Topical Collection: Coastal aquifers in the Middle East and North Africa region

The Middle East and North Africa (MENA) region suffers from low precipitation and high evaporation. Coastal areas of the MENA region are usually densely populated; hence, the coastal aquifers are easily over-exploited beyond their safe yield, and seawater intrusion and aquifer salinization have been caused by the groundwater-level declines. Four studies in MENA coastal aquifers, on seawater intrusion modeling and aquifer recharge and salinization using isotopes, have been brought together in a topical collection and are discussed in this essay. A brief overview is given of managed aquifer recharge as an effective method to combat groundwater-level decline, seawater intrusion and aquifer salinization in MENA counties.     

Distribution of gold in different size fractions of stream sediments as a guide to bedrock gold mineralisation along the Shyok Suture Zone and adjacent areas of the Kohistan Island Arc,Pakistan

Arabian Journal of Geosciences - This paper describes a new exploration methodology using stream sediments in remote and glaciated regions of northern Pakistan. Gold concentrations in 268 samples...     

Paleozoic convergence processes in the southwestern Central Asian Orogenic Belt:Insights from U–Pb dating of detrital zircons from West Junggar,northwestern China

The West Junggar orogen,located in the southwestern Central Asian Orogenic Belt(CAOB),preserves an abundant record of tectonic processes associated with the evolution of the Junggar Ocean.In this study,we use detrital zircon U–Pb age data from Ordovician to Carboniferous sandstones in the southern and central West Junggar domains,complemented by literature data,to better constrain the tectonic evolution of the southwestern CAOB.The Kekeshayi,Qiargaye,and Laba formations in the southern West Junggar domain were deposited during the Darriwilian-Sandbian,Katian-Aeronian,and Homerian-Emsian,respectively.Detrital zircon provenances of these formations display a marked shift from the southern West Junggar domain to the Paleo-Kazakhstan Continent(PKC).This suggests that the southern West Junggar intra-oceanic arc might have gradually accreted to the northern margin of the PKC prior to the Emsian,which has significantly contributed to the lateral growth of the PKC.The Carboniferous strata,Xibeikulasi,Baogutu,and Tailegula formations,in the central West Junggar domain represent a coherent sequence of volcaniclastic turbidites and were deposited in a progressively shrinking remnant oceanic basin during the Visean to Moscovian.They contain unimodal detrital zircon distributions and are derived from the local and coeval magmatic rocks in the central West Junggar domain.We propose that the final closure of the Junggar Ocean likely occurred in the end of the Late Carboniferous in response to regional amalgamation events in the southwestern CAOB,which marks the final assembly of the Kazakhstan Orocline.The central and southern West Junggar domains underwent individual evolution in the Paleozoic,and were recombined by the significant intra-continental reworking along the large-scale strike-slip faults.     

Location-allocation modeling for emergency evacuation planning with GIS and remote sensing: A case study of Northeast Bangladesh

This work developed models to identify optimal spatial distribution of emergency evacuation centers(EECs) such as schools, colleges, hospitals, and fire stations to improve flood emergency planning in the Sylhet region of northeastern Bangladesh.The use of location-allocation models(LAMs) for evacuation in regard to flood victims is essential to minimize disaster risk.In the first step, flood susceptibility maps were developed using machine learning models(MLMs), including: Levenberg–Marquardt back propagation(LM-BP) neural network and decision trees(DT) and multi-criteria decision making(MCDM) method.Performance of the MLMs and MCDM techniques were assessed considering the area under the receiver operating characteristic(AUROC) curve.Mathematical approaches in a geographic information system(GIS) for four well-known LAM problems affecting emergency rescue time are proposed: maximal covering location problem(MCLP), the maximize attendance(MA), p-median problem(PMP), and the location set covering problem(LSCP).The results showed that existing EECs were not optimally distributed, and that some areas were not adequately served by EECs(i.e., not all demand points could be reached within a 60-min travel time).We concluded that the proposed models can be used to improve planning of the distribution of EECs, and that application of the models could contribute to reducing human casualties, property losses, and improve emergency operation.     

GIS-based landslide susceptibility modeling: A comparison between fuzzy multi-criteria and machine learning algorithms

Hazards and disasters have always negative impacts on the way of life.Landslide is an overwhelming natural as well as man-made disaster that causes loss of natural resources and human properties throughout theworld.The present study aimed to assess and compare the prediction efficiency of different models in landslide susceptibility in the Kysuca river basin,Slovakia.In this regard,the fuzzy decision-making trial and evaluation laboratory combining with the analytic network process(FDEMATEL-ANP),Na?ve Bayes(NB)classifier,and random forest(RF)classifier were considered.Initially,a landslide inventory map was produced with 2000 landslide and nonlandslide points by randomly dividedwith a ratio of 70%:30%for training and testing,respectively.The geospatial database for assessing the landslide susceptibility was generated with the help of 16 landslide conditioning factors by allowing for topographical,hydrological,lithological,and land cover factors.The ReliefF methodwas considered for determining the significance of selected conditioning factors and inclusion in the model building.Consequently,the landslide susceptibility maps(LSMs)were generated using the FDEMATEL-ANP,Na?ve Bayes(NB)classifier,and random forest(RF)classifier models.Finally,the area under curve(AUC)and different arithmetic evaluation were used for validating and comparing the results and models.The results revealed that random forest(RF)classifier is a promising and optimum model for landslide susceptibility in the study area with a very high value of area under curve(AUC=0.954),lower value of mean absolute error(MAE=0.1238)and root mean square error(RMSE=0.2555),and higher value of Kappa index(K=0.8435)and overall accuracy(OAC=92.2%).     

Evaluating scale effects and bearing portions in centrifuge modeling of helical anchors: sand

Acta Geotechnica - Helical anchors are bearing elements that can resist uplift loads by a combination of shaft and helical plate bearing. The application of helical piles as offshore wind turbine...     

Flood risk mapping and crop-water loss modeling using water footprint analysis in agricultural watershed,northern Iran

Natural Hazards - Spatial information on flood risk and flood-related crop losses is important in flood mitigation and risk management in agricultural watersheds. In this study, loss of water bound...     

Role of land surface parameter change in dust emission and impacts of dust on climate in Southwest Asia

Natural Hazards - Spatial–temporal changes of land surface parameters (land cover change, net primary production, and vegetation phenology) affect the characteristics of atmospheric dust....