Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Remote Sensing and GIS-Based Soil Loss Estimation Using RUSLE in Bahir Dar Zuria District, Ethiopia

Domaine:

environment and energygeospatialagriculture

Type de record:

paper
Créateur:
NurDes
Éditeur:
Int
Hôte:
The severity of soil loss in the Ethiopian highlands has been increased from time to time. Hence, the assessment of soil erosion using models is very important for planning successful and sustainable soil management. This study was conducted in Bahir Dar Zuria district, Ethiopia with aiming to quantify the amount of soil loss using the GIS-based RUSLE (Revised Universal Soil Loss Equation) model. Based on the study, the most pronounced RUSLE factor that increases soil erosion was the slope length (L) and slope steepness (S). Compared with other land uses, bare land and cropland in the higher slopes were more vulnerable to erosion. As expected slope and soil losses have a direct relationship. About 80% of the study area experienced annual soil loss of less than 1.2 ton/ha/yr. Conversely, soil loss was very high for slopes greater than 30%. This indicated that slope has a great impact on regulating soil loss. The annual soil loss for cropland, vegetation, grassland, and degraded land was 19.05, 8.78, 8.82, and 71.16 ton/ha/yr., respectively. This is to means that land use land cover have a strong relationship with the amount of soil loss. The same land cover with different slopes have different soil loss amount. It was found that lack of vegetative cover during the critical period of rainfall, expansion of croplands, and absence of support practices increase soil erosion. Thus, the application of stone lines, contour tillage, terraces, and grass strip barriers are suggested to break the slope length into shorter distances, reducing overland flow velocity and soil erosion. Moreover, improving the awareness of society to reduce the illegal cutting of trees and apply conservation practices to reduce soil erosion in their farmland is very essential.

Visit

doi.org

Languages

Amharic

Licenses

https://creativecommons.org/licenses/by/3.0/legalcode

Similaires

Potential Soil Loss Estimation and Erosion-Prone Area Prioritization Using RUSLE, GIS, and Remote Sensing in Chereti Watershed, Northeastern EthiopiaSoil loss estimation and severity mapping using RUSLE model and GIS: a case study in Megech Watershed, EthiopiaAssessment of soil erosion of Burundi using remote sensing and GIS by RUSLE modelSoil Loss Estimation Using Remote Sensing and RUSLE Model in Koromi-Federe Catchment Area of Jos-East LGA, Plateau State, NigeriaSoil Erosion Assessment Using the RUSLE Model and Geospatial Techniques (Remote Sensing and GIS) in South-Central Niger (Maradi Region)Mapping malaria risk using geographic information systems and remote sensing: The case of Bahir Dar City, Ethiopia

Potential Soil Loss Estimation and Erosion-Prone Area Prioritization Using RUSLE, GIS, and Remote Sensing in Chereti Watershed, Northeastern Ethiopia

Soil erosion by water is the major form of land degradation in Chereti watershed, Northeastern Ethio

Soil loss estimation and severity mapping using RUSLE model and GIS: a case study in Megech Watershed, Ethiopia

Abstract Abstract Background: Soil erosion is the most serious problem that affects eco

Assessment of soil erosion of Burundi using remote sensing and GIS by RUSLE model

This present work is the results of study on water erosion in Burundi, a landlocked country amid the

Soil Loss Estimation Using Remote Sensing and RUSLE Model in Koromi-Federe Catchment Area of Jos-East LGA, Plateau State, Nigeria

Soil loss caused by erosion has destroyed landscapes, as well as depositing sterile material on fert

Soil Erosion Assessment Using the RUSLE Model and Geospatial Techniques (Remote Sensing and GIS) in South-Central Niger (Maradi Region)

A systematic method, incorporating the revised universal soil loss equation model (RUSLE), remote se

Mapping malaria risk using geographic information systems and remote sensing: The case of Bahir Dar City, Ethiopia

The main objective of this study was to develop a malaria risk map for Bahir Dar City, Amhara, which