Hydrogeochemical assessment of groundwater in Kashmir Valley,India

Groundwater samples (n = 163) were collected across Kashmir Valley in 2010 to assess the hydrogeochemistry of the groundwater in shallow and deep aquifers and its suitability for domestic, agriculture, horticulture, and livestock purposes. The groundwater is generally alkaline in nature. The electrical conductivity (EC) which is an index to represent the total concentration of soluble salts in water was used to measure the salinity hazard to crops as it reflects the TDS in groundwater ranging from 97 to 1385 μS/cm, except one well in Sopore. The average concentration of major ions was higher in shallow aquifers than in deeper aquifers. In general, Ca²⁺ is the dominant cation and HCO \(_{3}^{-}\) the dominant anion. Ca–HCO₃, Mg–HCO₃, Ca–Mg–HCO₃, Na–HCO₃ were the dominant hydrogeochemical facies. High concentration of HCO₃ and pH less than 8.8 clearly indicated that intense chemical weathering processes have taken place in the study area. The groundwater flow pattern in the area follows the local surface topography which not only modifies the hydrogeochemical facies but also controls their distribution. The groundwater in valley flows into four directions, i.e., SW–NE, NE–W, SE-NW and SE–NE directions. The results suggest that carbonate dissolution is the dominant source of major ions followed by silicate weathering and ion-exchange processes. The concentrations of all the major ions determined in the present study are within the permissible limits of WHO and BIS standards. The results of Total Hardness, SAR, Na%, Kelly Index, USDA classification, Magnesium absorption ratio, residual sodium carbonate, and PI suggested that groundwater is good for drinking, livestock, and irrigation purposes.     

A practical and efficient numerical scheme for the analysis of steady state unconfined seepage flows

The scaled boundary finite‐element method (SBFEM), a novel semi‐analytical technique, is applied to the analysis of the confined and unconfined seepage flow. This method combines the advantages of the finite‐element method and the boundary element method. In this method, only the boundary of the domain is discretized; no fundamental solution is required, and singularity problems can be modeled rigorously. Anisotropic and nonhomogeneous materials satisfying similarity are modeled without additional efforts. In this paper, SBFE equations and solution procedures for the analysis of seepage flow are outlined. The accuracy of the proposed method in modeling singularity problems is demonstrated by analyzing seepage flow under a concrete dam with a cutoff at heel. As only the boundary is discretized, the variable mesh technique is advisable for modeling unconfined seepage analyses. The accuracy, effectiveness, and efficiency of the method are demonstrated by modeling several unconfined seepage flow problems. Copyright © 2011 John Wiley & Sons, Ltd.     

New Criterion for Lunar Crescent Visibility

A new criterion for lunar crescent visibility has been established using 737 observations, almost half of them obtained by the Islamic Crescent Observation Project (ICOP). This criterion is based on two variables, viz. the topocentric arc of vision and the topocentric crescent width. The new model is able to predict the visibility of the lunar crescent both for naked eye and optically aided observations. From the database we found a Danjon limit of 6.4 degrees. Vice-President of “Crescents, Calendars and Mawaqeet Committee” of AUASS.     

An iteratively reweighted least-squares approach to adaptive robust adjustment of parameters in linear regression models with autoregressive and <Emphasis Type="Italic">t</Emphasis>-distributed deviations

In this paper, we investigate a linear regression time series model of possibly outlier-afflicted observations and autocorrelated random deviations. This colored noise is represented by a covariance-stationary autoregressive (AR) process, in which the independent error components follow a scaled (Student’s) t-distribution. This error model allows for the stochastic modeling of multiple outliers and for an adaptive robust maximum likelihood (ML) estimation of the unknown regression and AR coefficients, the scale parameter, and the degree of freedom of the t-distribution. This approach is meant to be an extension of known estimators, which tend to focus only on the regression model, or on the AR error model, or on normally distributed errors. For the purpose of ML estimation, we derive an expectation conditional maximization either algorithm, which leads to an easy-to-implement version of iteratively reweighted least squares. The estimation performance of the algorithm is evaluated via Monte Carlo simulations for a Fourier as well as a spline model in connection with AR colored noise models of different orders and with three different sampling distributions generating the white noise components. We apply the algorithm to a vibration dataset recorded by a high-accuracy, single-axis accelerometer, focusing on the evaluation of the estimated AR colored noise model.     

A new empirical equation for predicting the maximum initial amplitude of submarine landslide-generated waves

Landslides - The accurate prediction of landslide tsunami amplitudes has been a challenging task given large uncertainties associated with landslide parameters and often the lack of enough...     

Uncertainty quantification of landslide runout motion considering soil interdependent anisotropy and fabric orientation

Landslides - Natural soils often exhibit an anisotropic fabric pattern as a result of soil deposition, weathering, or filling. This paper aims to investigate the effect of soil interdependent...     

A probabilistic framework to make a decision on the post-earthquake functionality of bridges considering the damage,residual displacement,and aftershock

Bulletin of Earthquake Engineering - Making a decision on the post-earthquake functionality of structures has always been one of the most challenging issues in earthquake engineering. There is an...     

Reliability framework for characterizing heat wave and cold spell events

Natural Hazards - Extreme weather events such as heat waves and cold spells affect people’s lives. This study develops a probabilistic framework to evaluate heat waves and cold spells. As...     

Hydrogeochemistry and reservoir characterization of the Konya geothermal fields,Central Anatolia/Turkey

A conceptual model with water samples from ten geothermal fields (?smil, Ilg?n (Çavu?cugöl), Tuzlukçu-Ak?ehir, Seydi?ehir and Kavakköy, Hüyük, Ere?li-Akhüyük, Kad?nhan?, Cihanbeyli, Karap?nar and Bey?ehir) in the province of Konya defined the geothermal system. Carbonates, quartzite and marbles of Paleozoic metamorphics are the reservoir rocks and the heating sources are igneous rock intrusions and geothermal gradient. The variable thermal water (CaMgHCO₃, CaSO₄, NaSO₄, CaHCO₃, CaNaHCO₃, NaCl and CaNaClHCO₃) had EC and temperature between 177.8 and 56,100 μS/cm and between 18.3 and 44 °C, respectively. Ca²⁺ in geothermal fluids are associated with marble and carbonate rocks and the high chloride shows direct connection with deep geothermal system, and prolonged contact with evaporite rocks. Sulphate originates from dissolution of and oxidation of sulphate and sulphur-bearing minerals. The high As, B, F and Mn concentration in some thermal water samples were determined as 85 μg/l, 148.56 mg/l, 3.01 mg/l and 208.13 mg/l, respectively. Reservoir temperatures computed by Na/K geothermometers were between 85.37–158.89 °C for Ak?ehir thermal waters and 58.78–90.45 °C for Ere?li thermal waters. The maximum reservoir temperature of other geothermal waters was 75 °C by the silica geothermometers.