Geotechnical evaluation of Turkish clay deposits: a case study in Northern Turkey

Clay deposits in Oltu-Narman basins (Erzurum, northern Turkey) have been studied to determine their engineering properties and to evaluate their uses for geotechnical applications. These deposits are concentrated in two different stratigraphic horizons namely the Late Oligocene and the Early Miocene sequences. Clay-rich fine-grained sedimentary units are deposited in shallow marine and lagoonar mixed environments. Their clay minerals originated by the alteration of Eocene calc-alkaline island-arc volcanics, preferably from pyroclastics (trachite and andesite flow), which form the basement for the Oltu depression. Smectite group clay minerals are found abundant in clay deposits. The experimental results show that the clay soils have high plasticity behaviors and low hydraulic conductivity properties. The optimum water content, the free swell, and the swelling pressure of clay samples decreased and the maximum dry unit weight of clay samples increased under high temperature. Consequently, it is concluded that the expanding of clay soils is an important soil problem that cannot be avoided in the significant parts of Oltu city and its villages. However, the soils of clay-rich layers in the outcrops-section of clay deposits can be successfully used to build compacted clay liners for landfill systems and to construct vertical and horizontal barriers for protection of ground water and for preventing soil pollution in geotechnical applications.     

Batch and Continuous Design of a Full‐Scale Treatment Facility for Removing Dissolved Natural Organic Matter

Batch and continuous flow adsorption experiments are carried out and the design of a full‐scale facility for removing dissolved natural organic matter (DNOM) from Catalan Lakewater is demonstrated. The adsorption efficiency is proportional to the temperature and the amount of adsorbent unlike pH increase. The highest DNOM removal rate is obtained at 35 °C, pH 4, and an adsorbent amount of 0.8 g L^?1. Optimum contact time for batch studies is 60 min at equilibrium. Correlation constants (r) of Langmuir and Freundlich isotherms are 0.8905 and 0.9739, respectively. Based on the Freundlich isotherm, the highest adsorption capacity (q_max) obtained is 2.44 and 6.01 mg DNOM/g granulated activated carbon (GAC) for raw and enriched water, respectively. Consequently, the effects of adsorbent amount, bed depth, empty bed contact time, and organic loading on removal performance are investigated in the rapid small‐scale column test (RSSCT) columns. The targeted effluent concentration of 1 mg DNOM/L can easily be achieved in the columns. At the design capacity of the facility, 15 adsorption columns with dimensions of 7 m height, 4.33 m diameter, and 22 days of operation cycle are required to remove DNOM from raw water.     

Hydrochemical model and probable pollution in the water of Euphrates River (Qaem–Falluja)

The study of hydrochemical models and probable pollution in Euphrates River from Qaem–Al-Falluja was performed through regime observation in ten water points. The hydrochemical properties of Euphrates River waters are determined by using the analysis results of 21 physico-chemical variables during the water year (2008). The interpretation of the hydrochemical phenomena is achieved in accordance with the statistical results of Polynomial Regression Statistic, calculating the coefficient of variation among the physico-chemical components of the water terminating by 14 models. The results of monitoring during the water year 2008 indicate a pollution case by SO₄ and Cd in Ramadi and downstream stations; TDS, Mg, Na, Cl, Mn, and CO₂ in Ramadi station; TDS, Ca, Na, Cl, and Fe in Baghdadi station; and Ca and H _T in Qaem station and Mg in Obaydi station. The research suggests the best locations for hydrochemical monitoring as continuous hydrologic stations used for the long-term monitoring. These stations are in Qaem city as inlet location and Al-Baghdadi and Ramadi cities terminating in Falluja city as outlet location. Furthermore, daily record system is recommended for the other stations in each city to complete the regime observation of Euphrates water type. From the configuration approach of hydrochemical models with the pollution phenomena, there are potential point sources of pollution such as municipal effluent pipes and reused water from mining process for building materials in the first sector of river, which extends between Qaem and Haditha dam. Also groundwater seepages and springs discharge of mineralized water mixed with sewage water from cities act as potential point sources of pollution on the river water in the second sector extended between Haditha and Ramadi scheme. The third sector of the river is affected by all reasons in the first and second sectors as well as the effectiveness of agricultural activities throughout drainage canals and irrigation projects extended between Ramadi and Falluja cities.     

G-WADI—the first decade

The G-WADI network by UNESCO promotes the global capacity for management of water resources in arid and semi-arid areas. The primary aim has been to build a comprehensive global network to promote regional and international cooperation so as to increase knowledge and improve management practices through the sharing of information. The G-WADI objectives and achievements of the past 10 years are reviewed. A number of key initiatives have been implemented––the formation of five regional networks, the creation of a central G-WADI web site, promotion of near-real-time rainfall distribution software enhanced by the inclusion of satellite based precipitation estimations, as well as workshop and web-based activities on chemical and isotopic tracers and on rain water harvesting. Two workshops on surface and on groundwater modeling, supported by publications have been held in India and China. The Asian G-WADI network remains very active, but activities in the other three regions are developing (Africa, Arab Region, Latin America and the Caribbean).     

An Extended Approach of Particle Swarm Optimization for Shoreline Extraction from RASAT Imagery

This study presents an extended shoreline detection approach from pansharpened images of Turkish RASAT satellite which covers red, green and blue bands of the optical spectrum with 15 m ground resolution and panchromatic band with 7.5 m spatial resolution. The Lake Ercek of Turkey has been selected as the study area, which is a tectonic lake and home to a variety of water birds. The satellite images of the lake taken in 2013 and 2014 were considered for analysis. The proposed shoreline extraction system consists of a sequence of image processing steps in which simple linear clustering (SLIC) and particle swarm optimization (PSO) are the main components. SLIC was used to create superpixels that form basis for object-based image analysis while PSO was employed for classifying objects into corresponding classes. The resulting images still contained unwanted artefacts; therefore, a post-processing step was performed to improve the accuracy of segmentation by applying thresholding, morphological processing, and manual editing for noise removal. The proposed framework was applied on two temporal RASAT images to test the variations of defined parameter settings. The success of the proposed system was to obtain shorelines with satisfying accuracy without using NIR band. Finally, the extracted shorelines were vectorised and compared with manually digitized shorelines from pansharpened satellite images for accuracy assessment.     

Advanced Lake Shoreline Extraction Approach by Integration of SAR Image and LIDAR Data

Noise and an abnormal distributed-image histogram is the main challenge of using SAR data. From this point of view, this study’s authors motivated the non-use of user-defined input parameters. To achieve this purpose, a fuzzy approach was proposed to extract shoreline from SENTINEL-1A data. The parameters in the processing of the SENTINEL-1A image were generated automatically with LIDAR-intensity-derived object-based segmentation results. The LIDAR-intensity image was segmented with the Mean-shift method. The corresponding result was used to estimate the input parameters for fuzzy clustering of the SENTINEL-1A image. Fuzzy segmentation was proposed, due to the expected large number of values regarding water and land classes except for the pixels along the shoreline. The memberships for land and water classes were separately computed. In the proposed approach, the results from LIDAR and SENTINEL-1A dataset are promising, with differences below 1 pixel (10?m) by evaluation with the used reference vector data.     

The nature of urbanization in the gulf countries

This paper analyses the urban process in the oil producing countries of the Gulf. The mode of urbanization is identified as one characterized by an extreme case of primacy but with rates varying among the countries of the region. This pattern is related to the historical evolution of human settlements as affected by the local environmental qualities and the recent large scale development of urban infrastructures which favoured the already existing capital cities. The relative city growth rates are among the highest in the world but with a declining tendency which reflects expenditure patterns and the nature of the regional economies. The high growth rates are essentially due to massive foreign migration into the region and to extremely high natural increase rate — an abnormal condition in an urban process approaching saturation point. The role of these primate centres in the development of the region is undeniable and, furthermore, all indications suggest that this pattern of urban development will continue in the furture as it is, perhaps economically and politically less costly.     

River suspended sediment load prediction based on river discharge information: application of newly developed data mining models

ABSTRACT

Suspended sediment load (SSL) is one of the essential hydrological processes that affects river engineering sustainability. Sediment has a major influence on the operation of dams and reservoir capacity. This investigation is aimed at exploring a new version of machine learning models (i.e. data mining), including M5P, attribute selected classifier (AS M5P), M5Rule (M5R), and K Star (KS) models for SSL prediction at the Trenton meteorological station on the Delaware River, USA. Different input scenarios were examined based on the river flow discharge and sediment load database. The performance of the applied data mining models was evaluated using various statistical metrics and graphical presentation. Among the applied data mining models, the M5P model gave a superior prediction result. The current and one-day lead time river flow and sediment load were the influential predictors for one-day-ahead SSL prediction. Overall, the applied data mining models achieved excellent predictions of the SSL process.     

Integrative stochastic model standardization with genetic algorithm for rainfall pattern forecasting in tropical and semi-arid environments

ABSTRACT

Climate patterns, including rainfall prediction, is one of the most complex problems for hydrologist. It is inherited by its natural and stochastic phenomena. In this study, a new approach for rainfall time series forecasting is introduced based on the integration of three stochastic modelling methods, including the seasonal differencing, seasonal standardization and spectral analysis, associated with the genetic algorithm (GA). This approach is specially tailored to eradicate the periodic pattern effects notable on the rainfall time series stationarity behaviour. Two different climates are selected to evaluate the proposed methodology, in tropical and semi-arid regions (Malaysia and Iraq). The results show that the predictive model registered an acceptable result for the forecasting of rainfall for both the investigated regions. The attained determination coefficient (R²) for the investigated stations was approx. 0.91, 0.90 and 0.089 for Mosul, Baghdad and Basrah (Iraq), and 0.80, 0.87 and 0.94 for Selangor, Negeri Sembilan and Johor (Malaysia).