Flood events, fatalities and damages in India from 1978 to 2006

High temporal and spatial variability of rainfall qualifies India to be highly vulnerable to floods. Recurring floods of various magnitudes play havoc with the lives and property of the people, leading to unplanned development and unchecked environmental degradation, thwarting and retarding the overall development of the country. Therefore, the purpose of the present study is to analyze the types and trends in terms of flood events, frequency, number of people killed, injured, missing and economic damage both in space and time on the basis of a nationwide database published by India Meteorological Department, Pune, from 1978 to 2006. Analysis of these long-term data has revealed that 2,443 flood events claimed about 44,991 lives with the average of 1,551 lives each year. In terms of population size, these figures translate into a loss of 1.5 human lives per million of the population. A majority (56 %) of flood fatalities were caused during severe flood events. However, the frequency of these events was just 19 % in comparison with heavy rainfall events (65 %). In spatial context, flood-related fatalities are distributed all over the country with highest fatalities in Uttar Pradesh (17 %), Maharashtra (13 %), and Bihar and Gujarat (10 % each). Most fatalities occurred during the summer season monsoon months of August (30 %) followed by July (29 %) and September (20 %). The country suffered a cumulative flood-related economic loss of about 16 billion US$ between 1978 and 2006 and a maximum economic loss of 1.6 billion US$ in the year 2000 alone. The study further suggests that both flood events and fatalities have increased in India over a period of time.     

Using simple data experiments to explore the influence of non-temperature controls on maize yields in the mid-West and Great Plains

Several recent papers have suggested that high temperatures are associated with reduced maize yields. To better understand the conditions under which this association may occur, we conduct two analyses on maize yields from 1981 to 2011 for 100 U.S. counties with large areas planted to maize in the mid-West and Great Plains. First, we compare statistical yield models in non-irrigated and extensively irrigated counties, after carefully evaluating the degree of crop irrigation in a county and selecting only counties with no irrigation or extensive irrigation. We find that yields in extensively irrigated counties have minimal dependency on temperature factors in the regression model. Second, we compare statistical yield models across non-irrigated counties using data sets with and without years with known extreme moisture anomalies. We find that for Minnesota, Central Iowa, and Northern Illinois, the sufficiency of yield models based only on temperature factors are highly leveraged by the few years with extreme moisture anomalies. In western Iowa and much of Illinois, temperature factors consistently explain a moderate amount of yield variability, even when extreme moisture anomalies are removed. In general, these findings suggest that in many regions maize yields are not solely dependent on temperature and that other factors (e.g. humidity, soil moisture, flooding) likely need to be accounted for to improve statistical yield models and to make accurate projections of maize yield in a changing climate.     

Identification and characterization of size-segregated bioaerosols at Jawaharlal Nehru University, New Delhi

Ambient levels of viable bioaerosol were measured at four different sites on the campus of Jawaharlal Nehru University (JNU), New Delhi, India. Most of the viable bioaerosol was associated with the fungal fraction with the remainder due to bacteria. The highest concentrations of fungi were found at a health center (1,293 cfu/m³). The highest concentrations of both gram-positive (338.8 cfu/m²) and gram-negative (614 cfu/m²) bacteria were found at a garbage dump site. Gram-negative bacteria were found in larger numbers than gram-positive, possibly due to the higher ambient temperatures during their sampling. Most of the fungal bioaerosol identified is associated with immunotoxic diseases such as sick building syndrome and allergic diseases and was found in respirable fractions. Since the bacterial fractions were identified on the basis of morphology, i.e. only to the level of genus, their relationship to health effects could not be established. Although most of the sampling occurred indoors in naturally ventilated buildings, external temperature and humidity did not vary significantly during the study. Thus, it is more likely that the types of organisms and levels observed had more to do with the sources (decomposing garbage, spores carried from wooded areas, etc.) than the ambient or indoor environmental conditions.     

Semitransparent cirrus clouds in the tropical tropopause layer during two contrasting seasons

Association between semitransparent cirrus (STC) and tropospheric dynamics during the two contrasting seasons (Summer-monsoon and Winter) is studied using lidar and MST radar observations at Gadanki (13.5°N, 79.2°E) along with data from Geo-stationary satellite (KALPANA-1). The tropical tropopause layer (TTL) is found to be very conducive for the formation of STC. For those thicker STCs forming within TTL, the cloud top remains mostly steady with the top of the TTL, while the cloud base varies significantly in accordance with the altitude extent of tropospheric convective outflow. Based on depolarization characteristics of STCs (from lidar) along with regional distribution of tropospheric clouds derived from satellite data, altitude profile of horizontal wind, wind field at 150 hPa and air mass back trajectories, it can be reasonably inferred that, while the multi-layered and highly structured STCs during the monsoon period originate mostly from the deep convections, the sub-visual/ultra thin STCs during winter could mostly be of in situ origin.     

Relativistic model of radiating massive fluid sphere

In this paper we present a new class of nonsingular solutions representing time dependent balls of perfect fluid with matter-radiation in general relativity. The solution of the class is suitable for interior modeling of a quasar i.e. a massive radiating star. The interior solution is matched with a zero pressure Vaidya metric. From this solution we constructed a quasar model by assuming the life time of the quasar of ≈10⁷ year. We obtained a mass of the quasar of ≈10⁹ M _θ , linear dimension ≈10¹⁷ km and a rate of emission L _∞≈10⁴⁷ erg/s.     

Tectonic implications of the earthquakes in the Indian subcontinent

The Bhuj earthquake (26 January 2001) in India and the Ghori earthquake (8 October 2005) in Pakistan, both occurred close to the Indian-Iranian plate boundary related to the activity along the intercontinental Chaman transform fault. It is suggested that the seismic activity along NNW — NNE trending weak zones or faults is more intense in the sub-continent than along the WNW trending zones. Since the stress along the former is less compressive but more of the shear or translational type. The devastative Koyna (1967) and Latur (1993) earthquakes both occurred along faults or weak zones that were close to the meridional rather than the equatorial trend. The Indian plate is moving to the north or NNE or NNW, along a rotational trajectory and hence the force tends to be more compressive along the equatorial weak zones. In contrast, it tends to be less compressive and more of the shear or translational along the weak zones that are close to meridional trend. The seismic activity is therefore more intense along the weak zones with NNW to NNE trend than along the ENE to EW trending zones.     

Spatial homogeneity of extreme precipitation indices using fuzzy clustering over northeast India

Natural Hazards - Regionalization on the basis of the properties of hydro-meteorological data helps in identifying the regions reflecting the similar characteristics which could be useful in...     

Segmentation of well logs by maximum-likelihood estimation

A maximum-likelihood procedure for segmenting digital well-log data is presented. The method is based on a univariate state variable model in which an observed log is treated as a time-series consisting of two terms: a Gauss-Markov signal remaining constant over a segment, and an additive Gaussian, but not necessarily stationary, noise. The signal jumps by a random amount at a segment boundary. The inverse problem of log segmentation consists of detecting the segment boundaries from a given log. The problem is solved using a Bayesian approach in which the unknown parameters, the locations of segment boundaries and the jumps in the signal value, are estimated by maximizing the likelihood function for the observed data. An algorithm based on Kalman smoothing and single most likelihood replacement (SMLR) procedure is proposed. The performance of the method is illustrated with a case study comprising of multisuite log data from an exploratory well. The method is found to be rapid and robust. The resulting segments are found to be geologically consistent.     

Urban land use mapping: A case study of ahmedabad city and its environs

Proper urban planning and effective implementation requires reliable urban land use statistics. In this context, satellite remote sensing data has been studied using both visual and digital techniques. A portable eight-band radiometer has been used to collect spectral signatures of surface features present in Ahmedabad city and its environs. Using these signatures a suitable approach employing visual and digital techniques has been developed for urban land use/sprawl mapping. Urban land-use maps of Ahmedabad city and its environs were prepared on 1:25,000 scale and for Ahmedabad Urban Development Authority Area on 1:50,000 scale using this methodology. It has been found that edge-enhancement techniques are useful to enhance the contrast among different urban land uses. Classification techniques such as MXL and Bayes classifiers are not successful in discriminating urban land uses. Tonal characteristics alongwith other elements of interpretation are required to classify urban land uses such as residential, industrial etc. Spatial distribution of various urban and uses and the space devoted to each urban land use has been brought out.