Acoustics of weirs: Potential implications for micro-hydropower noise.

There is great potential for the expansion of the small or micro scale hydropower network. Of the 43 thousand weirs in the UK there are only 500 consented hydro schemes. Planning applications for such schemes require a noise assessment. Noise evaluation of a proposed renewable scheme is often complicated by the turbine sites having distinct noise characteristics in the first instance, which are often caused by the weirs themselves. Three types of weir were studied: Broad Crest weirs were studied in detail; this is complimented by further studies in Flat V and Crump weirs. Flow data was collected for ten sites from the Environment Agency and the National Rivers Flow Archive to assess the collected Sound Pressure Level (SPL) and calculated Sound poWer Level (SWL) in relation to various river flows. Weir head height, width and meteorological data were also collected. It has been shown that the SPL data collection method used was the right choice, as the greatest amplitudes at the water impact interface at all weir types was recorded. SPL and SWL were found to be within a 36e82 dBz and 45e86 dBz range respectively for all weir types. These values can be used in computer simulations of sound propagation. The mean SPL and SWL difference between the weir types are 6.1 dBz and 6.3 dBz. Head height has the greatest effect on SPLs. Attenuation with distance was found to be similar to that of a free field line source in general

Our Changing Planet

This document, which is produced annually, describes the activities and plans of the U.S. Global Change Research Program (USGCRP), which was established in 1989 and authorized by Congress in the Global Change Research Act of 1990. Strong bipartisan support for this inter-agency program has resulted in more than a decade's worth of scientific accomplishment. "Because there is considerable uncertainty in current understanding of how the climate system varies naturally and reacts to emissions of greenhouse gases and aerosols, current estimates of the magnitude of future warming should be regarded as tentative and subject to future adjustments (either upward or downward). Reducing the wide range of uncertainty inherent in current model predictions of global climate change will require major advances in understanding and modeling of both (1) the factors that determine atmospheric concentrations of greenhouse gases and aerosols, and (2) the so-called 'feedbacks' that determine the sensitivity of the climate system to a prescribed increase in greenhouse gases. There is also a pressing need for a global system designed for monitoring climate. Climate projections will always be far from perfect. Confidence limits and probabilistic information, with their basis, should always be considered as an integral part of the information that climate scientists provide to policy- and decision-makers. Without them, the IPCC SPM [Summary for Policymakers] could give the impression that the science of global warming is 'settled,' even though many uncertainties still remain. The emission scenarios used by the IPCC provide a good example. Human dimensions will almost certainly alter emissions over the next century. Because we cannot predict either the course of human populations, technology, or societal transitions with any clarity, the actual greenhouse gas emissions could either be greater or less than the IPCC scenarios. Without an understanding of the sources and degree of uncertainty, decision makers could fail to define the best ways to deal with the serious issue of global warming

Shifting Gears : 20 Tools for Reducing Global Warming Pollution from New England\u27s Transportation System

https://digitalmaine.com/nrcm_reports/1003/thumbnail.jp

A bivariate extension of the Hosking and Wallis goodness-of-fit measure for regional distributions

This study presents a bivariate extension of the goodness-of-fit measure for regional frequency distributions developed by Hosking and Wallis [1993] for use with the method of L-moments. Utilising the approximate joint normal distribution of the regional L-skewness and L-kurtosis, a graphical representation of the confidence region on the L-moment diagram can be constructed as an ellipsoid. Candidate distributions can then be accepted where the corresponding theoretical relationship between the L-skewness and L-kurtosis intersects the confidence region, and the chosen distribution would be the one that minimises the Mahalanobis distance measure. Based on a set of Monte Carlo simulations it is demonstrated that the new bivariate measure generally selects the true population distribution more frequently than the original method. Results are presented to show that the new measure remains robust when applied to regions where the level of inter-site correlation is at a level found in real world regions. Finally the method is applied to two different case studies involving annual maximum peak flow data from Italian and British catchments to identify suitable regional frequency distributions

Strength and ductility demands on wind turbine towers due to earthquake and wind load

In earthquake prone areas, wind and earthquake loads are assumed to be statistically uncorrelated, therefore their interaction is ignored by existing design guidelines. However, the fact that strong earthquake events are commonly followed by aftershocks and that wind is constantly flowing at high speeds around wind farms increase the probability of their joint occurrence, thus making current design assumptions questionable. This investigation shows that multi-hazard scenarios magnify strength demands of wind turbine towers designed against isolated load conditions, hence modifying their performance level. It is also shown that, under certain conditions, the probabilities associated to the joint occurrence of earthquake and low to strong wind events match or exceed those related to the original design, thus rendering wind energy infrastructure susceptible to unforeseen damage

The influence of substrate and vegetation configuration on green roof hydrological performance

A four-year record of rainfall and runoff data from nine different extensive (80 mm substrate) green roof test beds has been analysed to establish the extent to which the substrate composition and vegetation treatment affect hydrological performance. The test beds incorporated three different substrate components with different porosity and moisture retention characteristics, and three different vegetation treatments (Sedum, Meadow Flower and unvegetated). Consistent differences were observed, with the vegetated beds showing higher levels of rainfall retention and better detention compared with unvegetated beds. The seasonal Meadow Flower beds had similar hydrological performance to Sedum-vegetated beds. There was a 27% performance reduction in annual volumetric retention attributable to differences in substrate and vegetation. The beds with the most porous/permeable substrates showed the lowest levels of both retention and detention. As with previous studies, retention efficiency in all nine beds showed a strong dependency on rainfall depth (P), with retention typically >80% for events where P < 10 mm, but significantly lower when P > 10 mm. The effects of vegetation and substrate were most evident for rainfall events where P > 10 mm, with the mean per-event retention varying between beds from 26.8% to 61.8%. On average, the test beds were able to retain the first 5 mm of rainfall in 65% of events where P > 5 mm, although this ranged from 29.4% to 70.6% of events depending on configuration. In terms of detention, all but one of the test beds could achieve runoff control to a green field runoff equivalent of 2 l/s/ha for more than 75% of events. Detention was also characterised via the calibration of a reservoir-routing modelthatlinked net rainfall to the measured runoff response. The parameter values identified here – when combined with a suitable evapotranspiration/retention model – provide a generic mechanism for predicting the runoff response to a time-series or design rainfall for any unmonitored system with comparable components, permitting comparison against local regulatory requirements