Estimating groundwater vulnerability to pollution using a modified DRASTIC model in the Kerman agricultural area,Iran

Groundwater contamination from intensive fertilizer application affects conservation areas in a plain. The DRASTIC model can be applied in the evaluation of groundwater vulnerability to such pollution. The main purpose of using the DRASTIC model is to map groundwater susceptibility to pollution in different areas. However, this method has been used in various areas without modification, thereby disregarding the effects of pollution types and their characteristics. Thus, this technique must be standardized and be approved for applications in aquifers and particular types of pollution. In this study, the potential for the more accurate assessment of vulnerability to pollution is achieved by correcting the rates of the DRASTIC parameters. The new rates were calculated by identifying the relationships among the parameters with respect to the nitrate concentration in groundwater. The methodology was implemented in the Kerman plain in the southeastern region of Iran. The nitrate concentration in water from underground wells was tested and analyzed in 27 different locations. The measured nitrate concentrations were used to associate and correlate the pollution in the aquifer to the DRASTIC index. The Wilcoxon rank-sum nonparametric statistical test was applied to determine the relationship between the index and the measured pollution in Kerman plain. Also, the weights of the DRASTIC parameters were modified through the sensitivity analysis. Subsequently, the rates and weights were computed. The results of the study revealed that the modified DRASTIC model performs more efficiently than the traditional method for nonpoint source pollution, particularly in agricultural areas. The regression coefficients showed that the relationship between the vulnerability index and the nitrate concentration was 82 % after modification and 44 % before modification. This comparison indicated that the results of the modified DRASTIC of this region are better than those of the original method.     

Conjunctive use of surface water and groundwater via the bank infiltration method

The bank infiltration (BI) technique may be a viable option if the local climate, hydrological, and geological conditions are conducive. This study was specifically conducted to explore the possibility of using BI to source the polluted surface water in conjunction with groundwater. Three major factors were considered for evaluation: (1) investigation on the contribution of surface water through BI, (2) input of local groundwater, and (3) water quality characteristics of water supply. Initially, the geophysical method was employed to define the subsurface geology and hydrogeology, and isotope techniques were performed to identify the source of groundwater recharge and interaction between surface water and groundwater. The physicochemical and microbiological parameters of the local surface water bodies and groundwater were analyzed before and during water abstraction. Extracted water revealed a 5 %–98 % decrease in turbidity, as well as HCO₃ ⁺, SO₄ ^?, NO₃ ^?, Al, As, and Ca concentration reduction compared with those of Langat river water. However, water samples from test wells during pumping show high concentrations of Fe²⁺ and Mn²⁺. In addition, amounts of Escherichia coli, total coliform, and Giardia were significantly reduced (99.9 %). Pumping test results indicate that the two wells (DW1 and DW2) were able to sustain yields.     

Estimation of air-overpressure produced by blasting operation through a neuro-genetic technique

Blasting operations usually produce significant environmental problems which may cause severe damage to the nearby areas. Air-overpressure (AOp) is one of the most important environmental impacts of blasting operations which needs to be predicted and subsequently controlled to minimize the potential risk of damage. In order to solve AOp problem in Hulu Langat granite quarry site, Malaysia, three non-linear methods namely empirical, artificial neural network (ANN) and a hybrid model of genetic algorithm (GA)–ANN were developed in this study. To do this, 76 blasting operations were investigated and relevant blasting parameters were measured in the site. The most influential parameters on AOp namely maximum charge per delay and the distance from the blast-face were considered as model inputs or predictors. Using the five randomly selected datasets and considering the modeling procedure of each method, 15 models were constructed for all predictive techniques. Several performance indices including coefficient of determination (R ²), root mean square error and variance account for were utilized to check the performance capacity of the predictive methods. Considering these performance indices and using simple ranking method, the best models for AOp prediction were selected. It was found that the GA–ANN technique can provide higher performance capacity in predicting AOp compared to other predictive methods. This is due to the fact that the GA–ANN model can optimize the weights and biases of the network connection for training by ANN. In this study, GA–ANN is introduced as superior model for solving AOp problem in Hulu Langat site.     

Hydrochemical investigation and quality assessment of ground water in rural areas of Delhi,India

The suitability of groundwater quality for drinking and agricultural purposes was assessed in the rural areas of Delhi based on the various water quality parameters. A total of 50 ground water samples were collected randomly from different sources viz. hand pump, tube well, boring and analyzed for major ion chemistry to understand the operating mechanism of geochemical processes for ground water quality. The quality analysis is performed through the estimation of pH, EC, TDS, total hardness, total alkalinity, Na, K, Cl, NO₃, SO₄, DO, BOD, Cu, Cr, Cd, Ni, Zn and Pb. Hydrochemical facies were identified using Piper, Durov and Chadha diagram. Chemical data were also used for mathematical calculations (SAR, %Na, RSC, PI, KI, and chloroalkaline indices) for better understanding the suitability of ground water for irrigation purposes. The results of saturation index shows that all the water samples were supersaturated to undersaturated with respect to carbonate minerals and undersaturated with respect to sulphate and chloride minerals. According to USSL diagram, most of the samples fall in the field of C₃S₁, indicating medium salinity and low sodium water which can be used for almost all types of soil with little danger of exchangeable sodium. Assessment of water samples from various methods indicated that majority of the ground water in the study area is chemically suitable for drinking and agricultural uses.     

Bioenergy consumption and economic growth in the EU-28 region: evidence from a panel cointegration model

GeoJournal - The purpose of this research is to examine the correlation between the bioenergy industry and economic outgrowth. This study investigates the growth hypothesis within the setting of...     

Assessment of spatial variations in water quality of Garra River at Shahjahanpur,Ganga Basin,India

Arabian Journal of Geosciences - A comprehensive study on the chemical considerations of thermal waters (springs and geothermal wells) on the performance of solute geothermometers in predicting the...