Validation and development of composite indices for measuring vulnerability to earthquakes using a socio-economic perspective

While many approaches for assessing earthquake risk exist within the literature and practice, it is the dynamic interrelationships between earthquake hazard, physical risk, and the social conditions of populations that are the focal point for disaster risk reduction. Here, the measurement of vulnerability to earthquakes (i.e., characteristics that create the potential for harm or loss) has become a major focus area. However, metrics aimed at measuring vulnerability to earthquakes suffer from several key limitations. For instance, hazard and community context are often ignored, and attempts to validate metrics are largely non-existent. The purpose of this paper is to produce composite indices of the vulnerability of countries to earthquakes within three topical areas: social vulnerability, economic vulnerability, and recovery potential. To improve upon the status quo in indicators development for measuring vulnerability to seismic events, our starting point was to: (1) define a set of indicators that are context specific to earthquakes as defined by the literature; (2) delineate indicators within categorical areas of vulnerability that are easy to understand and could be put into practical use by DRR practitioners; and (3) propose indicators that are validated using historical earthquake impacts. When mapped, the geographic variations in the differential susceptibility of populations and economies to the adverse effects of damaging earthquake impacts become evident, as does differential ability of countries to recover from them. Drivers of this geographic variation include average country debt, the type and density of infrastructure, poverty, governance, and educational attainment, to name just a few.

     

Correlations between SPT,CPT, and Vs for Reclaimed Lands near Dubai

Geotechnical and Geological Engineering - Artificial islands near Dubai were constructed with geomaterials of significant gravel content from other areas of the United Arab Emirates (UAE). The...     

Impacts of basin-wide irrigation pumping on dry-period stream baseflow in an alluvial aquifer in the Kosi Fan region of India and Nepal

The Kosi Fan region of India and Nepal hosts a productive aquifer system. Regional hydrology is highly seasonal, and both groundwater and surface water are used for irrigation. Groundwater depletion is not currently occurring, but there is concern that plans to increase groundwater irrigation will reduce river baseflow, potentially affecting downstream water users. This study presents a model-based analysis of the impacts of groundwater withdrawal on dry-period streamflow and evaluation of management alternatives. A sensitivity analysis was performed in which a range of model parameters were tested around a best-estimate, base-case scenario. A high-reduction scenario was then developed which combined the factors that produced the greatest pumping-induced reduction in dry-season baseflow. Management strategies for 2.5, 5, and 10-km no-pumping buffers around the rivers were tested for the base-case and high-reduction scenarios. Simulations show that groundwater withdrawal equivalent to 30% and 60% of dry-season streamflow for the Kosi and Mahananda rivers, respectively, reduces the current dry-season flow by less than 4%. In the base-case scenario, simulated dry-season baseflow reduction is 1.8% and 2.6% for the rivers, respectively; these reduce to ~1% with a 2.5-km buffer zone. For the high-reduction scenario, dry-season baseflow reductions are 4.7% and 7.0% with no buffer; these reduce to 1.3% and 0.9% with a 5-km buffer for the Kosi and Mahananda rivers, respectively. The small reductions in baseflow relative to the total amount of pumping are due to a pumping-induced increase in rainfall recharge, thus the effects of additional pumping are mitigated.

     

Electrostatic electron acoustic solitons in electron-positron-ion plasma with superthermal electrons and positrons

Properties of fully nonlinear electron-acoustic solitary waves in an unmagnetized and collisionless electron-positron-ion plasma containing cold dynamical electrons, superthermal electrons and positrons obeying Cairns’ distribution have been analyzed in the stationary background of massive positive ions. A linear dispersion relation has been derived, from which it is found that even in the absence of superthermal electrons, the superthermal positron component can provide the restoring force to the cold inertial electrons to excite electron-acoustic waves. Moreover, superthermal electron and positron populations seem to enhance the electron acoustic wave phase speed. For nonlinear analysis, Korteweg-de Vries equation is obtained using the reductive perturbation technique. It is found that in the presence of positron both hump and dip type solitons appear to excite. The present work may be employed to explore and to understand the formation of electron acoustic soliton structures in the space and laboratory plasmas with nonthermal electrons and positrons.     

Simulating and predicting river discharge time series using a wavelet‐neural network hybrid modelling approach

Accurate simulation and prediction of the dynamic behaviour of a river discharge over any time interval is essential for good watershed management. It is difficult to capture the high‐frequency characteristics of a river discharge using traditional time series linear and nonlinear model approaches. Therefore, this study developed a wavelet‐neural network (WNN) hybrid modelling approach for the predication of river discharge using monthly time series data. A discrete wavelet multiresolution method was employed to decompose the time series data of river discharge into sub‐series with low (approximation) and high (details) frequency, and these sub‐series were then used as input data for the artificial neural network (ANN). WNN models with different wavelet decomposition levels were employed to predict river discharge 48 months ahead of time. Comparison of results from the WNN models with those of the ANN models alone indicated that WNN models performed a more accurate prediction. Copyright © 2011 John Wiley & Sons, Ltd.     

Optimization and simulation of reservoir operation with sediment evacuation: a case study of the Tarbela Dam,Pakistan

Many reservoirs around the world are being operated based on rule curves developed without considering the evacuation of deposited sediment. Current reservoir simulation and optimization models fall short of incorporating the concept of sustainability because the reservoir storage losses due to sedimentation are not considered. This study develops a new model called Reservoir Optimization‐Simulation with Sediment Evacuation (ROSSE) model. The model utilizes genetic algorithm based optimization capabilities and embeds the sediment evacuation module into the simulation module. The sediment evacuation module is implemented using the Tsinghua university flushing equation. The ROSSE model is applied to optimize the rule curves of Tarbela Reservoir, the largest reservoir in Pakistan with chronic sedimentation problems. In the present study, rule curves are optimized for maximization of net economic benefits from water released. The water released can be used for irrigation, power production, sediment evacuation, and for flood control purposes. Relative weights are used to combine the benefits from these conflicting water uses. Nine sets of rule curves are compared, namely existing rule curves and proposed rule curves for eight scenarios developed for various policy options. These optimized rule curves show an increase of net individual economic benefits ranging from 9 to 248% over the existing rule curves. The shortage of irrigation supply during the simulation period is reduced by 38% and reservoir sustainability is enhanced by 28% through increased sediment evacuation. The study concludes that by modifying the operating policy and rule curves, it is possible to enhance the reservoir's sustainability and maximize the net economic benefits. The developed methodology and the model can be used for optimization of rule curves of other reservoirs with sedimentation problems. Copyright © 2008 John Wiley & Sons, Ltd.     

Geoelectrical constraints on radar probing of shallow water-saturated zones within karstified carbonates in semi-arid environments

Shallow carbonates are of utmost importance as potential sources of groundwater in karstified semi-arid terrains. Ground-Penetrating Radar (GPR) is being increasingly used as a prominent mapping tool in such environments. However, its potential in exploring and identifying shallow water-saturated zones (WSZs) in carbonates is constrained by the geoelectrical properties of carbonate soils as a function of moisture content. We report results of a case study that includes laboratory geoelectrical characterization and their comparison to in situ GPR attenuation measurements performed on Cretaceous Edwards Formation rudist mounds in central Texas, which we hypothesize as analogs for water-bearing formations in semi-arid karstified carbonate terrains. Dielectric measurements on field-collected rock samples carried out in the laboratory under controlled conditions of moisture saturation suggest that real and imaginary parts of dielectric constants of rocks with higher porosity and/or permeability have steeper dependence on pore moisture content; they produce better dielectric contrasts but allow shallower penetration. Our analyses suggest that within carbonates, dielectric contrasts improve with decrease in sounding frequency and/or increase in moisture content; and the relationship between dielectric permittivity and moisture content may be represented by 3rd order polynomial equations. GPR surveys using a wide-band 400 MHz antenna reveal subsurface mound morphologies with heights of ～ 1–2 m and basal diameters of ～ 8–10 m resembling outcrop analogs. Each mound appears to be composed of smaller amalgamated lithounits that seem geoelectrically similar. Amplitudes decays of the backscattered radar signal correlate to moisture distribution. Measuring the differences in signal attenuation allows differentiation between saturated and non-saturated zones. Velocity analyses of GPR profiles enable estimation of moisture distribution in the vicinity of the mounds. Optimal delineation and production of high-resolution GPR data up to a depth of ～ 10 m were observed for a sounding frequency of ～ 250 MHz with moisture content of ～ 5% by weight. Below this moisture level, the dielectric contrast is insufficient to uniquely identify water-saturated zones from the surrounding geoelectrical context, and above it, the radar signal is substantially attenuated leading to a total inefficiency of the method.     

Semipermeable membrane devices link site-specific contaminants to effects: PART II - A comparison of lingering Exxon Valdez oil with other potential sources of CYP1A inducers in Prince William Sound, Alaska

We deployed semipermeable membrane devices (SPMDs) on beaches for 28 days at 53 sites in Prince William Sound (PWS), Alaska, to evaluate the induction potential from suspected sources of cytochrome P450 1A (CYP1A)-inducing contaminants. Sites were selected to assess known point sources, or were chosen randomly to evaluate the region-wide sources. After deployment, SPMD extracts were analyzed chemically for persistent organic pollutants (POPs) and polycyclic aromatic hydrocarbons (PAH). These results were compared with hepatic CYP1A enzyme activity of juvenile rainbow trout injected with the same extracts prior to clean-up for the chemical analyses. Increased CYP1A activity was strongly associated with PAH concentrations in extracts, especially chrysene homologues but was not associated with POPs. The only apparent sources of chrysene homologues were lingering oil from Exxon Valdez, asphalt and bunker fuels released from storage tanks during the 1964 Alaska earthquake, creosote leaching from numerous pilings at one site, and PAH-contaminated sediments at Cordova Harbor. Our results indicate that PWS is remarkably free of pollution from PAH when nearby sources are absent as well as from pesticides and PCBs generally.     

A wavelet based approach for combining the outputs of different rainfall–runoff models

The rainfall–runoff modelling being a stochastic process in nature is dependent on various climatological variables and catchment characteristics and therefore numerous hydrological models have been developed to simulate this complex process. One approach to modelling this complex non-linear rainfall–runoff process is to combine the outputs of various models to get more accurate and reliable results. This multi-model combination approach relies on the fact that various models capture different features of the data, and hence combination of these features would yield better result. This study for the first time presented a novel wavelet based combination approach for estimating combined runoff The simulated daily output (Runoff) of five selected conventional rainfall–runoff models from seven different catchments located in different parts of the world was used in current study for estimating combined runoff for each time period. Five selected rainfall–runoff models used in this study included four data driven models, namely, the simple linear model, the linear perturbation model, the linearly varying variable gain factor model, the constrained linear systems with a single threshold and one conceptual model, namely, the soil moisture accounting and routing model. The multilayer perceptron neural network method was used to develop combined wavelet coupled models to evaluate the effect of wavelet transformation (WT). The performance of the developed wavelet coupled combination models was compared with their counterpart simple combination models developed without WT. It was concluded that the presented wavelet coupled combination approach outperformed the existing approaches of combining different models without applying input WT. The study also recommended that different models in a combination approach should be selected on the basis of their individual performance.