Estimating soil loss for sustainable land management planning at the Gelana sub-watershed, northern highlands of Ethiopia

Soil erosion by water is the major form of land degradation in Chereti watershed, Northeastern Ethiopia. This problem is exacerbated by high rainfall after a long period of dry seasons, undulating topography, intensive cultivation, and lack of proper soil and water conservation measures. Hence, this study aimed to estimate the 23 years (1995-2018) average soil erosion rate of the watershed and to identify and prioritize erosion-vulnerable subwatersheds for conservation planning. The integration of the revised universal soil loss equation (RUSLE), geographic information system, and remote sensing was applied to estimate the long-term soil loss of the watershed. The RUSLE factors such as rainfall erosivity ( R), soil erodibility ( K), topography ( LS), cover and management ( C), and support and conservation practices ( P) factors were computed and overlayed to estimate the soil loss. The result showed that the annual soil loss rate of the watershed ranged up to 187.47 t ha−1 year−1 in steep slope areas with a mean annual soil loss of 38.7 t ha−1 year−1, and the entire watershed lost a total of about 487 057.7 tons of soil annually. About 57.9% of the annual watershed soil loss was generated from 5 subwatersheds which need prior intervention for the planning and implementation of soil conservation measures. The integrated use of RUSLE with GIS and remote sensing was found to be indispensable, less costly, and effective for the estimation of soil erosion, and prioritization of vulnerable subwatersheds for conservation planning.

Ethiopia faces a significant challenge in combating soil erosion. This study addresses the concern within Ada’a watershed of the Awash River basin. GIS and the Universal Soil Loss Equation (USLE) Model were used to predict soil loss and the sediment transport index (STI) in the Ada’a watershed of the Awash River basin. RUSLE model required intensive rainfall data registered continuously for 30 min, due to unavailability of this Rainfall data USLE model were preferred. Moreover, USLE model was chosen because of its straightforward methodology and accessibility to data. The study's objectives were to determine the mean annual soil loss rate, STI, and to identify and rank the most important erosion-prone spots for soil conservation planning. Using the interactive Spatial Analyst Tool Map Algebra Raster Calculator in the ArcGIS environment, the mean annual soil loss was estimated based on grid cells by multiplying the corresponding USLE factor values (R, K, LS, C, and P). The STI was also calculated on the Raster Calculator in ArcGIS using flow accumulation and slope gradients. The result shows that R, K, LS, C, and P factor values were estimated in the watershed as 344.9 to 879.65 MJ mm h−1 year−1, 0.11 to 0.38, 0% to 22.23%, 0 to 1, and 0.55 to 1, respectively. The overall annual soil loss in the watershed ranged from 0 to 457.4 tons ha−1 year−1. The Sediment Transport Index ranges from 0 to 856.193. The result implies there is increasing rate of soil losses and sediments observed at alarming rate. The highest rate of soil loss was found in the watershed’s lowest parts. Accordingly, sustainable erosion control mechanisms based on topography and land use types are highly recommended, especially in the upper part of the watershed.

Soil erosion modeling is becoming more significant in the development and implementation of soil management and conservation policies. For a better understanding of the geographical distribution of soil erosion, spatial-based models of soil erosion are required. The current study proposed a spatial-based model that integrated geographic information systems (GIS) techniques with both the universal soil loss equation (USLE) model and the Index of Land Susceptibility to Wind Erosion (ILSWE). The proposed Spatial Soil Loss Model (SSLM) was designed to generate the potential soil erosion maps based on water erosion and wind erosion by integrating factors of the USLE and ILSWE models into the GIS environment. Hence, the main objective of this study is to predict, quantify, and assess the soil erosion hazards using the SSLM in the Dakhla Oasis as a case study. The water soil loss values were computed by overlaying the values of five factors: the rainfall factor (R-Factor), soil erodibility (K-Factor), topography (LS-Factor), crop types (C-Factor), and conservation practice (P-Factor). The severity of wind-driven soil loss was calculated by overlaying the values of five factors: climatic erosivity (CE-Factor), soil erodibility (E-Factor), soil crust (SC-Factor), vegetation cover (VC-Factor), and surface roughness (SR-Factor). The proposed model was statistically validated by comparing its outputs to the results of USLE and ILSWE models. Soil loss values based on USLE and SSLM varied from 0.26 to 3.51 t ha−1 yr−1 with an average of 1.30 t ha−1 yr−1 and from 0.26 to 3.09 t ha−1 yr−1 with a mean of 1.33 t ha−1 yr−1, respectively. As a result, and according to the assessment of both the USLE and the SSLM, one soil erosion class, the very low class (<6.7 t ha−1 yr−1), has been reported to be the prevalent erosion class in the study area. These findings indicate that the Dakhla Oasis is slightly eroded and more tolerable against water erosion factors under current management conditions. Furthermore, the study area was classified into four classes of wind erosion severity: very slight, slight, moderate, and high, representing 1.0%, 25.2%, 41.5%, and 32.3% of the total study area, respectively, based on the ILSWE model and 0.9%, 25.4%, 43.9%, and 29.9%, respectively, according to the SSLM. Consequently, the Dakhla Oasis is qualified as a promising area for sustainable agriculture when appropriate management is applied. The USLE and ILSWE model rates had a strong positive correlation (r = 0.97 and 0.98, respectively), with the SSLM rates, as well as a strong relationship based on the average linear regression (R2 = 0.94 and 0.97, respectively). The present study is an attempt to adopt a spatial-based model to compute and map the potential soil erosion. It also pointed out that designing soil erosion spatial models using available data sources and the integration of USLE and ILSWE with GIS techniques is a viable option for calculating soil loss rates. Therefore, the proposed soil erosion spatial model is fit for calculating and assessing soil loss rates under this study and is valid for use in other studies under arid regions with the same conditions.

Soil erosion and the resulting deposition of sediment in rivers and waterways have major environmental, economic and social implications for Brunei Darussalam. This paper demonstrates a tool for incorporating erosion risk into the strategic land use planning process. Through the application of the Revised Universal Soil Loss Equation (RUSLE), we can predict the approximate rate of soil loss and therefore, erosion risk based on a number of factors, including: rainfall, soil type, slope length and gradient and existing ground cover. RUSLE erosion risk maps produced at a resolution of 100 m2 cells across the country as part of the Sedimentation Study of Main Rivers in Brunei Darussalam provide a planning constraints map that can guide decisions on the location of land use activities. Of particular relevance are the RUSLE maps that were compiled under the assumed scenario that land has been cleared ready for development to provide a realistic estimation of erosion risk if land clearing or land use change was to occur. Erosion risk is classified into seven hazard classes based on the predicted rate of soil loss expressed in tonnes per hectare per year. Urban development, mining and forestry are not recommended in areas within erosion hazard classes 4–7 (moderate to extremely high erosion hazard).

Abstract. Soil erosion is one of the major factors affecting sustainability of agricultural production in Ethiopia. The objective of this paper is to estimate soil erosion using the universal soil loss equation (RUSLE) model and to evaluate soil conservation practices in a data-scarce watershed region. For this purpose, soil data, rainfall, erosion control practices, satellite images and topographic maps were collected to determine the RUSLE factors. In addition, measurements of randomly selected soil and water conservation structures were done at three sub-watersheds (Asanat, Debreyakob and Rim). This study was conducted in Koga watershed at upper part of the Blue Nile basin which is affected by high soil erosion rates. The area is characterized by undulating topography caused by intensive agricultural practices with poor soil conservation practices. The soil loss rates were determined and conservation strategies have been evaluated under different slope classes and land uses. The results showed that the watershed is affected by high soil erosion rates (on average 42 t ha−1 yr−1), greater than the maximum tolerable soil loss (18 t ha−1 yr−1). The highest soil loss (456 t ha−1 yr−1) estimated from the upper watershed occurred on cultivated lands of steep slopes. As a result, soil erosion is mainly aggravated by land-use conflicts and topographic factors and the rugged topographic land forms of the area. The study also demonstrated that the contribution of existing soil conservation structures to erosion control is very small due to incorrect design and poor management. About 35 % out of the existing structures can reduce soil loss significantly since they were constructed correctly. Most of the existing structures were demolished due to the sediment overload, vulnerability to livestock damage and intense rainfall. Therefore, appropriate and standardized soil and water conservation measures for different erosion-prone land uses and land forms need to be implemented in Koga watershed.

A comprehensive methodology that combines Revised Universal Soil Loss Equation (RUSLE), Remote Sensing data and Geographic Information System (GIS) techniques was used to determine the soil loss vulnerability of an agriculture mountainous watershed in Maharashtra, India. The spatial variation in rate of annual soil loss was obtained by integrating raster derived parameter in GIS environment. The thematic layers such as TRMM [Tropical Rainfall Measuring Mission] derived rainfall erosivity (R), soil erodibility (K), GDEM based slope length and steepness (LS), land cover management (C) and factors of conservation practices (P) were calculated to identify their effects on average annual soil loss. The highest potential of estimated soil loss was 688.397 t/ha/yr. The mean annual soil loss is 1.26 t/ha/yr and highest soil loss occurs on the main watercourse, since high slope length and steepness. The spatial soil loss maps prepared with RUSLE method using remote sensing and GIS can be helpful as a lead idea in arising plans for land use development and administration in the ecologically sensitive hilly areas.

Water erosion is a major problem in semi-arid region where decreases the dam reservoir design capacity, agricultural yield productivity, and increases other environmental impacts. This phenomenon is widely predominant in Morocco, particularly in the Oued El Malleh watershed in the Casablanca Settat region. Most soil erosion happens gradually which makes it challenging to notice. Hence, the monitoring of soil degradation under a modelling-based, such as Geographic Information System (GIS) can help the decision-makers to quantify the eroded soil and choose the best mitigation measures. Many erosion control practices have been implemented in The Oued El Malleh watershed in 2008, which covers a surface area of 3127 km2. Even though, the soil erosion still dramatic in the region. To date, no one has attempted to work on the impact of the soil conservation factor at the level of the Oued El Malleh watershed, as well as monitoring the sustainability and effectiveness of the water erosion control practices already implemented. Therefore, periodic monitoring and evaluating soil degradation is imposed. To achieve this purpose, we used the Universal Soil Loss Equation (USLE) to spatially assess water erosion in the study area, to find out the most vulnerable area to erosion, to notice the efficiency of the actual erosion control practices and elaborate on new mitigation measures. The results of this study have been shown that the rate of soil loss in the Oued El Malleh, including the actual control erosion interventions, varies from 0 to 90 t. ha-1.year-1; with an average erosion rate of 0.65 t. ha-1.year-1. The study area characterized by a moderate to severe slopes, in some area, the Length and Steepness Factor LS exceeds 90 %. For this reason, we have been elaborated new soil loss map, including soil conservation measures according to the slope. The soil loss rate; following this approach; varies from 0 to 64 t.ha-1.year-1. Furthermore, the followed approach could be valuable for assessing the soil loss in similar area.
 HIGHLIGHTS
 
 Casablanca-Settat agricultural lands become progressively infertile and depleted soils
 Soil degradation by water erosion is a tidal problem in the Oued El Malleh watershed
 Soil loss was estimated at a watershed level using the USLE model and ArcGIS tool
 The soil loss rate is estimated to be 0.65 t. ha-1.year-1, and the average sedimentary yield is found at 8.27 t. ha-1.year-1
 Sustainable land management can limit soil degradation
 
 GRAPHICAL ABSTRACT

Optimization of land management measures for soil erosion risk using GIS in agricultural landscape of western Hararghe highlands, Ethiopia

A quantitative assessment of soil loss was done using Revised Universal Soil Loss Equation (RUSLE) model, remote sensing and digital elevation model (DEM) in integrated raster based GIS in Bareli watershed, Seoni district of Madhya Pradesh. GIS data layers including rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management (C) and conservation practice (P) factors were computed and integrated to compute average annual soil loss in the watershed. The watershed has been delineated into very low (<10 t ha-1yr-1), low (10–25 t ha-1yr-1), moderate (25–50 t ha-1yr-1), severe (50–100 t ha-1yr-1) and very severe (>100 t ha-1yr-1) soil erosion classes. The study indicated that 63.8% of TGA is under very low to low followed by 14.3% of TGA under moderate soil erosion class. The severe and very severe erosion classes constitute 21.9 % of TGA which warrant immediate attention for preparing strategies for soil and water conservation measures. Various soil and water conservation measures have been suggested based on landforms, soil, slope, land use and soil loss for sustainable management of land resources to improve the productivity of these lands.

Soil loss is estimated by different models in which the soil erodibility factor, K, is one of the important parameters, especially in soils with rock fragments. The objective of this study was to determine the soil erodibility factor by the Universal Soil Loss Equation (USLE) and USLE-M models by direct soil loss measurements for six soil series (three of them contained high amounts of rock fragments) under a rainfall simulator with rainfall intensities of 26–55 mm h−1. The erodibility factor of the six soil series varied between 0.0053 and 0.0125 t ha h (ha MJ mm)−1, in which the three gravelly soils (Bamoo, Loamy-skeletal over fragmental, carbonatic, mesic, Typic Xerorthents; Kuye-asateed, Loamy-skeletal over fragmental, carbonatic, mesic, Typic Xerorthents; and Shekarbany, Fragmental, mixed, mesic, Typic Xerorthents) had medium K values [0.006 t ha h (ha MJ mm)−1]. Other soils (Pump-namazi, Fine, mixed, mesic, Fluventic Haploxerepts; Ramjerdi, Fine, mixed, mesic, Fluventic Haploxerepts; and Daneshkadeh, Fine, mixed, mesic, Typic Calcixerepts) had high K values [0.01 t ha h (ha MJ mm)−1]. Using Wischmeier–Smith nomograph, the estimated K factor (Ku) for the six soil series were by average 5.1 times that of measured K values by the USLE model. The K factor from Wischmeier–Smith nomograph (Ku) was modified for gravel contents for Bamoo, Shekarbany, and Kuye-asateed soil series, therefore, its average value was about 3.5 folds of the amount determined by the USLE model. This modification decreased the Ku/K ratio about 33%. The erodibility factor obtained by USLE-M (Kum) for the six soil series ranged from 0.0184 to 0.0509 t ha h (ha MJ mm)−1. Kum for the six soil series was on the average 5.7 times of that measured K values by USLE models. Ratio of the modified Ku to Kum for the six soil series was on the average 1.39. Therefore, it was concluded that the USLE-M model and the Wischmeier–Smith nomograph after modification for gravel content closely determined the soil erodibility factor.

Quantitative evaluation of soil erosion rate is an important basic to investigate and improve land use system, which has not been sufficiently conducted in Indonesia. The Universal Soil Loss Equation (USLE) and Erosion Three Dimension (E3D) in Surfer were used to identify characteristic of dominant erosion factors in Sumani Watershed in West Sumatra, Indonesia using data soil survey and monitoring sediment yield in outlet watershed. Climatology data from three stations were used to calculate Rainfall erosivity (R) factor. As many as101 sampling sites were used to investigate soil erodibility (K-factor) with physico-chemical laboratory analysis. Digital elevation model (DEM) of Sumani Watershed was used to calculate slope length and Steepness (LS-factor). Landsat TM imagery and field survey were used to determine crop management (C-factor) and conservation practices (P-factor). Calculating soil loss and map of USLE factor were determined by Kriging method in Surfer 9. Sumani Watershed had erosion hazard in criteria as: severe to extreme severe (26.23%), moderate (24.59%) and very low to low (49.18%). Annual average soil loss for Sumani watershed was 76.70 Mg ha-1 y-1 in 2011. Upland area was designated as having a severe to extreme severe erosion hazard compared to lowland which was designated as having very less to moderate. On the other land, soil eroded from upland were deposited in lowland. These results were verified by comparing one year’s sediment yield observation on the outlet of the watershed. Land use (C-factor), rainfall erosivity (R- factor), soil erodibility (K-factor), slope length and steepness (LS-factor) were dominant factors that affected soil erosion. Traditional soil conservation practices were applied by farmer for a long time such as terrace in Sawah. The USLE model in Surfer was used to identify specific regions susceptible to soil erosion by water and was also applied to identify suitable sites to conduct soil conservation planning in Sumani Watershed.[How to Cite : Aflizar, R Afrizal, T Masunaga. 2013. Assessment Erosion 3D Hazard with USLE and Surfer Tool: A Case Study of Sumani Watershed in West Sumatra Indonesia. J Trop Soils, 18 (1): 81-92. doi: 10.5400/jts.2013.18.1.81][Permalink/DOI: www.dx.doi.org/10.5400/jts.2013.18.1.81]

Background: Because of natural and anthropogenic phenomena, most mountain areas experience significant soil loss. It is critical for watershed management to identify high soil loss rates and prone areas. Therefore, the present research aimed to estimate spatial annual soil loss rates and prioritize soil erosion prone areas of the Finca’aa watershed at sub-watershed level. Methods: The revised universal soil loss equation (RUSLE) model, the extension of geographic information system based on five parameters: rainfall erosivity (R), soil erodibility (K), slope length and slope steepness (LS), vegetation cover (C), and conservation techniques (P), was applied. This study also used weather data, a soil type map, a digital elevation model (DEM), and land use land cover, which were all analyzed using ArcGIS 10.4. Results: Annual soil loss rates ranged from negligible to 234 t ha-1 yr-1. The average rates of soil loss was 33.3 t ha-1 yr-1. Approximately 63.36% of the catchment was within and 36.64% of the catchment was above the maximum permissible level, respectively. Approximately 1.96% were in critical condition. Agricultural practices were the primary cause in the watershed’s mountain and hilly areas. Conclusion: The outcome is critical for planners and resource managers interested in long-term watershed management. Also, it is very important for sustainable growth development of 2030 agendas.

Numerous studies found that the main factor contributing to the export of sediment from the Ethiopian highlands is soil erosion, which is related to the expansion of cultivated land at the expense of steep slopes of natural vegetation covers. Plantation practices on steep slopes of bare surfaces and utilizing effective water and soil conservation measures on cultivated lands, may, however, have an impact on the rate of soil loss and the sediment yield ratio. Thus, the main objective of the research was to determine how changes in land use and land cover introduced by soil conservation affected the spatiotemporal variability in soil loss and sediment delivery ratio. RUSLE, InVEST, and integrated GIS technology were used to quantify the study's results. The expansion of farmed land at the expense of natural forests, woodlands, shrubs, and grasslands between 1990 and 2000 resulted in a significant increase in soil loss and sediment yield. This was mostly seen where natural vegetation cover areas on steep slopes were turned into cultivable land. Watershed development interventions significantly decreased both the mean annual soil loss and sediment yields between 2003 and 2021. For instance, from 2010 to 2021, the mean annual soil loss in the watershed dropped by 23.5 t ha−1 and the sediment export declined by 6.13 t ha−1yr−1. To prevent soil loss and sediment export at the extensive level, it is therefore concluded that sustainable soil management on cultivated land and plantation techniques on community land should be expanded up to the adjacent watersheds.

Soil erosion is one of the main reasons for low crop productivity. Identification of areas vulnerable to soil erosion is crucial in applying soil conservation measures especially in river basin. Kirindi Oya river basin is one of the important river basins that supply irrigation for the downstream dry zone of Sri Lanka. This study assessed the soil erosion and generated soil erosion hazard map for Kirindi Oya basin using revised universal soil loss equation (RUSLE) model in Arc GIS 10.2. Predicted soil erosion rates estimated from RUSLE model ranged from 19 to 184 t ha−1 year−1 with an average 33 t ha−1 year−1 for the entire river basin. The basin was categorized into five different erosion hazard classes, low, moderate, high, very high, and extremely high. The study revealed that majority of extremely vulnerable soil erosion areas (> 60 t ha−1 year−1) belongs to Haldummulla area in Badulla district of the basin. About 47% of the basin area in the dry zone was categorized into low erosion hazard class (< 30 t ha−1 year−1). However, these soil loss rates were above the critical soil loss rates (6.7 t ha−1 year−1) stipulated to dry zone, Sri Lanka. The results of this study may help stakeholders to implement soil conservation measures in the Kirindi Oya basin.

Soil erosion by water is a serious concern worldwide problem and it is difficult to assess its economic and environmental impacts accurately. West Hararghe zone is one of the most erosion-prone areas in the eastern highland of Ethiopia which little attention is given. The objectives of this study were to estimate the magnitude of soil loss rate, assess the change of erosion risk, and elucidate their implication for SWC planning in West Hararghe Zone, Eastern Ethiopia. Applying remote sensing data, the study first derived the Revised Universal Soil Loss Equation (RUSLE) model parameters in an ArcGIS 10.3 environment and estimated the soil loss rates. This model was developed based on the integrated use of precipitation data, Landsat images in 2017, and 2018, terrain parameters (slope gradient/steepness and slope length), soil loss management practice and soil composition in west Harerge Zone, Oromia Regional state, Ethiopia. The estimated total soil loss in the Zone was 47,288,835.17 tons in 2017/18 with a mean erosion rate of 28.62 t ha −1 yr −1 . The study area was divided into six erosion risk classes ranging from low to high. About 27.70% (457,687.19 ha) of zone was classified under high to very high soil loss class while the remaining 72.30% (1,194,613.1314 ha) of the zone categorized under slow to moderate soil loss class. Keywords: - GIS, RUSLE, Soil loss potential, West Harerge Zone, Ethiopia DOI : 10.7176/CER/11-2-02 Publication date :March 31 st 2019