Relationship between background invertebrate drift concentration and flow over natural flow recession and prediction with a drift transport model

2019 ◽  
Vol 76 (6) ◽  
pp. 871-885 ◽  
Author(s):  
John W. Hayes ◽  
Eric O. Goodwin ◽  
Karen A. Shearer ◽  
D. Murray Hicks
Keyword(s):  
Transport Model ◽  
Low Flow ◽  
Invertebrate Drift ◽  
Transport Models ◽  
Drift Feeding ◽  
Class Level ◽  
Natural Flow ◽  
Flow Dependency ◽  
Taxonomic Groups ◽  
Negative Relationships

This study advances understanding of the flow dependency of invertebrate drift in rivers and its relevance to drift-feeding fish. Background drift concentration varied spatially and with flow over natural flow recession (lower mid-range to low flow) in a reach of a New Zealand river, largely consistent with passive entrainment. Seven taxonomic groups (dominated by Leptophlebiidae and Chironomidae) exhibited positive drift concentration–flow relationships, and one (sandy/stony-cased caddisflies (Conoesucidae)) exhibited negative relationships. A mechanistic drift transport model accurately predicted the slope, but not y intercept, of the drift concentration–flow relationship for the total drift community that positively responded to flow but performed more poorly at the taxon or size-class level. Partitioning the relative influence of drift entry and dilution revealed that positive drift concentration–flow relationships arose from entry overwhelming dilution with increasing flow. Drift transport models have potential for predicting relative (%) effects of flow change on concentration and rate of drift-prone invertebrates. This paves the way for drift transport models to inform inputs to net rate of energy intake models for drift-feeding fish.

The effect of the pool and riffle on dissolved, non-conservative mass transport in rivers

2013 ◽  
Vol 48 (3) ◽  
pp. 232-242
Author(s):  
Ian H. Halket ◽  
Peter F. Rasmussen ◽  
John C. Doering
Keyword(s):  
Transport Model ◽  
Low Flow ◽  
Transport Models ◽  
Cross Sectional ◽  
Lower Velocity ◽  
Regulatory Limits ◽  
Uniform Channel ◽  
River Reach ◽  
Model Equations ◽  
Sectional Shape

One-dimensional substance transport models assume that the river reach modelled has a uniform cross-sectional shape which manifests as a constant average velocity in the model equations. Rarely do rivers meet this criterion. Their channels are seldom uniform in shape but rather alternate in a quasi-periodic manner between pool and riffle sections. This bedform sequencing imparts a corresponding variation in the average cross-sectional velocity which is not accounted for in constant velocity transport models. The literature points out that the pool and riffle planform may be the reason for the sometimes poor predictions obtained from these models. This paper presents a new variable velocity transport model and confirms that the fluctuation in average cross-sectional velocity caused by the pool and riffle planform does have a marked effect on transport in rivers. The pool and riffle planform promotes an enhanced decay of a substance when a first-order biochemical reaction is simulated with the new transport equation. Investigation of the analytical solution shows that the enhanced decay is the result of the overall lower velocity experienced in a pool and riffle channel as opposed to a uniform channel. This difference in transport velocity between a pool and riffle channel and a uniform channel becomes more pronounced as flow declines a critical finding for total maximum daily load calculations because these regulatory limits are usually determined for low flow levels by models that do not account for this phenomenon.

scholarly journals Skill-Testing Chemical Transport Models across Contrasting Atmospheric Mixing States Using Radon-222

2018 ◽  
Author(s):  
Scott D. Chambers ◽  
Elise-Andree Guérette ◽  
Khalia Monk ◽  
Alan D. Griffiths ◽  
Yang Zhang ◽  
...  
Keyword(s):  
Air Quality ◽  
Diurnal Cycle ◽  
Transport Model ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Transport Models ◽  
Potential Health ◽  
Meteorological Model ◽  
Model Skill ◽  
Chemical Transport Models

We propose a new technique to prepare statistically-robust benchmarking data for evaluating chemical transport model meteorology and air quality parameters within the urban boundary layer. The approach employs atmospheric class-typing, using nocturnal radon measurements to assign atmospheric mixing classes, and can be applied temporally (across the diurnal cycle), or spatially (to create angular distributions of pollutants as a top-down constraint on emissions inventories). In this study only a short (<1-month) campaign is used, but grouping of the relative mixing classes based on nocturnal mean radon concentrations can be adjusted according to dataset length (i.e., number of days per category), or desired range of within-class variability. Calculating hourly distributions of observed and simulated values across diurnal composites of each class-type helps to: (i) bridge the gap between scales of simulation and observation, (ii) represent the variability associated with spatial and temporal heterogeneity of sources and meteorology without being confused by it, and (iii) provide an objective way to group results over whole diurnal cycles that separates ‘natural complicating factors’ (synoptic non-stationarity, rainfall, mesoscale motions, extreme stability, etc.) from problems related to parameterizations, or between-model differences. We demonstrate the utility of this technique using output from a suite of seven contemporary regional forecast and chemical transport models. Meteorological model skill varied across the diurnal cycle for all models, with an additional dependence on the atmospheric mixing class that varied between models. From an air quality perspective, model skill regarding the duration and magnitude of morning and evening “rush hour” pollution events varied strongly as a function of mixing class. Model skill was typically the lowest when public exposure would have been the highest, which has important implications for assessing potential health risks in new and rapidly evolving urban regions, and also for prioritizing the areas of model improvement for future applications.

scholarly journals Model – TCCON comparisons of column-averaged methane with a focus on the stratosphere

2016 ◽  
Author(s):  
Andreas Ostler ◽  
Ralf Sussmann ◽  
Prabir K. Patra ◽  
Sander Houweling ◽  
Marko De Bruine ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
Meteorological Data ◽  
Michelson Interferometer ◽  
Total Carbon ◽  
Data Sets ◽  
Transport Models ◽  
Improved Model ◽  
The Impact ◽  
Chemistry Experiment

Abstract. The distribution of methane (CH4) in the stratosphere can be a major driver of spatial variability in the dry-air column-averaged CH4 mixing ratio (XCH4), which is being measured increasingly for the assessment of CH4 surface emissions. Chemistry-transport models (CTMs) therefore need to simulate the tropospheric and stratospheric fractional columns of XCH4 accurately for estimating surface emissions from XCH4. Simulations from three CTMs are tested against XCH4 observations from the Total Carbon Column Network (TCCON). We analyze how the model-TCCON agreement in XCH4 depends on the model representation of stratospheric CH4 distributions. Model equivalents of TCCON XCH4 are computed with stratospheric CH4 fields from both the model simulations and from satellite-based CH4 distributions from MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) and MIPAS CH4 fields adjusted to ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) observations. In comparison to simulated model fields we find an improved model-TCCON XCH4 agreement for all models with MIPAS-based stratospheric CH4 fields. For the Atmospheric Chemistry Transport Model (ACTM) the average XCH4 bias is significantly reduced from 38.1 ppb to 13.7 ppb, whereas small improvements are found for the models TM5 (Transport Model, version 5; from 8.7 ppb to 4.3 ppb), and LMDz (Laboratoire de Météorologie Dynamique model with Zooming capability; from 6.8 ppb to 4.3 ppb), respectively. MIPAS stratospheric CH4 fields adjusted to ACE-FTS reduce the average XCH4 bias for ACTM (3.3 ppb), but increase the average XCH4 bias for TM5 (10.8 ppb) and LMDz (20.0 ppb). These findings imply that the range of satellite-based stratospheric CH4 is insufficient to resolve a possible stratospheric contribution to differences in total column CH4 between TCCON and TM5 or LMDz. Applying transport diagnostics to the models indicates that model-to-model differences in the simulation of stratospheric transport, notably the age of stratospheric air, can largely explain the inter-model spread in stratospheric CH4 and, hence, its contribution to XCH4. This implies that there is a need to better understand the impact of individual model transport components (e.g., physical parameterization, meteorological data sets, model horizontal/vertical resolution) on modeled stratospheric CH4.

Comparison of a Nonlinear k-ε Turbulence Closure Model With Stress Transport Models

1993 ◽  
Author(s):  
Muhammad A. R. Sharif ◽  
Yat-Kit E. Wong
Keyword(s):  
Pipe Flow ◽  
Flow Problem ◽  
Swirling Flow ◽  
Transport Model ◽  
Turbulent Pipe Flow ◽  
Turbulence Closure ◽  
Closure Model ◽  
Transport Models ◽  
Mean Velocity ◽  
Turbulence Closure Model

Abstract The performance of a nonlinear k-ϵ turbulence closure model (NKEM), in the prediction of isothermal incompressible turbulent flows, is compared with that of the stress transport models such as the differential Reynolds stress transport model (RSTM) and the algebraic stress transport model (ASTM). Fully developed turbulent pipe flow and confined turbulent swirling flow with a central non-swirling jet are numerically predicted using the Marker and Cell (MAC) finite difference method. Comparison of the prediction with the experiment show that all three models perform reasonably well for the pipe flow problem. For the swirling flow problem, the RSTM and ASTM is superior than the NKEM. RSTM and ASTM provide good agreement with measured mean velocity profiles. However, the turbulent stresses are over- or under-predicted. NKEM performs badly in prediction of mean velocity as well as the turbulent stresses.

scholarly journals A Method for the Evaluation of Urban Freight Transport Models as a Tool for Improving the Delivery of Sustainable Urban Transport Policy

2019 ◽  
Vol 11 (6) ◽  
pp. 1535 ◽  
Author(s):  
Daniel Kaszubowski
Keyword(s):  
Transport Model ◽  
Freight Transport ◽  
Urban Transport ◽  
Data Availability ◽  
Transport Models ◽  
Local Authorities ◽  
Strategic Objectives ◽  
Urban Freight ◽  
Urban Freight Transport ◽  
Freight Management

The article presents a method which helps local authorities to evaluate urban freight transport models. Given the complex requirements for input data and the inability to supply them for most cities, a proper quantitative evaluation of model functionality may be quite difficult for local authorities. Freight transport models designed to support sustainable urban freight transport objectives are a particular example. To overcome these difficulties, the structure of the method is based on a qualitative analysis of strategic and operational conditions of urban freight management for modelling purposes. A consistent set of criteria is developed to help with parameterising strategic objectives and the analytical requirements of tools to achieve those objectives. The problems of data availability and capture are also included. The method consists of three tiers that are arranged hierarchically to reflect the interrelations. The proposed method was verified against Gdynia’s (Poland) urban freight management requirements. The city was chosen for its early experience of urban freight studies and improvement measures and because it has already defined its strategic objectives. Two comprehensive freight transport models (Freturb and Wiver) and existing city’s transport model were evaluated. The results have ruled out the existing transport model rendering it ineffective as a tool to support urban freight management to meet the city’s strategic objectives. While Freturb turned out to be much better suited for the needs, dedicated models still face a basic barrier of cities having to redesign their systems for collecting urban transport data.

Modelling of the Transport of Chlorinated Hydrocarbon Solvents in Groundwater: A Case Study

1985 ◽  
Vol 17 (9) ◽  
pp. 13-21 ◽  
Author(s):  
W K. H. Kinzelbach
Keyword(s):  
Transport Model ◽  
Model Parameters ◽  
Dispersive Transport ◽  
Transport Models ◽  
Chlorinated Hydrocarbon ◽  
First Order ◽  
Hydrocarbon Solvents ◽  
Simplifying Assumptions ◽  
Environmental Engineer

At present chlorinated hydrocarbon solvents rank among the major pollutants found in groundwater. In the interpretation of field data and the planning of decontamination measures numerical transport models may be a valuable tool of the environmental engineer. The applicability of one such model is tested on a case of groundwater pollution by 1,1,1,-trichloroethane. The model is composed of a horizontally 2-D flow model and a 3-D ‘random-walk' transport model. It takes into account convective and dispersive transport as well as linear adsorption and a first order decay reaction. Under certain simplifying assumptions the model allows an adequate reproduction of observed concentrations. Due to uncertainty in data and limited comparabili ty of simulated and measured concentrations the model parameters can only be estimated within bounds. The decay rate of 1,1,1-trichloroethane is estimated to lie between 0 and 0.0005 l/d.

scholarly journals Characterizing uncertainties in atmospheric inversions of fossil fuel CO<sub>2</sub> emissions in California

2019 ◽  
Vol 19 (5) ◽  
pp. 2991-3006 ◽  
Author(s):  
Kieran Brophy ◽  
Heather Graven ◽  
Alistair J. Manning ◽  
Emily White ◽  
Tim Arnold ◽  
...  
Keyword(s):  
Fossil Fuel ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Temporal Distribution ◽  
Potential Effect ◽  
Spatial And Temporal Distribution ◽  
Transport Models ◽  
Total State ◽  
Pseudo Data ◽  
Atmospheric Inversions

Abstract. Atmospheric inverse modelling has become an increasingly useful tool for evaluating emissions of greenhouse gases including methane, nitrous oxide, and synthetic gases such as hydrofluorocarbons (HFCs). Atmospheric inversions for emissions of CO2 from fossil fuel combustion (ffCO2) are currently being developed. The aim of this paper is to investigate potential errors and uncertainties related to the spatial and temporal prior representation of emissions and modelled atmospheric transport for the inversion of ffCO2 emissions in the US state of California. We perform simulation experiments based on a network of ground-based observations of CO2 concentration and radiocarbon in CO2 (a tracer of ffCO2), combining prior (bottom-up) emission models and transport models currently used in many atmospheric studies. The potential effect of errors in the spatial and temporal distribution of prior emission estimates is investigated in experiments by using perturbed versions of the emission estimates used to create the pseudo-data. The potential effect of transport error was investigated by using three different atmospheric transport models for the prior and pseudo-data simulations. We find that the magnitude of biases in posterior total state emissions arising from errors in the spatial and temporal distribution in prior emissions in these experiments are 1 %–15 % of posterior total state emissions and are generally smaller than the 2σ uncertainty in posterior emissions. Transport error in these experiments introduces biases of −10 % to +6 % into posterior total state emissions. Our results indicate that uncertainties in posterior total state ffCO2 estimates arising from the choice of prior emissions or atmospheric transport model are on the order of 15 % or less for the ground-based network in California we consider. We highlight the need for temporal variations to be included in prior emissions and for continuing efforts to evaluate and improve the representation of atmospheric transport for regional ffCO2 inversions.

scholarly journals Mixing times of organic molecules within secondary organic aerosol particles: a global planetary boundary layer perspective

2017 ◽  
Author(s):  
Adrian M. Maclean ◽  
Christopher L. Butenhoff ◽  
James W. Grayson ◽  
Kelley Barsanti ◽  
Jose L. Jimenez ◽  
...  
Keyword(s):  
Organic Molecules ◽  
Secondary Organic Aerosol ◽  
Transport Model ◽  
Laboratory Data ◽  
Chemical Transport ◽  
Organic Aerosol ◽  
Mixing Times ◽  
Chemical Transport Model ◽  
Transport Models ◽  
Lack Of Information

Abstract. When simulating the formation and life cycle of secondary organic aerosol (SOA) with chemical transport models, it is often assumed that organic molecules are well mixed within SOA particles on the time scale of 1 h. While this assumption has been debated vigorously in the literature, the issue remains unresolved in part due to a lack of information on the mixing times within SOA particles as a function of both temperature and relative humidity. Using laboratory data, meteorological fields and a chemical transport model, we determine how often mixing times are

scholarly journals The importance of transport model uncertainties for the estimation of CO<sub>2</sub> sources and sinks using satellite measurements

2010 ◽  
Vol 10 (20) ◽  
pp. 9981-9992 ◽  
Author(s):  
S. Houweling ◽  
I. Aben ◽  
F.-M. Breon ◽  
F. Chevallier ◽  
N. Deutscher ◽  
...  
Keyword(s):  
Transport Model ◽  
Atmospheric Transport ◽  
A Priori ◽  
Model Errors ◽  
Tracer Transport ◽  
Satellite Measurements ◽  
Transport Models ◽  
Sources And Sinks ◽  
The Impact ◽  
Ppm Level

Abstract. This study presents a synthetic model intercomparison to investigate the importance of transport model errors for estimating the sources and sinks of CO2 using satellite measurements. The experiments were designed for testing the potential performance of the proposed CO2 lidar A-SCOPE, but also apply to other space borne missions that monitor total column CO2. The participating transport models IFS, LMDZ, TM3, and TM5 were run in forward and inverse mode using common a priori CO2 fluxes and initial concentrations. Forward simulations of column averaged CO2 (xCO2) mixing ratios vary between the models by σ=0.5 ppm over the continents and σ=0.27 ppm over the oceans. Despite the fact that the models agree on average on the sub-ppm level, these modest differences nevertheless lead to significant discrepancies in the inverted fluxes of 0.1 PgC/yr per 106 km2 over land and 0.03 PgC/yr per 106 km2 over the ocean. These transport model induced flux uncertainties exceed the target requirement that was formulated for the A-SCOPE mission of 0.02 PgC/yr per 106 km2, and could also limit the overall performance of other CO2 missions such as GOSAT. A variable, but overall encouraging agreement is found in comparison with FTS measurements at Park Falls, Darwin, Spitsbergen, and Bremen, although systematic differences are found exceeding the 0.5 ppm level. Because of this, our estimate of the impact of transport model uncerainty is likely to be conservative. It is concluded that to make use of the remote sensing technique for quantifying the sources and sinks of CO2 not only requires highly accurate satellite instruments, but also puts stringent requirements on the performance of atmospheric transport models. Improving the accuracy of these models should receive high priority, which calls for a closer collaboration between experts in atmospheric dynamics and tracer transport.

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