erosion and ...runoff in China were affected by land use, slope gradient, slope length and mean annual precipitation. Our results show that land use dominates the variation of soil loss and runoff: Soil loss and runoff rates on land covered by grass and trees are one to three orders of magnitude lower than rates on cropland. Slope gradient and slope length affect soil loss and runoff rates on cropland but there is no statistically significant effect on either soil loss or runoff on plots with a permanent vegetation cover. Runoff rates consistently increase with mean annual precipitation. The relationship between soil loss and mean annual precipitation is, on the contrary, nonlinear for all land use types, with a clear increase of soil loss with precipitation up to a mean annual precipitation of ca. 700 mm yr-1, a subsequent decline and a second rise when the mean annual precipitation exceeds ca. 1400 mm yr-1. We attribute this non-linear response to the interplay of an increasing rainfall erosivity and an increasing protection due to vegetation cover with increasing mean annual precipitation. This non-linear response implies that the effect of precipitation changes induced by climate change on the erosion risk depends on how both rainfall erosivity and vegetation cover change with changing climate. Our study provides important insights as to how soil loss and runoff in China are related to controlling factors and this will allow improving assessments of total soil erosion and runoff rates over the entire territory of China.
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•An erosion plot database of soil loss and runoff measurements in China was compiled.•Land use is the dominant control on soil loss with the highest rates on cropland.•Soil loss increases with slope gradient and length on cropland.•Runoff rates consistently increase with annual precipitation for each land use type.•Soil losses show a local maximum at an annual precipitation of ca. 700 mm.
Understanding soil erosion processes in the Ecuadorian Andes with a tropical wet-dry climate and a variable topography, is fundamental for research on agriculture sustainable, environmental ...management, as well as for a stable water supply for the local populations. This work proposes method to estimate soil erosion risk in the semiarid Catamayo basin with limited data. The results show that the rainfall distribution and the erosivity along with the rugged topography, followed by the land cover (C-factor), are the most important factors to estimate soil erosion risk. The soil erodibility is the most important factor in the dry season for agricultural areas and where the ground cover is sparse. Soil erosion risk is higher in the centre and southwest than in the northeast of Catamayo basin. In protected areas with evergreen vegetation, the soil erosion risk is very low, even with steep slopes and high annual rainfall amounts. The methodology developed allows understanding of the soil erosion processes and the factors that lead to the spatio-temporal variability of soil erosion risk, and as a consequence improves the potential to achieve sustainability of this ecosystem through proposed conservation measures.
•The relation climate–altitude–topography and their influence over erosivity were analyzed.•The conservation of ground cover is key to preventing soil erosion in tropical dry forest.•Seasonality effects on soil erosion process in semiarid watersheds of the Andes.•The relation between climate, soil and land cover was verified at mountain basin scale.
Tropical savannah landscapes are faced with high soil degradation due to climate change and variability coupled with anthropogenic factors. However, the spatiotemporal dynamics of this is not ...sufficiently understood particularly, in the tropical savannah contexts. Using the Wa municipality of Ghana as a case, we applied the Revised Universal Soil Loss Equation (RUSLE) model to predict the potential and actual soil erosion risk for 1990 and 2020. Rainfall, soil, topography and land cover data were used as the input parameters. The rate of predicted potential erosion was in the range of 0–111 t ha−1yr−1 and 0–83 t ha−1yr−1 for the years 1990 and 2020, respectively. The prediction for the rate of potential soil erosion risk was generally higher than the actual estimated soil erosion risk which ranges from 0 to 59 t ha−1yr−1 in 1990 and 0 to 58 t ha−1yr−1 in 2020. The open savannah areas accounted for 75.8 % and 73.2 % of the total soil loss in 1990 and 2020, respectively. The validity of the result was tested using in situ data from a 2 km2 each of closed savannah, open savannah and settlement area. By statistical correlation, the predicted soil erosion risk by the model corresponds to the spatial extent of erosion damages measured in the selected area for the validation. Primarily, areas with steep slopes, particularly within settlement, were identified to have the highest erosion risk. These findings underscore the importance of vegetation cover and effective management practices in preventing soil erosion. The results are useful for inferences towards the development and implementation of sustainable soil conservation practice in landscapes with similar attributes.
This study investigated the intersection between empirically derived and farmers perceived soil erosion risk in a medium-sized catchment on the Ugandan side of mountain Elgon. We postulated that ...farmers' perception of soil erosion risk was high and this influenced their employment of Soil and Water Conservation (SWC) measures on their land. An adapted Revised Universal Soil Loss Equation (RUSLE) was employed to model the soil erosion risk in a Geographical Information System (GIS) environment. Participatory Learning and Action (PLA) tools covering household interviews and Focus Group Discussions (FGDs) were implemented in two representative subcounties of the catchment to elicit information on farmers' perception of soil erosion risk. Household interviews covering 184 respondents were georeferenced using a Geographical Positioning System (GPS). Farmers perceived soil erosion risk on their land was then matched with RUSLE modelled risk using GPS positional data. The modelled soil erosion risk was substantial and a sizeable proportion of the catchment (63%) exhibited soil losses >10 t ha-1 yr-1, which is considered above the tolerable limit for mountain environments. A slight but significant agreement (p < 0.001) between the modelled and farmers perceived soil erosion risk was observed. In general, farmers perceived soil erosion risk was less than the RUSLE model estimates. Although 95% of farmers recognize soil erosion as problematic, only 65% implemented some aspect of SWC on their land albeit with varied purposes. Chi-square tests did not detect a strong association (p > 0.05) between farmers' perceived soil erosion risk and implementation of SWC on their land. On this basis, our postulation that perceived high soil erosion risk influences the implementation of SWC does not suffice in the studied catchment. We surmise that successful risk mitigation should be directed more on increasing farmer's awareness of the long-term adverse consequences of soil erosion on their land.
•We matched RUSLE modeled soil erosion with farmers perceived risk at farm scale in a mountain catchment.•We evaluated the convergence of empirical quantitative soil loss risk rating to with qualitative at varied hillslope segments.•We elicit contradictions between soil erosion risk perception and adoption of soil and water conservation measures (SWC).•Farmers are aware of the adverse consequences of soil erosion, but consider their land to be of good quality.•Sufficiency of implementing SWC is hinged on increasing farmers awareness of the long-term negative implications of erosion.
Cavitation erosion in gear transmissions is lack of study at present, but closely correlating to the damage on tooth surface due to the high impact pressure generated by collapsing bubbles. In this ...study, combined the gear dynamics and two-phase flow simulations, the cavitation erosion risk indicators (CERI) are used for predicting the tooth erosion. In the proposed computational fluid dynamics model considering vibration and cavitation, the gear displacement from finite element model is employed as boundary condition, and the moving mesh technology is used to adapt deformed fluid domain. Subsequently, this method is validated by the available experiments. The erosion on meshing surface is estimated by twelve different CERIs, and the three most reasonable indicators are remained.
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•A two-phase CFD model considering gear dynamics and cavitation is proposed.•Cavitation erosion risk indicators are applied in predicting tooth surface erosion.•Dynamic characteristics of cavitation vapor are studied during teeth engagement.•The cavitation erosion area and degree on meshing surface are investigated.
This research was done in Legedadi watershed since the area was highly susceptible to soil erosion problem that could be aggravated by heavy rainfall, and steep slope. The aim of the present study ...was to examine the impact of LULC change on soil erosion potential in Legedadi watershed, and its implication on sedimentation problems. Multi-temporal Landsat imagery of TM (1985), TM (1997) and ETM+ (2013) were deployed to categorize a LULC map of the study watershed. Soil erosion risk was calculated by using GIS and RUSLE. Digital image processing and classification technique have been done using ERDAS Imagine 9. 2. Results indicate that there was a continuous and active LULC change observed in the watershed for the last 28 years. The settlement area and cultivated land were increased by 14.34% and 18.3%, whereas grazing land and bare land classes were reduced continuously by 25.74% and 18.47% between (1985-2103) respectively. The estimated annual soil losses were 0.0-330 t ha
−1
year
−1
in 2013 whereas in 1997 its range was 0-257.1 t ha
−1
year
−1
. A mean annual soil loss in the watershed was 54.19 t ha
−1
year
−1
in 1997and 66.21 t ha
−1
year
−1
in 2013, respectively. The average annual soil loss from each sub-watershed ranges from 34.57-89.19 t ha
−1
year
−1
. This calls for the coordinated action of the local communities and government in ensuring sustainable natural resource conservation systems considering the Climate Resilient Green Economy strategy of Ethiopia.
Forest ecosystems provide many ecosystem services including soil erosion prevention. Forest areas prone to soil erosion risk should be carefully determined and the appropriate management ...interventions should be designed to ensure the soil protection service of the forest ecosystems. In Turkey, the soil protection function of forests is determined by considering mainly the topographical condition (i.e., slope) of forest landscape. In this study, GIS-based Multi-Criteria Decision Analysis (MCDA) was developed and used to determine forest areas for soil protection function based on erosion risk factors including bedrock, crown closure, ground slope and rainfall. The priorities of the risk factors were determined using Analytical Hierarchy Process (AHP) technique and the spatial data layer of each factor was used to generate the map of soil protection function for a case study area located in the city of Adıyaman, Turkey. The results indicated that the most effective factor on erosion risk was slope, followed by bedrock type. It was found that 36.25% of the study area was under low erosion risk, while 21.47% was classified as high and very high risk. On the other hand, the areas subject to soil protection function was found to be 12.05% of the area when using the classical method which was based on solo ground slope factor. Obviously, the difference (9.42%) comes from the combined use of various other erosion risk factors such as crown closure, bedrock and ground slope. The methodology presented provides decision makers with a practical and an effective prediction approach of soil erosion to develop and take necessary action for minimizing soil loss in forest ecosystems.
Soil erosion affects agricultural landscapes worldwide, threatening food security and ecosystem viability. In arable environments, soil loss is primarily caused by short, intense rainstorms, ...typically characterized by high spatiotemporal variability. The complexity of erosive events challenges modeling efforts and explicit inclusion of extreme events in long-term risk assessment is missing. This study is intended to bridge this gap by quantifying the discrete and cumulative impacts of rainstorms on plot-scale soil erosion and providing storm-scale erosion risk analyses for a cropland region in northern Israel. Central to our analyses is the coupling of (1) a stochastic rainfall generator able to reproduce extremes down to 5-minute temporal resolutions; (2) a processes-based event-scale cropland erosion model (Dynamic WEPP, DWEPP); and, (3) a state-of-the-art frequency analysis method that explicitly accounts for rainstorms occurrence and properties. To our knowledge, this is the first study in which DWEPP runoff and soil loss are calibrated at the plot-scale on cropland (NSE is 0.82 and 0.79 for event runoff and sediment, respectively). We generated 300-year stochastic simulations of event runoff and sediment yield based on synthetic precipitation time series. Based on this data, the mean annual soil erosion in the study site is 0.1 kg m−2 1.1 t ha−1. Results of the risk analysis indicate that individual extreme rainstorms (>50 return period), characterized by high rainfall intensities (30-minute maximal intensity > ~60 mm h−1) and high rainfall depth (>~200 mm), can trigger soil losses even one order of magnitude higher than the annual mean. The erosion efficiency of these rainstorms is mainly controlled by the short-duration (≤30 min) maximal intensities. The results demonstrate the importance of incorporating the impact of extreme events into soil conservation and management tools. We expect our methodology to be valuable for investigating future changes in soil erosion with changing climate.
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•The impact of extreme rainstorms on plot-scale soil erosion was quantified.•The DWEPP erosion model effectively predicts storm-scale plot runoff and erosion.•300-year record of event-based erosion was simulated using a rainfall generator.•Soil erosion risk was calculated by a new statistical method.•Erosion from extreme rainstorm can be about 10 times greater than the annual mean.
Soil erosion is a danger that threatens the world today and the basis of the fight against erosion must be sought in the role human. The aim of this study is determine a logical relationship between ...natural and planted forests conditions with soil erosion risk classes in the kasilian watershed. This basin is located in the Hyrcanian vegetation area on the northern slopes of the Alborz Mountains in northern Iran. In this research, the erosion risk map was prepared using the ICONA model and RS/GIS techniques and it was adapted to the physical realities of the area. The results showed that human interventions and pressures have reduced habitat good species percentage in the downstream areas in the northern part and upstream areas near the forest-rangeland boundary in the southern part. Also, the choice of species was incorrect in some planted forest. Therefore, high erosion risk class is clearly seen in these areas. There is a low erosion risk class (19.3%) in natural forest and a very low erosion risk class (2.73%) in plantation forest. The main reason for the high percentage of very low erosion risk class in planted forests can be due to the presence of 70–80% of canopy, which is a combination of 90% of broadleaf plants with 10% of conifers. These results are consistent with the realities in the study area. The ICONA model and RS/GIS techniques can be used as a reliable framework for erosion risk assessment.
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