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Mapping landslide susceptibility in the Debretabor-Alember road sector, Northwestern Ethiopia through geospatial tools and statistical approaches Tesfaye, Betelhem; Jothimani, Muralitharan; Dawit, Zerihun
Journal of Degraded and Mining Lands Management Vol. 11 No. 2 (2024)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2024.112.5169

Abstract

This study aimed to locate areas along the Debretabor-Alember route segment in northern Ethiopia that are susceptible to landslides. Geospatial tools, specifically frequency ratios (FR) and information values (IV), were used to develop landslide susceptibility maps (LSMs). A comprehensive on-site investigation and analysis of Google Earth imagery were conducted, resulting in the detection and analysis of 89 landslides, including current and historical events. The dataset used for validation comprised 78% of the previously documented landslides, whereas the remaining 22% was used for training. Several factors were considered in this study to determine landslide susceptibility, including "slope, aspect, curvature, elevation, lithology, distance from streams, land use and cover, precipitation, normalized difference vegetation index (NDVI)", and the FR and IV models. Based on the results obtained using the FR approach, specific areas exhibited different levels of susceptibility, ranging from very low to moderately high, medium, high, and very high. These areas covered a total of 18.4 km2 (19.9%), 18.9 km2 (20.5%), 19.7 km2 (20.3%), 17.7 km2 (20%), and 17.7 km2 (19%), respectively. The LSMs generated by the IV model indicated multiple susceptibility classes in the study area, varying from very low to very high. These maps revealed that 18.4 km2 (19.8%), 18.8 km2 (20%), 18.9 km2 (19.5%), 18.8 km2 (20.5%), and 18.3 km2 (19.8%) of the area fell into these susceptibility classes. The landslide density indicator method was employed to validate the LSMs. The FR and IV models demonstrated that a significant proportion of confirmed past and current landslide records (72.16% and 73.86%, respectively) occurred in regions with a high or very high susceptibility to landslides. Overall, the IV model, which utilized latent variable structural modeling (LSM) in the independent variable model, outperformed the fixed effects regression model (FR).
Assessing landslide susceptibility in Lake Abya catchment, Rift Valley, Ethiopia: A GIS-based frequency ratio analysis Oyda, Yonas; Jothimani, Muralitharan; Regasa, Hailu
Journal of Degraded and Mining Lands Management Vol. 11 No. 3 (2024)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2024.113.5885

Abstract

Ethiopia's varied landscape, significant rainfall, and diverse geological characteristics pose risks of landslides. The specific research area spans 40 km2 within the Lake Abaya catchment area in the Rift Valley of Ethiopia. This investigation aimed to map landslide susceptibility using remote sensing information, GIS technology, and frequency ratio analysis. It evaluated multiple factors influencing landslide susceptibility. The process involved meticulous mapping of thematic layers, utilizing GIS techniques and diverse data sources, including primary data, satellite imagery, and secondary sources. A combination of Google Earth image analysis and field surveys was used to map landslide susceptibility in inaccessible areas. It was determined that 138 landslide sites existed. Of these, 30% (41 points) were assigned to the test of the model and another 30% to the training of the model, for a total of 97 points. The landslide susceptibility was classified into five categories based on frequency ratio analysis of the landslide susceptibility index (LSI): very low, low, moderate, high, and very high. The northeastern sector of the study area demonstrated a comparatively diminished susceptibility to landslides, ranging from low to moderate, whereas the central and southern regions showcased markedly elevated vulnerability. An evaluation of the model's accuracy using the area under the curve (AUC) method based on test inventory landslide data produced encouraging results: 84.8% accuracy on the success rate curve and 78.8% accuracy on the prediction rate curve. Based on the frequency ratio model, a susceptibility map is derived to represent susceptibility levels accurately.
Remote sensing, GIS, and RUSLE in soil loss estimation in the Kulfo river catchment, Rift valley, Southern Ethiopia Jothimani, Muralitharan; Getahun, Ephrem; Abebe, Abel
Journal of Degraded and Mining Lands Management Vol. 9 No. 2 (2022)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2022.092.3307

Abstract

Quantification of soil is crucial for maximizing the advantages of land resources while minimizing the negative consequences of land degradation in the long term. It will also make it possible to identify locations that need immediate soil erosion management. The present study was carried out in the Kulfo river catchment, Rift valley, Southern Ethiopia. The Revised Universal Soil Loss Equation (RUSLE) method was utilized to estimate the mean yearly soil loss in the research region using remote sensing, other collateral data. The RUSLE model inputs were mapped and integrated into the ArcGIS software, and the results show that 0 and 1211 t ha−1year−1 are the minima and maximum soil loss in the present study area. Soil erosion-prone regions were divided into three categories: 0-42 t ha−1year−1 (low), 43-128 t ha−1 year−1 (medium), and > 128 t ha−1 year−1 (high). And the average rate of soil erosion is 68.47 t ha−1year−1. Low, medium, and high soil erosion areal extent and area percentages in the current research area is 270 km2 (77 %), 61 km2 (17 %), and 19 km2 (6%), respectively. A high rate of soil erosion was found where high steep slope, barren land, and high precipitation occurred in the present study area. The current study's outcomes were confirmed by comparing soil loss estimates in the same geo-environmental conditions found in Ethiopia's highlands. The outcome of this study is important for decision-makers and policymakers.
Groundwater quality mapping for drinking and irrigation purposes using statistical, hydrochemical facies, and water quality indices in Tercha District, Dawuro Zone, Southern Ethiopia Arota, Arefegn; Atlabachew, Abunu; Abebe, Abel; Jothimani, Muralitharan
Journal of Degraded and Mining Lands Management Vol. 9 No. 2 (2022)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2022.092.3367

Abstract

When groundwater quality is good, it may be a substantial water supply for various applications. However, no systematic research on hydrogeochemistry and water quality features for drinking and irrigation has been undertaken in the present study area. As a result, the current study looked at hydrogeochemical variables and groundwater quality for drinking and irrigation in Tercha district, Dawuro Zone, Southern Ethiopia. Forty-seven groundwater samples were collected and tested to satisfy the required target for various physicochemical properties. The hydrogeochemical features of the groundwater in the study region were assessed using in-situ testing and laboratory analysis of physicochemical parameters. Groundwater samples from the research region were slightly acidic to slightly basic, with the principal cations and anions decreasing in sequence: Na+ > Ca2+ > Mg2+ > K+ and HCO3-> Cl-> SO42-. The hadrochemical facies of the studied region evolved from mildly mineralized dominant highland Ca-HCO3 water types to moderately mineralized mixed Ca-Na-HCO3 water types to highly mineralized deep rift floor Na-HCO3 water types. Additionally, the World Health Organization and the Ethiopian Standard Agency were utilized to compare the drinking water quality. Except for NO3- (4.25 %), Fe (8.51 %), and F- (2.12%), all groundwater samples from the research region were determined to be within permitted limits and appropriate for drinking. According to the Water Quality Index, about 80.86% of groundwater samples are excellent, and 19.14% are good drinking water. Sodium absorption ratio (SAR), sodium (Na) percentage, residual sodium carbonate RSC, permeability index (PI), and magnesium hazard were among the irrigation water quality indicators calculated (MH). The great majority of groundwater samples are suitable for agricultural use.
Integrated assessment of groundwater quality for drinking and irrigation using WQI, GIS, hydrochemical and statistical analysis Belete, Fonose; Govindhasamy, Kumar; Yusoof, Peer Mohamed Appa Mooppan Abdul Rahman; Ramachandran, Poomalai; Jothimani, Muralitharan
Journal of Degraded and Mining Lands Management Vol. 13 No. 4 (2026)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2026.134.11201

Abstract

Groundwater is the principal source of domestic and irrigation water in Limuna Bilbilo Woreda, East Arsi Zone, Ethiopia. The study was conducted to evaluate groundwater quality using the Water Quality Index (WQI), GIS, hydrochemical facies analysis, irrigation-water indices, lithological interpretation, and statistical analysis. Eighteen groundwater samples from ten springs and eight boreholes were analyzed for 21 physicochemical parameters. The suitability of drinking water was determined using the weighted arithmetic WQI method based on WHO and Ethiopian standards, and irrigation suitability was determined using EC, TDS, SAR, Na%, RSC, PI, MAR, and Kelley's index. The WQI results indicated that 61.1% of the samples were excellent, 27.8% good, 5.6% poor, and 5.6% very poor for drinking. The majority of groundwater sources were suitable for irrigation, though some boreholes had local sodium and magnesium hazards. The Ca-Mg-HCO3 water type was the most dominant hydrochemical facies, associated with recharge, mineral weathering, and water-rock interaction. The results provide a baseline for groundwater monitoring, aquifer protection, and water-supply planning in rural volcanic terrains.