Identification of soil erosion hotspot areas for sustainable land management in the Gerado catchment, North-eastern Ethiopia

Asmamaw, Legass; Assen, Mohammed

doi:10.1016/j.rsase.2018.11.010

Cited by 27 publications

(25 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This result is consistent with the study by Kamaludin et al (2013) and Lihan et al (2018). Similar study by Asmamaw and Mohammed (2019) has stated that at the steeper slope, the velocity and volume of the surface runoff will be accelerated which lead to much higher potential of soil loss. There is no significant different between predicted and measured values for LS factor as p value is more than 0.05 for 95% confidence level.…”

Section: Discussionsupporting

confidence: 92%

See 1 more Smart Citation

Prediction of Soil Erosion in Pansoon Sub-basin, Malaysia using RUSLE Integrated in Geographical Information System

Yusof¹,

Lihan²,

Idris³

et al. 2019

JSM

View full text Add to dashboard Cite

Water-borne erosion problem is one of the environmental problems faced globally particularly in developing countries. The objective of this study was to estimate the erosion rate at the Pansoon sub-basin using combination of conventional approach and remote sensing technology. Pansoon sub-basin is the upper stream of Langat watershed, Malaysia located in the mountainous area dominated by steep slopes and various type of soils which are the important factors contributed to soil erosion. The Revised Universal Soil Loss Equation (RUSLE) integrated in a Geographical Information System used to predict the soil erosion rate and spatially maps its distribution using rainfall, soil series and topography data to generate rainfall erosivity factor, soil erodibility factor and topography factor. Land use map was used to produce coverage and management practice factor. The result shows that 66% (7433 ha) of the Pansoon sub-basin is classified at very low risk, 22% of low risk (2433 ha), 5% of moderate (582 ha), 2% of the area with high risk (251 ha) and 5% of very high risk of erosion (549 ha). Pansoon sub-basin is prone to soil erosion problem on the southwest region may due to soil erodibility factor, slope length and slope steepness. Accuracy assessment was obtained between prediction model and field observation data (p=0.97) which means the RUSLE approach integrated in GIS is suitable to be used to predict and assessing the soil erosion rate. In conclusion, the prediction of soil erosion using RUSLE in GIS can be accurately assessed with the combination of field observation data. ABSTRAKMasalah hakisan yang disebabkan oleh air merupakan salah satu masalah alam sekitar yang dihadapi di seluruh dunia terutamanya di negara membangun. Objektif kajian ini adalah untuk menganggarkan kadar hakisan di sub-lembangan Pansoon menggunakan gabungan pendekatan konvensional dan teknologi penderiaan jauh. Sub-lembangan Pansoon adalah kawasan hulu lembangan Langat, Malaysia yang terletak di kawasan pergunungan yang dikelilingi oleh cerun curam dan beberapa jenis tanih yang merupakan faktor penting yang menyumbang kepada hakisan tanah. Semakan Semula Persamaan Kehilangan Tanih Universal (RUSLE) yang diintegrasikan dalam Sistem Maklumat Geografi digunakan untuk meramal kadar hakisan tanah dan peta ruangan dengan menggunakan data hujan, siri tanih dan topografi bagi menghasilkan faktor erosiviti hujan, faktor kebolehhakisan tanah dan faktor topografi. Peta guna tanah digunakan bagi menghasilkan faktor liputan dan amalan pengurusan. Hasil kajian mendapati 66% (7433 ha) daripada sub-lembangan Pansoon dikelaskan sebagai berisiko sangat rendah, 22% daripadanya adalah berisiko rendah (2433 ha), 5% daripadanya adalah sederhana (582 ha), 2% (251 ha) dan 5% daripadanya adalah hakisan yang sangat tinggi (549 ha). Sub-lembangan Pansoon terdedah kepada masalah hakisan tanah di wilayah barat daya mungkin disebabkan oleh faktor kebolehhakisan tanah, panjang cerun dan kecerunan. Kajian ketepatan diperoleh antara model ramalan dan data kerja lapangan (p=0...

show abstract

Section: Discussionsupporting

confidence: 92%

“…Soil erodibility factor, K refers to the ability of soil to be displaced by the rainfall forces (Asmamaw & Mohammed 2019;Jazouli et al 2019). K factor can be computed using soil texture, soil structure, organic content and permeability.…”

Section: Soil Erodibility Factormentioning

confidence: 99%

Prediction of Soil Erosion in Pansoon Sub-basin, Malaysia using RUSLE Integrated in Geographical Information System

Yusof¹,

Lihan²,

Idris³

et al. 2019

JSM

View full text Add to dashboard Cite

show abstract

“…However, in the study area, there were no conservation measures, as data were lacking on permanent management factors and there were no management practices the P-factor suggested by Wischmeier and Smith [57]. This method has also been used in the highlands of Ethiopia by others [4,24,37,48,54]. This method categorizes land covers into agricultural land, shrubland, and forest land.…”

Section: Erosion Control Practice Factor (P)mentioning

confidence: 99%

Estimation of soil loss rate using the USLE model for Agewmariayam Watershed, northern Ethiopia

Girmay¹,

Moges

Muluneh

2020

Agric & Food Secur

View full text Add to dashboard Cite

Background Soil erosion and nutrient depletion threaten food security and the sustainability of agricultural production in sub-Saharan Africa. Estimating soil loss and identifying hotspot areas support combating soil degradation. The aim of this paper is to estimate the soil loss rate and identify hotspot areas using USLE model in the Agewmariam watershed, northern Ethiopia. Methods Rainfall erosivity factor was determined from annual rainfall, soil erodibility factor from soil data, slope length and gradient factor were generated from DEM, cover factor and conservation practice factor obtained from land use cover map. Finally, the parameters were integrated with ArcGIS tools to estimate soil loss rates of the study watershed. Results Mean annual soil loss rates were estimated to be between 0 and 897 t ha−1 year−1 on flatter and steeper slopes, respectively. The total annual soil loss was 51,403.13 tons from the watershed and the annual soil loss rate of the study area was 25 t ha−1 year−1. More than 33% of the study areas were above tolerable soil loss rate (11 t ha−1 year−1). The spatial risk categorization rate was 67.2% severe (> 51 t ha−1 year−1), 5.4% very high (31–50 t ha−1 year−1), 5.8% high (19–30 t ha−1 year−1), 3.2% moderate (12–18 t ha−1 year−1) and 18.3% slight (0–11 t ha−1 year−1). Conclusion The results showed that the severity of erosion occurred on the steep slope cultivation, absence of conservation measures, and sparse nature of the vegetation cover. This area required immediate action of soil and water conservation which accounts for about 33.5% of the total watershed.

show abstract

“…Within the study area, there exists a broad series of both mechanical, biological and agronomic measures for erosion control include terracing, infiltration ditches, contour bunds, trenches, hedgerows, intercropping, mulching and agroforestry techniques [23,24]. Since it is not feasible to quantify the impact of different support practices applied on a large scale [78], this research adopted the P factor values ( Table 2) suggested by Wischmeier and Smith [33] which considers only two types of land uses-agricultural and other-and land slopes [79,80]. Accordingly, the LULC map for 2000 and 2015 ( Figure 2) was reclassified as agricultural (cropland) and other lands (forestland and grassland) ( Table 2).…”

Section: Support Practice (P) Factormentioning

confidence: 99%

Land Use Change Impacts on Water Erosion in Rwanda

Nambajimana

Zhou

et al. 2019

Sustainability

View full text Add to dashboard Cite

Rwanda has experienced accelerated soil erosion as a result of unsustainable human activities and changes in land use. Therefore, this study aimed at applying the RUSLE (Revised Universal Soil Loss Equation) model using GIS (Geographical Information System) and remote sensing to assess water erosion in Rwanda, focusing on the erosion-prone lands for the time span 2000 to 2015. The estimated mean annual soil losses were 48.6 t ha −1 y −1 and 39.2 t ha −1 y −1 in 2000 and 2015, respectively, resulting in total nationwide losses of approximately 110 and 89 million tons. Over the 15 years, 34.6% of the total area of evaluated LULC (land use/land cover) types have undergone changes. The highest mean soil loss of 91.6 t ha −1 y −1 occurred in the area changing from grassland to forestland (0.5%) while a mean soil loss of 10.0 t ha −1 y −1 was observed for grassland converting to cropland (4.4%). An attempt has been made to identify the embedded driving forces of soil erosion in Rwanda. As a result, we found that mean soil loss for Rwanda's districts in 2015 was significantly correlated with poverty (r = 0.45, p = 0.013), increased use of chemical fertilizers (r = 0.77, p = 0.005), and especially was related to extreme poverty (r = 0.77, p = 0.000). The soil conservation scenario analysis for Rwanda's cropland in 2015 revealed that terracing could reduce the soil loss by 24.8% (from 14.6 t ha −1 y −1 to 11.7 t ha −1 y −1 ). Most importantly, the study suggests that (1) terracing integrated with mulching and cover crops could effectively control water erosion while ameliorating soil quality and fertility, and (2) reforestation schemes targeting the rapid-growing tree species are therefore recommended as an important feature for erosion control in the study area.

show abstract

Identification of soil erosion hotspot areas for sustainable land management in the Gerado catchment, North-eastern Ethiopia

Cited by 27 publications

References 20 publications

Prediction of Soil Erosion in Pansoon Sub-basin, Malaysia using RUSLE Integrated in Geographical Information System

Prediction of Soil Erosion in Pansoon Sub-basin, Malaysia using RUSLE Integrated in Geographical Information System

Estimation of soil loss rate using the USLE model for Agewmariayam Watershed, northern Ethiopia

Land Use Change Impacts on Water Erosion in Rwanda

Contact Info

Product

Resources

About