Changes in daily maximum temperature extremes across India over 1951–2014 and their relation with cereal crop productivity

This study used gridded daily maximum temperature data (1°?×?1°) for 1951–2014 period to analyze the trend in monthly extreme warm days (ExWD) and changes in its probability distribution in each grid. It also analyzed the trend in spatial spread of annual ExWD over the study period at four exceedance levels and further related the number of ExWDs with cereal crop productivity of India. Extreme warm days have increased throughout India but were statistically significant in 42% grids. The increase was consistent over all the months in north-eastern region, southern plateau and both the coastal plains. It also increased significantly over north-western and central India during April to June summer period. The probability distribution of ExWD also changed significantly in many grids, especially in southern plateau and both the coastal plains. The changes indicated increased frequency in the existing levels of extremes and new occurrences of higher frequency of extremes. The analysis of land area affected by different levels of extremes indicated significant increase, with the rate being highest for higher extremes. In terms of extreme warm day temperatures, the study identified southern plateau, east and west coast plains, and north-eastern India as highly vulnerable. Using copula probability model, study showed that increase in ExWD from 20 to 60% may increase the probability of 5% or more yield loss from 17 to 53% for Kharif cereals, 11 to 43% for Rabi cereals and 19 to 63% for wheat crop. The results may be used for devising zone specific adaptation strategies.     

Estimation of spatial variability of aquifer parameters from geophysical methods: a case study of Sindhudurg district,Maharashtra, India

Accurate estimation of aquifer parameters, especially from crystalline hard rock area, assumes a special significance for management of groundwater resources. The aquifer parameters are usually estimated through pumping tests carried out on water wells. While it may be costly and time consuming for carrying out pumping tests at a number of sites, the application of geophysical methods in combination with hydro-geochemical information proves to be potential and cost effective to estimate aquifer parameters. Here a method to estimate aquifer parameters such as hydraulic conductivity, formation factor, porosity and transmissivity is presented by utilizing electrical conductivity values analysed via hydro-geochemical analysis of existing wells and the respective vertical electrical sounding (VES) points of Sindhudurg district, western Maharashtra, India. Further, prior to interpolating the distribution of aquifer parameters of the study area, variogram modelling was carried out using data driven techniques of kriging, automatic relevance determination based Bayesian neural networks (ARD-BNN) and adaptive neuro-fuzzy neural networks (ANFIS). In total, four variogram model fitting techniques such as spherical, exponential, ARD-BNN and ANFIS were compared. According to the obtained results, the spherical variogram model in interpolating transmissivity, ARD-BNN variogram model in interpolating porosity, exponential variogram model in interpolating aquifer thickness and ANFIS variogram model in interpolating hydraulic conductivity outperformed rest of the variogram models. Accordingly, the accurate aquifer parameters maps of the study area were produced by using the best variogram model. The present results suggest that there are relatively high value of hydraulic conductivity, porosity and transmissivity at Parule, Mogarne, Kudal, and Zarap, which would be useful to characterize the aquifer system over western Maharashtra.     

Seismic response analysis of a hydraulic fill dam

Acta Geotechnica - The seismic response of a highly heterogeneous hydraulic fill dam was evaluated by studying the natural frequencies of the first and second modes of vibration and analyzing the...     

A hybrid deterministic and stochastic approach for tsunami hazard assessment in Iquique,Chile

Natural Hazards - This paper presents an investigation of the collapse of a 325-year-old multi-tiered heritage temple during the 2015 Gorkha earthquake in Kathmandu, Nepal. The research comprises a...     

A parametric design study for a semi/SCR system in Northern North Sea

In recent years, offshore reservoirs have been developed in deeper and deeper water environments. Steel catenary risers (SCRs) are being considered in deepwater development such as Northern North Sea. SCRs used in conjunction with a semi-submersible or floating production, storage and offloading (FPSO) in deepwater harsh environments present significant design challenges. The large vertical motions at the semi or FPSO induce severe riser response, which results in difficulty meeting strength and fatigue criteria at the hang off and touch down point locations. To improve the understanding of SCR behaviour and increase the confidence in the design of such systems in deepwater harsh environments, a parametric study on a SCR connected to a semi-submersible was carried out in this paper to deal with the factors that mainly influence the loading condition and fatigue life of the riser. Weight-optimized configurations were applied during the course of riser design. Riflex combined with DeepC was the primary analysis tool used for the long-term response of the nonlinear SCR structure simulations, which requires a large amount of computer time. Hence, the parameters affecting the efficiency and accuracy of the simulations have also been studied during the analysis process.     

Simulation of rain-bearing summer monsoon systems along the west coast of India by use of ARMEX re-analysis

Re-analysis, using surface, upper-air, and satellite observations specially collected during the Arabian Sea Monsoon Experiment-I (ARMEX-I), has been performed with a global data assimilation system at T-80/L18 resolution. Re-analysis was performed for the entire ARMEX-I period (15th June–16th August 2002). In this paper we discuss the results based on re-analysis and subsequent forecasts for two successive intensive observation periods associated with heavy rainfall along the west coast of India during 2–12 August, 2002. Results indicate that the re-analysed fields can bring out better synoptic features, for example troughs along the west coast and mid tropospheric circulation over the Arabian Sea. Simulated rainfall distribution using re-analysis as initial condition also matches observed rainfall better than data from the initial analysis.     

Damage‐based design with no repairs for multiple events and its sensitivity to seismicity model

Conventional design methodology for the earthquake‐resistant structures is based on the concept of ensuring ‘no collapse’ during the most severe earthquake event. This methodology does not envisage the possibility of continuous damage accumulation during several not‐so‐severe earthquake events, as may be the case in the areas of moderate to high seismicity, particularly when it is economically infeasible to carry out repairs after damaging events. As a result, the structure may collapse or may necessitate large scale repairs much before the design life of the structure is over. This study considers the use of design force ratio (DFR) spectrum for taking an informed decision on the extent to which yield strength levels should be raised to avoid such a scenario. DFR spectrum gives the ratios by which the yield strength levels of single‐degree‐of‐freedom oscillators of different initial periods should be increased in order to limit the total damage caused by all earthquake events during the lifetime to a specified level. The DFR spectra are compared for three different seismicity models in case of elasto‐plastic oscillators: one corresponding to the exponential distribution for return periods of large events and the other two corresponding to the lognormal and Weibull distributions. It is shown through numerical study for a hypothetical seismic region that the use of simple exponential model may be acceptable only for small values of the seismic gap length. For moderately large to large seismic gap lengths, it may be conservative to use the lognormal model, while the Weibull model may be assumed for very large seismic gap lengths. Copyright © 2006 John Wiley & Sons, Ltd.     

Remote sensing and GIS for artificial recharge study, runoff estimation and planning in Ayyar basin, Tamil Nadu, India

This paper focuses on artificial groundwater recharge study in Ayyar basin, Tamil Nadu, India. The basin is covered by hard crystalline rock and overall has poor groundwater conditions. Hence, an artificial recharge study was carried out in this region through a project sponsored by Tamil Nadu State Council for Science and Technology. The Indian Remote Sensing satellite 1A Linear Imaging Self Scanning Sensor II (IRS 1A LISS II) satellite imagery, aerial photographs and geophysical resistivity data were used to prioritize suitable sites for artificial recharge and to estimate the volume of aquifer dimension available to recharge. The runoff water available for artificial recharge in the basin is estimated through Soil Conservation Service curve number method. The land use/land cover, hydrological soil group and storm rainfall data in different watershed areas were used to calculate the runoff in the watersheds. The weighted curve number for each watershed is obtained through spatial intersection of land use/land cover and hydrological soil group through GeoMedia 3.0 Professional GIS software. Artificial recharge planning was derived on the basis of availability of runoff, aquifer dimension, priority areas and water table conditions in different watersheds in the basin.     

Uncertainty Analysis in Atmospheric Dispersion Modeling

The concentration of a pollutant in the atmosphere is a random variable that cannot be predicted accurately, but can be described using quantities such as ensemble mean, variance, and probability distribution. There is growing recognition that the modeled concentrations of hazardous contaminants in the atmosphere should be described in a probabilistic framework. This paper discusses the various types of uncertainties in atmospheric dispersion models, and reviews sensitivity/uncertainty analysis methods to characterize and/or reduce them. Evaluation and quantification of the range of uncertainties in predictions yield a deeper insight into the capabilities and limitations of atmospheric dispersion models, and increase our confidence in decision-making based on models.