Applied Geology Sector

Jeddah, Saudi Arabia

Applied Geology Sector

Jeddah, Saudi Arabia
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Youssef A.M.,Sohag University | Pradhan B.,University Putra Malaysia | Al-Kathery M.,Applied Geology Sector | Bathrellos G.D.,National and Kapodistrian University of Athens | Skilodimou H.D.,National and Kapodistrian University of Athens
Journal of African Earth Sciences | Year: 2015

Rockfall is one of the major concerns along different urban areas and highways all over the world. Al-Noor Mountain is one of the areas that threaten rockfalls to the Al-Noor escarpment track road and the surrounding urban areas. Thousands of visitors and tourisms use the escarpment track road to visit Hira cave which is located at the top of Al-Noor Mountain. In addition, the surrounding urban areas of Al-Noor Mountain are continuously spreading over the recent years. The escarpment track road and the surrounding urban areas are highly vulnerable and suffers from recurrent rockfall mostly in the rainy season. The steep and highly jointed slope along the different faces of the mountain makes these zones prone to failure due to different actions such as weathering, erosion and anthropogenic effect. Therefore, an attempt has been made in this study to determine the Al-Noor cliff stability, by identifying the unstable areas, and to apply the rockfall simulations. A combination of remote sensing, field study and 2D computer simulation rockfall program were performed to assess surface characteristics of the cliff faces. Bounce height, total and translational kinetic energy, translational velocity, and number of blocks have been estimated. Different unstable zones along the Al-Noor Mountain and escarpment track road were determined using filed investigation and remote sensing based image analysis. In addition the rockfall simulation analysis indicated that rockfall in zone 1 and zone 2 of the Al-Noor Mountain may reach the urban areas, whereas rockfall in zone 3 will not reach the urban areas, and rockfalls along the Al-Noor escarpment track road will have highly impact on the tourists. Proper preventive measures are also suggested to arrest the movement of falling rocks before reaching the urban areas and the Al-Noor escarpment track road. If proper care is taken, then further uncertain rockfall hazards can be prevented. © 2014 Elsevier Ltd.


Youssef A.M.,Sohag University | Pourghasemi H.R.,Shiraz University | Pourtaghi Z.S.,University of Yazd | Al-Katheeri M.M.,Applied Geology Sector
Landslides | Year: 2015

The purpose of the current study is to produce landslide susceptibility maps using different data mining models. Four modeling techniques, namely random forest (RF), boosted regression tree (BRT), classification and regression tree (CART), and general linear (GLM) are used, and their results are compared for landslides susceptibility mapping at the Wadi Tayyah Basin, Asir Region, Saudi Arabia. Landslide locations were identified and mapped from the interpretation of different data types, including high-resolution satellite images, topographic maps, historical records, and extensive field surveys. In total, 125 landslide locations were mapped using ArcGIS 10.2, and the locations were divided into two groups; training (70 %) and validating (25 %), respectively. Eleven layers of landslide-conditioning factors were prepared, including slope aspect, altitude, distance from faults, lithology, plan curvature, profile curvature, rainfall, distance from streams, distance from roads, slope angle, and land use. The relationships between the landslide-conditioning factors and the landslide inventory map were calculated using the mentioned 32 models (RF, BRT, CART, and generalized additive (GAM)). The models’ results were compared with landslide locations, which were not used during the models’ training. The receiver operating characteristics (ROC), including the area under the curve (AUC), was used to assess the accuracy of the models. The success (training data) and prediction (validation data) rate curves were calculated. The results showed that the AUC for success rates are 0.783 (78.3 %), 0.958 (95.8 %), 0.816 (81.6 %), and 0.821 (82.1 %) for RF, BRT, CART, and GLM models, respectively. The prediction rates are 0.812 (81.2 %), 0.856 (85.6 %), 0.862 (86.2 %), and 0.769 (76.9 %) for RF, BRT, CART, and GLM models, respectively. Subsequently, landslide susceptibility maps were divided into four classes, including low, moderate, high, and very high susceptibility. The results revealed that the RF, BRT, CART, and GLM models produced reasonable accuracy in landslide susceptibility mapping. The outcome maps would be useful for general planned development activities in the future, such as choosing new urban areas and infrastructural activities, as well as for environmental protection. © 2015 Springer-Verlag Berlin Heidelberg


Youssef A.M.,Applied Geology Sector | Pourghasemi H.R.,Shiraz University | El-Haddad B.A.,Sohag University | Dhahry B.K.,Applied Geology Sector
Bulletin of Engineering Geology and the Environment | Year: 2015

The purpose of the current study is to produce landslide susceptibility maps using different probabilistic and bivariate statistical approaches; namely, frequency ratio (FR), weights-of-evidence (WofE), index-of-entropy (IofE), and Dempster–Shafer (DS) models, at Wadi Itwad, Asir region, in the southwestern part of Saudi Arabia. Landslide locations were identified and mapped from interpretation of high-resolution satellite images, historical records, and extensive field surveys. In total, 326 landslide locations were mapped using ArcGIS and divided into two groups; 75 % and 25 % of landslide locations were used for training and validation of models, respectively. Twelve layers of landslide-related factors were prepared, including altitude, slope degree, slope length, topography wetness index, curvature, slope aspect, distance from lineaments, distance from roads, distance from streams, lithology, rainfall, and normalized difference vegetation index. The relationships between the landslide-related factors and the landslide inventory map were calculated using different statistical models (FR, WofE, IofE, and DS). The model results were verified with landslide locations, which were not used during the model training. In addition, receiver operating characteristic curves were applied, and area under the curve (AUC) was calculated for the different susceptibility maps using the success (training data) and prediction (validation data) rate curves. The results showed that the AUC for success rates are 0.813, 0.815, 0.800, and 0.777, while the prediction rates are 0.95, 0.952, 0.946, and 0.934 for FR, WofE, IofE, and DS models, respectively. Subsequently, landslide susceptibility maps were divided into five susceptibility classes, including very low, low, moderate, high, and very high. Additionally, the percentage of training and validating landslides locations in high and very high landslide susceptibility classes in each map were calculated. The results revealed that the FR, WofE, IofE, and DS models produced reasonable accuracy. The outcomes will be useful for future general planned development activities and environmental protection. © 2015 Springer-Verlag Berlin Heidelberg


Youssef A.M.,Applied Geology Sector | Youssef A.M.,Sohag University | Sabtan A.A.,King Abdulaziz University | Maerz N.H.,Missouri University of Science and Technology | Zabramawi Y.A.,Applied Geology Sector
Natural Hazards | Year: 2014

The formation of earth fissures due to groundwater depletion has been reported in many places in North America, Europe, and Asia. Najran Basin is in the southern part of the Kingdom of Saudi Arabia, and agricultural activities and other groundwater uses have caused significant groundwater depletion there. The basin recently experienced a sudden appearance of numerous earth fissures. An interdisciplinary study consisting of an evaluation of land-use changes, and hydrological, hydrogeological, and geophysical investigations was conducted to determine the reason for the formation of the earth fissures. The hydrological analysis strongly revealed that the groundwater level is decreasing with time. Groundwater depletion would lead to the accumulation of subsurface stress, causing soil hydro-consolidation which creates the ideal condition for the formation of earth fissures. Electrical resistivity, data indicated that there are anomalies in the profiles, which are most probably due to the presence of subsurface topography, another key factor for the formation of the earth fissures. © 2013 Springer Science+Business Media Dordrecht.


Youssef A.M.,Sohag University | Al-kathery M.,Applied Geology Sector | Pradhan B.,University Putra Malaysia | El-sahly T.,Applied Geology Sector
Geomatics, Natural Hazards and Risk | Year: 2014

Jizan mountainous areas in Kingdom of Saudi Arabia are suffering from a variety of slope failures. Most of these failures happen due to heavy rainfalls from time to time. These landslides include rock topples, rockslides, debris flow, and some combination of these which affected many roads, highways, and buildings. The Al-Raith Road is one of these roads connecting Red Sea coast cities with Asir and Al-Hasher areas. The length of this road reaches about 45 km and it has been exposed to landslides during each heavy rain storm. One of these events happened in 24 August 2013, which caused huge debris flows that cut and damaged the road. The current research aims to evaluate the debris flow assessment along this highway using remote sensing data and field studies. According to the detailed analysis of geological and geomorphological maps, as well as field investigation, it is evident that the debris flow materials are mainly related to the different types of landslides. These landslides included rock topples which are frequently observed along the side walls of the channels (flexture which occur in foliated rocks and block which occurs in massive rocks), rock sliding (planner failures) where many rock joints and shear zones dip towards the channel, and rockfalls. Debris range in their size from up to 2 m in diameter to fine materials less than 2 mm. These materials can be easily moved with water causing a risk to vehicles, roads, and housing in the area. Field study indicated that these debris channels especially at the lower part have been reactivated several times in the past. Finally, suitable solutions have been suggested to these critical sites to minimize and/or avoid the debris flow hazards in the future. © 2014 © 2014 Taylor & Francis.


Youssef A.M.,Sohag University | El-Kaliouby H.M.,Sultan Qaboos University | El-Kaliouby H.M.,National Research Center of Egypt | Zabramawi Y.A.,Applied Geology Sector
Journal of Applied Geophysics | Year: 2012

Different types of sinkholes have been recognized in the Kingdom of Saudi Arabia. The sinkholes are of various sizes and shapes and occur at different depths. Their presence may create a direct risk to the infrastructural facilities such as urban areas, roads, future development areas, and farmlands. Recently, more than eight sinkholes have collapsed to the west of the Al Khafji and An Nu'ayriyah areas (northern eastern side of the Kingdom). Geologically, the area is composed of Dammam, Hadrukh, and Dibdibba formations. The essence of this paper is to integrate remote sensing analysis throughout surface features with the geophysical studies to detect the subsurface sinkholes. Our findings show that there are possible correlations between the clear circular features (ring structures) detectable in remote sensing images and geophysical observations (using two electrical resistivity surveys), indicating unconsolidated material in the subsurface (karst phenomena). © 2012 Elsevier B.V.


Youssef A.M.,Sohag University | Pradhan B.,University Putra Malaysia | Al-Harthi S.G.,Applied Geology Sector
Arabian Journal of Geosciences | Year: 2015

Samma escarpment road is located in Asir Region, Saudi Arabia. It is located NW of Abha city. This escarpment road represents a major corridor in the area which connects different cities and touristic resorts in the region. It is descended from Sudah plateau at about 2700 m above sea level (asl) toward Wadi al Aws at about 1500 m asl. The total length of the road section is about 8 km which is passing through a highly mountainous area characterized by a complex geological and structural elements. This road has been exposed to frequent slope failures from time to time due to various factors such as intense rain storms, different geological and structural elements (weak rocks, shear zones, and faults), road characteristics (different horizontal/vertical curvatures and narrow road section), and human activities (uncontrolled rock cuts). Many sliding events have been documented along this escarpment road, particularly during and following rainstorms. The purpose of this paper is to evaluate the geology and structures by applying the rock mass rating (RMR) and slope stability (structurally controlled failures) along the Samma escarpment road. The stability analysis was performed using two Dips and RockPack III programs with the help of RocLab software. The Summa escarpment rock cuts were classified into 51 stations which were investigated in detail. Results indicated that most rock stations are poor quality, and 31, 32, and 41 stations are stable, 4, 6, and 7 stations are marginally stable, and 16, 13, and 3 stations are potentially unstable due to planar, wedge, and toppling failures, respectively. Finally, different recommendations and remediation methods were suggested as mitigation measures. © 2014, Saudi Society for Geosciences.


Youssef A.M.,Sohag University | Sefry S.A.,Applied Geology Sector | Pradhan B.,University Putra Malaysia | Alfadail E.A.,Applied Geology Sector
Geomatics, Natural Hazards and Risk | Year: 2015

The Jeddah city is located in a coastal plain area, in the middle of the western side of the Kingdom of Saudi Arabia, bounded by the Red Sea to the west and mountains to the east. Jeddah city receives rainfall runoff from the foothills through different drainage pathways (wadis). During intense rainfall events, runoff flows westward from the hills and mountains towards the Red Sea, causing flash floods in the urban areas along the pathways of these wadis. Two major flash flood events occurred in Jeddah city during 20 November 2009 - January 2011. These events were characterized by rainfall precipitation values of 70 and 111 mm, respectively. Each flash flood event has duration of three hours. The impact of these two flood events have been disastrous causing extensive flooding that killed 113 people in 2009 and damaged infrastructure and property (more than 10,000 homes and 17,000 vehicles). This study deals with the analysis of the different factors that caused these flash flood events. The results indicate that the causes of these floods are related to a number of factors which play as a major contribution to the worsening of the flood disaster. These factors were classified into the following: geomorphological features, anthropogenic activities (urban changes), network and catchment factors, and rainfall and climatic changes factors. The climatic changes have a major impact on the rainfall intensity and will appear more in the future. Other factors related to the wadis tributaries are narrow passes, and high slope of the wadi has additional impacts in the flash floods in the area. The anthropogenic activities include the proliferation of slums and construction in the valleys coupled with the lack of suitable water streams to accommodate the amount of water flowing and the presence of dirt led to the direction of flow. © 2015 Taylor & Francis


Youssef A.M.,Applied Geology Sector | Youssef A.M.,Sohag University | Pradhan B.,University Putra Malaysia | Sefry S.A.,Applied Geology Sector
Environmental Earth Sciences | Year: 2016

The city of Jeddah (Saudi Arabia) has experienced two catastrophic flash flood events in 2009 and 2011. These flood events had catastrophic effect on human lives and livelihoods around the wadi Muraikh, wadi Qus, wadi Methweb, and wadi Ghulail in which 113 people were dead and with 10,000 houses and 17,000 vehicles were damaged. Thus, a comprehensive flood management is required. The flood management requires information on different aspects such as the hydrological, geotechnical, environmental, social, and economic aspects of flooding. Flood susceptibility mapping for any area helps the decision makers to understand the flood trends and can aid in appropriate planning and flood prevention. In this study, two models were used for the generation of flood susceptibility maps for the Jeddah region. The first model includes bivariate probability analysis (frequency ratio), and the second model uses the multivariate analysis. For the multivariate model, the acquired weights of the FR model were entered into the logistic regression model to evaluate the correlation between flood occurrence and each related factor. This integration will overcome some of the weakness of the logistic regression, and the performance the LR will be enhanced. A flood inventory map was prepared with a total of 127 flood locations. These flood locations were extracted from different sources including field investigation and high-resolution satellite image (IKONOS 1 m). These flood locations were randomly split into two groups, one dataset representing 70 % was used for training the models, and the remaining 30 % was used for models validation. Various independent flood-related factors such as slope, elevation, curvature, geology, landuse, soil drain, and distance from streams were included. The impact of each independent flood-related factors on flooding was evaluated by analyzing each independent factor with the historical flood inventory data. The training and validation datasets were used to evaluate the flood susceptibility maps using the success and the prediction rate methods. The results of the accuracy assessment showed a success rate of 90.4 and 91.6 % and a prediction rate of 89.6 and 91.3 % for FR and ensemble FR and LR models, respectively. In addition, a comparison has been made between real flood events in 2009 and the resultant susceptibility maps. Hence, it is concluded that the FR and ensemble Fr and LR models can provide an acceptable accuracy in the prediction of flood susceptibility in the Saudi Arabia. Our findings indicated that these flood susceptibility maps can assist planners, decision makers, and other agencies to deal with the flood management and planning in the area. © 2015, Springer-Verlag Berlin Heidelberg.


Youssef A.M.,Sohag University | Al-Kathery M.,Applied Geology Sector | Pradhan B.,University Putra Malaysia
Geosciences Journal | Year: 2015

Mountain areas in the southern western corner of the Kingdom of Saudi Arabia frequently suffer from various types of landslides due to rain storms and anthropogenic activities. To resolve the problem related to landslides, landslide susceptibility map is important as a quick and safe mitigation measure and to help making strategic planning by identifying the most vulnerable areas. This paper summarizes findings of landslide susceptibility analysis at Al-Hasher area, Jizan, KSA, using two statistical models: frequency ratio and index of entropy models with the aid of GIS tools and remote sensing data. The landslide locations (inventory map) were identified in the study area using historical records, interpretation of high-resolution satellite images that include Geo-Eye in 2.5 m and Quickbird in 0.6m resolution, topographic maps of 1:10,000 scale, and multiple field investigations. A total of 207 landslides (80% out of 257 detected landslides) were randomly selected for model training, and the remaining 50 landslides (19%) were used for the model validation. Ten landslide conditioning factors including slope angle, slope-aspect, altitude, curvature, lithology, distance to lineaments, normalized difference vegetation index (NDVI), distance to roads, precipitation, and distance to streams, were extracted from spatial database. Using these conditioning factors and landslide locations, landslide susceptibility and weights of each factor were analyzed by using frequency ratio and index of entropy models. Our findings showed that the existing landslides of high and very high susceptibility classes cover nearly 80.4% and 79.1% of the susceptibility maps produced by frequency ratio and index of entropy models respectively. For verification, receiver operating characteristic (ROC) curves were drawn and the areas under the curve (AUC) were calculated for success and prediction rates. For success rate the results revealed that for the index of entropy model (AUC = 77.9%) is slightly lower than frequency ratio model (AUC = 78.8%). For the prediction rate, it was found that the index of entropy model (AUC = 74.9%) is slightly lower than the frequency ratio model (AUC = 76.7%). The landslide susceptibility maps produced from this study could help decision makers, planners, engineers, and urban areas developers to make suitable decisions. © 2015, The Association of Korean Geoscience Societies and Springer-Verlag Berlin Heidelberg.

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