On the dissipation rate of temperature fluctuations in stably stratified flows

Environmental Fluid Mechanics - In this study, we explore several integral and outer length scales of turbulence which can be formulated by using the dissipation of temperature fluctuations (...     

Turbulent Prandtl number and characteristic length scales in stably stratified flows: steady-state analytical solutions

Environmental Fluid Mechanics - In this study, the stability dependence of turbulent Prandtl number ( $$Pr_t$$ ) is quantified via a novel and simple analytical approach. Based on the variance and...     

Uncertainty quantification of large-eddy simulation results of riverine flows: a field and numerical study

Environmental Fluid Mechanics - We present large-eddy simulations (LES) of riverine flow in a study reach in the Sacramento River, California. The riverbed bathymetry was surveyed in...     

Hydrodynamics of a periodically wind-forced small and narrow stratified basin: a large-eddy simulation experiment

Environmental Fluid Mechanics - We report novel results of a numerical experiment designed for examining the basin-scale hydrodynamics that control the mass, momentum, and energy distribution in a...     

Estimation of critical submergence for an intake in a stratified fluid media by neuro-fuzzy approach

Most of the large surface reservoirs are stably stratified throughout most or all of the year. One means of assisting in the management is to allow for the selective withdrawal from the reservoir. The value of the intake’s submergence when the upper layer fluids begin to be drawn into the intake is known as “critical submergence”. In this study, the critical submergence for a circular intake pipe in a stratified body is investigated. Experiments were conducted on a vertically flowing downward intake pipe in a still-water reservoir. Experimental results are compared with that of the neuro-fuzzy models.     

Dominant features in three-dimensional turbulence structure: comparison of non-uniform accelerating and decelerating flows

The results are presented from an experimental study to investigate three-dimensional turbulence structure profiles, including turbulence intensity and Reynolds stress, of different non-uniform open channel flows over smooth bed in subcritical flow regime. In the analysis, the uniform flow profiles have been used to compare with those of the non-uniform flows to investigate their time-averaged spatial flow turbulence structure characteristics. The measured non-uniform velocity profiles are used to verify the von Karman constant κ and to estimate sets of log-law integration constant B_r and wake parameter П, where their findings are also compared with values from previous studies. From κ, B_r and П findings, it has been found that the log-wake law can sufficiently represent the non-uniform flow in its non-modified form, and all κ, B_r and П follow universal rules for different bed roughness conditions. The non-uniform flow experiments also show that both the turbulence intensity and Reynolds stress are governed well by exponential pressure gradient parameter β equations. Their exponential constants are described by quadratic functions in the investigated β range. Through this experimental study, it has been observed that the decelerating flow shows higher empirical constants, in both the turbulence intensity and Reynolds stress compared to the accelerating flow. The decelerating flow also has stronger dominance to determine the flow non-uniformity, because it presents higher Reynolds stress profile than uniform flow, whereas the accelerating flow does not.     

Budgets of turbulent kinetic energy,Reynolds stresses,and dissipation in a turbulent round jet discharged into a stagnant ambient

Environmental Fluid Mechanics - This paper presents a set of stereoscopic particle image velocimetry (SPIV) measurements of a turbulent round water jet (jet exit Reynolds number $$Re = 2679$$ and...     

Contaminant transport in an unsaturated soil: laboratory tests and numerical simulation model as procedure for parameters evaluation

In this paper, lab tests coupled to a semi-pilot test section are used to derive data for the calibration of a numerical model. The paper is aimed at proposing a set of experiments, which can be used to calibrate a numerical model before using it on defined soils. The complexity of the phenomenon of transport of reactive pollutants in soil has to be faced in the most complete way. The different behaviour of soil after wet/dry cycles with respect to the fluidodynamic characteristics and the importance to consider the local biomass behaviour in case of organic contaminant has been underlined. An optimal approach has to take into account all the different components and here a simple series of experimental procedure is presented. The sensitivity analysis of the numerical model has shown that its results are not so much dependent on the classical numerical aspects (time or space increments) but mainly on a set of parameters related to soil structure which must then be derived through a good calibration.     

Modelling landscape effects on density-contact rate relationships of deer in eastern Alberta: Implications for chronic wasting disease

Managing wildlife diseases requires an understanding of disease transmission, which may be strongly affected by host population density and landscape features. Transmission models are typically fit from time-series disease prevalence data and modelled based on how the contact rate among hosts is affected by density, which is often assumed to be a linear (density-dependent transmission) or constant (frequency-dependent transmission) relationship. However, long-term time-series data is unavailable for emerging diseases, and this approach cannot account for independent effects of landscape. We developed a mechanistic model based on ecological data to empirically derive the contact rate-density relationship in white-tailed and mule deer in an enzootic region of chronic wasting disease (CWD) in Alberta, Canada and to determine whether it was affected by landscape. Using data collected from aerial surveys and GPS-telemetry, we developed empirical relationships predicting deer group size, home range size, and habitat selection to iteratively simulate deer distributions across a range of densities and landscapes. We calculated a relative measure of total per-capita contact rate, which is proportional to the number of other deer contacted per individual per unit time, for each distribution as the sum of pairwise contact rates between a target deer and all other individuals. Each pairwise contact rate was estimated from an empirical relationship developed from GPS-telemetry data predicting pairwise contact rates as a function of home range overlap and landscape structure. Total per-capita contact rates increased as a saturating function of density, supporting a transmission model intermediate between density- and frequency-dependent transmission. This pattern resulted from group sizes that reached an asymptote with increasing deer density, although this relationship was mediated by tree and shrub coverage in the landscape, such that in heavily wooded areas, the contact rate saturated at much lower densities. These results suggest that CWD management based on herd reductions, which require a density-dependent contact rate to be effective, may have variable effects on disease across a single management region. The novel mechanistic approach we employed for estimating effects of density and landscape on transmission is a powerful complement to typical data-fitting approaches for modelling disease transmission.     

Studying ecological communities from a neutral standpoint: A review of models’ structure and parameter estimation

Neutral models provide an alternative to niche-based assembly rules of ecological communities by assuming that communities’ properties are shaped by the stochastic interplay between ecological drift, migration and speciation. The recent and ongoing interest about neutral assumptions has produced many developments on the theoretical side, with nevertheless limited echoes in terms of analyses of real-world data. The present review paper aims to help bridge the widening gap between modellers and field ecologists through two objectives. First, to provide a multi-criteria typology of the main neutral models, including those from population genetics that have not yet been transposed to ecology, by considering how the fundamental processes of ecological drift, speciation and migration are modelled and, specifically, how space is taken into account. Second, to review methods recently proposed to estimate models parameters from field data, a point that should be mastered to allow for broader applications.     

Spatial structure and habitat associations of demersal assemblages in the Gulf of Lions: a multicompartmental approach

Experimental trawl surveys were performed in the Gulf of Lions. A multicompartmental approach was used to study the spatial distribution of demersal assemblages and to estimate their associations with two other components of the ecosystem: the benthic macrofauna and substratum type. At the Gulf scale, we found that these components explained 38 and 19% of the total variability of the spatial organization of groundfishes, respectively. Our results showed that groundfish and benthic macrofauna species were primarily distributed along a coast–open sea gradient and secondarily along a longitudinal axis. The longitudinal variability of the spatial organisation of species was maximal in the shelf area, whereas the upper-slope and coastal areas were characterized by strong homogeneity. Although no partitioning could be made based on their spatial distribution, the coastal groundfish assemblages were split into two groups. In the first group, groundfishes were strongly associated with both benthic macrofauna and type of substratum; in the second group, they were strongly independent of these two components. Furthermore, in the Gulf of Lions, the presence of productive zones associated with the Rhône river plume or with shelf-break upwelling seemed to attract some groundfishes. This study illustrates how useful such a multicompartmental approach can be for both fisheries management and community ecology.     

Development and environmental application of a genus-specific quantitative PCR approach for Pseudo-nitzschia species

Quantitative polymerase chain reaction (qPCR) for the identification and quantification of microbes has become a common tool for the study of harmful algal blooms (HABs). We developed a qPCR method for the diatom genus Pseudo-nitzschia. Several species of this genus form toxic blooms through the production of the neurotoxin domoic acid (DA). Outbreaks of toxicity attributed to DA along the US west coast have caused sickness and death of marine mammals and seabirds through food web contamination. The method developed here quantifies Pseudo-nitzschia spp. at low abundances in natural samples, thereby, providing a method to improve our understanding of the environmental conditions leading to blooms of these species. This has been accomplished previously by techniques for identification and quantification that are slow and laborious compared to qPCR. The approach was successfully tested and validated using eight species of Pseudo-nitzschia and 33 non-target organisms and employed to follow local bloom dynamics.     

Impact of energy structure adjustment on air quality: a case study in Beijing, China

Energy consumption is a major cause of air pollution in Beijing, and the adjustment of the energy structure is of strategic importance to the reduction of carbon intensity and the improvement of air quality. In this paper, we explored the future trend of energy structure adjustment in Beijing till 2020, designed five energy scenarios focusing on the fuel substitution in power plants and heating sectors, established emission inventories, and utilized the Mesoscale Modeling System Generation 5 (MM5) and the Models-3/Community Multiscale Air Quality Model (CMAQ) to evaluate the impact of these measures on air quality. By implementing this systematic energy structure adjustment, the emissions of PM₁₀, PM_2.5, SO₂, NO _x , and non-methane volatile organic compounds (NMVOCs) will decrease distinctly by 34.0%, 53.2%, 78.3%, 47.0%, and 30.6% respectively in the most coalintensive scenario of 2020 compared with 2005. Correspondingly, MM5-Models-3/CMAQ simulations indicate significant reduction in the concentrations of major pollutants, implying that energy structure adjustment can play an important role in improving Beijing??s air quality. By fuel substitution for power plants and heating boilers, PM₁₀, PM_2.5, SO₂, NO _x , and NMVOCs will be reduced further, but slightly by 1.7%, 4.5%, 11.4%, 13.5%, and 8.8% respectively in the least coal-intensive scenario. The air quality impacts of different scenarios in 2020 resemble each other, indicating that the potential of air quality improvement due to structure adjustment in power plants and heating sectors is limited. However, the CO₂ emission is 10.0% lower in the least coal-intensive scenario than in the most coal-intensive one, contributing to Beijing??s ambition to build a low carbon city. Except for energy structure adjustment, it is necessary to take further measures to ensure the attainment of air quality standards.     

Evaluation of spatiotemporal differences in suspended sediment concentration derived from remote sensing and numerical simulation for coastal waters

Remote sensing and numerical models are often used to monitor the suspended sediment concentration (SSC) in coastal waters; however, the derived SSC varies between the two methods in both space and time. In this study, a method was proposed to assess the spatiotemporal differences in SSC derived from Moderate Resolution Imaging Spectroradiometer (MODIS) images and numerical simulation for coastal waters, using the Bohai Sea in China as an example. An empirical model for SSC retrieval from remote sensed images was initially established. A comparison of the temporal synchronicity over a single day period was performed between the observed data and the numerically simulated results. The range in the SSC at different observation sites was significantly different. Both the SSC values and their daily variation ranges were larger near the estuary of the Yellow River compared with the open area due to the concurrence of tidal flow and the introduction of fresh river water with high turbidity near the estuary. The areas that exhibited spatial differences were defined according to their differences in remotely sensed and numerically simulated SSC distribution patterns. Finally, the reasons for these spatiotemporal differences were discussed. The results provided understanding into the spatiotemporal differences that were introduced when multi-source data were used, thus improving the accuracy of the results when monitoring coastal environments for the management of coastal conservation.     

Rice straw for energy and value-added products in China: a review

Environmental Chemistry Letters - The rise of global waste and the decline of fossil fuels are calling for recycling waste into energy and materials. For example, rice straw, a by-product of rice...     

Longleaf pine (Pinus palustris) and hardwood dynamics in a fire-maintained ecosystem: A simulation approach

Longleaf pine (Pinus palustris) savannas of the southeastern U.S. represent an archetype of a fire dependent ecosystem. They are known to have very short fire return intervals (∼1-3 years) that perpetuate understory plant diversity (up to 50 species m⁻²), support pine recruitment, and suppress fire sensitive hardwoods. Understanding the relationships that regulate longleaf and southern hardwoods is especially critical. With decreased fire frequency, insufficient intensity, or lack of underground competition, a woody mid-story rapidly develops, dominated by fire sensitive trees and shrubs that in-turn suppress more fire dependent species (including pine seedlings). This may occur in forest gaps, where pine-needle abundance is diminished, reducing fire spread potential. The interactions between longleaf pine, hardwoods, forest fuels, and fire frequency are complex and difficult to understand spatially. The objective of this study was to develop a spatially explicit longleaf pine-hardwood stochastic simulation model (LLM), incorporating tree demography, plant competition, and fuel and fire characteristics. Data from two longleaf pine study sites were used to develop and evaluate the model with the goal to incorporate simple site-specific calibration parameters for model versatility. Specific model components included pine seed masting, hardwood clonal sprouting, response to fire (re-sprouting, mortality), and tree density driven competition effects. LLM spatial outputs were consistent with observed forest gap dynamics associated with pine seedling establishment and hardwood encroachment. Changes in fire frequency (i.e., fire probability = 0.35-0.05) illustrated a shift in community structure from longleaf pine dominated to a hardwood dominated community. This approach to assessing model response may be useful in characterizing longleaf ecosystem resilience, especially at intermediate fire frequencies (e.g., 0.15) where the community may be sensitive to small changes in the fire regime. Height distributions and population densities were similar to in situ findings (field and LIDAR data) for both study sites. Height distributions output by the LLM illustrated fluctuations in population structure. The LLM was especially useful in determining knowledge gaps associated with fuel and fire heterogeneity, plant-plant interactions, population structure and its temporal fluctuations, and hardwood demography. This is the first known modeling work to simulate interactions between longleaf pine and hardwoods and provides a foundation for further studies on fire and forest management, especially in relation to ecological forestry practices, restoration, and site-specific applications.     

A simulation approach to evolutionary game theory: the evolution of time-sharing behaviour in a dragonfly mating system

Summary The time-sharing behaviour of dragonfly males (Aeschna cyanea, Odonata) at the mating place is investigated. By computer simulation of the males' interactions the expected number of copulations for different strategies is quantified. The simulation results show that a male's mating succes depends on his strategy and that a strategy's specific pay-off depends on the frequency distribution of strategies in the population. Based on these results, a method for the simulation of the evolutionary process is presented. This approach to evolutionary game theory allows the prediction of evolutionarily stable strategies (ESS), even when the system studied is far too complex for an analytical solution. For the time-sharing behaviour of Ac. cyanea males at the mating place the ESS predicted by the simulation approach complies with field observations.