Showing papers in "Arabian Journal of Geosciences in 2015"

Groundwater potential mapping at Kurdistan region of Iran using analytic hierarchy process and GIS

Abstract: Multi-criteria decision analysis (MCDA) as an advantageous tool has been applied by various researchers to improve their management ability. Management of groundwater resource, especially under data-scarce and arid areas, encountered a lot of problems and issues which drives the planers to use of MCDA. In this research, a standard methodology has been applied to delineate groundwater resource potential zonation based on integrated analytical hierarchy process (AHP), geographic information system (GIS), and remote sensing (RS) techniques in Kurdistan plain, Iran. At first, the effective thematic layers on the groundwater potential such as rainfall, lithology, drainage density, lineament density, and slope percent were derived from the spatial geodatabase. Then, the assigned weights of thematic layers based on expert knowledge were normalized by eigenvector technique of AHP. To prepare the groundwater potential index, the weighted linear combination (WLC) method was applied in GIS. Finally, the receiver operating characteristic (ROC) curve was drawn for groundwater potential map, and the area under curve (AUC) was computed. Results indicated that the rainfall and slope percent factors have taken the highest and lowest weights, respectively. Validation of results showed that the AHP method (AUC = 73.66 %) performed fairly good predication accuracy. Such findings revealed that in the regions suffering from data scarcity through the MCDM methodology, the planners would be able to having accurate knowledge on groundwater resources based on geospatial data analysis. Therefore, the developing scenario for future planning of groundwater exploration can be achieved in an efficient manner.

Groundwater spring potential mapping using bivariate statistical model and GIS in the Taleghan Watershed, Iran

Abstract: The aim of the current study was to produce groundwater spring potential map using a bivariate statistical model (frequency ratio) and geographical information system (GIS) in the Taleghan Watershed, Alborz Province, Iran. Firstly, field surveys were done for identifying and springs inventory mapping. In total, 457 springs were identified and mapped in GIS; out of that, 320 (70 %) locations were selected for training and the remaining 137 (30 %) cases were used for the model validation. The effective factors on the groundwater spring such as: slope percent, slope aspect, altitude, topographic wetness index, stream power index, slope length, plan curvature, distance from rivers, distance from roads, distance from faults, lithology, land use, soil hydrology groups, and drainage density were derived from the spatial database. Using the above effective factors, groundwater spring potential mapping was calculated using FR model as a bivariate statistical model, and the results were plotted in Arc GIS. Eventually, the receiver operating characteristic curve was drawn for spring potential map and the area under the curve (AUC) was figured. Validation of results indicated that the frequency ratio model (AUC = 75.99 %) performed fairly good predication accuracy. The results of groundwater spring potential map may be helpful for planners and engineers in water resource management and land use planning.

Regional prediction of groundwater potential mapping in a multifaceted geology terrain using GIS-based Dempster–Shafer model

Abstract: A prediction at a regional scale of groundwater productivity potential mapping in an area is subjected to uncertainties that must be efficiently managed for enhancing decision making. This study explored the potential of a GIS-based Dempster–Shafer theory (DST) model as a spatial prediction model to offer solution to this problem. Seven criteria/factors regarded as positive indicators to the existence of promising groundwater reservoir in a given study area were selected and weighted in a probability-based DST approach to compute degrees of belief functions component indexes. The results of the computed belief function indexes values were processed in GIS environment to generate belief functions maps among which the uncertainty index map established uncertainty result of relatively low range of <1 to 9 % prediction in the area. The belief index map which provides concrete support for the existence of promising aquifers in the area was modeled to produce the groundwater potential zones prediction (GPZP) map. A developed mathematical model based on the relationship between the estimated Belief index values and borehole yield data established the influences of diverse rock type’s properties on the aquifer productivity in the area. The effect of coherence of criteria on the efficiency of DST model as a prediction model was also examined. The GPZP map produced was found to be 85.71 % accurate. The results of the examination of the effect of coherence of the criteria revealed that the ability of the DST model to produce accurate prediction is dependent on the exhaustiveness of the set of criteria used. The obtained results illustrate the usefulness of knowledge-driven DST model in GIS-based predictive mapping of groundwater potential zones. The results also show the capability of DST model in managing uncertainty associated with the predictive potential zones in the study area.

Content-based image retrieval using PSO and k-means clustering algorithm

Abstract: In various application domains such as website, education, crime prevention, commerce, and biomedicine, the volume of digital data is increasing rapidly. The trouble appears when retrieving the data from the storage media because some of the existing methods compare the query image with all images in the database; as a result, the search space and computational complexity will increase, respectively. The content-based image retrieval (CBIR) methods aim to retrieve images accurately from large image databases similar to the query image based on the similarity between image features. In this study, a new hybrid method has been proposed for image clustering based on combining the particle swarm optimization (PSO) with k-means clustering algorithms. It is presented as a proposed CBIR method that uses the color and texture images as visual features to represent the images. The proposed method is based on four feature extractions for measuring the similarity, which are color histogram, color moment, co-occurrence matrices, and wavelet moment. The experimental results have indicated that the proposed system has a superior performance compared to the other system in terms of accuracy.

Application of two intelligent systems in predicting environmental impacts of quarry blasting

Abstract: Blasting, as the most frequently used method for hard rock fragmentation, is a hazardous aspect in mining industries. These operations produce several undesirable environmental impacts such as ground vibration, air-overpressure (AOp), and flyrock in the nearby environments. These environmental impacts may cause injury to human and damage to structures, groundwater, and ecology of the nearby area. This paper is aimed to predict the blasting environmental impacts in granite quarry sites through two intelligent systems, namely artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). For this purpose, 166 blasting operations at four granite quarry sites in Malaysia were investigated and the values of peak particle velocity (PPV), AOp, and flyrock were precisely recorded in each blasting operation. Considering some model performance indices including coefficient of determination (R2), value account for (VAF), and root mean square error (RMSE), and also using simple ranking procedure, the best models for prediction of PPV, AOp, and flyrock were selected. The results demonstrated that the ANFIS models yield higher performance capacity compared to ANN models. In the case of testing datasets, the R2 values of 0.939, 0.947, and 0.959 for prediction of PPV, AOp, and flyrock, respectively, suggest the superiority of the ANFIS technique, while in predicting PPV, AOp, and flyrock using ANN technique, these values are 0.771, 0.864, and 0.834, respectively.

Neuro-fuzzy technique to predict air-overpressure induced by blasting

Abstract: In addition to all benefits of blasting in mining and civil engineering applications, blasting has some undesirable impacts on surrounding areas. Blast-induced air-overpressure (AOp) is one of the most important environmental impacts of blasting operation which may cause severe damage to nearby residents and structures. Hence, it is a major concern to predict and subsequently control the AOp due to blasting. This paper presents an adaptive neuro-fuzzy inference system (ANFIS) model for prediction of blast-induced AOp in quarry blasting sites. For this purpose, 128 blasting operations were monitored in three quarry sites, Malaysia. Several models were constructed to obtain the optimum model in which each model involved five inputs and one output. Values of maximum charge per delay, powder factor, burden to spacing ratio, stemming length, and distance between monitoring station and blast face were set as input parameters to predict AOp. For comparison purposes, considering the same data, AOp values were predicted through the pre-developed artificial neural network (ANN) model and multiple regression (MR) technique. The results demonstrated the superiority of the ANFIS model to predict AOp compared to other methods. Moreover, results of sensitivity analysis indicated that the maximum charge per delay and powder factor and distance from the blast face are the most influential parameters on AOp.

Paddy soil heavy metal contamination and uptake in rice plants from the adjacent area of Barapukuria coal mine, northwest Bangladesh

Abstract: This study was carried out to estimate the heavy metal contamination in paddy soil and subsoil and uptake by rice plants collected from Barapukuria coal mine area of Bangladesh. The mean contents of As, Cr, Cu, Mn, Ni, Pb, and Zn in paddy soil and subsoil exceed the world averages, and the observed soils are moderately to extremely polluted with inputs from mining activities. Correlation and regression model analyses suggest that pH and TOC have distinct effect on the availability of observed metals in soils. Sequential extraction of paddy soil and subsoil samples demonstrate that the mobility of heavy metals increases in the order of Cu > Zn > Pb > Fe > Cr > Ni > Mn > As. The uptake of metals in rice root is much higher than those in straw and rice grains. Arsenic, Cr, and Pb uptake in rice grains are 6.87-, 1.58-, and 5.26-fold higher than the maximum permissible concentration which shows a tendency of transformation of these elements from contaminated soil to rice plants.

Experimental study on stabilization of a low plasticity clayey soil with cement/lime

Abstract: One of the possible problems that may be encountered by execution of future projects such as highway, mass construction, and also industrial buildings in Farmahin (in the northwestern of Arak, Iran) is low strength and large deformation of the field soil. Such soils can be treated with the general traditional soil stabilization methods such as lime or cement stabilization methods. In the current study, the effects of two types of additive for the soil (i.e., lime/cement) on the geotechnical and engineering properties of the soil are studied. The results of the study indicate that optimum moisture content, maximum dry unit weight, and plasticity index are affected by the addition of cement or lime. Also cement treatment results in increase of unconfined compressive strength (UCS) of the soils significantly, whereas the test results indicate that there is an optimum of lime content so that the addition of a few percentage of lime results in increase of unconfined compressive strength. Generally, improvement in mechanical behaviors of the soil due to cement treatment was noticeably higher than lime treatment. Also the results of tests show that the change of UCS of the specimens with the initial water content and curing time is significant, so that decreasing of initial water content or increasing of curing time results in increase of USC of the specimens. Also, the current study sought to characterize the relationship between secant modulus (E50) and UCS, curing time, and cement or lime content.

Effect of rock strength on failure mode and mechanical behavior of composite samples

Abstract: Many dynamic events in coal mine are caused by the instability of coal–rock body. In order to study the influence of rock strength on this type of instability, uniaxial compression experiments of rock–coal–rock composite samples with different rock strengths are carried out, and the effect and mechanism of rock strength on the mechanical behavior and fracture mode of the composite samples are analyzed. The results show that major failure modes of the composite samples are conjugate X-shaped shearing fracture and splitting fracture. The angle between the shear fracture surface and the end face increases with rock strength. The splitting fracture in the coal body expands to the rock when the rock strength is low. The strength properties of the composite samples mainly depend on the coal strength instead of the rock strength. With the rock strength increasing, the peak strain of the composite samples decrease, and the differences from the coal strain and strain rate to rock strain and strain rate become greater. These failure modes and characteristics of deformation are shown to be determined by the difference between the elastic modulus of rock and coal constituting the composite samples.

Identification of critical soil erosion prone areas and annual average soil loss in an upland agricultural watershed of Western Ghats, using analytical hierarchy process (AHP) and RUSLE techniques

Abstract: The present work integrates analytical hierarchy process (AHP) with Revised Universal Soil Loss Equation (RUSLE) model to determine the critical soil erosion prone areas along with the spatial pattern of annual average soil erosion rates of an upland agricultural sub-watershed in the Western Ghats of Kerala, India. The critical soil erosion prone areas were identified by integrating geo-environmental variables such as land use/land cover, geomorphology, drainage density, drainage frequency, lineament frequency, slope, and relative relief after determining its relative contribution in conditioning the terrain susceptible to soil erosion by AHP technique, in a raster-based Geographic Information Systems environment. The spatial pattern of average annual soil erosion rates was obtained by RUSLE model that consider five factors, viz., rainfall erosivity (R), soil erodability (K), slope length and steepness (LS), cover management (C) and conservation practice (P) factors. The soil erosion probability map prepared by the AHP method was reclassified into soil erosion severity map showing regions of different erosion probability. Among this, the critical erosion zone occupies 4.23 % of the total area followed by high erosion severity zone occupies 18.39 % of the study area. Nil and low zones together constitute 44.15 % of the total area. The assessed annual average soil loss from the watershed shows an increased value of 4,227 t−1 h−1 year−1 as the maximum loss. The cross-comparison of potential soil erosion severity map with annual average soil loss in the area validates the finding of the study by a high spatial correlation. More erosion proneness and annual loss were observed in areas where the side slope plateau, denudational slope, and valley fills comes with high slope and relative relief. The intense terrain modification in this area with improper soil conservation measures makes the watershed more vulnerable to soil erosion.

Heavy metals in the soils of the Arabian Gulf coast affected by industrial activities: analysis and assessment using enrichment factor and multivariate analysis

Abstract: The concentrations of nine heavy metals (Fe, Mn, Zn, Cu, Ni, Cd, Cr, Co, and Pb) in soil samples of Arabian Gulf coast, Saudi Arabia, were investigated. Sediment Quality Guideline (SQGs), SQG-Quotient (SQG-Q), toxicity degree index (TDI), enrichment factor (EF), and multivariate analysis, including principle component analysis (PCA) and hierarchical cluster analysis (HCA), were used to measure heavy metals of concern in the study area and to identify their possible sources. The results showed that the concentrations of different heavy metals were 530–5,700 mg kg? 1 for Fe; 9–150 mg kg−1 for Mn and 8–69 mg kg−1 for Zn; 1–21 mg kg−1 for Cu and not detectable—17 mg kg−1 for Ni; 6.9–130 mg kg−1 for Cr and not detectable—5 mg kg−1 for Co; and not detectable—24 mg kg−1 for Pb. Based on SQGs, only the maximum and mean Cr concentrations of study area were in heavy and moderate rates of pollution, respectively. The values of SQG-Q and TDI revealed that the investigated sampling points showed the lowest potential of adverse biological effects. The considerable number of collected soil samples has relatively higher EF values of 5–20 for Zn, Cu, Cr, and Pb, suggesting that these four metals may be derived from anthropogenic origin. Multivariate analysis also confirmed this finding that the sources of Zn, Cu, and Pb resulted primarily from anthropogenic sources, whereas Co, Ni, Fe, and Mn were mainly attributed to lithogenic sources. It could be generally concluded that it is possible to use multivariate analyses in combination with EF values as useful tools to identify the natural or anthropogenic sources of heavy metals in soils.

Risk assessment of water inrush in karst tunnels and software development

Abstract: Water inrush makes time extended, instruments destructed, and casualty increased, which is the biggest threat for safe construction of tunnels in karst areas. A software system for risk assessment of water inrush was established with considering eight risk factors, including groundwater level, unfavorable geology, formation lithology, topography, strata inclination, excavation, advanced geological prediction, and monitoring. In the present software system, fuzzy mathematics and Analytical Hierarchy Process (AHP) were used to quantitatively describe the risk levels for each factor. The influence degree of each factor to water inrush was assigned an objective weight and a subjective weight, and the proportion of the two weights in the risk assessment was defined as weight distribution. The objective weights of the risk factors were obtained from more than 100 water inrush instances in karst tunnels, whereas the weight distribution was totally derived from expert field assessment and subjective weights were determined by using AHP in the risk assessment. Two case studies of karst tunnels were applied to check the reliability of the proposed software system, and the comparisons between the software assessment and practical excavation yield good consistency. Therefore, the software system can appropriately be used in practice to forecast water inrush in karst tunnels.

Experimental study of strength characteristics of coal specimens after water intrusion

Abstract: We carried out uniaxial compressive experiments on coal specimens with different moisture contents to gain a better understanding of the water-induced weakening characteristics of coal. The effects of moisture content on the strength and deformation characteristics of the specimens were analyzed. The results of the uniaxial compressive experiment demonstrate that the full stress–strain curve presents plastic deformation characteristics with the increase of the moisture content in the coal specimens. A positive linear relation between the peak strain and moisture content and a negative one between the compressive strength and moisture content were observed. The results also show that the elastic modulus and the moisture content satisfy a negative exponential function. Taking the obtained relation as boundary conditions and applying the statistical damage theory and strain equivalence hypothesis, we derived a statistical constitutive damage model for coal which can reflect the effects of the moisture content.

The use of weather radar for rainfall-runoff modeling, case of Seybouse watershed (Algeria)

Abstract: The use of radar for rainfall and runoff estimation is beneficial because of the high spatial and temporal resolution and large areal coverage; the main objective of this research is the calibration of the weather radar of Annaba for hydrological applications. To improve rainfall distribution estimation for the maritime watershed (1,129 km2) (Seybouse, Annaba), located in the north eastern of Algeria, a new technique was used based on the creation of six virtual rainfall stations uniformly throughout the area. The rainfall data for these virtual stations are estimated from raw weather radar data using a newly developed program called “Rain-Data ver1.0.” The calibrated radar-derived rainfall is used as input data in the Gridded Surface Subsurface Hydrologic Analysis model; the results show that all radar rainfall input data tend to produce more accurate runoff hydrographs than rain gauge data. Finally, the use of radar rainfall data to estimate runoff gives encouraging results, especially in regions where continuous gauge rainfall measurements are not available and rain gauges are sparsely distributed.

Application of fuzzy inference system for prediction of rock fragmentation induced by blasting

Abstract: Appropriate prediction of rock fragmentation is a vital task in the blasting operations of open pit mines Rock fragmentation is affected by various parameters including blast pattern and rock characteristics, causing understanding the process difficult As such, application of the robust techniques such as artificial intelligence can be utilized in this regard In this paper, a predictive model was developed to predict rock fragmentation using fuzzy inference system (FIS) in Sarcheshmeh copper mine, Iran For this purpose, blasting parameters including burden, spacing, hole diameter, Schmidt hammer rebound number, density of joint, powder factor, and stemming length were considered as model inputs to predict rock fragmentation (D80) In addition, by using the same data, a multiple equation was proposed with the help of multiple regression analysis (MRA) Results of coefficient of determination (R 2) between predicted and measured rock fragmentation were computed as 0922 and 0738 for FIS and MRA models, respectively Moreover, root mean square error (RMSE) and variance account for (VAF) FIS model were obtained as 2423 and 92195 %, respectively, while these values were achieved for MRA technique as 4393 and 73835 %, respectively Comparison of the performance indices of the predictive models showed the superiority of the FIS model over the regression technique Results of sensitivity analysis indicated that burden, spacing, and powder factor are the most influential parameters on rock fragmentation

The effect of freeze–thaw cycles on physical and mechanical properties of Upper Red Formation sandstones, central part of Iran

Abstract: This paper presents the influence of freeze–thaw cycles on physical and mechanical properties of Upper Red Formation sandstones in the southwestern Qom province in central Iran. For this purpose, five different types of sandstones were selected. Freeze–thaw test was carried out for 30 cycles and P wave velocity, porosity and uniaxial compressive strength of specimens were determined after every 5 cycles. Also, long-term durability of sandstones against freeze–thaw cycles using a decay function model was evaluated. The results of this study show that an increase in number of freeze–thaw cycles decreases uniaxial compressive strength and P wave velocity, whereas the effective porosity increases. The results obviously indicate that rock strength and petrographic properties such as grain size and contacts between grains alone does not provide enough information regarding sample durability against freeze–thaw cycles. Finally, it was found that pore size distribution plays the main role on the resistance of sandstones in freeze–thaw cycles.

Application of artificial neural networks and multivariate statistics to predict UCS and E using physical properties of Asmari limestones

Abstract: Geomechanical properties of rocks such as uniaxial compressive strength (UCS) and modulus of elasticity (E) have been essentially evaluated for rock engineering projects as well as dam sites. In this paper, in order to estimate the parameters, some mathematical methods are proposed including multiple linear regression, multiple nonlinear regression, and artificial neural networks (ANNs). These methods were employed to predict UCS and E for limestone rocks in terms of P wave velocity, density, and porosity. The data of 105 rock samples from two different dam sites (located in Asmari Formation, Karun 4, and Khersan 3 dams) were obtained and analyzed for developing predictive models. Comparison of the multiple linear and nonlinear regressions and ANNs results indicated that respective ANN models were more acceptable for predicting UCS and E than the others. Also, it observed that between multiple linear and nonlinear regressions, second case has more capability to predict UCS. It should be noted that there were no strong relationships between the predicted and measured E in the both multiple regressions.

Landslide susceptibility mapping by frequency ratio and logistic regression methods: an example from Niksar–Resadiye (Tokat, Turkey)

Abstract: Turkey confronts loss of life and large economic losses due to natural disasters caused by its morphologic structure, geographical placement, and climate characteristics. The Kuzulu (Koyulhisar) landslide, which caused loss of life and property on 17th March 2005, occurred in an area near the country’s most important active fault, the North Anatolian Fault Zone. To mitigate and prevent landslide damages, prediction of landslide susceptibility areas based on probabilistic methods has a great importance. The purpose of this study was to produce a landslide susceptibility map by the logistic regression and frequency ratio methodologies for a 733-km2 area near the North Anatolian Fault Zone from the southeast of Niksar to Resadiye in Tokat province. Conditioning parameters, such as elevation, slope gradient, slope aspect, distance to streams, roads, and faults, drainage density, and fault density, were used in the analysis. Before susceptibility analysis, the landslides observed in the area were separated into two groups for use in analysis and verification, respectively. The susceptibility maps produced had five different susceptibility classes such as very low, low, moderate, high, and very high. To test the performance of the susceptibility maps, area under curve (AUC) approach was used. For the logistic regression method, the AUC value was 0.708; while for the frequency rate method, this value was 0.744. According to these AUC values, it could be concluded that the two landslide susceptibility maps obtained were successful.

Provenance and tectonic setting of Miocene siliciclastic sediments, Sibuti formation, northwestern Borneo

Abstract: Provenance and tectonic setting of sandstone and mudstone units of the Miocene Sibuti Formation from northwest Borneo have been studied based on the mineralogy, major and trace element geochemistry data. The X-ray diffraction (XRD) and scanning electron microscopy-energy dispersive spectrometry (SEM-EDS) data revealed that the sandstones and mudstones were abundant in quartz, pyrite, clay, and heavy minerals such as zircon, rutile, and some detrital cassiterite. Geochemically, the sandstones and mudstones are classified into quartz arenite, litharenite, sublitharenite, arkose, and wacke. Quartz arenites are enriched with SiO2, Zr, and Th and depleted in Al2O3, CaO, and other elements compared to other sandstone types, indicating high maturity and intensive weathering. Chemical index of alteration (CIA: 77–90), plagioclase index of alteration (PIA: 86–100), and A-CN-K diagram suggest intense weathering in the source area. Elemental ratios such as La/Sc, Th/Sc, Cr/Th, La/Co, and Th/Co are similar to sediments derived from the felsic rocks. Also, the provenance discrimination diagrams suggest recycled continental nature of these clastic sediments which are mostly derived from metasedimentary source (Rajang Formation). Discriminant-function diagram for the tectonic discrimination of siliciclastic sediments revealed that the sediments of Sibuti Formation were derived from a collision zone, which is consistent with the geology of the study area.

The potential of in situ rainwater harvesting in arid regions: developing a methodology to identify suitable areas using GIS-based decision support system

Abstract: The first step in any rainwater harvesting system involves methods to increase the amount of water stored in the soil profile by trapping or holding the rain where it falls. This may involve small movements of rainwater as surface runoff in order to concentrate the water where it is wanted most. This paper presents a geographic information system (GIS) methodology based on a decision support system (DSS) that uses remote-sensing data, filed survey, and GIS to delineate potential in situ rainwater harvesting areas. The GIS-based DSS implemented as well as evaluated the existing rainwater harvesting structures in the study area. The input into the DSS included a map of rainfall surplus, slope, potential runoff coefficient (PRC), land cover/use, and soil texture. The outputs were map showing potential sites for in situ water harvesting (IWH). The spatial distribution of the suitability map showed that 1.5 and 27.8 % of the study area have excellent and good suitability for IWH, relatively, while 45 % of the area has moderate suitability. Validation of the existing IWH structures was done during a field survey using collected data and the suitability map. The validation depends on comparing rainwater harvesting/recharge dam’s locations in the generated suitability map and the location of the surveyed IWH structures using the proximity analysis tool of ArcGIS 10.1. From the proximity analysis result, all the exiting IWH structures categorized as successful (99 %) were within the good suitable areas.

Reservoir zonation and discrimination using the routine core analyses data: the Upper Jurassic Sab’atayn sandstones as a case study, Sab’atayn basin, Yemen

Abstract: Sab’atayn basin is one of the two main hydrocarbon fields in Yemen. The present study is a trial to use the measured conventional core analysis data to define the potential reservoir zones in Alif and Seen members in Sab'atayn basin and to discriminate them into conductive and superconductive zones, and into potential and impervious zones using the concept of Reservoir Quality index (RQI), the Flow zone Index (FZI), and the Reservoir Potentiality Index (RPI). Samples from Alif and Seen members are composed mostly of pebbly quartz arenite, sometimes of dolomitic and ferruginous quartz arenite. Based on the petrophysical behavior, the studied Alif member is subdivided into three petrophysical facies in Alif 003 well and into two facies in Alif 005 well. Seen member is also subdivided into two petrophysical facies in Alif 005 well. The bulk density of the measured Alif and Seen samples is dependent mostly on the measured porosity with no dependence on the grain density. Due to the measuring technique, summation fluid porosity shows scattered data and is not recommended to be used for further development and exploration of future plans in the studied field. The reservoir zonation and discrimination shows a main reservoir body in Alif member in both Alif 003 and Alif 005 wells, with very good and excellent potentiality (RPI, 4–5) in Alif 003 well. The reservoir potentiality decreases to the southwest of the field in Alif 005 well, where the RPI varies from 2 to 4, ranked as fair to very good. Downward, Seen member is characterized mostly by negligible, poor to fair petrophysical data in the most top parts (RPI, 1–3). The quality controlled parameters, RPI and FZI, are mostly controlled by horizontal permeability ‘K’ and can be calculated precisely in terms of it.

Evaluation of coastal erosion and accretion processes along the southwest coast of Kanyakumari, Tamil Nadu using geospatial techniques

Abstract: The impact of coastal erosion has adversely affected the socioeconomic conditions of the coastal community worldwide. The coastal environment is experiencing a wide range of natural and anthropogenic pressure in India. This study was carried out along the southwest coast of Kanyakumari, South India using multitemporal Landsat satellite images from 1999 to 2011. The long-term coastal erosion and accretion rates have been calculated for the periods between 1999 and 2011, and the subsequent short-term changes were performed during 1999–2000, 2005–2006, and 2010–2011. Thus, the long-term coastal changes indicate that the net erosion rate is higher on the coasts of Kanyakumari, Kovalam, Manavalakurichi, Mandaikadu, and Thengapattinam; the values are 0.118, 0.105, 0.127, 0.133, and 0.017 m2, respectively. Meanwhile, the annual erosion rate of these areas is 10,000, 9,000, 11,000, and 1000 m2/year. The coastal zones Ganapathipuram and Enayamputhandurai have experienced accretion; the net accretion rate is 0.271 and 0.081 m2, respectively. Coastal beaches, beach ridges, and marine terraces are predominantly disturbed by the hydrodynamic processes including wave action, littoral current, and intervention of littoral drift by the artificial coastal structures like groins, revetments, and seawalls. Moreover, the study area has been demarcated with site-specific erosion and accretion zones based on the frequent seaward or landward coastline fluctuation through geospatial technique.

A GIS-based assessment of water quality pollution indices for heavy metal contamination in Tuticorin Corporation, Tamilnadu, India

Abstract: The present study was conducted to evaluate the metal pollution of groundwater in the vicinity of Tuticorin Corporation in Tamilnadu State, India, used by various pollution indices such as heavy metal pollution index (HPI), heavy metal evaluation index (HEI), and degree of contamination (DOC). Thirty-six groundwater samples were collected during the summer season (May 2013) and the concentration of metals Al, Cr, Fe, Cu, Mn, Ni, Zn, Cd, and Pb was analyzed. Consequences exhibited that groundwater was contaminated with Mn (59.12 ppb), Cu (162.41 ppb), Pb (196.15 ppb), Cr (187.12 ppb), and Cd (10.11 ppb). Correlation and factor analysis revealed that the sources of metals in groundwater in the study area are the same, and it may due to the leachates from the nearby sewage farm, industrial activity (State Industries Promotion Corporation of Tamil Nadu Limited (SIPCOT)), Buckle canal, and solid wastes dumped in the residential area. Groundwater pollution indices of HPI, HEI, and DOC revealed that most of groundwater samples belonged to the medium to high zones, which was adjacent to the polluted Buckle canal, SIPCOT industrial waste, and sewage fish farm in the coastal area. The present study points out that the metal pollution causes the degradation of groundwater quality around Tuticorin coastal corporation. These study results will be very helpful for sustainable management of groundwater resources, and they will enable planners and policymakers to evolve a strategy to solve similar problems elsewhere.

Estimation of soil salinity using three quantitative methods based on visible and near-infrared reflectance spectroscopy: a case study from Egypt

Abstract: Soil salinization is a progressive soil degradation process that reduces soil quality and decreases crop yields and agricultural production. This study investigated a method that provides improved estimations of soil salinity by using visible and near-infrared reflectance spectroscopy as a fast and inexpensive approach to the characterisation of soil salinity. Soil samples were collected from the El-Tina Plain on the northwestern Sinai Peninsula in Egypt and measured for electrical conductivity (ECe) using a saturated soil-paste extract. Subsequently, the samples were scanned with an Analytical Spectral Devices spectrometer (350–2,500 nm). Three spectral formats were used in the calibration models derived from the spectra and ECe: (1) raw spectra (R), (2) first-derivative spectra smoothened using the Savitzky–Golay technique (FD-SG) and (3) continuum-removed reflectance (CR). The spectral indices (difference index (DI), normalised difference index (NDI) and ratio index (RI)) of all of the band–pair combinations of the three types of spectra were applied in linear regression analyses with the ECe. A ratio index that was constructed from the first-derivative spectra at 1,483 and 1,918 nm with an SG filter produced the best predictions of the ECe for all of the band–pair indices (R 2 = 0.65). Partial least-squares regression models using the CR of the 400–2,500 nm spectral region resulted in R 2 = 0.77. The multivariate adaptive regression splines calibration model with CR spectra resulted in an improved performance (R 2 = 0.81) for estimating the ECe. The results obtained in this study have potential value in the field of soil spectroscopy because they can be applied directly to the mapping of soil salinity using remote sensing imagery in arid regions.

Assessment of contaminated sediment by phosphate fertilizer industrial waste using pollution indices and statistical techniques in the Gulf of Gabes (Tunisia)

Abstract: On July 2010, 26 surface sediments of the Gulf of Gabes, Tunisia were sampled at depth ranging from 05 to 10 m These specimens were analyzed to determine Al, Cd, Cr, Cu, Pb, Zn, F, P, and N concentrations and total organic carbon contents The distribution map shows that the high amounts of pollutants are principally located between the commercial harbor and the fishing harbor of Gabes Measurements of heavy metal contents were carried out using (absorption atomic spectrometer), where the enrichment factor (EF), the geoaccumulation index (I geo), and the contamination index (CI) are determined The EF values of all metals were >15, corroborate anthropogenic impact on the metal levels in this studied area However, the I geo and CI values of Cd and Zn elements indicated that sediments collected from sites at the vicinity of the commercial harbor are very contaminated, although for Pb, Cr, and Cu elements these indices indicated that the same sediments are uncontaminated Statistical analyses (principal component analysis/factor analysis and matrix correlation) show that heavy metals, fluoride, and phosphorus are resulting from the same anthropogenic source

The water quality index and hydrochemical characterization of groundwater resources in Hafar Albatin, Saudi Arabia

Abstract: The main objectives of this study were to: evaluate and compare the treated and untreated groundwater quality in Hafar Albatin, Saudi Arabia for drinking purpose using water quality index (WQI), study the suitability of untreated groundwater for irrigation purpose, and investigate hydrochemical processes that control the groundwater chemistry. The WQI calculations required several physiochemical water parameters including EC, pH, Ca2+, Mg2+, Na+, K+, Cl−, SO4 2−, and NO3 −. The results showed that more than 47 % of the untreated wells considered unsuitable (class V), 39 % considered very poor water (class IV), and 14 % considered poor water (class III) for drinking purposes. The treatment of groundwater improved its quality to poor (class III) and even good (class II). Approximately 64 % of all treated waters were of good quality; however, the rest remained poor. Most studied untreated groundwaters were considered unsuitable for irrigation due to salinity hazards; however, no sodicity hazards were anticipated. US salinity laboratory diagram revealed that the groundwater samples were grouped into five categories; 53.6 % of water samples were distributed in category C4–S2 highlighting very high salinity hazards and medium sodium hazards class. Durov and Piper diagrams revealed that the majority of investigated waters were sodium chloride and calcium sulfate–chloride water type. The Gibbs’s diagram revealed that the chemical weathering of rock-forming minerals and evaporation are influencing the groundwater quality. The hydrochemical modeling indicated that all water samples were undersaturated for halite and 89 % of water samples were saturated for anhydrite and gypsum.

Shoreline change assessment using remote sensing and GIS techniques: a case study of the Medjerda delta coast, Tunisia

Abstract: Eight scenes of Landsat Multispectral Scanner, Thematic Mapper, Enhanced Thematic Mapper Plus, and Operational Land Imager sensors, covering the period between 1972 and 2013, were used to demarcate shoreline positions and estimate shoreline change rates of the Medjerda delta coast, northeastern Tunisia The method relies on image processing techniques using the IDRISI software, and the Digital Shoreline Analysis System, a free extension for ArcGIS software, which provides a set of tools permitting transects-based calculation of shoreline displacement First, the Landsat images were radiometrically and geometrically corrected Second, band ratioing, reclassification, raster to vector conversion, and smoothing techniques are applied successively to detect and extract the multi-temporal shoreline data Third, these data are overlaid and the changes are calculated using the end points and linear regression methods The results indicate significant shoreline changes ranging from 86 to −426 m/year, while some parts remained unchanged The estimated shoreline change rates are comparable with those obtained through in situ measurements and from the analysis of multi-date aerial photos and toposheets The main causes of erosion in particular are related to the natural shifting of the Medjerda River course and mouth, damming of Medjerda and its tributaries, construction of Ghar El Melh port, and the destruction of the small bordering dunes in addition to the wave-induced longshore currents, relative sea level rise due mainly to accelerated coastal subsidence, and sand mining

Landfill site selection using multi-criteria evaluation in the GIS interface: a case study from the Gaza Strip, Palestine

Abstract: Selection of landfill sites for solid waste disposal is one of the biggest problems in urban areas because of impacts on public health. Based on the nature of the study area, appropriate landfill sites should be selected using multi-criteria evaluation techniques. There are three main landfill sites in the Gaza Strip, one in the Rafah Governorate, one in the Middle Governorate, and one in the Gaza Governorate. The Gaza Strip is one of the most densely populated areas in the world having a population density of 4660 persons per square kilometer and, hence, faces enormous difficulties with respect to waste disposal. At present, the available waste disposal sites are insufficient. This study focuses on the selection of new suitable landfill sites in the Gaza Strip using multi-criteria decision analysis (MCDA) with the help of the analytical hierarchy process (AHP) method. To achieve this aim, different thematic layers such as land use, soil type, depth to groundwater, distance from roads, rainfall, and elevation are considered. The results show that only 5.5 % of the total area of the Gaza Strip is highly suitable for landfill sites. The high suitable zone for landfill sites is predominantly located in the southeast of the Khan-Younis and Rafah Governorates. These suitable areas consist of cultivated area or natural resources, with sandy loess soil over loess, clay loam, or loessal sandy soil. The depth to ground water varies from 70 to 100 m from soil surface, the rainfall varies from 200 to 350 mm/year, and the altitudes are between 60 and 80 m above mean sea level. Moreover, these suitable sites are also located within 500 m from the road network. This information can be used by concerned authorities and stakeholders for establishing new solid waste disposal sites in the Gaza Strip.

A simplified analysis for deformation behavior of buried pipelines considering disturbance effects of underground excavation in soft clays

Abstract: Underground excavation, such as tunneling and deep foundation pit, will no doubt induce the soil disturbance and have result in uneven settlements of adjacent buried pipelines which adversely affect and even damage the structures. In order to explicitly point out construction interaction mechanism and rapidly predict the structure mechanical behavior, a simplified displacement-controlled two-stage method and stress-controlled two-stage method are presented for determining the deformation behavior of pipeline structures caused by underground excavation in soil clays. According to tunneling project, the free soil deformation calculated by the displacement-controlled boundary element solution is used to estimate the soil disturbance effects of underground excavation. The oval-shaped ground deformation pattern is imposed to the tunnel opening to consider the nonuniform convergence characters. According to foundation pit project, the free soil stress based on the Mindlin solution is used to predict the soil disturbance effects of underground excavation. The situations that the excavation unloading center is not acting on the pipeline axis and that the excavation boundary and pipeline axis are formed with an arbitrary angle can fully be considered. Then, the free soil deformation and free soil stress are imposed onto existing pipelines to analyze the interaction mechanics between the disturbance soil and buried structures. The accuracy of proposed method is demonstrated with existing calculation results, centrifuge model tests, and site investigation data. In addition, the parametric analyses for the deformation influence factors of existing tunnel induced by foundation pit excavation, including the horizontal distance between the excavation boundary and tunnel axis, the tunnel buried depth, the tunnel bending stiffness, and the crossing angle between the excavation boundary and tunnel axis, are presented to demonstrate the performance of the proposed method. The results indicate that the proposed method can be used to estimate the mechanical behavior of buried pipelines considering disturbance effects of underground excavation with higher precision.

Characterizing spatial variability of soil properties in salt affected coastal India using geostatistics and kriging

Abstract: Soil salinization is a major problem affecting 955 Mha globally and 7 Mha in India. Soil properties vary spatially and knowing the extent of spatial variability of soil physicochemical characteristics is highly essential for management of these soils and crop cultivation. This study was conducted in salt-affected coastal parts of eastern India, with the following objectives: (i) to explore the spatial variability of soil properties (soil electrical conductivity (ECe), soil pH, soil organic carbon (SOC), available soil nitrogen, available soil phosphorus, and available soil potassium) and fitting the semivariogram models; (ii) to estimate the values of soil properties at unsampled locations using geostatistical tools; and (iii) to prepare the spatial maps of soil properties using parameters of best fit semivariogram model and interpolation by ordinary kriging technique. A total of 132 soil samples were collected. Gaussian, exponential, circular, spherical, K-Bessel, and spherical semivariogram models were found to be the best fit for assessing the spatial variability in ECe, soil pH, SOC, available soil nitrogen, available soil phosphorus, and available soil potassium, respectively. The best fit model parameters were used to create the spatial maps for these soil properties by ordinary kriging. It was concluded that geostatistical and kriging tools can be used to estimate the value of soil properties at unsampled locations and ultimately to develop spatial maps for site-specific nutrient management.