Water quality index and fractal dimension analysis of water parameters

Statistical analysis of water quality parameters were analyzed at Harike Lake on the confluence of Beas and Sutlej rivers of Punjab (India). Mean, median, mode, standard deviation, kurtosis, skewness, coefficient of variation, regression lines, correlation coefficient, Hurst exponent, fractal dimension and predictability index were estimated for each water parameter. Monthly variation of water quality index using month-wise and parameter-wise value of quality rating and actual value present in water sample was calculated and compared with World Health Organization/Environmental Protection Agency standard value of these parameters. It was observed that Brownian time series behavior exists of potential of hydrogen with total dissolved solids, hardness, alkalinity, sulfate, chloride and conductance parameters; biochemical oxygen demand with total dissolved solids, hardness, alkalinity, sulfate, chloride, conductance and calcium parameters; dissolved oxygen with total dissolved solids, hardness, alkalinity, sulfate, chloride, conductance and calcium parameters; ferrous with total dissolved solids, hardness, alkalinity, sulfate, conductance and calcium parameters; chromium with total dissolved solids, hardness, alkalinity, sulfate, chloride, conductance and zinc parameters; zinc with total dissolved solids, hardness, sulfate, chloride, conductance and calcium parameters; fluoride with total dissolved solids, hardness, alkalinity, sulfate, chloride and conductance parameters; nitrate with total dissolved solids, sulfate and conductance parameters; nitrite with potential of hydrogen, total dissolved solids, hardness, alkalinity, sulfate, chloride, conductance and calcium parameters. Also, using water quality index, it was observed that water of the lake was severely contaminated and became unfit for drinking and industrial use.     

Analysis and very short range forecast of cyclone “AILA” with radar data assimilation with rapid intermittent cycle using ARPS 3DVAR and cloud analysis techniques

In this study, both reflectivity and radial velocity are assimilated into the Weather Research and Forecasting (WRF) model using ARPS 3DVAR technique and cloud analysis procedure for analysis and very short range forecast of cyclone ÁILA. Doppler weather radar (DWR) data from Kolkata radar are assimilated for numerical simulation of landfalling tropical cyclone. Results show that the structure of cyclone AILA has significantly improved when radar data is assimilated. Radar reflectivity data assimilation has strong influence on hydrometeor structures of the initial vortex and precipitation pattern and relatively less influence is observed on the wind fields. Divergence/convergence conditions over cyclone inner-core area in the low-to-middle troposphere (600–900 hPa) are significantly improved when wind data are assimilated. However, less impact is observed on the moisture field. Analysed minimum sea level pressure (SLP) is improved significantly when both reflectivity and wind data assimilated simultaneously (RAD-ZVr experiment), using ARPS 3DVAR technique. In this experiment, the centre of cyclone is relocated very close to the observed position and the system maintains its intensity for longer duration. As compared to other experiments track errors are much reduced and predicted track is very much closer to the best track in RAD-ZVr experiment. Rainfall pattern and amount of rainfall are better captured in this experiment. The study also reveals that cyclone structure, intensification, direction of movement, speed and location of cyclone are significantly improved and different stages of system are best captured when both radar reflectivity and wind data are assimilated using ARPS 3DVAR technique and cloud analysis procedure. Thus optimal impact of radar data is realized in RAD-ZVr experiment. The impact of DWR data reduces after 12 h forecast and it is due to the dominance of the flow from large-scale global forecast system model. Successful coupling of data assimilation package ARPS 3DVAR with WRF model for Indian DWR data is also demonstrated.     

Groundwater appraisal of Dhekiajuli,Assam, India: an insight of agricultural suitability and arsenic enrichment

The present work is an effort to develop an appraisal of the hydrogeochemical regime for the aquifers of Dhekiajuli, Sonitpur district, Assam, which is imperative considering: (i) excessive use of groundwater for irrigation; (ii) reported high arsenic (As) contamination; (iii) application of fertilizer is an inevitable process undergoing in this region to achieve higher yield owing to deteriorating water quality; and (iv) study area being the location of many tea estates of Assam, that export tea in many foreign countries. The highest As concentration of 44.39 µg/L was detected in this study (Bachasimalu and Sitalmari region), implying high As-contaminated aquifers being used for drinking and irrigation purposes in the area. The relative abundance pattern of major cations and anions was in the order of Na⁺ > Mg²⁺ > Ca²⁺ > K⁺ and HCO₃ ^? > Cl^? > SO₄ ^2?, respectively. Majority of the samples belong to Na⁺–K⁺–Cl^?–HCO₃ ^? and mixed water type. Closer inspection of Piper plot reveals that a higher As value (>40 µg/L) was prevalent in HCO₃ ^? water type. Results of hydrogeochemical plots suggest silicate and carbonate weathering, ion exchange and anthropogenic activities to be the dominant processes governing groundwater contamination, including As which is further supported from PCA loadings. The Singri area to the east of the affected areas and adjacent to the Brahmaputra River has oxic aquifers owing to the absence of mass deposition of younger sediments, while reducing conditions prevails in the Bachasimalu and Sitalmari region. High positive correlation between As and Fe (r = 0.83**) and a negative correlation between ORP and Fe (r = ?0.68**) further add that Fe (hydr)oxides are the direct source of As release in the affected region, the mechanism being reductive hydrolysis of such (hydr)oxides. The study implies that although groundwater is suitable for irrigation use, there is a high probability of As getting into the food chain through tea and other edible plants irrigated with As-contaminated water; thus, the area has a maximum probability of facing health hazards caused by As-contaminated groundwater.