Macroscale hydrological modelling approach for study of large scale hydrologic impacts under climate change in Indian river basins

In climate‐change studies, a macroscale hydrologic model (MHM) operating over large scales can be an important tool in developing consistent hydrological variability estimates over large basins. MHMs, which can operate at coarse grid resolutions of about 1° latitude by longitude, have been used previously to study climate change impacts on the hydrology of continental scale or global river basins. They can provide a connection between global atmospheric models and water resource systems on large spatial scales and long timescales. In this study, the variable infiltration capacity (VIC) MHM is used to study large scale hydrologic impacts of climate change for Indian river basins. Large‐scale changes in runoff, evapotranspiration and soil moisture for India, as well as station‐scale changes in discharges for three major river basins with distinct climatic and geographic characteristics are examined in this study. Climate model projections for meteorological variables (precipitation, temperature and wind speed) from three general circulation models (GCMs) and three emissions scenarios are used to drive the VIC MHM. GCM projections are first interpolated to a 1° by 1° hydrologic model grid and then bias‐corrected using a quantile–quantile mapping. The VIC model is able to reproduce observed statistics for discharges in the Ganga, Narmada and Krishna basins reasonably well, even at the coarse grid resolution employed using a calibration period for years 1965–1970 and testing period from 1971–1973/1974. An increasing trend is projected for summer monsoon surface runoff, evapotranspiration and soil moisture in most central Indian river basins, whereas a decrease in runoff and soil moisture is projected for some regions in southern India, with important differences arising from GCM and scenario variability. Discharge statistics show increases in mid‐flow and low flow at Farakka station on Ganga River, increased high flows at Jamtara station upstream of Narmada, and increased high, mid‐flow and low flow for Vijayawada station on Krishna River in the future. Copyright © 2013 John Wiley & Sons, Ltd.     

Assessment of genotoxic and humoral immune system alterations in silica exposed workers from pottery industries in South India

Chemicals, especially silica, have been suspected to cause genetic alterations in pottery industry workers. The present study aims to analyze the frequency of chromosomal aberrations (CA), micronucleus (MN) and DNA damage (comet assay) in the peripheral blood lymphocytes and the immunological alterations workers chronically exposed to silica and in control subjects. In our study, 50 silica exposed workers and 35 control subjects were recruited and silica level was measured by respirable dust and respirable quartz concentrations of badge dosimeter. The serum immunoglobulins (IgM, IgG, and IgA) of all the subjects were measured by using ELISA method. The individuals exposed to silica have a significant increase in the frequency of CA, MN and the total DNA damage (p < 0.05). Immunoglobulin elevation on silica exposed workers was statistically significant (p < 0.05) on comparison with their respective controls. Investigation of the smoking and alcohol habitats coupled with silica exposure in exposed and control subjects represents alcohol consumption and smoking as additional risk factors and must be avoided. Multiple linear regression analysis obtained for CA, MN and comet assay confirm these tests as biomarkers for silica exposed pottery workers. Some confounding factors also showed significant influence on exposed subjects. These results indicate the mutagenic risk in the working environment has a high probability of association with the silica dust exposure in pottery industries. Nevertheless, the present study will create awareness and public concern not only among the silica exposed workers but also to the welfare of their progeny.     

RESOURCESAT-1 LISS-4 MX bands onground co-registration by in-flight calibration and attitude refinement

RESOURCESAT-1 satellite was launched in October of 2003. Since then it has been consistently providing high quality 5 m monochromatic and multispectral images of same resolution. LISS-4 MX sensor has complex acquisition geometry. It operates in three spectral bands imaged by 3 CCD arrays, which are separated by a finite time in imaging along the satellite track direction. Individual band data is acquired at different times while the satellite is driven by a pre-determined yaw profile. In addition, the odd–even pixels are too shifted by a small fixed delay in time. A unique challenge in LISS-4 MX Level-2 data processing sub-system is to autonomously rectify and additionally co-register the three bands data because of the influence of orbit and attitude in the time gap in the imaging sequence. In this paper, authors bring out details of in-flight calibration arrived for LISS-4 MX sensor. It addresses parameterization of co-registration problem by doing sensitivity analysis of the geometric model parameters to achieve co-registration among all bands. This approach can also be used for other sensor system having similar imaging geometry to achieve improved image co-registration among bands.     

Development of fragility functions as a damage classification/prediction method for steel moment‐resisting frames using a wavelet‐based damage sensitive feature

Fragility functions are commonly used in performance‐based earthquake engineering for predicting the damage state of a structure subjected to an earthquake. This process often involves estimating the structural damage as a function of structural response, such as the story drift ratio and the peak floor absolute acceleration. In this paper, a new framework is proposed to develop fragility functions to be used as a damage classification/prediction method for steel structures based on a wavelet‐based damage sensitive feature (DSF). DSFs are often used in structural health monitoring as an indicator of the damage state of the structure, and they are easily estimated from recorded structural responses. The proposed framework for damage classification of steel structures subjected to earthquakes is demonstrated and validated with a set of numerically simulated data for a four‐story steel moment‐resisting frame designed based on current seismic provisions. It is shown that the damage state of the frame is predicted with less variance using the fragility functions derived from the wavelet‐based DSF than it is with fragility functions derived from an alternate acceleration‐based measure, the spectral acceleration at the first mode period of the structure. Therefore, the fragility functions derived from the wavelet‐based DSF can be used as a probabilistic damage classification model in the field of structural health monitoring and an alternative damage prediction model in the field of performance‐based earthquake engineering. Copyright © 2011 John Wiley & Sons, Ltd.     

Chemical weathering and carbon dioxide consumption in a small tropical river catchment,southwestern India

Aquatic Geochemistry - Studies done on small tropical west-flowing river catchments located in the Western Ghats in southwestern India have suggested very intense chemical weathering rates and...     

Assessment of various parameters on 3D semantic object-based point cloud labelling on urban LiDAR dataset

Semantic labelling of LiDAR point cloud is critical for effective utilization of 3D points in numerous applications. 3D segmentation, incorporation of ancillary data, feature extraction and classification are the key stages in object-based point cloud labelling. The choice of algorithms and tuning parameters adopted in these stages has substantial impact on the quality of results from object-based point cloud labelling. This paper critically evaluates the performance of object-based point cloud labelling as a function of different 3D segmentation approaches, incorporation of spectral data and computational complexity of the point cloud. The designed experiments are implemented on the datasets provided by the ISPRS and the results are independently validated by the ISPRS. Results indicate that aggregation of dense point cloud into higher-level object analogue (e.g. supervoxels) before 3D segmentation stage offers superior labelling results and best computational performance compared to the popular surface growing-based approaches.     

Bacterial contribution to mitigation of iron and manganese in mangrove sediments

The Mandovi and Chapora are two tropical estuaries lying in close geographic proximity on the west coast of India. Seasonal changes in down core variation of Fe, Mn and Total Organic Carbon (TOC) in the mangrove sediments adjoining these estuaries were studied to assess their influence on some of the representative benthic bacteria belonging to heterotrophic and autotrophic groups. Heterotrophic bacteria (HB) cultured on different nutrient concentrations (0.01%, 0.1% and 25%) together with nitrifiers (NtB; representating autotroph) were chosen to assess the influence of the above-mentioned abiotic parameters on the former. The experimental site located along the Mandovi is under the influence of extensive ferromanganese ore mining, while the control site at Chapora is relatively free from such influences. Geoaccumulation index computed for Mandovi showed that sediments (0-10cm) were 'uncontaminated to moderately contaminated' by Fe during the pre monsoon and monsoon seasons, while in the post monsoon season the 4-10cm fraction was almost completely restored from contamination. Similar computations for Mn showed that in pre monsoon, sediments fell in the 'moderately contaminated' and 'moderately to strongly contaminated' categories, while in the monsoon and post monsoon seasons all the sections were 'Uncontaminated'. The difference observed in correlation between Fe and Mn with the various fractions of heterotrophs and nitrifiers indicated that though these two elements shared a similar chemistry in the environment, microbes involved in biogeochemical processes might prefer them differentially. The relationship between TOC and HB enumerated on 0.01% dilute nutrient agar remained at r=0.50, p<0.05 throughout the year. Hence, it could be apparently linked to their preferred concentration of organic carbon requirement. A relationship of r=0.61, p<0.01 between manganese concentration and heterotrophs recovered on different strengths of nutrient agar is suggestive of their response to the metal enrichment. They could thus contribute towards maintaining the level of Mn at par with reference levels at Chapora. A positive correlation between Mn with NtB (n=10, p<0.05, r=0.58) at the experimental site during the non-monsoon months is suggestive of the latter's contribution to regulation of the metal concentration in the sediment probably through anaerobic nitrification at the expense of manganese. The study therefore supports our hypothesis that both autochthonous autotrophs and heterotrophs work in tandem to mitigate concentration of Mn and related metals in mangrove sediments.     

Automatic Tree Identification and Diameter Estimation Using Single Scan Terrestrial Laser Scanner Data in Central Indian Forests

Forest inventory parameters, primarily tree diameter and height, are required for several management and planning activities. Currently, Terrestrial Laser Scanning (TLS) is a promising technology in automated measurements of tree parameters using dense 3D point clouds. In comparison with conventional manual field inventory methods, TLS systems would supplement field data with detailed and relatively higher degree of accurate measurements and increased measurement frequency. Although, multiple scans from TLS captures more area, they are resource and time consuming to ensure proper co-registration between the scans. On the other hand, Single scans provide a fast and recording of the data but are often affected by occlusions between the trees. The current study evaluates potential of single scan TLS data to (1) develop an automatic method for tree stem identification and diameter estimation (diameter at breast height—DBH) using random sample consensus (RANSAC) based circle fitting algorithm, (2) validate using field based measurements to derive accuracy estimates and (3) assess the influence of distance to scanner on detection and measurement accuracies. Tree detection and diameter measurements were validated for 5 circular plots of 20 m radius using single scans in dry deciduous forests of Betul, Madhya Pradesh. An overall tree detection accuracy of 85 and 70% was observed in the scanner range of 15 and 20 m respectively. The tree detection accuracies decreased with increased distance to the scanner due to the decrease in visible area. Also, estimated stem diameter using TLS was found to be in agreement with the field measured diameter (R² = 0.97). The RMSE of estimated DBH was found to be 3.5 cm (relative RMSE ~20%) over 202 trees detected over 5 plots. Results suggest that single scan approach suffices the cause of accuracy, reducing uncertainty and adds to increased sampling frequency in forest inventory and also implies that TLS has a seemingly high potential in forest management.