Variation of flow field around twin cylinders with and without the outer perforated cylinder — Numerical study

Presence of the outer perforated cylinder reduces the direct wave impact on the inner cylinder, which has been testified by many researchers. However, the force reduction mechanism, which is complicated due to the wave-porous structure interaction, needs to be addressed in detail. The present study explains the mechanism with the aid of the computational fluid dynamics (CFD) tool STAR CCM+. This package is chosen for its capabilities to simulate viscous and turbulence effects caused by passage of waves. For the present study, flow fields around the twin cylinders with different orientations are examined with and without the outer perforated cover. Mechanism contributing to the reduction of force on the existing structure is explained in physical terms, and force reduction is quantified. The present study has direct application in the retrofitting application of offshore members.     

The impact of urbanization on water vulnerability: A coupled human–environment system approach for Chennai,India

While there is consensus that urbanization is one of the major trends of the 21^st century in developing countries, there is debate as to whether urbanization will increase or decrease vulnerability to droughts. Here we examine the relationship between urbanization and water vulnerability for a fast-growing city, Chennai, India, using a coupled human–environment systems (CHES) modeling approach. Although the link between urbanization and water vulnerability is highly site-specific, our results show some generalizable factors exist. First, the urban transformation of the water system is decentralized as irrigation wells are converted to domestic wells by private individuals, and not by the municipal authority. Second, urban vulnerability to water shortages depends on a combination of several factors: the formal water infrastructure, the rate and spatial pattern of land use change, adaptation by households and the characteristics of the ground and surface water system. Third, vulnerability is dynamic, spatially variable and scale dependent. Even as household investments in private wells make individual households less vulnerable, over time and cumulatively, they make the entire region more vulnerable. Taken together, the results suggest that in order to reduce vulnerability to water shortages, there is a need for new forms of urban governance and planning institutions that are capable of managing both centralized actions by utilities and decentralized actions by millions of households.     

Global sensitivity analysis in an ocean general circulation model: a sparse spectral projection approach

Polynomial chaos (PC) expansions are used to propagate parametric uncertainties in ocean global circulation model. The computations focus on short-time, high-resolution simulations of the Gulf of Mexico, using the hybrid coordinate ocean model, with wind stresses corresponding to hurricane Ivan. A sparse quadrature approach is used to determine the PC coefficients which provides a detailed representation of the stochastic model response. The quality of the PC representation is first examined through a systematic refinement of the number of resolution levels. The PC representation of the stochastic model response is then utilized to compute distributions of quantities of interest (QoIs) and to analyze the local and global sensitivity of these QoIs to uncertain parameters. Conclusions are finally drawn regarding limitations of local perturbations and variance-based assessment and concerning potential application of the present methodology to inverse problems and to uncertainty management.     

A nonlinear data‐driven model for synthetic generation of annual streamflows

A hybrid model that blends two non‐linear data‐driven models, i.e. an artificial neural network (ANN) and a moving block bootstrap (MBB), is proposed for modelling annual streamflows of rivers that exhibit complex dependence. In the proposed model, the annual streamflows are modelled initially using a radial basis function ANN model. The residuals extracted from the neural network model are resampled using the non‐parametric resampling technique MBB to obtain innovations, which are then added back to the ANN‐modelled flows to generate synthetic replicates. The model has been applied to three annual streamflow records with variable record length, selected from different geographic regions, namely Africa, USA and former USSR. The performance of the proposed ANN‐based non‐linear hybrid model has been compared with that of the linear parametric hybrid model. The results from the case studies indicate that the proposed ANN‐based hybrid model (ANNHM) is able to reproduce the skewness present in the streamflows better compared to the linear parametric‐based hybrid model (LPHM), owing to the effective capturing of the non‐linearities. Moreover, the ANNHM, being a completely data‐driven model, reproduces the features of the marginal distribution more closely than the LPHM, but offers less smoothing and no extrapolation value. It is observed that even though the preservation of the linear dependence structure by the ANNHM is inferior to the LPHM, the effective blending of the two non‐linear models helps the ANNHM to predict the drought and the storage characteristics efficiently. Copyright © 2007 John Wiley & Sons, Ltd.     

Factors influencing surface runoff generation from two agricultural hillslopes in central Pennsylvania

The variable source area (VSA) concept provides the underlying paradigm for managing phosphorus losses in runoff in the north‐eastern USA. This study sought to elucidate factors controlling runoff along two hillslopes with contrasting soils, including characterizing runoff generation mechanisms and hydrological connectivity. Runoff monitoring plots (2 m × 1 m) were established in various landscape positions. Footslope positions were characterized by the presence of a fragipan that contributed to seasonally perched water tables. In upslope positions without a fragipan, runoff was generated primarily via the infiltration‐excess (IE) mechanism (96% of events) and was largely disconnected from downslope runoff. Roughly 80% of total runoff originated from the north footslope landscape position via saturation‐excess (SE) (46% of events; 62% of runoff) and IE (54% of events; 38% of runoff) mechanisms. Runoff from the north hillslope was substantially greater than the south hillslope despite their proximity, and apparently was a function of the extent of fragipan representation. Results demonstrate the influence of subsurface soil properties (e.g. fragipan) on surface runoff generation in variable source area hydrology settings, which could be useful for improving the accuracy of existing runoff prediction tools. Published in 2009 by John Wiley & Sons, Ltd.     

The once and future pulse of Indian monsoonal climate

We present a comprehensive assessment of the present and expected future pulse of the Indian monsoon climate based on observational and global climate model projections. The analysis supports the view that seasonal Indian monsoon rains in the latter half of the 21th century may not be materially different in abundance to that experienced today although their intensity and duration of wet and dry spells may change appreciably. Such an assessment comes with considerable uncertainty. With regard to temperature, however, we find that the Indian temperatures during the late 21st Century will very likely exceed the highest values experienced in the 130-year instrumental record of Indian data. This assessment comes with higher confidence than for rainfall because of the large spatial scale driving the thermal response of climate to greenhouse gas forcing. We also find that monsoon climate changes, especially temperature, could heighten human and crop mortality posing a socio-economic threat to the Indian subcontinent.     

Risk perception and evacuation decisions of Florida tourists under hurricane threats: a stated preference analysis

Though most hurricane evacuation studies have focused on residents, tourists are also a vulnerable population. To assess their perceptions of risk and evacuation likelihood under different hurricane conditions, we surveyed 448 tourists visiting central Florida. Respondents viewed four maps emulating track forecast cones produced by the National Hurricane Center and text information featuring variations of storm intensity, coast of landfall, centerline position relative to the survey site, time until landfall, and event duration. We performed chi-square tests to determine which hurricane conditions, and aspects of tourists such as their demographics and previous hurricane experience, most likely influenced their ratings of risk and evacuation likelihood for respondents located on Pinellas County beaches or inland near Orlando, FL. Highly rated scenarios featured a Category 4 hurricane making landfall along the Gulf Coast with the centerline passing over the sampling site. Overall, tourists that indicated the highest risk and evacuation ratings were not previously affected by a hurricane, had a trip duration of less than 6 days, and had checked for the possibility of a hurricane strike before departure. However, results for other tourist attributes differed between tourists in coastal and inland locations. We found that although somewhat knowledgeable about hurricanes, tourists misinterpreted the track forecast cone and hurricane conditions, which led to a lower perception of risk and subsequent likelihood to evacuate. Tourists, particularly those from outside of Florida, need to be better educated about the risks they face from hurricanes that make landfall.     

A priori testing of sparse adaptive polynomial chaos expansions using an ocean general circulation model database

This work explores the implementation of an adaptive strategy to design sparse ensembles of oceanic simulations suitable for constructing polynomial chaos surrogates. We use a recently developed pseudo-spectral algorithm that is based on a direct application of the Smolyak sparse grid formula and that allows the use of arbitrary admissible sparse grids. The adaptive algorithm is tested using an existing simulation database of the oceanic response to Hurricane Ivan in the Gulf of Mexico. The a priori tests demonstrate that sparse and adaptive pseudo-spectral constructions lead to substantial savings over isotropic sparse sampling in the present setting.