Applications of generalized additive model (GAM) to satellite-derived variables and fishery data for prediction of fishery resources distributions in the Arabian Sea

This study aims to illustrate how remotely sensed oceanic variables and fishing operations data can be used to predict suitable habitat of fishery resources in Geographic Information System. We used sea surface height anomaly (SSHa), sea surface temperature (SST), chlorophyll concentration (CC), photosynthetically active radiation (PAR) and fishing depth as predictor variables. Fishery data of Indian squid (Loligo spp.) and catfish (Tachysurus spp.) for study period (1998–2004) were segregated randomly to create training and validation. Catch was normalized into Catch per unit Effort (kg h^?1). Generalized additive modelling was performed on training data and then tested on validation data. Suitable ranges of SST, CC, SSHa and PAR for different species distributions were derived and integrated to predict their spatial distributions. Results indicated good match between predicted and actual catch. Monthly probability maps of predicted habitat areas coincide with high catch of the particular month for the study period.     

Variability of surface roughness and turbulence intensities at a coastal site in India

Surface-layer features with different prevailing wind directions for two distinct seasons (Southwest Monsoon and Northeast Monsoon) on the west coast of India are studied using data obtained from tower-based sensors at a site located about 500 m from the coast. Only daytime runs have been used for the present analysis. The surface boundary-layer fluxes have been estimated using the eddy correlation method. The surface roughnessz ₀ obtained using the stability-corrected wind profiles (Paulson, 1970) has been found to be low for the Southwest monsson season. For the other season,z ₀ is relatively high. The drag coefficientC _D varies with height in the NE monsoon season but not in the season with lowz ₀. This aspect is reflected in the wind profiles for the two seasons and is discussed in detail. The scaling behaviour of friction velocityu _* and the turbulence intensity of longitudinal, lateral and vertical winds _u, _v and _w, respectively) are further examined to study their dependence on fetch. Our study shows that for the non-dimensional case, _u/u_* and _v/u_* do not show any surface roughness dependence in either season. On the other hand, for _w/u_* for the season with lowz ₀, the values are seen to agree well with that of Panofskyet al. (1977) for homogeneous terrain whereas for the other season with highz ₀, the results seem to conform more to the values observed by Smedman and Högström (1983) for coastal terrain. The results are discussed in the light of observations by other investigators.     

The Armagh Observatory Meteor Camera Cluster: Overview and Status

Armagh Observatory installed a sky monitoring system consisting of two wide angle (90° × 52°) and one medium angle (52° × 35°) cameras in July 2005. The medium angle camera is part of a double station setup with a similar camera in Bangor, ∼73 km ENE of Armagh. All cameras use UFOCapture to record meteors automatically; software for off-line photometry, astrometry and double station calculations is currently being developed. The specifications of the cameras and cluster configuration are described in detail. 2425 single station meteors (1167, 861 and 806 by the medium-angle and the wide-angle cameras respectively) and 547 double station meteors were recorded during the months July 2005 to Dec 2006. About 212 double station meteors were recorded by more than one camera in the cluster. The effects of weather conditions on camera productivity are discussed. The distribution of single and double station meteor counts observed for the years 2005 and 2006 and calibrated for weather conditions are presented.     

Sea level changes induced by local winds on the west coast of India

The contribution of atmospheric pressure and local wind to sea level variability at Goa (West coast of India) for the period 2007–2008 is investigated. Sea level data from a tide gauge are compared with measured local surface meteorological as well as oceanographic data. Multilinear regression analysis is used to resolve the dependence of sea level on various forcing parameters. The multilinear regression analysis performed over approx. 2-year data shows that the local surface meteorological data and water temperature account for the sea level variability only up to 6%. The accounted sea level variability increases to 25%, when the local wind and the surface currents obtained from satellite altimetry in the near vicinity of the study area are incorporated in the regression analysis. The contribution of local wind increases substantially when the regression is performed over a 2-month duration, and it is variable within the year. During the summer monsoon season (May–September), the sea level variability attributable to wind is up to 47% and 75%, respectively, for 2007 and 2008; however, it reduces to <20% during the winter monsoon (November–February) season. A significant part of the variability observed in sea level remains unaccounted for and is attributed to remote forcing.     

A comparative study of sequential minimal optimization-based support vector machines,vote feature intervals,and logistic regression in landslide susceptibility assessment using GIS

Landslide susceptibility assessment using GIS has been done for part of Uttarakhand region of Himalaya (India) with the objective of comparing the predictive capability of three different machine learning methods, namely sequential minimal optimization-based support vector machines (SMOSVM), vote feature intervals (VFI), and logistic regression (LR) for spatial prediction of landslide occurrence. Out of these three methods, the SMOSVM and VFI are state-of-the-art methods for binary classification problems but have not been applied for landslide prediction, whereas the LR is known as a popular method for landslide susceptibility assessment. In the study, a total of 430 historical landslide polygons and 11 landslide affecting factors such as slope angle, slope aspect, elevation, curvature, lithology, soil, land cover, distance to roads, distance to rivers, distance to lineaments, and rainfall were selected for landslide analysis. For validation and comparison, statistical index-based methods and the receiver operating characteristic curve have been used. Analysis results show that all these models have good performance for landslide spatial prediction but the SMOSVM model has the highest predictive capability, followed by the VFI model, and the LR model, respectively. Thus, SMOSVM is a better model for landslide prediction and can be used for landslide susceptibility mapping of landslide-prone areas.     

Mapping groundwater recharge potential using GIS approach in Darwha block

Groundwater is the most important source of water in meeting irrigation, drinking, and other needs in India. The assessment of the potential zone for its recharge is critical for sustainable usage, quality management, and food security. This study reports alternative mapping of the groundwater recharge potential of a selected block by including large-scale soil data. Thematic layers of soil, geomorphology, slope, land use land cover, topographical wetness index, and drainage density of Darwha block (District Yavatmal, Maharashtra, India) were generated and integrated in a geographic information system environment. The topographic maps, thematic maps, field data, and satellite image were processed, classified, and weighted using analytical hierarchical process for their contribution to groundwater recharge. The layers were integrated by weighted linear combination method in the GIS environment to generate four groundwater potential zones viz., “poor,” “poor to moderate,” “moderate to high,” and “high.” Based on the generated groundwater potential map, about 9830 ha (12%) of the study area was categorized as high potential for recharge, 25,558 ha (31%) as poor to moderate, 33,398 ha (40%) as moderate to high, and 12,565 ha (15%) as poor potential zone. The zonation corresponds well with the field data on greater well density (0.22/ha) and irrigated crop area (27%) in the high potential zone as against 0.02 wells/ha and only 6% irrigated area in the poor zone. The map is recommended for use in regulating groundwater development decisions and judicious expenditure on drilling new wells by farmers and the state authorities.     

Assessment of Kalpana-1 Rainfall Product over Indian Meteorological Sub-Divisions During the Summer Monsoon Season

In this paper, Kalpana-1 derived INSAT Multispectral Rainfall Algorithm (IMSRA) rainfall estimates are compared with two multisatellite rainfall products namely, TRMM Multisatellite Precipitation Analysis (TMPA)-3B42 and Global Satellite Mapping of Precipitation (GSMaP), and India Meteorological Department (IMD) surface rain gauge (SRG)-based rainfall at meteorological sub-divisional scale over India. The performance of the summer monsoon rainfall of 2013 over Indian meteorological sub-divisions is assessed at different temporal scales. Comparison of daily accumulated rainfall over India from IMSRA shows a linear correlation of 0.72 with TMPA-3B42 and 0.70 with GSMaP estimates. IMSRA is capable to pick up daily rainfall variability over the monsoon trough region as compared to TMPA-3B42 and GSMaP products, but underestimates moderate to heavy rainfall events. Satellite-derived rainfall maps at meteorological sub-divisional scales are in reasonably good agreement with IMD-SRG based rainfall maps with some exceptions. However, IMSRA performs better than GSMaP product at meteorological sub-divisional scale and comparable with TMPA data. All the satellite-derived rainfall products underestimate orographic rainfall along the west coast, the Himalayan foothills and over the northeast India and overestimate rainfall over the southeast peninsular India. Overall results suggest that IMSRA estimates have potential for monsoon rainfall monitoring over the Indian meteorological sub-divisions and can be used for various hydro-meteorological applications.     

The ice sheet dynamics around Dakshin Gangotri glacier,Schirmacher Oasis,East Antarctica vis-à-vis topography and meteorological parameters

Recession of the snout of Dakshin Gangotri glacier in the western part of Schirmacher Oasis, East Antarctica has been recorded over two decades. However, the rate of retreat is not uniform and varies at different locations. The ice wall forming the western flank of the glacier has shown an average retreat of 17.07 m between 2001 and 2009 while the snout had gone back by 6.94 m (average) during the same period. Before 2001, the snout had shown a complete recession of 3.13 m (average). The snout occupies valley area receiving less amount of solar radiation as compared to the western wall, which is a vertical cliff receiving maximum amount of solar radiation. The notable difference in the rate of recession in different parts of the Dakshin Gangotri glacier overriding Schirmacher Oasis can be attributed to combined effect of natural factors, including meteorological parameters, ice sheet dynamics and geomorphology of that area.     

Construction and Characterization of Transportable Calibration Pads for Calibration of Portable and Airborne Gamma Ray Spectrometers in India

Characterization of the Panandhro lignite deposits from western Indian state of Gujarat, based on the geochemical and palynological evidences, has been performed to assess the floral composition, maturity and hydrocarbon potential of the sequence. Elementally, the lignites consist of moderate carbon, low hydrogen and moderate sulfur contents. The samples are characterized by high TOC contents (lignite: av. 46.43 wt.%, resin: 62.47 wt.%). The average HI values for the lignite is 136 mg HC/g TOC, and that of the associated resin is 671 mg HC/g TOC. The highest T_max is recoded in lignite (422°C) and lowest in the resin (39°C) samples. The FTIR spectrum of lignite is characterized by highly intense OH stretching peak ~3350 cm^-1, aliphatic CH_x stretching peaks between 3000-2800 cm^-1, aromatic C=O stretching and an aromatic C=C stretching. The spectrum of resin shows strongest absorption due to aliphatic CHx stretching between 2940-2915 cm^-1 and 2870-2850 cm^-1, and deformation by the medium peak between 1450 and 1650 cm^-1. The recovered palynofloral assemblage indicates the dominance of angiosperm pollen grains with maximum abundance of Arecaceae family, and subdominant pteridophytic spores. Marine influence is indicated by the presence of abundant dinoflagellate cysts. The occurrence of flora from a variety of ecological niches suggests a luxuriant diverse vegetation pattern existed in the vicinity of depositional site under humid tropical conditions. The overall characteristics of the lignite deposits point towards their ability to generate (upon maturation) hydrocarbons as they have types III–II admixed kerogen (organic matters).     

Wind-driven estuarine turbidity maxima in Mandovi Estuary,central west coast of India

Systematic studies on the suspended particulate matter (SPM) measured on a seasonal cycle in the Mandovi Estuary, Goa indicate that the average concentrations of SPM at the regular station are ∼20mg/l, 5mg/l, 19mg/l and 5mg/l for June–September, October–January, February–April and May, respectively. SPM exhibits low-to-moderate correlation with rainfall indicating that SPM is also influenced by other processes. Transect stations reveal that the SPM at sea-end stations of the estuary are at least two orders of magnitude greater than those at the river-end during the monsoon. Estuarine turbidity maximum (ETM) of nearly similar magnitude occurs at the same location in two periods, interrupted by a period with very low SPM concentrations. The ETM occurring in June–September is associated with low salinities; its formation is attributed to the interactions between strong southwesterly winds (5.1–5.6ms⁻¹) and wind-induced waves and tidal currents and, dominant easterly river flow at the mouth of the estuary. The ETM occurring in February–April is associated with high salinity and is conspicuous. The strong NW and SW winds (3.2–3.7ms⁻¹) and wind-driven waves and currents seem to have acted effectively at the mouth of the estuary in developing turbidity maximum. The impact of sea breeze appears nearly same as that of trade winds and cannot be underestimated in sediment resuspension and deposition