Integrated approach for identification of potential groundwater zones in Seethanagaram Mandal of Vizianagaram District,Andhra Pradesh,India

Identifying a good site for groundwater exploration in hard rock terrain is a challenging task. In hard rocks, groundwater occurs in secondary porosity developed due to weathering, fracturing, faulting, etc., which is highly variable within short distance and contributing to near-surface inhomogeneity. In such situations topographic, hydrogeological and geomorphological features provide useful clues for the selection of suitable sites. Initially, based on satellite imagery, topographical, geomorphological and hydrogeological features, an area of about 149 km² was demarcated as a promising zone for groundwater exploration in the hard rock tract of Seethanagaram Mandal, Vizianagaram District, Andhra Pradesh, India. A total of 50 Vertical Electrical Soundings (VES) were carried out using Wenner electrode configuration. An interactive interpretation of the VES data sharpened the information inferred from geomorphological and hydrogeological reconnaissance. Ten sites were recommended for drilling. Drilling with Down-The-Hole Hammer (DTH) was carried out at the recommended sites down to 50 to 70 m depths. The interpreted VES results matched well with the drilled bore well lithologs. The yields of bore wells vary from 900 to 9000 liters per hour (lph).     

Deciphering potential groundwater zone in hard rock through the application of GIS

Remote Sensing and Geographic Information System has become one of the leading tools in the field of hydrogeological science, which helps in assessing, monitoring and conserving groundwater resources. It allows manipulation and analysis of individual layer of spatial data. It is used for analysing and modelling the interrelationship between the layers. This paper mainly deals with the integrated approach of Remote Sensing and geographical information system (GIS) to delineate groundwater potential zones in hard rock terrain. The remotely sensed data at the scale of 1:50,000 and topographical information from available maps, have been used for the preparation of ground water prospective map by integrating geology, geomorphology, slope, drainage-density and lineaments map of the study area. Further, the data on yield of aquifer, as observed from existing bore wells in the area, has been used to validate the groundwater potential map. The final result depicts the favourable prospective zones in the study area and can be helpful in better planning and management of groundwater resources especially in hard rock terrains.     

Rice is a major exposure route for arsenic in Chakdaha block,Nadia district,West Bengal,India: A probabilistic risk assessment

The importance or otherwise of rice as an exposure pathway for As ingestion by people living in Bengal and other areas impacted by hazardous As-bearing groundwaters is currently a matter of some debate. Here this issue is addressed by determining the overall increased cancer risk due to ingestion of rice in an As-impacted district of West Bengal. Human target cancer health risks have been estimated through the intake of As-bearing rice by using combined field, laboratory and computational methods. Monte Carlo simulations were run following fitting of model probability curves to measured distributions of (i) As concentration in rice and drinking water and (ii) inorganic As content of rice and fitting distributions to published data on (i) ingestion rates and (ii) body weight and point estimates on bioconcentration factors, exposure duration and other input variables. The distribution of As in drinking water was found to be substantially lower than that reported by previous authors for As in tube wells in the same area, indicating that the use of tube well water as a proxy for drinking water is likely to result in human health risks being somewhat overestimated. The calculated median increased lifetime cancer risk due to cooked rice intake was 7.62 × 10⁻⁴, higher than the 10⁻⁴–10⁻⁶ range typically used by the USEPA as a threshold to guide determination of regulatory values and similar to the equivalent risk from water intake. The median total risk from combined rice and water intake was 1.48 × 10⁻³. The contributions to this median risk from drinking water, rice and cooking of rice were found to be 48%, 44% and 8%, respectively. Thus, rice is a major potential source of As exposure in the As-affected study areas in West Bengal and the most important exposure pathway for groups exposed to low or no As in drinking water.     

Is the interdecadal variation of the summer rainfall over eastern China associated with SST?

The present study examined the major features of the interdecadal variation of the summer rainfall over eastern China (IVRC) and the possible association with sea surface temperature (SST). We noted that the first leading mode of IVRC (accounting for nearly half of the total variance and with maximum loading for the summer rainfall anomalies over South China) may be not forced by SST. On the other hand, the second and third leading modes [accounting for 17.1 and 13.6 % of the total variance and mainly associated with the summer rainfall anomalies over the Yangtze River valley (YRV) and North China, respectively] in some extent are forced by SST anomalies. These observational results are confirmed by atmospheric general circulation model (AGCM) simulations forced by observed SST. By eliminating the internal dynamical process driven rainfall though ensemble mean, the simulations further suggest an overall enhancement of the intensity of IVRC in the corresponding ensemble mean, especially in the YRV and North China regions, but not in South China. That implies the different role of SST in driving IVRC over different regions.     

Multiple statistical approaches for the discrimination of mangrove species of Rhizophoraceae using transformed field and laboratory hyperspectral data

This study aims at discriminating eight mangrove species of Rhizophoraceae family of Indian east coast using field and laboratory spectra in spectral range (350–2500 nm). Parametric and non-parametric statistical analyses were applied on spectral data in four spectral modes: (i) reflectance (ii) continuum removed, (iii) additive inverse and (iv) continuum removed additive inverse. We introduced continuum removal of inverse spectra to utilize the advantage of continuum removal in reflectance region. Non-parametric test gave better separability than parametric test. Principal component analysis and stepwise discriminant analysis were applied for feature reduction and to identify optimal wavelengths for species discrimination. To quantify the separability, Jeffries–Matusita distance measure was derived. Green (550 nm), red edge (680–720 nm) and water absorption region (1470 and 1850 nm) were found to be optimal wavelengths for species discrimination. The continuum removal of additive inverse spectra gave better separability than the continuum removed spectra.     

Electrical analogy for modelling thermal regime and moisture distribution in sandy soils

The soil mass is subjected to temperature variation due to several human activities (viz. tanks storing heated fluids, buried cables and pipelines, air-conditioning ducts, disposal of nuclear and thermal power plant wastes etc.), which result in heat-induced migration of the moisture in it. Though several studies have been conducted in the past to investigate the mechanism of heat migration through the soil mass, a methodology for ‘real-time measurement of the variations in temperature, flux and moving moisture front, in tandem, with respect to space' has rarely been attempted. In this context, extensive laboratory investigations were conducted to measure real-time flux and temperature variations in the sandy soils, and the validation of results has been done by employing an equivalent electrical circuit programme, LTspice. Subsequently, a mathematical model PHITMDS (i.e. Prediction of Heat-Induced Temperature and Moisture Distribution in Soil) has been developed and its utility and efficacy, for predicting the depth-wise temperature and heat-induced moisture migration, due to evaporation, in terms of position of moving moisture front in the sandy soil has been critically discussed and demonstrated.     

RS & GIS-based landslide susceptibility mapping of the Balason River basin,Darjeeling Himalaya,using logistic regression (LR) model

The present study deals with the preparation of a landslide susceptibility map of the Balason River basin, Darjeeling Himalaya, using a logistic regression model based on Geographic Information System and Remote Sensing. The landslide inventory map was prepared with a total of 295 landslide locations extracted from various satellite images and intensive field survey. Topographical maps, satellite images, geological, geomorphological, soil, rainfall and seismic data were collected, processed and constructed into a spatial database in a GIS environment. The chosen landslide-conditioning factors were altitude, slope aspect, slope angle, slope curvature, geology, geomorphology, soil, land use/land cover, normalised differential vegetation index, drainage density, lineament number density, distance from lineament, distance to drainage, stream power index, topographic wetted index, rainfall and peak ground acceleration. The produced landslide susceptibility map satisfied the decision rules and ?2 Log likelihood, Cox &; Snell R-Square and Nagelkerke R-Square values proved that all the independent variables were statistically significant. The receiver operating characteristic curve showed that the prediction accuracy of the landslide probability map was 96.10%. The proposed LR method can be used in other hazard/disaster studies and decision-making.