Late-Quaternary miliolite (biogenic carbonate) deposits and their implications for sea-level fluctuations and climatic variability

The western coast of India (Kachchh) has ubiquitous preservations of Quaternary carbonate deposits popularly known as “miliolites”. Field-based detail documentation of the nature and distribution of miliolites supported by sedimentology and scanning electron microscopy (SEM) microtextural studies indicates that the miliolites were primarily deposited by wind as aeolinites and are termed “primary miliolites (PM)”. These were subsequently fluvially eroded and deposited and such deposits are termed “secondary miliolites (SM)”. The PM are dated between 28 ka to 16 ka largely clustering around the Last Glacial Maxima (LGM). In comparison, the fluvially reworked SM occurs as valley-fill deposits and were deposited episodically during 23 ka to 10 ka before present. Climatically, the deposition of PMs suggests enhanced aridity whereas SMs represent episodic strengthening of the Indian Summer Monsoon (ISM). The bedding attitudes of the PMs indicate that they were deposited predominantly by the northeasterly winds whereas the presence of the deflation lag deposits suggests downwind migration of sands during the equilibrium condition (reduced sediment supply). The aeolian parameters (based on the grain size and wind velocities) for PMs indicate high shear velocity (~23 to 48 cm⁻¹) and high transport rate (< 0.1 to 0.2 g/cm s). The short average flying distance implies that the biogenic sands were transported in multiple pulses (from coast to inland) at rates varying from ~200 m/h to ~1 km/h. Comparing our data with related occurrences along the biologically productive coasts in the mid-latitudinal belt indicates that the regional/global aridity during the lowered sea level was responsible for inland occurrences of aeolinites, particularly during the LGM. The strengthened northeast monsoon winds during the LGM was conducive to upwelling and production of biogenic carbonates along the coasts. The subsequent reworking of the aeolinites were mainly the results of local variability in precipitation.     

Assimilation of snow covered area information into hydrologic and land-surface models

This paper describes a data assimilation method that uses observations of snow covered area (SCA) to update hydrologic model states in a mountainous catchment in Colorado. The assimilation method uses SCA information as part of an ensemble Kalman filter to alter the sub-basin distribution of snow as well as the basin water balance. This method permits an optimal combination of model simulations and observations, as well as propagation of information across model states. Sensitivity experiments are conducted with a fairly simple snowpack/water-balance model to evaluate effects of the data assimilation scheme on simulations of streamflow. The assimilation of SCA information results in minor improvements in the accuracy of streamflow simulations near the end of the snowmelt season. The small effect from SCA assimilation is initially surprising. It can be explained both because a substantial portion of snowmelts before any bare ground is exposed, and because the transition from 100% to 0% snow coverage occurs fairly quickly. Both of these factors are basin-dependent. Satellite SCA information is expected to be most useful in basins where snow cover is ephemeral. The data assimilation strategy presented in this study improved the accuracy of the streamflow simulation, indicating that SCA is a useful source of independent information that can be used as part of an integrated data assimilation strategy.     

Ground water potential in fractured aquifers of Ophiolite formations,Port Blair,South Andaman Islands using Electrical Resistivity Tomography (ERT) and Vertical Electrical Sounding (VES)

Ground water occurs in weathered formations of unsaturated zone and fractured rocks of saturated zone. The ground water occurring in the unsaturated zone is not sustainable while the ground water occurring in the fractured rocks are sustainable if properly exploited. But, targeting the productive fractured rocks needs careful evaluation and systematic approach of geophysical survey owing to the heterogeneity, magmatic and metamorphic activities of multiple episodes of rocks. Hence, judicious planning in ground water exploration is warranted because of the huge money involved in drilling, manpower and time factor. In this context, an attempt has been made to locate the fractured rocks of ground water potential in the Ophiolite formations of Port Blair, South Andaman Islands using Electrical Resistivity Tomography (ERT) and Vertical Electrical Soundings (VES) since the ground water database of Andaman and Nicobar islands is poor as not much work has been carried out so far and the ground water is not properly utilised. The ERT have been carried out along different azimuth of fractures to ascertain the resistivities in vertical and horizontal direction and the conductivity and/or the resistivity of the varied fractures was also evaluated by spot VES. The 2-D Electrical Resistivity Images in conjunction with the geoelectrical parameters brought out by VES revealed that E-W fractures are expected to be productive fractures showing more conductivity as it is compared with the NE-SW and NW-SE fractures. The potentiality of the E-W fractures was also validated with the borehole data.     

A new ensemble-based data assimilation algorithm to improve track prediction of tropical cyclones

This paper proposes a new ensemble-based algorithm that assimilates the vertical rain structure retrieved from microwave radiometer and radar measurements in a regional weather forecast model, by employing a Bayesian framework. The goal of the study is to evaluate the capability of the proposed technique to improve track prediction of tropical cyclones that originate in the North Indian Ocean. For this purpose, the tropical cyclone Jal has been analyzed by the community mesoscale weather model, weather research and forecasting (WRF). The ensembles of prognostic variables such as perturbation potential temperature (θ, k), perturbation geopotential (?, m²/s²), meridional (U) and zonal velocities (V) and water vapor mixing ratio (q _v , kg/kg) are generated by the empirical orthogonal function technique. An over pass of the tropical rainfall-measuring mission (TRMM) satellite occurred on 06th NOV 0730 UTC over the system, and the observations from the radiometer and radar on board the satellite(1B11 data products) are inverted using a combined in-home radiometer-radar retrieval technique to estimate the vertical rain structure, namely the cloud liquid water, cloud ice, precipitation water and precipitation ice. Each ensemble is input as a possible set of initial conditions to the WRF model from 00 UTC which was marched in time till 06th NOV 0730 UTC. The above-mentioned hydrometeors from the cloud water and rain water mixing ratios are then estimated for all the ensembles. The Bayesian filter framework technique is then used to determine the conditional probabilities of all the candidates in the ensemble by comparing the retrieved hydrometeors through measured TRMM radiances with the model simulated hydrometeors. Based on the posterior probability density function, the initial conditions at 06 00 UTC are then corrected using a linear weighted average of initial ensembles for the all prognostic variables. With these weighted average initial conditions, the WRF model has been run up to 08th Nov 06 UTC and the predictions are then compared with observations and the control run. An ensemble independence study was conducted on the basis of which, an optimum of 25 ensembles is arrived at. With the optimum ensemble size, the sensitivity of prognostic variables was also analyzed. The model simulated track when compared with that obtained with the corrected set of initial conditions gives better results than the control run. The algorithm can improve track prediction up to 35 % for a 24 h forecast and up to 12 % for a 54 h forecast.     

Geochemical characteristics and controlling factors of chemical composition of groundwater in a part of Guntur district,Andhra Pradesh,India

A survey on quality of groundwater was carried out for assessing the geochemical characteristics and controlling factors of chemical composition of groundwater in a part of Guntur district, Andhra Pradesh, India, where the area is underlain by Peninsular Gneissic Complex. The results of the groundwater chemistry show a variation in pH, EC, TDS, Ca²⁺, Mg²⁺, Na⁺, K⁺, HCO₃ ^?, Cl^?, SO₄ ^2?, NO₃ ^? and F^?. The chemical composition of groundwater is mainly characterized by Na⁺?HCO₃ ^? facies. Hydrogeochemical type transits from Na⁺–Cl^?–HCO₃ ^? to Na⁺–HCO₃ ^?–Cl^? along the flow path. Graphical and binary diagrams, correlation coefficients and saturation indices clearly explain that the chemical composition of groundwater is mainly controlled by geogenic processes (rock weathering, mineral dissolution, ion exchange and evaporation) and anthropogenic sources (irrigation return flow, wastewater, agrochemicals and constructional activities). The principal component (PC) analysis transforms the chemical variables into four PCs, which account for 87% of the total variance of the groundwater chemistry. The PC I has high positive loadings of pH, HCO₃ ^?, NO₃ ^?, K⁺, Mg²⁺ and F^?, attributing to mineral weathering and dissolution, and agrochemicals (nitrogen, phosphate and potash fertilizers). The PC II loadings are highly positive for Na⁺, TDS, Cl^? and F^?, representing the rock weathering, mineral dissolution, ion exchange, evaporation, irrigation return flow and phosphate fertilizers. The PC III shows high loading of Ca²⁺, which is caused by mineral weathering and dissolution, and constructional activities. The PC IV has high positive loading of Mg²⁺ and SO₄ ^2?, measuring the mineral weathering and dissolution, and soil amendments. The spatial distribution of PC scores explains that the geogenic processes are the primary contributors and man-made activities are the secondary factors responsible for modifications of groundwater chemistry. Further, geochemical modeling of groundwater also clearly confirms the water–rock interactions with respect to the phases of calcite, dolomite, fluorite, halite, gypsum, K-feldspar, albite and CO₂, which are the prime factors controlling the chemistry of groundwater, while the rate of reaction and intensity are influenced by climate and anthropogenic activities. The study helps as baseline information to assess the sources of factors controlling the chemical composition of groundwater and also in enhancing the groundwater quality management.     

Transfer function noise modelling of groundwater level fluctuation using threshold rainfall-based binary-weighted parameter estimation approach

Considerable uncertainty occurs in the parameter estimates of traditional rainfall–water level transfer function noise (TFN) models, especially with the models built using monthly time step datasets. This is due to the equal weights assigned for rainfall occurring during both water level rise and water level drop events while estimating the TFN model parameters using the least square technique. As an alternative to this approach, a threshold rainfall-based binary-weighted least square method was adopted to estimate the TFN model parameters. The efficacy of this binary-weighted approach in estimating the TFN model parameters was tested on 26 observation wells distributed across the Adyar River basin in Southern India. Model performance indices such as mean absolute error and coefficient of determination values showed that the proposed binary-weighted approach of fitting independent threshold-based TFN models for water level rise and water level drop scenarios considerably improves the model accuracy over other traditional TFN models.

EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR A. Fiori     

A novel wavelet approximation method for the solution of nonlinear differential equations with variable coefficients arising in astrophysics

Lane-Emden type equations are well known model equations for the singular nonlinear boundary value problem that arise in the field of astrophysics. In this paper, a new method incorporated by the Legendre wavelet operational matrix of derivatives and block-pulse function approximation is adopted to investigate the solution of Lane-Emden type equations. Illustrative examples are given to demonstrate the simplicity and effectiveness of the proposed method. The obtained results are compared with other available results.