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Seepage flow through pervious media or formations is one of the causative factors for dam failure. In order to reduce and control this problem, seepage modeling and analysis are very important. The main aim of this article is to present the comprehensive review on various modeling approaches and methods available for seepage evaluation through or beneath dam. Furthermore, an attempt is also made to assess the application and effectiveness of these techniques in dam seepage modeling and analysis. Moreover, case studies of dam seepage analysis in Ethiopia were also reviewed. For a century, various techniques have been developed that can be used to study the seepage cases of hydraulic structures including dams. Broadly, these techniques can be categorized in to continuum and discontinuum seepage modeling approaches. Continuum approach includes pore-network model, whereas discontinuum approach includes equivalent continuum, discrete fracture network, dual-porosity, and triple-porosity models. Each of these approaches may consider different causative factors and utilizes various methods for seepage analysis. The experimental, analytical, and numerical methods are commonly used in the modeling approaches based on Darcian and non-Darcian laws. The selection of appropriate modeling approaches depends on various factors and considerations including the spatial and temporal scale of flow regime, material type and properties, dam width and height, water level, availability of data, and modeler's skill. In comparison, each of these models has its own advantages and disadvantages over the other. [ABSTRACT FROM AUTHOR]

Dessie town has faced slope instability problems for many decades. The main objective of this study is to conduct a detailed slope stability analysis along selected critical slope sections so as to identify and locate the potential slope instability, determine the engineering properties of soils and rocks, and analyze the slope stability. For this study, six rock and four soil critical slope sections were selected and analyzed using kinematic analysis, limit equilibrium, and finite element models. Discontinuity surveying, in situ strength testing, sampling, and laboratory testing have been carried out. Rock quality was analyzed through rock quality designation (RQD), rock mass rating (RMR), and geological strength index (GSI). The RQD of rocks ranges from very poor to good rocks. The RMR of rock masses ranges from fair to good rocks, and GSI results showed that the rock mass ranges from blocky/disturbed to very blocky rock. For kinematic analysis, four planar and two toppling modes of failures were used in which the stability analysis using the Rocplane software in the four rock slope sections for planar failure indicated a stable condition under static dry condition with a factor of safety (FoS) ranging between 1.3 and 2.01 but unstable under dynamic saturated condition (FoS = 0.27 − 0.75). Similarly, the stability conditions in the two rock slope sections with a toppling mode of failure were stable with the FoS of 1.325 and 3.245 under a static dry condition but were unstable with the FoS of 0.172 and 0.797 under dynamic saturated conditions. The selected four soil slope sections were loam, clayey, silt-loam, and silt-clayey soils that showed a high plasticity index. The computed FoS from the limit equilibrium model (LEM) using the Slide software and the stress reduction factor (SRF) from the finite element model (FEM) using the Phase2 software showed that all soil slope sections are unstable under static dry, dynamic dry, static saturated, and dynamic saturated conditions as soils are taken from the failed slope sections. The LEM and FEM results for the four soil slope sections indicated a decreasing trend in terms of FoS and SRF, respectively, as we go from static dry to dynamic dry, static saturated, and dynamic saturated conditions. However, rock slope sections are stable under static dry but unstable under dynamic saturated conditions. [ABSTRACT FROM AUTHOR]

Ground motion from an earthquake is the most devastating geo-hazard in seismically active areas as it affects human life and infrastructure as well as their day-to-day activities. Hawassa town has faced distress of building due to earthquake of small to intermediate magnitudes. The main aim of this study is to predict ground motion parameters using DEEPSOILV.7 program. For this purpose, linear, equivalent linear, and nonlinear approaches at five sites were applied. In this study, the natural period (T30) and amplification (A30) of the site were used to determine the amplification. Two input ground motions from the DEEPSOILV.7 software were used to generate site's PGA (g), spectral acceleration (PSA) (g), maximum strain (%), and amplification factor (AF) at the surface. In addition, T30 and A30 maps at a depth of 30 m were prepared by krigging interpolation techniques. The PGA (g), AF, and maximum strain (%) and PSA (g) showed the amplification at a shallow depth for the input motion at four sites but deamplification at one sites. The highest maximum strain (%) values were observed at a shallow depth indicating the probability of liquefaction induced ground deformation. The T30 and A30 map showed a long period and high amplification in the northern part but a short period and low amplification in the southern part. The results of this study will be used at local, zonal, regional, and federal levels for the design of critical structures as it provides first-hand information on the seismic hazard of the area. [ABSTRACT FROM AUTHOR]

Arjo Didesa dam is located in western Ethiopia which is designed for irrigation purposes to improve the food security problem in the country. This site is characterized by a complex geological and structural setup that makes it susceptible to engineering geological problems of leakage and slope instability. This study is, therefore, aimed at evaluating the leakage and abutment slope stability of the dam site. The leakage evaluation was done based on results obtained from the Lugeon tests, while slope stability analysis was performed using the kinematic method, limit equilibrium method (LEM), and finite element method (FEM). From the Lugeon tests conducted along the dam axis, more than 57% showed a potential for excessive leakage which needs grouting to control leakage. From these percentages with more than 3 Lugeon units (Lu), about 19.04% were classified into high and very high permeability classes. This indicates that rock masses along the dam axis are mostly cut by interconnected open joints. Slope stability analysis through kinematic analysis showed that some slope sections of both abutments are unstable for a planar mode of failure. Further stability analysis using LEM for a planar mode of failure revealed the presence of potentially unstable slopes at saturated conditions. Moreover, both LEM and FEM showed that some slope sections of both abutments are unstable for a circular mode of failure at saturated conditions with the factor of safety (FOS) and stress reduction factor (SRF) as low as 0.1 and 0.132, respectively. The results from slope stability analysis indicated that the water pressure through seepage is the major causative factor of slope instability. Hence, curtain grouting to the depths of 40 m at the left abutment, 53 m at the central foundation, and 43 m at the right abutment was recommended to control the leakage problem. Moreover, removal of overhanging rocks and slope angle reduction and applying rock bolts and inserting drain holes were recommended for slope stabilization in the dam site. [ABSTRACT FROM AUTHOR]

Landslide risk assessment is an extension of landslide hazard or susceptibility mapping. It is the most critical component of a landslide hazard reduction plan. The present study was carried out in Shafe and Baso catchments which are found in Gamo high land of Southern Ethiopia and are about 437 km south of Addis Ababa. The areal extent of the present study area is about 284 km2. This research was mainly aimed to characterize the landslide risk in the study area for rural population their property and services. In the present research, the landslide risk assessment was made with a major limitation of archived data. In order to overcome the deficiency of landslide data, the danger pixel concept and fuzzy set theory were utilized to evaluate the landslide risk in the study area. In the former approach total number of pixels of different resources that were affected by the landslide hazard in the area was determined. Similarly, the fuzzy set theory, a semi-quantitative method, was used to characterize the risk level of each resource in the study area. This fuzzy linguistic approach has characterized landslide risk in to a matrix form which was further used to determine the landslide risk in the study area. The resource categories that were considered in this research were; settlement, agricultural land, moderate forest, sparse forest, rangeland, bare land, and water body. The risk assessment maps prepared by both methods have delineated different risk zones with more or less similar area coverage. In the landslide risk map, the risk was classified into five classes; very high risk (6.86%), high risk (21.15%), moderate (43.26%), low (10.97%), and very low risk (17.76%). Thus, based on the results, suitable biological and mechanical remedial measures are required to mitigate the landslide hazard in the study area. These measures are particularly required to control the landslide triggering factors such as; gulley erosion, stream erosion, human activities, and groundwater conditions. [ABSTRACT FROM AUTHOR]

This study aims to identify the possible causes of ground cracks south of Butajira town (ground crack 2) and at Ureb Kebele (ground crack 1) using integrated geological, geotechnical, and geophysical investigations. From geological investigation, ignimbrite and tuff and scoriaceous basalt and NNE-SSW trending scoria cones were identified. For geotechnical investigation, 17 disturbed samples were collected. Grain size analysis showed that most of these soils are fine grained in which the plastic limit and liquid limit fall in the ranges of 28.95–58.54 and 37.74–78.95 respectively. Using USCS, most of the soils were classified as inorganic silty soils where 42.86% of them are highly dispersive. Direct shear test results indicated that most cohesion values are lower while most friction angle values are higher. The consolidation test indicated that 40% of the samples fall in severe trouble while 40% of them fall in trouble classes. The geophysical investigation results were compared with geological logs from boreholes, hand dug wells, old ground crack, and river cut exposure at ground crack 2. Ground crack 2 was located at layer three that consists of volcanic ash/tuff with an average thickness 30 m. The integrated investigation results suggested that the occurrence of ground crack in the study area is primarily associated with surface hydrology (stream increment and impoundment), swampy nature of the area, depressed area, and presence of subsurface volcanic ash/tuff and pyroclastic soils with high collapsibility potential. However, the role of earthquake could not be justified as there was no any seismic record during ground crack development. [ABSTRACT FROM AUTHOR]

Landslide hazard zonation plays an important role in safe and viable infrastructure development, urbanization, land use, and environmental planning. The Shafe and Baso catchments are found in the Gamo highland which has been highly degraded by erosion and landslides thereby affecting the lives of the local people. In recent decades, recurrent landslide incidences were frequently occurring in this Highland region of Ethiopia in almost every rainy season. This demands landslide hazard zonation in the study area in order to alleviate the problems associated with these landslides. The main objectives of this study are to identify the spatiotemporal landslide distribution of the area; evaluate the landslide influencing factors and prepare the landslide hazard map. In the present study, lithology, groundwater conditions, distance to faults, morphometric factors (slope, aspect and curvature), and land use/land cover were considered as landslide predisposing/influencing factors while precipitation was a triggering factor. All these factor maps and landslide inventory maps were integrated using ArcGIS 10.4 environment. For data analysis, the principle of logistic regression was applied in a statistical package for social sciences. The result from this statistical analysis showed that the landslide influencing factors like distance to fault, distance to stream, groundwater zones, lithological units and aspect have revealed the highest contribution to landslide occurrence as they showed greater than a unit odds ratio. The resulting landslide hazard map was divided into five classes: very low (13.48%), low (28.67%), moderate (31.62%), high (18%), and very high (8.2%) hazard zones which was then validated using the goodness of fit techniques and receiver operating characteristic curve with an accuracy of 85.4. The high and very high landslide hazard zones should be avoided from further infrastructure and settlement planning unless proper and cost-effective landslide mitigation measures are implemented. [ABSTRACT FROM AUTHOR]

Ethiopia is currently developing irrigation schemes like micro dams to improve its food security. Chalchal Dam project is one of such dams to be constructed in the Bale Zone of Southeastern Ethiopia. However, this dam is subjected to engineering geological problems due to the presence of carbonate and shale rocks in this area. To address this problem, engineering geological mapping, discontinuity surveying, core drilling, geophysical surveying, in situ permeability, and laboratory testing were carried out. From these integrated investigations, the dam site is underlain by colluvial and alluvial soil deposits, sandstone, limestone with decomposed shale, shale, marly limestone, and massive limestone rocks with different degrees of weathering and fracturing. The Lugeon test conducted along the dam axis revealed the presence of potential seepage zones at the left abutment and river center in which the former is underlain by highly permeable rocks with Lugeon values as high as 39.58 and the latter with permeable rocks with a Lugeon value of 9. The geo-mechanical properties of rocks such as friction angle, cohesion, and modulus of deformation at the dam site, as determined using Hoek–Brown failure criteria, were in ranges of 21.52 to 32.06°, 0.123 to 3.006 MPa, and 0.747 to 9.308 GPa, respectively. The bearing capacity of the dam foundation was determined using empirical methods and the result pointed out that the allowable bearing capacity of the dam foundation ranges from 0.116 to 5.321 MPa. After the removal of colluvial and alluvial deposits along the dam axis, ground improvements were recommended along the dam axis mainly in terms of curtain grout and slurry trench or concrete cutoff. [ABSTRACT FROM AUTHOR]

Earthquake is a sudden release of energy due to faults. Natural calamities like earthquakes can neither be predicted nor prevented. However, the severity of the damages can be minimized by development of proper infrastructure which includes microzonation studies, appropriate construction procedures and earthquake resistant designs. The earthquake damaging effect depends on the source, path and site conditions. The earthquake ground motion is affected by topography (slope, hill, valley, canyon, ridge and basin effects), groundwater and surface hydrology. The seismic hazard damages are ground shaking, structural damage, retaining structure failures and lifeline hazards. The medium to large earthquake magnitude (< 6) reported in Ethiopia are controlled by the main Ethiopian rift System. The spatial and temporal variation of earthquake ground motion should be addressed using the following systematic methodology. The general approaches used to analyze damage of earthquake ground motions are probabilistic seismic hazard assessment (PSHA), deterministic seismic hazard assessment (DSHA) and dynamic site response analysis. PSHA considers all the scenarios of magnitude, distance and site conditions to estimate the intensity of ground motion distribution. Conversely, DSHA taken into account the worst case scenarios or maximum credible earthquake to estimate the intensity of seismic ground motion distribution. Furthermore, to design critical infrastructures, DSHA is more valuable than PSHA. The DSHA and PSHA ground motion distributions are estimated as a function of earthquake magnitude and distance using ground motion prediction equations (GMPEs) at top of the bedrock. Site response analysis performed to estimate the ground motion distributions at ground surface using dynamic properties of the soils such as shear wave velocity, density, modulus reduction, and material damping curves. Seismic hazard evaluation of Ethiopia shown that (i) amplification is occurred in the main Ethiopian Rift due to thick soil, (ii) the probability of earthquake recurrence due to active fault sources. The situation of active fault is oriented in the N-S direction. Ethiopia is involved in huge infrastructural development (including roads, industrial parks and railways), increasing population and agricultural activity in the main Ethiopian Rift system. In this activity, socio-economic development, earthquake and earthquake-generated ground failures need to be given attention in order to reduce losses from seismic hazards and create safe geo-environment. [ABSTRACT FROM AUTHOR]

Landslide is the most frequently occurring geo-hazard in mountainous terrains of the world. It affects human life, infrastructures, landscapes, and human properties as well as their day-to-day activities. In the current study area which is found in the Gamo Zone of south Ethiopia, recurrent landslide hazards have occurred. To minimize this landslide hazard on human life and their properties, landslide susceptibility mapping is an important step for environmental planning. For this purpose, 1554 landslides and 9 landslide causative factors (both conditioning and triggering factors) were used. Each thematic layer has different classes and some of these classes influence landslide occurrence more than others. The most influencing factor classes which were identified by the frequency ratio model include slope classes between12 and 45°; convex and concave classes of the curvature; aspect classes of north, northeast, south, and southwest directions; and elevation classes in between 2118 and 2492 m. The distances factors, proximity to streams, and lineaments 0–100 m and 0–200 m respectively have a very high on landslide occurrences. Land use/land cover factor has different classes and they have different levels of direct and indirect influences on landslide occurrences. The landslide susceptibility map was classified as very low, low, moderate, high, and very high classes each accounting for 17.8%, 29.19%, 28.55%, 17.52%, and 6.91% of the area respectively. To evaluate the reliability of this model, the landslide susceptibility map was verified using a receiver operating characteristic (ROC) curve with a value of 82% and through field observation. Therefore, this can be used by local, zonal, regional, and federal governments for land use planning, disaster prevention, and mitigation as it offers first-hand information. [ABSTRACT FROM AUTHOR]

Kabi-Gebro locality of Gundomeskel area is located within the Abay Basin at Dera District of North Shewa Zone in the Central highland of Ethiopia and it is about 320Km from Addis Ababa. This is characterized by undulating topography, intense rainfall, active erosion and highly cultivated area. Geologically, it comprises weathered sedimentary and volcanic rocks. Active landslides damaged the gravel road, houses and agricultural land. The main objective of this research is to prepare the landslide susceptibility map using GIS-based Weights of Evidence model. Based on detailed field assessment and Google Earth image interpretation, 514 landslides were identified and classified randomly into training landslides (80%) and validation landslides (20%). The most common types of landslides in the study area include earth slide (rotational and translational slide), debris slide, debris flow, rock fall, topple, rock slide, creep and complex. Nine landslide causative factors such as lithology, slope, aspect, curvature, land use/land cover, distance to stream, distance to lineament, distance to spring and rainfall were used to prepare a landslide susceptibility map of the study area by adding the weights of contrast values of these causative factors using a rater calculator of the spatial analyst tool in ArcGIS. The final landslide susceptibility map was reclassified as very low, low, moderate, high and very high susceptibility classes. This susceptibility map was validated using landslide density index and area under the curve (AUC). The result from this model validation showed a success rate and a validation rate accuracy of 82.4% and 83.4% respectively. Finally, implementing afforestation strategies on bare land, constructing surface drainage channels & ditches, providing engineering reinforcements such as gabion walls, retaining walls, anchors and bolts whenever necessary and prohibiting hazardous zones can be recommended in order to lessen the impact of landslides in this area. [ABSTRACT FROM AUTHOR]

The quality of crushed stone aggregates influences the durability and performance of pavement and concrete as they are the dominant component in the mix. Hence, the selection of a suitable quarry site with the quality source material is essential. Since the quarry site suitability assessment involves various factors, it is more economical to follow a stage-wise suitability assessment approach (i.e., preliminary evaluation and then refinement based on field data). The preliminary evaluation was done using readily available data in the office such as lithology, land use–land cover, proximity to built-up areas, distance to watercourses, distance to existing roads, relative relief, and slope angle. The purpose of the present work is to refine the preliminary limestone crushed stone aggregate suitability map (produced in the preceding work) considering the rock mass quality, slope stability, reserve, depth to groundwater table, and overburden thickness. The required data, such as unconfined compressive strength, rock quality designation, and geometrical properties of discontinuity, were collected during a detailed field survey from preliminary highly and moderately suitable sites. Rock mass classification systems, such as rock mass rating (RMR) and slope mass rating (SMR), were used to assess rock mass quality and slope stability, respectively. The weighting scheme approach is then applied and the ratings assigned to each factor (RMR, SMR, reserve, depth to water table, and overburden thickness) summed up to produce a total estimated suitability (TES) map. The map showed that 40.4% of the preliminary suitable sites are unsuitable, 20.3% moderately suitable, 14.7% highly suitable, and 24.7% most suitable. [ABSTRACT FROM AUTHOR]

Simada area is found in the South Gondar Zone of Amhara National Regional State and it is 780Km far from Addis Ababa. Physiographically, it is part of the northwestern highlands of Ethiopia. This area is part of the Guna Mountain which is characterized by weathered volcanic rocks, rugged morphology with deeply incised gorges, heavy rainfall and active surface processes. Many landslides have occurred on August 2018 after a period of heavy rainfall and they caused many damages to the local people. In this study, Frequency Ratio (FR) and Weights of Evidence (WoE) models were applied to evaluate the landslide causative factors and generate landslide susceptibility maps (LSMs). The landslide inventory map that consists of 576 active and passive landslide scarps was prepared from intensive fieldwork and Google Earth image interpretation. These landslide locations were randomly divided into 80% training and 20% validation datasets. Seven landslide causal factors including aspect, slope, curvature, lithology, land use, rainfall and distance to stream were combined with a training dataset using GIS tools to generate the LSMs of the study area. Then the area was divided into five landslide susceptibility zones of very low, low, moderate, high and very high. Later, the resulting maps have been validated by using area under the curve and landslide density index methods. The result showed that the predictive rate of FR and WoE models were 88.2% and 84.8%, respectively. This indicated that the LSM produced by FR model showed a better performance than that of WoE model. Finally, the LSMs produced by FR and WoE models can be used by decision-makers for land use planning and landslide mitigation purpose. [ABSTRACT FROM AUTHOR]

Landslides are the most destructive geological hazard in the hilly regions. For systematic landslide mitigation and management, landslide evaluation and hazard zonation is required. Over the past few decades several techniques have been developed that can be used for landslide evaluation and zonation. These techniques can broadly be classified into qualitative and quantitative approaches. Qualitative approaches include geomorphological analysis and heuristic techniques whereas quantitative approaches include statistical, artificial intelligence and deterministic techniques. In quantitative techniques prediction for landslide susceptibility is based on the actual realistic data and interpretations. Further, the quantitative techniques also overcome the subjectivity of qualitative approaches. Each of these techniques may consider different causative factors and utilizes various means for factor evaluation and analysis. When compared, each of these techniques has its own advantage and disadvantage over other techniques. The selection of appropriate technique for landslide hazard evaluation and zonation is very crucial. The factors that need to be considered to adopt an appropriate approach are; investigation purpose, the extent of the area to be covered, the type of mapping units, the scale of map to be produced, type of data to be used, type of landslides, availability of resources, capability and skill set of an evaluator and the accessibility to the study area. The main aim of this article is to present a comprehensive review on various techniques and approaches available for landslide susceptibility and hazard zonation mapping. Further, attempt is also made to assess the effectiveness of these techniques in landslide hazard zonation studies. [ABSTRACT FROM AUTHOR]

Ethiopia has a mountainous landscape which can be divided into the Northwestern and Southeastern plateaus by the Main Ethiopian Rift and Afar Depression. Debre Sina area is located in Central Ethiopia along the escarpment where landslide problem is frequent due to steep slope, complex geology, rift tectonics, heavy rainfall and seismicity. In order to tackle this problem, preparing a landslide susceptibility map is very important. For this, GIS-based frequency ratio (FR) and logistic regression (LR) models have been applied using landslide inventory and the nine landslide factors (i.e. lithology, land use, distance from river & fault, slope, aspect, elevation, curvature and annual rainfall). Database construction, weighting each factor classes or factors, preparing susceptibility map and validation were the major steps to be undertaken. Both models require a rasterized landslide inventory and landslide factor maps. The former was classified into training and validation landslides. Using FR model, weights for each factor classes were calculated and assigned so that all the weighted factor maps can be added to produce a landslide susceptibility map. In the case of LR model, the entire study area is firstly divided into landslide and non-landslide areas using the training landslides. Then, these areas are changed into landslide and non-landslide points so as to extract the FR maps of the nine landslide factors. Then a linear relationship is established between training landslides and landslide factors in SPSS. Based on this relationship, the final landslide susceptibility map is prepared using LR equation. The success-rate and prediction-rate of FR model were 74.8% and 73.5%, while in case of LR model these were 75.7% and 74.5% respectively. A close similarity in the prediction and validation rates showed that the model is acceptable. Accuracy of LR model is slightly better in predicting the landslide susceptibility of the area compared to FR model. [ABSTRACT FROM AUTHOR]

Landslide susceptibility mapping is an important tool for disaster management and development activities such as planning of transportation infrastructure, settlement and agriculture. Selelkula area of the Jema River Gorge in Central Ethiopian Highland was chosen as a study area. Fuzzy logic (FL) and rock engineering system (RES) in a GIS environment were employed to prepare landslide susceptibility maps for this area. Data sets including slope, aspect, profile curvature, plan curvature, lithology, land use, distance from river and distance from lineament were generated using the field data, remote sensing and GIS. In FL, the fuzzy membership values were calculated by normalizing the frequency ratio values of each factor's class in a range between 0 and 1. Then, the fuzzy membership values were combined by fuzzy AND, fuzzy OR, fuzzy gamma, fuzzy sum and fuzzy product operators. A total of twelve landslide susceptibility maps were produced using FL and the best map was chosen based on area under the curve (AUC) of the receiver operating characteristic (ROC) curve and the highest difference between minimum and maximum susceptibility index values. Based on these criteria, the landslide susceptibility map produced using fuzzy gamma ( γ = 0.8) operator was selected. RES is a semi-quantitative method which assigns each factor's classes a value between 0 and 4 based on the principles of Hudson (Rock engineering systems, theory and practice. Ellis Horwood, Chichester, ) and uses an interaction matrix through a coding system of five values in previous researches but a coding system of nine values has been used in this study to provide a wider range of values for interactions among each pair of landslide factors and each landslide factor with a landslide. Unlike other methods, RES has a freedom to evaluate and assign each interaction based on expert's knowledge and experience. But it also bears the problem of subjectivity in assigning the interaction values. On the other hand, FL is completely data driven and does not show any subjectivity in assigning values for each factor class. The prediction accuracies of FL and RES, which can be determined from ROC curves, were found to be 87.2 and 88.6 %, respectively. For validation purpose, the existing landslides were overlaid over the two landslide susceptibility maps and the percentage of landslides in each susceptibility class was calculated. The percentages of landslides that fall in the high and very high susceptibility classes are slightly higher in RES than FL method and hence the former is more accurate in predicting the future landslide occurrence than the later. [ABSTRACT FROM AUTHOR]