USLE Model Research Articles

Estimation of soil erosion by USLE model using GIS technique (A case study of upper Citarum Watershed)

Citarum Watershed is categorized as a critical watershed due to erosion and environmental damage. Erosion is a continuing long-term problem because of its impact to the economic use and environment. The purpose of this study is to determine the distribution of annual soil erosion by USLE model using Geographic Information System (GIS). The four major input parameters affecting to soil erosion are rainfall erosivity factor (R), length slope factor (LS), soil erodibility factor (K), and land use factor (CP). The result showed that the average annual soil erosion was 122,76 ton/ha/year. The erosion hazard categorized into four classes which are low, moderate, high and very high. The low level of erosion is <15 ton/ha/year has about 2,47% area of low level and located in the north of Upper Citarum Watershed. The moderate level of erosion is 15 - 60 ton/ha/year has about 11,13% area of moderate level and located in the north, east, southeast and south of Upper Citarum Watershed. The high level of erosion is 61 - 180 ton/ha/year has about 78,53% of high level which dominates Upper Citarum Watershed. The very high level of erosion is >180 ton/ha/year has about 7,87% of very high level and located in south and southwest of Upper Citarum Watershed. The result can be used as a consideration for soil erosion prevention measures by local people and government to reduce soil loss.

Estimation of soil loss by USLE Model using Remote Sensing and GIS Techniques - A Case study of Coastal Odisha, India

Globally, Soil erosion is the major land degradation problem, which impacts seriously on economic and environmental status. Geospatial techniques support and provided quantitative approach to estimate soil erosion in different conditions. In the present study, Revised Universal Soil Loss Equation (RUSLE) integrated with GIS has been used to estimate soil loss in the part of coastal Odisha system. The study area, Ganjam block have undulating topography covering 0-35% slopes. The quantitative soil loss was estimated and classified into different classes and soil erosion map was generated. The soil erosion map is classified into seven classes from very slight (<5 t ha -1 yr -1 ) to extremely severe (>80 t ha -1 yr -1 ). The results indicate that 90.9% (22330 ha) of the study area falls in very low erosion category, which may be due to level topography and regular vegetation cover. The other erosion classes such as moderate, high and very high erosion occurred in the range of 2.12%, 2.23% and 1.49 %, respectively. The high soil erosion risk is spatially situated in the foothills and upper steep slope of the area. The results can certainly aid in implementation of soil management and conservation practices to reduce the soil erosion in the coastal Odisha regions of Eastern India.

Effect of hillslope topography on soil erosion and sediment yield using USLE model

Catchment hillslopes in nature have a complex geometry. Complex hillslopes have different plans (convergent, parallel and divergent) and different curvature (straight, concave and convex). In this study, the erosion rates of the nine complex hillslopes were investigated using the universal soil loss (USLE) method. The topography factor (LS function) in the USLE was developed as a function of plan shape and profile curvature. The hillslopes studied were divided into sets of complex pixels and the erosion over the pixels was calculated. Total erosion was regarded as the sum of erosion of all pixels. Furthermore, to calculate the sediment delivery ratio of each pixel, a new travel time equation for complex hillslopes was employed. Results showed that the mean erosion of convex hillslopes was 1.43 times that of concave and 1.19 times that of straight slopes. The effect of curvature shape on erosion was much greater than plan shape effect. The highest erosion belonged to convex divergent slopes, and the least erosion was related to concave divergent slopes. The laboratory results intended for validation of the numerical model also show that in hillslopes with fixed plan, the erosion rate in the convex hillslopes exceeds that of concave and straight hillslopes. Also, in the hillslopes with fixed curvature profile, the erosion rate in the convergent hillslopes is more than in the divergent and parallel ones.

Sediment Yield Estimation Using RS and GIS for Upper Karha Watershed Maharashtra India

Soil erosion and water conservation are major concerns arising from agricultural acceleration, changing land patterns and uncertain rainfall pattern. Soil erosion within watersheds results in increasing the deposition of sedimentation in the water bodies and thus dropping their carrying capacity and life span. Soil erosion studies are crucial for watershed design and management. The objective of current investigation is to quantify sediment yield of Upper Karha watershed of Pune district, Maharashtra, India, which is a semi-arid zone and rain-shadow region. In the present study, the sediment yield assessment by USLE model and RUSLE model is performed with the help of remote sensing and geographical information system. The average annual sediment yield is observed, i.e. 4.54 tonne/acre/year and 4.14 tonne/acre/year by USLE and RUSLE models, respectively. To address the current issue of sedimentation, suitable sites and suitable types of structures were suggested for soil and water conservation.

Terasering Mekar Erosion Control Model in Batur Lake Zone

Erosion control in Lake Batur area is community-based directed to maintain lake balance. The aims of this research is; (1) to obtain a community-based erosion control model, (2) to analyze the role of communities in the application of land management models. (3) Analyzing other plant species in collaboration with the arrangement model . (4) Analyzing the impact of terraces blooming against sedimentation. This research is field experiments and surveys, and the sampling was conducted by purposive sampling with 64 samples. The socio-economic support data of the community was determined by 180 respondents by cluster sampling. Interviews and questionnaires were conducted through closed questions on a conventional scale. The characteristics of the lake were analyzed statistically and descriptively by using the SPSS tool. Land mapping was conducted by GPS method with GIS device. Prediction of erosion was by using USLE Model, while sedimentation was measured by the Stanford Sediment model. The analysis shows that the increase of settlement is averagely of 115,85%, plantation is 245,50% and the sedimentation level is 1,017,93 m3 / year. Conclusions and outcomes were in the form of community-based terracing model that collaborate with elephant grass and vetiveria plants.

Community-based erosion control model in Batur Lake zone

Erosion control in Lake Batur area is community-based directed to maintain lake balance. The aims of this research is: 1) to obtain a community-based erosion control model, 2) to analyze the role of communities in the application of land management models, 3) to analyze other plant species in collaboration with the arrangement model, and 4) to analyze the impact of terraces blooming against sedimentation. This research is field experiments and surveys, and the sampling was conducted by purposive sampling with 64 samples. The socio-economic support data of the community was determined by 180 respondents by cluster sampling. Interviews and questionnaires were conducted through closed questions on a conventional scale. The characteristics of the lake were analyzed statistically and descriptively by using the SPSS tool. Land mapping was conducted by GPS method with GIS device. Prediction of erosion was by using USLE Model, while sedimentation was measured by the Stanford Sediment model. The analysis shows that the increase of settlement is averagely of 115.85%, plantation is 245.50% and the sedimentation level is 1,017,93 m3/year. Conclusions and outcomes were in the form of community-based terracing model that collaborate with elephant grass and vetiveria plants.

Estimation of Soil Losses in a Slope Area of Tokat Province through USLE and WEPP Model

Tokat is one of the developing provinces in terms of urbanism. Therefore, the land use changes city-wide which closely affects soil erosion. Numerical estimation of soil erosion is very important to prevent soil losses. In this study, USLE and WEPP Hillslope model were used to estimate the long-term soil losses in a slope area which used to be a pasture land and then turned into a fruit orchard in Büyükbeybağı area of Tokat province. Erosion sensitivity of the soil in the slope area was detected to be very low. Erosivity value of the area is low, soil is resistant to erosion due to pasture land use type and fruit orchard use type does not require intense soil cultivation practices. For all these reasons, both estimation technologies estimated soil losses of the land to be low.

A GIS-based USLE Model to Estimate Soil Loss Potential of Arid Lands of Southern Iran

A GIS-based USLE Model to Estimate Soil Loss Potential of Arid Lands of Southern Iran

A stochastic estimation of sediment production in an urban catchment using the USLE model

ABSTRACTThe goals of this study were to map the spatial distribution of sediment production and to estimate the probability of this production at the waterline based on a high potential of silting. The RUSLE-GIS model and Monte Carlo simulation were used. A sensitivity analysis of stochastic factors was performed by calculating the simple correlation coefficient. This procedure was applied to the Estrada Nova catchment, located in the city of Belém, northern Brazil, which has been subject to channel improvements and the construction of a detention basin. The results indicate that, following the urbanization and drainage improvements, there was a reduction in the annual sediment production probability, which is consistent with the dynamics in land use. The erodibility was the most sensitive factor in the sedimentation estimates. The methodology was considered an alternative to estimate sediment production in an urban catchment.

AVALIAÇÃO DO POTENCIAL DE UTILIZAÇÃO DOS DADOS DA SRTM - SHUTTLE RADAR TOPOGRAPHY MISSION POR MEIO DA ANÁLISE DA ESTIMATIVA DE PERDA DE SOLO

A qualidade dos resultados depende da acurácia dos dados disponíveis. Dados topográficos de todo o globo, provenientes da SRTM - Shuttle Radar Topography Mission, são disponibilizados gratuitamente. Se corretos, estes dados constituem recurso poderoso para o planejamento territorial e ambiental. O objetivo deste trabalho foi verificar o grau de semelhança da informação disponibilizada pela SRTM com outra de maior resolução, aplicada ao modelo EUPS – Equação Universal de Perda de Solo para estimar a perda de solo em uma microbacia em São Carlos, São Paulo, Brasil. A acurácia do MDT SRTM foi avaliada por meio do índice KAPPA que, através de uma matriz de erro, mostra o grau de semelhança entre dois mapas. O índice KAPPA revelou que o MDT SRTM possui um nível de precisão considerado razoável (0.6594) para os mapas de estimativa de perda de solo, entretanto os mapas do fator LS, potencial natural de erosão e estimativa de perda de solo possuem níveis de acurácia considerados baixo (0.2584), baixo (0.2582) e moderado (0.4199), respectivamente. Finalmente, os dados fornecidos pela SRTM apresentaram resultados razoáveis, quando multiplicados por dados de maior resolução em cenários de relevo pouco acidentado. Contudo devem ser utilizados com precaução em outras situações.

CHANGE ANALYSIS ON SOIL EROSION OF FUJIAN PROVINCE FROM 1990 TO 2015

Abstract. Soil erosion is one of major environment problems in the world, and China is one of the most serious soil erosion country. In this paper, Fujian province was used as a study area for its typical red soil region. Based on USLE model, the soil erosion modulus in 1990 and 2015 were calculated and turned to soil erosion intensity. The soil erosion distribution trend in Fujian province was decrease from south-east coastal zone to north-west inland region. In soil erosion areas, the main erosion type was light level with about 80 %, and the soil erosion levels above serious type were mainly sporadic distribution with less than 10 %. The soil erosion improved for the past 25 years. The areas of different erosion types all decreased, and the total erosion area reduced by 26.59 %. The improvement area mainly located in north-east, south and west region. The aggravation area mainly located in the north and some middle hilly regions. The impact of human activities is more significant for erosion control.

Effects of Land-use Management Scenarios on Soil Erosion Rate using GIS and USLE Model in Yamchi Dam Watershed, Ardabil

Effects of Land-use Management Scenarios on Soil Erosion Rate using GIS and USLE Model in Yamchi Dam Watershed, Ardabil

Determining the spacing of ridge terraces on arable land in central and south-western Poland

Abstract The practice of many countries has shown that terraces can significantly prevent land degradation processes such as excessive soil erosion, landslides. Condition is good layout, proper construction, and then proper maintenance. Practical application in many countries showed that terraces can significantly prevent processes leading to the degradation of land, such as the excessive erosion of soils and landslides. The requirement for this is well-planned, adequate construction, and later – proper conservation. In Poland this is a little popular method. In the article, the dorsal spacing terraces were calculated for two catchments – in the central and south-western parts of Poland. Meteorological and soil data were used for Puczniew station (Ner catchment) and Boleścin station (Mielnica catchment). Kolmogorov–Smirnov test was performed to assess the compatibility of a given feature with a normal distribution, then the distribution of the probability distribution was developed. For probability 1, 50 and 90% the spacing of terraces was calculated using Ramser and Morgan method. The results obtained were combined with the results from the USLE model. Hydraulic methods have shown greater spacing for the Mielnica catchment (loess soils) compared to the Ner basin (clay loam). For the USLE model, the larger spacing was calculated for the Ner basin. From the practical application to the acceptance of land user will be the maximum distance calculated by different methods. The highest terrace spacing values were obtained using the Morgan method for the Mielnica catchment, for the Ner catchment model USLE.

English

English

Comparing Sediment Trap Data with Erosion Models for Evaluation of Forest Haul Road Stream Crossing Approaches

Abstract. Soil erosion and sediment delivery models have been developed to estimate the inherent complexities of soil erosion, but most models are not specifically modified for forest operation applications. Three erosion models, the Universal Soil Loss Equation for forestry (USLE-Forest), Revised Universal Soil Loss Equation Version 2 (RUSLE2), and Water Erosion Prediction Project (WEPP), were compared to one year of trapped sediment data for 37 forest haul road stream crossings. We assessed model performance from five variations of the three erosion models: USLE-Roadway, USLE-Soil Survey, RUSLE2, WEPP-Default, and WEPP-Modified. Each road approach was categorized into one of four levels of erosion (very low, low, moderate, and high) based on trapped erosion rate data and erosion rates reported in recent peer-reviewed literature. Model performance metrics included: (1) summary statistics and nonparametric analysis, (2) linear relationships, (3) percent agreement within erosion categories and tolerable error ranges, and (4) contingency table metrics. Sediment trap data varied from negligible ( -1 year -1 . The soil erosion models evaluated could estimate erosion within 5 Mg ha -1 year -1 for most approaches having erosion rates less than 11.2 Mg ha -1 year -1 , while models estimates varied widely for approaches that eroded at rates above 11.2 Mg ha -1 year -1 . Kruskal-Wallis nonparametric analyses revealed that only WEPP-Modified estimates were not significantly different from trapped sediment data (p ≥ 0.107). While WEPP-Modified ranked best for most model performance metrics, the time, effort, modeling expertise, and uncertainty associated with model results may discourage the use of WEPP as a forest management tool. WEPP is better suited for researchers and government agencies that have the capability to measure extensive parameter data. Additional sensitivity analysis is needed to expand default parameters for forest roads within the WEPP and USLE models.

Estimation of Soil Erosion in Rodnei Mountains National Park Using G.I.S. Technique

Abstract Erosion is one of the biggest and most widely spread forms of soil degradation, having an impact on both the surrounding environment and the economical one as well. According to a recent study from 2014-2015 by the Common Research Center an estimate of approximately 11.4% of the EU’s territory has been affected by the erosion process in moderate to high levels, the soil’s erosion rate being higher than 5t/ha/year. A significant part of Romania’s surface feels the negative effects of the soils degradation, erosion being the most widely spread long-term complex phenomena. Identifying as exactly as possible the areas with erosion risk is recommended in order to intervene with measures of consolidation, leveling, terrain modeling and other hydro-improving constructions. For this reason, for the studied area, Rodnei Mountains National Park (Maramureș County, Bistrita-Nasaud County), having a surface of 47.177 ha, the soil’s erosion has been modeled via the USLE model, developed by Motoc in 1979, taking into consideration all the climate conditions specific to Romania. Following the implementation of the G.I.S environment model, the soil’s erosion estimate values have been obtained, subsequently being divided in 8 classes of erosion, losses of soil less than 0.5t/ha/year representing 89.3% out of the park’s total surface. Researching the model’s obtained results and comparing them to existing values of soil erosion, locally and nationally, we can draw the conclusion that the results of the USLE model are truthful, and that the model can be successfully used in the studied area. Thereby, the study has targeted the determination of vulnerabilities at the erosional processes and vulnerabilities to erosion, the risk of erosion susceptibility being assessed.

Soil erosion degradation of Ukraine under the impact of climate change

Uncontrolled and intensive development of erosion process increases the risk of soil surface degradation and desertification in the agricultural landscapes. Climate change amplifies the frequency of extreme rainfalls, which reduce the erosion resistance of agricultural landscapes, especially the agricultural systems with row crops. The risk of erosion soil degradation due to the increased frequency of extremedaily rainfall was estimated. The current rate of year soil loss, caused by water erosion, was estimated using USLE model, and forecast for 2045 was simulated in the case study in typical Ukrainian agricultural landscapes of forest-steppe zone within Kanivskyi and Myronivskyi districts. It is confirmed, that in areas where the soil protection measures are not taken, a significant intensification of erosion processes is predicted as a result of exposure to extreme weather conditions. The measures to adapt to climate change through the implementing a system of erosion control measures on river basin principles and integrated management of land, water, biological and agrarian resources are suggested

Testing of Coupled SCS Curve Number Model for Estimating Runoff and Sediment Yield for Eleven Watersheds

Abstract: The soil conservation service (SCS) methodology for computing direct run-off, using soil-cover-moisture complexes involves the selection of a runoff curve number (CN) for such complex events. This method has been further simplified by introducing an assumption on initial abstraction, with only one unknown parameter CN, which is represented by the potential retention capacity of the watershed (S). In this study, coupled SCN-CN with USLE model was used for the estimation of the runoff and sediment yield for eleven watersheds of different land uses (urban, agricultural, and forest) from Damodar Valley Corporation (DVC), Hazaribagh district, Jharkhand, India. For the validation, runoff-sediment yield model is employed to a large set of rainfall-runoff-sediment yield data (68 storm events) observed from eleven watersheds. Model performance was assessed by using Nash and Sutcliffe statistical method. The efficiency of results was varying from 60.42 to 92.99 % for sediment yield and 54.23 to 96.12 % for runoff; this efficiency showed a reliable performance of model for estimating the sediment yield and runoff.

Modification of the USLE K factor for soil erodibility assessment on calcareous soils in Iran

The measurement of soil erodibility (K) in the field is tedious, time-consuming and expensive; therefore, its prediction through pedotransfer functions (PTFs) could be far less costly and time-consuming. The aim of this study was to develop new PTFs to estimate the K factor using multiple linear regression, Mamdani fuzzy inference systems, and artificial neural networks. For this purpose, K was measured in 40 erosion plots with natural rainfall. Various soil properties including the soil particle size distribution, calcium carbonate equivalent, organic matter, permeability, and wet-aggregate stability were measured. The results showed that the mean measured K was 0.014thMJ−1mm−1 and 2.08 times less than the estimated mean K (0.030thMJ−1mm−1) using the USLE model. Permeability, wet-aggregate stability, very fine sand, and calcium carbonate were selected as independent variables by forward stepwise regression in order to assess the ability of multiple linear regression, Mamdani fuzzy inference systems and artificial neural networks to predict K. The calcium carbonate equivalent, which is not accounted for in the USLE model, had a significant impact on K in multiple linear regression due to its strong influence on the stability of aggregates and soil permeability. Statistical indices in validation and calibration datasets determined that the artificial neural networks method with the highest R2, lowest RMSE, and lowest ME was the best model for estimating the K factor. A strong correlation (R2=0.81, n=40, p<0.05) between the estimated K from multiple linear regression and measured K indicates that the use of calcium carbonate equivalent as a predictor variable gives a better estimation of K in areas with calcareous soils.

Estimate of the (R)USLE rainfall erosivity factor from monthly precipitation data in mainland Spain

The need for continuous recording rain gauges makes it difficult to determine the rainfall erosivity factor (R-factor) of the (R)USLE model in areas without good temporal data coverage. In mainland Spain, the Nature Conservation Institute (ICONA) determined the R-factor at few selected pluviographs, so simple estimates of the R-factor are definitely of great interest. The objectives of this study were: (1) to identify a readily available estimate of the R-factor for mainland Spain; (2) to discuss the applicability of a single (global) estimate based on analysis of regional results; (3) to evaluate the effect of record length on estimate precision and accuracy; and (4) to validate an available regression model developed by ICONA. Four estimators based on monthly precipitation were computed at 74 rainfall stations throughout mainland Spain. The regression analysis conducted at a global level clearly showed that modified Fournier index (MFI) ranked first among all assessed indexes. Applicability of this preliminary global model across mainland Spain was evaluated by analyzing regression results obtained at a regional level. It was found that three contiguous regions of eastern Spain (Catalonia, Valencian Community and Murcia) could have a different rainfall erosivity pattern, so a new regression analysis was conducted by dividing mainland Spain into two areas: Eastern Spain and plateau-lowland area. A comparative analysis concluded that the bi-areal regression model based on MFI for a 10-year record length provided a simple, precise and accurate estimate of the R-factor in mainland Spain. Finally, validation of the regression model proposed by ICONA showed that R-ICONA index overpredicted the R-factor by approximately 19%.