Showing papers in "Arabian Journal of Geosciences in 2019"

Analysis of hydraulic fracturing techniques: hybrid fuzzy approaches

Abstract: Hydraulic fracturing technologies revolutionize the way petroleum industries drill the conventional and unconventional formations by the purpose for oil recovery enhancement. Multi-criteria decision-making (MCDM) methods are always considered as the preferable techniques in organizational and industrial operational performances that some of them are being widely administered for numerous purposes. The objective of this comprehensive study is to conduct an investigation about the considerable influence of five important criteria on the hydraulic fracturing techniques and select the best technology regarding enhancing oil recovery factor. Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) analyses are applied to compare each criterion. Consequently, among the five fundamental criteria for selecting and operating hydraulic fracturing, in situ stress-strain with the score weight of 0.421 is the most important selectivity criteria. Furthermore, after analyzing the results derived from FAHP and FTOPSIS methods, hydra-jet fracturing and zipper fracturing techniques with the normalized weights of 0.186 and 0.194, and relative closeness coefficients of 0.69 with a 0.66 are considered respectively as the best and optimum techniques of hydraulic fracturing. Last but not least, the cavitation hydro-vibration fracturing and explosive fracturing are the least preferable methods among hydraulic fracturing techniques.

Application of the GIS based multi-criteria decision analysis and analytical hierarchy process (AHP) in the flood susceptibility mapping (Tunisia)

Abstract: Flooding is considered as the most dangerous natural catastrophe in the world. This paper develops a spatial multi-criteria decision production prototype for the evaluation of flooding susceptibility for the city of Tunis. Eight criterions were considered in order to identify and assess the spatial distribution of hazardous zones and were integrated in the Geographical Information System (ArcGIS). The analytical hierarchy process (AHP) is a mathematical technique for flood hazard modeling and decision support based on the weight and rank of each flood factor in order to calculate Flood Hazard Index (FHI) to generate a flood susceptibility map. This was classified from very low to very high classes flood potential. Five classes are observed: 2.85% (very low), 7.5% (low), 17.95% (moderate), 20.63% (high), and 51.06% (very high). FHI was coupled with a sensitivity analysis to derive the Flood Hazard Index with sensitivity (FHIS). This index evaluates the effect of each criteria which allows for better assessment of the role of each parameter in flood susceptibility. The results of this study provide a basis to limit the impacts of flood and protect urban zone against inundation.

Drought indices and indicators revisited

Abstract: There are numerous drought indicators used by decision makers all around the globe which have been developed to fulfill specific needs. By far, risks associated with drought and related consequences have become a bold topic for scientists in which debates still taking place everywhere. No global drought indices could provide universally accepted results since almost all of these indices are based on observed data as key performance indicators. In this respect, researchers spend a lot of effort on this issue for a better understanding on the various indices which are proposed until now. It is crucial to get a better sense on how drought can develop and how it can be monitored. It is also important to understand that, recent global challenges like climate change also amplifies the obligation on continues effort toward developing better indicators and methods to monitor droughts. As climate patterns change or a seasonal shift occurs, predefined drought indicators become useless. In this review, the concepts of drought indices and indicators are revisited and evaluated. Pros and cons of frequently used indices are addressed and the major differences between them are bolded. It is concluded that each index is applicable to fulfill expectations of a specific drought type while pre-knowledge about each case is very crucial. However, there is a need to develop a composite drought index to integrate all relevant data and drought definitions, with respect to the dominant types of monthly droughts in time and space together with climate change scenarios.

Spatial-temporal trend analysis of seasonal and annual rainfall (1966–2015) using innovative trend analysis method with significance test

Abstract: This study investigates the spatial and temporal patterns of trends on seasonal (pre-monsoon, monsoon, post-monsoon, and winter) and annual rainfall time series data (1966–2015) at 13 stations located in the central Himalayan region of the Uttarakhand State of India. The temporal trend was analyzed using recently proposed innovative trend analysis (ITA) method with significance test. The results of the ITA method were compared with the Mann-Kendall (MK) test at 5% significance level. The spatial variation of the trends in seasonal and annual rainfall series was interpolated using the Thiessen polygon (TP) method in ArcGIS 10.2 environment. The results of comparison revealed that the trend detected by MK test (significantly positive in 3-time series and significantly negative in 6-time series) can be effectively identified using ITA (significantly positive in 19-time series and significantly negative in 32-time series). The ITA method could detect some trends that cannot be observed by the MK test. According to the spatial distribution of MK test, significantly increasing (decreasing) trends were observed in 1 (0), 1 (2), 0 (1), 1 (1), and 1 (1) polygons in pre-monsoon, monsoon, post-monsoon, winter, and annual rainfall data, while the ITA method detected significant trends in 3 (7), 6 (5), 1 (9), 4 (5), and 5 (6) polygons in the study region. The developed maps of spatial variability of rainfall trends may help the stakeholders and/or water resource managers to figure out the risk and vulnerability related to climate change in the study region.

Influence of hydro-geochemical processes on groundwater quality through geostatistical techniques in Kadava River basin, Western India

Abstract: Hydrogeochemistry and groundwater quality of the Kadava River Basin have been performed by analyzing 40 groundwater samples for pre- and post-monsoon seasons of 2011 through different geostatistical techniques. Analyses showed that the concentrations of Mg2+ exceeded Ca2+ in both the seasons suggesting silicate weathering as a source of ions. Average Ca + Mg values contribute 73.53% of total cations and signify the major supply of mafic minerals. Elevated TDS and TH limit drinking potential and other beneficial uses indicate permanently hard water. The average concentrations of the anions were found within Indian PL except NO3, attributed to use of fertilizers. The spatial distribution maps show the EC, Mg, Na, Cl, and SO4 to be generally higher for both the seasons in flood plain deposits than denuded landforms and middle-level/high-level plateaus containing fractured basalt aquifers. It is confirmed that silicate weathering is the dominant process followed by carbonate weathering. Inputs of TDS, Cl, SO4, Mg, Na, and NO3 are influenced by rainfall and human activities. Groundwater sample numbers 20, 37, and 38 have been severely impacted from agricultural runoff as these samples are located along the surface water flow path. The high loading of TDS and TH is controlled by the Mg, Na, Cl, and SO4 ions. Elevated concentration of Na over Ca represents the ion exchange between Ca and Na. High contents of Mg, Na, Cl, and SO4 corroborate that the groundwater is influenced by anthropogenic sources. This study is an insight for water managers to address groundwater pollution problems.

A new intelligent method for monthly streamflow prediction: hybrid wavelet support vector regression based on grey wolf optimizer (WSVR–GWO)

Abstract: Forecasting daily and monthly streamflows is necessary for short- and long-term water resources management, particularly in extreme cases, e.g., flood and drought. Accurate models are needed to plan and manage water resources in watersheds. Recently, support vector regression (SVR) shows the ability to handle the hydrological forecasting issues, but the accuracy of SVR depends on the appropriate choice of parameters and selection of proper inputs. A new meta-heuristic algorithm called grey wolf optimizer (GWO) is used in the current research in order to improve SVR accuracy in forecasting monthly streamflow. The proposed approach is compared with other evolutionary methods, particle swarm optimization, shuffled complex evolution, and multi-verse optimization, that are employed in tuning SVR parameters. Furthermore, the proposed methods were also combined with wavelet transform and tested using monthly streamflow data from two gauging stations, Ain Bedra and Fermatou, in Algeria. To assess the performance of the developed models, Nash–Sutcliffe efficiency (NSE), correlation coefficient, root mean squared error (RMSE), and mean absolute error (MAE) were used. The obtained results indicate that multi-linear regression provides appropriate input variables to SVR models. According to all of the performance measures used, hybrid models exhibit better performances, in monthly streamflow prediction, compared with single versions. For example, for the Ain Bedra station, the NSEcriterion and the correlation coefficient values increased considerably from 27.36% and 0.5405, for the single models, to 95.72% and 0.9786, for the hybrid models. A great decrease has also been obtained for the RMSE and MAE values, which decreased from 0.1562 m3/s and 0.1244 m3/s to 0.6433m3/s and 0.3047 m3/s. In addition, the new GWO algorithm outperformed the other algorithms in terms of both forecasting accuracy and convergence.

Trend analysis of rainfall and drought over the Oum Er-Rbia River Basin in Morocco during 1970–2010

Abstract: In a context of water scarcity in Morocco, the proper management of water resources is becoming a national priority. However, the strong spatiotemporal fluctuation of rainfall, considered as the first source of surface water intakes, complicates attempts to work on such a long-term purpose. In this work, we aim to provide an analysis of rainfall variability over the Oum Er-Rbia (OER) River basin, one of the most important basins in Morocco. For this, we assessed the annual rainfall deficit using the Standardized Precipitation Index (SPI) and then analyzed trends at annual, seasonal, and monthly bases using the Mann–Kendall test. The study was conducted on a set of data from 15 stations over a 40-years period (1970–2010). The results show that the OER River basin tends towards drier conditions. An abundance of deficit seasons has been noticed (50 to 63% of the seasons), especially after 1980–1981. Since then, the basin has known several deficit periods, sometimes of great spatial extent such as those that occurred in the 1980s and 1990s. Moreover, during the study period, the total annual rainfall has demonstrated a general decreasing tendency. The latter was mainly induced by changes in winter and spring months, which experienced some of the largest decline rates with a special abundant significance during the month of April.

Pan evaporation modeling by three different neuro-fuzzy intelligent systems using climatic inputs

Abstract: Modeling pan evaporation (Epan) estimation is a vital issue in water resources management because it directly affects water reservoir and water supply systems. In the developing countries (e.g., India), Epan data are generally limited, and in such a circumstance, theoretical estimates from available climatic data could be beneficial. The study investigates the capability of three adaptive neuro-fuzzy methods, adaptive neuro-fuzzy inference system (ANFIS)–embedded grid partition (GP), subtractive clustering (SC), and fuzzy c-means clustering (FCM), in estimation of monthly pan evaporation using climatic inputs of minimum and maximum air temperatures, wind speed, sunshine hours, and relative humidity obtained from two stations, Uttarakhand, India. Cross validation method is applied by dividing data into three equal parts, and methods are tested using each part. Methods are evaluated by applying various combinations of inputs and using root mean square error (RMSE), mean absolute error (MAE), Nash–Sutcliffe efficiency (NSE), and determination coefficient (R2) criteria. The ANFIS-FCM is found to be superior to the ANFIS-GP and ANFIS-SC methods in Epan modeling. Cluster-based proposed neuro-fuzzy method increases performance of the best ANFIS-GP and ANFIS-SC models with respect to RMSE by about 9–14% for the both stations. The three ANFIS methods are also compared with each other and Stephen Stewart (SS) method by dividing data into three stages, training, validation, and test. The results indicate the superior accuracy of the ANFIS methods to SS for the same input variables. The ANFIS-FCM generally produces better Epan estimates than the other two ANFIS methods.

Morphometric analysis and prioritization of sub-watersheds in a hilly watershed using weighted sum approach

Abstract: In this study, morphometric analysis of 14 hilly sub-watersheds (SWs) of Naula watershed located in upper Ramganga River basin, Uttarakhand State, India, was done using remote sensing (RS) and geographical information system (GIS). The morphometric parameters used for sub-watersheds prioritization were watershed area, perimeter, stream order, mean stream length, basin length, bifurcation ratio, drainage density, stream frequency, texture ratio, mean length of overland flow, form factor, circularity ratio, compactness coefficient, and elongation ratio. The cross-correlation analysis between morphometric parameters was performed and tested at 5% level of significance. The priority rank and category (very high, high, moderate, low, and very low) for each sub-watershed were assigned based on compound factor value. The value of compound factor for each sub-watershed was calculated using weighted sum approach (WSA). The results of this analysis illustrated that the 20.34% area under highly susceptible sub-watersheds (SW-5 and SW-10) needs appropriate soil and water conservation measures for its development and management.

Experimental study on stress wave attenuation and energy dissipation of sandstone under full deformation condition

Abstract: Excavation behaviours not only destroy the balance of original stress in rock mass but lead to the redistribution of initial stress, resulting in rock mass in a new stress environment. The static stress in rock mass has the characteristics of dynamic change. For the purpose of investigating the effect of increasing static stress on attenuation mechanism and energy dissipation of stress wave in sandstone under the overall deformation condition, small disturbance experiments on sandstone bar are carried out with a modified split-Hopkinson pressure bar test system. The stress waveform, p wave velocity, temporal and spatial attenuation of amplitude, and energy dissipation are studied under various static stresses. Results show that stress waveforms at different locations are approximately the same, those at the same locations vary greatly, and the tensile waves that appeared at the tails of stress waves are larger with increasing static stress. With increasing static stress, p wave velocity experiences a dramatic increase, then develops gently, and finally a sharp decrease; the stress demarcation points are σs/σc = 30% and σs/σc = 55%, respectively. P wave velocity can be predicted by a quadratic equation when σs/σc > 63.69%. The relation between longitudinal wave velocity and static stress can be described by a quadratic function. Stress wave amplitudes decrease exponentially with increasing distance and time. Values of temporal spatial response intensity (RI) and spatial RI are approximately equal and present the same development tendency of nonlinear and linear stages due to the same dimensions. Values of temporal attenuation characteristic (AC) and spatial AC are differed by 2 or 3 orders of magnitude although they present the same development tendencies. Ratios of RI and AC can indicate the sensitivity of temporal and spatial attenuation to different static stresses. Full-wave energy declines in an exponential function with increasing static stress and decays as a logarithmic function with increasing distance. Widespread attenuation characteristics like these should provide a theoretical basis for rock mass stability analysis.

Layered double hydroxide–loaded biochar as a sorbent for the removal of aquatic phosphorus: behavior and mechanism insights

Abstract: This study was aimed to enhance the phosphorus (P) sorption capability of biochar through embedding of Mg-Fe layered double hydroxide (LDH) particles within its matrix. The structure, morphology, and surface chemistry of the prepared LDH/biochar composite were investigated via X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and Fourier transform infrared (FTIR) analysis. The P sorption behavior of LDH/biochar composite was assessed in comparison with the raw biochar under batch conditions. The effects of initial P concentrations, pH levels, and contact times on P sorption were examined. Results showed that the P sorption on LDH/biochar composite was pH-dependent, and the maximum P sorption was found at the pH range of 2–4. The sorption isotherm and kinetic data were best fitted with the Langmuir and pseudo-second-order models, respectively. The maximum P sorption capacity (Qmax) improved from 1.39 mg g−1 for raw biochar to 17.46 mg g−1 for LDH/biochar composite, respectively. Also, the equilibrium contact time decreased from 8 h for raw biochar to 1 h for LDH/biochar composite, respectively. The sorption process followed electrostatic attraction, ligand exchange, and surface inner-sphere complex formation mechanisms. Overall, the results of the present study revealed that the synthesized LDH/biochar composite can be potentially used as a carbon-based sorbent for the removal of phosphorus from aqueous solutions.

Response of soil microbial biomass and enzymatic activity to biochar amendment in the organic carbon deficient arid soil: a 2-year field study

Abstract: The application of pyrolyzed organic carbon (C) to soils has been assessed worldwide to play a vital role in improving the physical-chemical characteristics of the soil. However, the effects of co-use of biochar and nitrogen (N) fertilizer on soil biological process in an arid region are not well understood. For this, a 2-year field experiment was conducted in an arid region to assess the co-use of biochar and nitrogen (N) fertilizer on soil microbial biomass and enzyme activity in the rhizosphere of the wheat crop. Sugarcane bagasse was used as biochar feedstock and applied with three levels of biochar (0, 0.5, and 1% C ha−1) on carbon equivalent basis in the presence and absence of N fertilization (46 kg N ha−1). Biochar was incorporated in the soil before sowing of wheat, and the soil samples were taken from each treatment at crop maturity. Findings of the study indicated that biochar amendments enhance the soil organic carbon, DOC, inorganic N, and soil moisture contents, while reducing the bulk density and salinity of soil in both wheat growing season. Microbial biomass carbon and nitrogen increased by 18% and 63% with biochar amended at 1% C ha−1 with nitrogenous fertilizer and the same trend was observed in the following year. Urease and dehydrogenase activities also significantly increased with biochar applied at 1% C ha−1 with N fertilization illustrating 15% and 19%, respectively. During the second year of wheat trial, the enzymatic activity also boosted up as the first year. The results revealed that sugarcane bagasse-derived biochar addition can be utilized in improving the soil health, nutrient status, and soil biological functions in the calcareous soil of the arid region.

Monitoring LULC changes and its impact on the LST and NDVI in District 1 of Shiraz City

Abstract: Today, immediate and long-term change detection and monitoring using remote sensing (RS) data and geographical information system (GIS) is of paramount importance in generating information about the latest land use/land cover (LULC), land surface temperature (LST), and normalized difference vegetation index (NDVI) in accordance with spatial and temporal changes. Therefore, to obtain these components, a multi-temporal dataset was used consisting of two sets of Landsat Thematic Mapper (TM) images from 1986 to 2011 period across District 1 of Shiraz. Additionally, to investigate the relationship between LST and NDVI over seasons, four Landsat images were used. LULC, LST, and NDVI components were retrieved using Landsat image in ERDAS IMAGINE 9.2 image processing software. Results showed that during the study period, the city had experienced a massive urban (residential) growth. Moreover, change detection suggested that residential areas had increased by 13.17 km2 and vegetation zones (garden) and barren lands had decreased by 4.6 and 8.63 km2, respectively, during 1985–2011 period. The study of the relationship between vegetation index (land cover) and vegetation (land use) in District 1 showed that with reduced vegetation zone (land use), the quality of vegetation (land cover) had deteriorated. These findings indicate that reduced quality of vegetation cover and consequently its Reduction can have a positive effect on the temperature patterns. In general, the negative correlation between vegetation and LST caused by lower vegetation quality was less significant in 2011 compared to 1986, while there the correlation between vegetation and LST in summer was higher than other seasons.

Artificial recharge to groundwater using geospatial and groundwater modelling techniques in North Western Himalaya, India

Abstract: Artificial recharge to groundwater is an important process for the management of surface and subsurface water resources. In the present study suitable sites for artificial recharge to groundwater were delineated using geospatial techniques and groundwater modelling in Jammu Himalaya, India. Different thematic layers were prepared from remote sensing data (IRS-P6 and LISS-IV), and SRTM-DEM and aquifer parameters thematic layers were prepared from pumping test data and well inventory data collected during the field observations were integrated using the weighted index overlay method in the GIS environment to prepare the artificial recharge zone map. Further, suitable sites for artificial recharge map were determined by superimposing a drainage network map over the artificial recharge zones map, considering the terrain and local conditions for artificial recharge. The groundwater modelling for artificial recharge to groundwater was also carried out using Visual Modflow Flex software to determine the modeling zones for artificial recharge to groundwater. The lithologs data, aquifer thickness, hydraulic conductivity, specific yield and water level data were used to generate simulations of groundwater modelling zones. Finally, GIS based artificial recharge zones map and groundwater modelling zones were compared to validate artificial recharge zones. Simultaneously, a case study was also carried out to determine the impact of discharge and artificial recharge to surrounding aquifers. The results achieved from the current research proved the efficiency of geospatial technology and groundwater modelling techniques for delineating suitable zones and sites for artificial recharge to groundwater and their implementation in the field.

Morphometric analysis of watershed using remote sensing and GIS—a case study of Nanganji River Basin in Tamil Nadu, India

Abstract: Morphometric analysis of a river basin is essential to identify and assess seasonal changes in drainage basin characteristics, understand the groundwater potential, and address issues related to management of soil erosion due to flash floods during the high flows. Nanganji River Basin is one of the least studied seasonal river basins in India which carry substantial flows during the monsoon period. In this study, morphometry of Nanganji River Basin, located in the central Tamil Nadu prairies, has been studied using remote sensing and GIS. The interrelationship between the various morphometric factors of the basin has been studied using a correlation matrix. Factor analysis has been applied to group the individual morphometric parameters into a smaller number of factors. Further, these factors have been studied in relation to the sub-basins to understand the existing relation between the factors and the sub-basins. Finally, the study identifies environmental issues of the Nanganji River Basin mostly related to the river flow regime which widens significantly during the monsoon months.

Integrated effect of nano-Zn, nano-Si, and drainage using crop straw–filled ditches on saline sodic soil properties and rice productivity

Abstract: Soil salinity and sodicity issues due to limited water resources and arid climate are the main sources of land degradation in the North Nile delta. Moreover, burning rice and cotton straw is a very common practice in this region contributing to global warming and further polluting the environment. Improving saline sodic properties by biological drainage has received less attention so far. The study aimed to evaluate the effect of burying some crop residuals in field ditches and foliar application of nanoparticles on salt affected soil properties and rice productivity. The obtained results revealed that burying rice or cotton straw in field ditches prior to rice planting resulted in significant increase in rice yield and its components with superiority of cotton stalk–filled ditches to that filled by rice straw especially in the second season. Likewise, the incorporation of crop residual improved soil properties including soil fertility. The decomposition of rice straw or cotton stalk obviously decreased soil electric conductivity and soil compaction and slightly decreased bulk density. Also, soil hydraulic conductivity and organic matter content were positively responded to incorporation of crop residues. In addition, the availability of N and Zn in soil was increased due to the application of crop residues. The yield and yield components of rice were significantly affected by the foliar application of nano-Si and Zn with superiority of nano-Zn. Also, soil properties such as soil salinity, bulk density, soil compaction, hydraulic conductivity, organic matter, and available nitrogen were slightly affected by these nanoparticles while the available Zn was clearly increased.

Mechanism of mine water inrush from overlying porous aquifer in Quaternary: a case study in Xinhe Coal Mine of Shandong Province, China

Abstract: Mine water inrush from coal seam roof is one of the serious disasters that threaten safe production of coal mines. Identification of water inrush source and water inrush pathway is a key task for preventing and controlling such mine water hazards. A water inrush accident at approximately 1316 m3/h occurred at no. 3301 working face of Xinhe Coal Mine in Shandong Province, China. Multiple lines of evidence including characteristics of mine water inflow rate, dynamic monitoring data of water levels in different aquifers, geochemical fingerprinting, and drill hole core examination suggest that the water inrush source originated from the overlying Lower Quaternary porous aquifer with calcite cementation. Structural analysis and numerical simulation with FLAC3D indicate that a low-angle fault, DF49, and mining-induced fractures provided the pathway for the water inrush. Mining activities made the fault hydraulically conductive and connected to the Quaternary aquifer. The numerical simulation demonstrated that the water-conducting fracture zone in the coal seam roof extended to the fault. Groundwater gushed into the mining area from the Quaternary aquifer via the combined pathway of the activated fault and mining-induced fractures. Presence of the fault in the overlying formations played a critical role in occurrence of the water inrush. Results from this case study can be of reference to all coal mines with faults or other geological discontinuities present in the overlying formation. These discontinuities may significantly extend the height of the mining-induced water-conducting fracture zone in the roof and thus increase water inrush risks.

A particle-based numerical investigation on longwall top coal caving mining

Abstract: A 3D particle-based numerical approach to simulate the longwall top coal caving (LTCC) process was proposed, which for the first time the effect of continuous support advance and the face-end support were considered. The shape of drawing body and top coal boundary and the distribution characteristics of coal loss were analysed. The top coal flow trajectories and velocity fields were visualized and consistent with the assumptions in Bergmark-Roos model. The vertical forces on the drawing support beams were continuously monitored during the process of simulation. It was found that both the drawing procedure and the support advance will lead to a reduction of the vertical forces on support beams. Results of the numerical simulations and laboratory testing were compared and good consistency was obtained.

The compressive-shear fracture strength of rock containing water based on Druker-Prager failure criterion

Abstract: The stresses at the tips of the compressive-sheared cracks were calculated by applying the superposition principle. Then, the principal stresses at the tips of the compressive-shear crack were obtained. According to the Druker-Prager criterion, a fracture criterion for the compressive-shear crack, verified reasonable, was proposed. In addition, considering the influence of water, the above criterion was modified to investigate the influence of water on the stress intensity factors of cracks. The results show that the third principal stress of the main crack surface significantly increases the rock strength when the internal friction angle of the rock is lower than crack inclination angle. However, when the internal friction angle is higher than crack inclination angle, the increase of water pressure dramatically decreases the rock strength. When the internal friction angle is equal to crack inclination angle, the influences of water pressure and the third principal stress on the rock strength are the same. In addition, when crack inclination angle is lower than 30°, the third principal stress greatly influences the rock strength.

Multi-scale effect of acoustic emission characteristics of 3D rock damage

Abstract: Scale effect and acoustic emission characteristics of rock damage are two important topics in rock engineering research. In this paper, considering different rock scales and establishing the 3D numerical rock models by means of PFC software platform firstly, the mechanical properties and acoustic emission characteristics were studied. Finally, based on the acoustic emission, characteristic discussed the damage evolution law of the rock models. The research result shows that the multi-scale mainly affects the peak strength, peak strain, and elastic modulus of the mechanic properties, affects the maximum acoustic emission event number, strain range of serious acoustic emission events of the acoustic emission characteristics, affects the damage rapid increase and damage failure stages of the damage evolution process. The stress-strain curves, acoustic emission events curves, and damage variable curves can be divided into three stages and different scales have different effect on these stages.

Effect of cow manure biochar on heavy metals uptake and translocation by zucchini (Cucurbita pepo L)

Abstract: Little is known about the efficiency of biochar in the safety of food production in arid and semiarid contaminated soils. A field experiment in the semiarid region of Upper Egypt was conducted to explore heavy metals uptake by zucchini (Cucurbita pepo L) plants as affected by the application of cow manure biochar (CMB). Three rates of CMB were added, i. e., 0, 4, and 8 tonnes ha−1. The roots and shoots of zucchini plants stored 75 and 78% of Zn and Cu, respectively, while 25 and 22% were transported to the edible portions. On the other hand, the roots and shoots of zucchini plants stored more than 99% of Pb and Cd, while less than 1% was transported to the edible portions. Cow manure biochar (CMB) minimized the values of bioaccumulation factor (BAC) for Zn, Cd, and Ni by 5.6, 21.9, and 27.9%, respectively, while these reductions in the case of translocation factor (TF) were 4.9, 7.5, 23, and 5.9%. Cow manure biochar at a rate of 4 tonnes ha−1 reduced the availability of Zn, Cu, Pb, Cd, and Ni by 13.3, 8.3, 13.8, 9.1, and 3.6%, respectively, compared to the control treatment. Cow manure biochar at a rate of 8 tonnes minimized Zn, Cu, Pb, Cd, and Ni concentrations in the edible parts of zucchini plants by 10, 17, 66, 20, and 26%, respectively, in comparison with the untreated soil. Biochar reduced the heavy metals bioavailability, moreover; biochar minimized the soil-root transfer and the root-shoot of toxic metals. It is recommended to add cow manure biochar to zucchini plants to reduce the accumulating of hazard metals in the edible tissues.

Source characterization and human health risk assessment of nitrate in groundwater of middle Gangetic Plain, India

Abstract: Nitrate ( $$ {\mathrm{NO}}_3^{-} $$ ) pollution is a global concern as it affects the whole ecosystem: human, livestock, economy, and environment. The elevated levels of nitrate in groundwater can directly pose risks to population. A total of 156 representative groundwater samples were collected from groundwater sources such as hand pumps and bore wells across the study area. To identify the source of nitrate with its associated attributes, multivariate statistical methods (factor analysis (FA), sparse principal component analysis (SPCA)) were used in this study. In addition, empirical Bayesian kriging (EBK) modeling was used to predict the nitrate at ungauged locations of the study area. From the analysis of results, it was found that 5% of the groundwater samples exceeded the acceptable limit (50 mg l−1) of nitrate as specified by the World Health Organization (WHO). The first principal component (PC) indicated by the SPCA was salinity factor, which was significantly contributed by electrical conductivity followed by sulfate. The fourth PC represented the nitrate as a factor and positive loading of nitrate was strongly associated with chloride, sulfate, and calcium. The associated loading of nitrate with water quality attributes indicated that elevated level of nitrate in groundwater may be due to external sources that came through anthropogenic activity. A similar conclusion was drawn from factor analysis as well, indicating that SPCA can be applied as a new method for groundwater geochemistry. Hazard index calculations showed that infants of the study region were at a higher risk compared to the adults and children.

Effect of poultry litter biochar on chromium (Cr) bioavailability and accumulation in spinach (Spinacia oleracea) grown in Cr-polluted soil

Abstract: Chromium (Cr) pollution in soil has the greatest threat to human beings as it has a potential to enter into the food chain through contaminated soil. Chromium has no defined role in plant biology and has detrimental effects on plants. Biochar used as soil amendment has been demonstrated to diminish the bioavailability of trace elements. The current study investigated the effect of poultry litter biochar (PLB) on Cr bioavailability and its accumulation in spinach grown on Cr-contaminated soil. Data showed significant decline in bioavailable Cr concentration (DTPA-extraction) with an increasing biochar concentration, especially at 5% application rate in soil. With the 3% and 5% application of PLB, Cr concentration in shoots significantly (P < 0.05) decreased by 32% and 49%, respectively, over the control. The results showed that PLB significantly enhanced the plant growth and biomass over the control. Under Cr stress, the PLB addition increased the catalase and superoxide dismutase activities while decreased malondialdehyde and hydrogen peroxide concentrations as compared to control. Overall, it was concluded that PLB application might be effective in reducing the toxic effects of Cr in spinach and enhancing plant growth.

A slip-flow model for multi-component shale gas transport in organic nanopores

Abstract: With the rapid development of shale gas resources, the accurate simulation of shale gas development process is becoming more and more important. Shale gas transport through nanopores of shale formation is the basic of shale gas development simulation. At present, the effect of impurities on methane transport through nanopores is neglected. In this paper, a novel model is presented for simulating multi-component shale gas transport through nanopores of shale formation. The effects of multi-component, slippage flow, and Knudsen diffusion are considered in the model. Results show that when the shale gas in nanopores is very thin, the Knudsen diffusion plays the dominant role over wide range of nanopore radius. While the effect of multi-component on Knudsen number and contribution degree can be neglected, both of the slippage flow rate and the Knudsen diffusion rate increase with increasing of CO2 content. Under medium pressure condition, there exists two turning points where the slippage flow and Knudsen diffusion take turns in charge of the shale gas transmission. Under high pressure condition, the slippage flow is the dominant factor over wide range of nanopore sizes. While the conductivities increase with decreasing methane content, the effect of multi-component on contribution degrees of slippage and Knudsen diffusion can be neglected.

Aeromagnetic data for mapping geologic contacts at Samr El-Qaa area, North Eastern Desert, Egypt

Abstract: Delineating the edges of different magnetized sources represents a fundamental tool for interpreting and mapping rock boundaries of magnetic data. The present study deals with the enhancement of reduced to the pole map (RTP) of Samr El-Qaa area, North Eastern Desert, Egypt, to map deep and surface geologic contacts. The edge detection of geologic contacts is ensured by the upward continuation of reduced to the pole data at an altitude of 3 km, followed by the calculation of theta derivative and horizontal tilt angle derivative (HTAD) for RTP and upward continuation (3 km). The results obtained from the application of these techniques showed that the theta derivative delineates RTP source edges well, but the response of deeper sources is diffused. While HTAD presented well, responds to shallow and deep sources and also the edges of the sources were delineated well. HTAD showed a much sharper gradient over the edges of the magnetized sources at Samr El-Qaa area. The interpreted structural trends derived from shallow and deep Theta and HTAD maps of Samr El-Qaa territory illustrated that the most shallow dominant trends are NNE, NE, N-S, NNW, WNW, E-W and NW directions. While the deep structural ones are the ENE, NW, N-S, and E-W directions. This approach for edge detection used in this study is comprehensively applicable to other portions of the Egyptian Eastern Desert and other areas with alike geologic conditions around the world to give much sharper gradient over the edges of the magnetized sources which can be used for mineral and oil/gas exploration.

Integrated study on soil erosion using RUSLE and GIS in Yangtze River Basin of Jiangsu Province (China)

Abstract: Based on the geographical information system (GIS) and revised universal soil loss equation (RUSLE), the parameter factors are calculated by means of the observed rainfall, soil data, digital elevation model (DEM), and remote sensing (RS) image data to obtain the moduli of the soil erosion, discuss its spatial distribution characteristics, and propose the planning of soil and water conservation measures further according to the distribution of soil erosion intensity, the sandy soil and the thickness of soil layer distribution in the area along the Yangtze River in Jiangsu Province. The study results show that the total amount of soil loss in the area is 6.5 million (t a−1) approximately, the average soil erosion modulus is 3.839 (t ha−1a−1), and the total erosion area is 16,935.1km2, accounting for 33.2% of the total area along the Yangtze River in Jiangsu Province. The intensity of soil erosion is mainly micro or slight, which is distributed all over the area, with dispersed distribution on the most domain and concentrated distribution in specific part; however, severe or worse soil erosion seldom occurs, which is only scattered in the hilly and mountainous areas on the south bank of the Yangtze River and the surrounding area of the Taihu Lake if any. The soil erosion area of cultivated land is the largest, and the second one is the urban land, accounting for 49.1% and 27.4% of the total erosion area, respectively. 99.7% of the total soil erosion occurs in the areas with an elevation of less than 100 m, while 98.6% soil erosion occurs in the areas with a slope within 0–15 degree. The map of soil and water conservation measure planning is drawn, and the two most widespread measures for soil and water conservation in the study area are ecological restoration and soil conservation tillage, which are mostly concentrated in the plain area of the north of the Yangtze River with an underdeveloped economy in comparison with the south bank.

Experimental investigation on mechanical behavior and permeability evolution in coal-rock combined body under unloading conditions

Abstract: Coal-gas compound dynamic disasters remain to be unsolved, which has a huge impact on deep mining and coalbed methane (CBM) exploitation. In this research, a series of triaxial tests were conducted on gas-containing coal-sandstone combination samples under two types of unloading conditions. One is unloading confining pressure tests (UCPs), the other is unloading confining pressure-reloading axial stress tests (UCP-RAS). Simultaneously, the permeabilities in the mechanical tests were obtained. Our results demonstrated that the bearing strength decreased under unloading conditions compared to conventional triaxial compression (CTC). Mohr-Coulomb strength criterion was also applicable to gas-bearing coal-sandstone combined bodies under unloading stress paths. For gas-bearing coal-sandstone combined bodies, the peak strain in UCP and UCP-RAS was smaller than that in CTC. The lateral deformation in UCP-RAS was the largest, which showed strong dilatation characteristics. There is no significant difference between degree of damage of combined body under UCP and CTC test scheme. Under UCP-RAS condition, the coal part of combined body was more prone to present deformation and fracture, and the degree of damage was more intense. The permeability of coal-sandstone composite samples under unloading conditions was also mainly determined by the crack evolution in the rock part. Moreover, the crack evolution was synthetically affected by gas deposit condition, mining-induced stress and multiple stress paths.

Landslide susceptibility mapping of the Mediterranean coastal zone of Morocco between Oued Laou and El Jebha using artificial neural networks (ANN)

Abstract: The goal of this study was to experiment artificial neural network (ANN) classifier on various available physical factors in the study area to produce a reliable landslide susceptibility map. The mapping of landsides is classically established through the identification and analysis of hillslope instability factors. Even if a variety of approaches use these analyses with geographic information system (GIS) performances to carry out a good result, there is no satisfaction because of the complexity of the landslides encountered in the field. In the present study, landslide susceptibility models were produced by using multilayer perceptron (MLP) ANN in the Mediterranean Rif coastal zone of Morocco. This was established in the following steps: (i) production of landslide inventory map; (ii) production of the hillslope factors, twenty factors composed of geology, geomorphometry, proximity, and thematic data derived from satellite imageries; (iii) extraction of vector model to be used to train ANN, construction of ANN models; (iv) validation and evaluation of results. The results of the prediction models were evaluated by the receiver operating characteristic (ROC) curves. The obtained area under the curve (AUC) values are greater than 0.90, indicating that the models are quite accurate. The visual comparisons between landslide susceptibility maps and the input factor maps show that roads and geology are the most important factors influencing five types of mass movements (complex, slide, flow, and rockfall). The success of this work will be helpful to expand this method to the whole Rif mountains in Morocco.

Prediction of maximal water bursting discharge from coal seam floor based on multiple nonlinear regression analysis

Abstract: Aimed at the influences of various complicated factors for water inrush from a coal seam floor during coal seam mining, the prediction of the maximal water bursting discharge from a coal seam floor is regarded as a problem of pattern identification with nonlinear, high dimensions, and finite samples. Based on information fusion theory and regarding the prediction of maximal water bursting discharge from a coal seam floor as a process of multisource information fusion and state estimation, an evaluation system of the main controlling factors for predicting the maximal water bursting discharge from a coal seam floor was established. An evaluation model for forecasting the maximal water bursting discharge from a coal seam floor was also structured according to multiple nonlinear regression theory. Considering the major coal mines of Xinwen coalfield as the research background, six factors are selected as the basic discriminant factors, i.e., aquifer thickness, unit water inflow, water pressure, aquiclude thickness, fault influencing factor, and depth of a coal seam floor destroyed by rock pressure. Deng’s grey relational theory was used to analyze the correlation degrees between each main controlling factor and the maximal water bursting discharge from a coal seam floor. A structural equation model was adopted to reveal the internal connecting links among the key influencing factors and determine the weights of each main controlling factor for predicting the maximal water bursting discharge from a coal seam floor. An SPSS scatter plot and MATLAB functional programming were applied to fit the correlativity curves between each main controlling factor and the maximal water bursting discharge from a coal seam floor in the Xinwen Mining Area. The optimal unitary nonlinear regression models between the maximal water bursting discharge from the coal seam floor and each main control factor were established. A multiple nonlinear regression–modified model for predicting the maximal water bursting discharge from the coal seam floor was acquired using a multiple nonlinear regression analysis with the combined weights of each main control factor. Compared with the bivariant multiple regression equation and the measured data, the results showed that the average values of forecasting errors predicted by the multiple nonlinear regression–modified model and bivariant multiple regression equation are 10.53% and 16.76%, respectively, which indicates that the multiple nonlinear regression–modified model and the bivariant multiple regression equation have higher prediction accuracy and relatively smaller error ranges, with comparatively better application value in the prediction of maximal water bursting discharge from a coal seam floor.

Drought monitoring in the Lake Urmia basin in Iran

Abstract: Drought is a reptile phenomenon that is caused by rising temperatures and decreasing rainfall than normal. This phenomenon has a significant impact on the human lives and other organisms. We tried to study the drought status by using the MATLAB software and integrated SEPI in two 3- and 9-month scale in the lake of Urmia. For this purpose, we used the climate data of 5 synoptic stations of Lake Urmia (Tabriz, Maragheh, Urmia, Saghez, Mahabad). The findings of the study indicate that the Standardized Evapotranspiration and Precipitation Index (SEPI) reflects the characteristics of both the Standardized Precipitation Index (SPI) and Standardized Evapotranspiration Index (SEI) indicators, and also introduces the temperature as one of the effective parameters in the change of drought severity in drought conditions; therefore, the study of drought using SEPI is better than that using SPI. Drought investigation indicates that the drought trend is increasing based on SEPI in the Lake Urmia. Temperature is also increasing more intensively. The longest period of drought persistence occurred at the Urmia station on a 3-month scale from June to December 1995 to December 2016 for 24 months in the Lake Urmia basin. The highest drought incidence rate was observed at the Saghez station at the 3-month scale and the lowest in Maragheh.