The effects of surcharged manholes on the travel time and dispersion of solutes in sewer systems

1995 ◽  
Vol 31 (7) ◽  
pp. 51-59 ◽  
Author(s):  
Ian Guymer ◽  
Rob O'Brien
Keyword(s):  
Travel Time ◽  
Moment Method ◽  
In Situ Measurements ◽  
Time Change ◽  
Longitudinal Dispersion ◽  
Laboratory System ◽  
Environmental Load ◽  
Hydraulic Characteristics ◽  
Sewer Systems

Previously, the design of sewer systems has been limited to studies of their hydraulic characteristics, in particular the ability of the system to convey the maximum discharge. Greater environmental awareness has necessitated that new designs, and some existing schemes, are assessed to determine the environmental load which the scheme will deliver to any downstream component. This paper describes a laboratory programme which has been designed to elucidate the effects of manholes on the longitudinal dispersion of solutes. A laboratory system is described, which allows in situ measurements to be taken of the concentration of a fluorescent solute tracer, both up- and down-stream of a surcharged manhole junction. Results are presented from a preliminary series of studies undertaken for a single manhole geometry over a range of discharges, with varying levels of surcharge. Results are presented showing the variation of travel time, change in second moment of the distribution and of a dispersion factor with surcharge, assuming a Taylor approach and determining the dispersion factor using a ‘change in moment’ method. The effect of the stored volume within the manhole is clearly evident. The limitations and the applicability of this approach are discussed.

The Carbon:²³⁴Thorium ratios of sinking particles in the California Current Ecosystem 2: Examination of a thorium sorption, desorption, and particle transport model

2019 ◽  
Author(s):  
Michael Stukel ◽  
Thomas Kelly
Keyword(s):  
Organic Carbon ◽  
Water Column ◽  
Particulate Organic Carbon ◽  
Transport Model ◽  
California Current ◽  
In Situ Measurements ◽  
Power Law Distribution ◽  
Sinking Particles ◽  
Organic Carbon Concentration

Thorium-234 (234Th) is a powerful tracer of particle dynamics and the biological pump in the surface ocean; however, variability in carbon:thorium ratios of sinking particles adds substantial uncertainty to estimates of organic carbon export. We coupled a mechanistic thorium sorption and desorption model to a one-dimensional particle sinking model that uses realistic particle settling velocity spectra. The model generates estimates of 238U-234Th disequilibrium, particulate organic carbon concentration, and the C:234Th ratio of sinking particles, which are then compared to in situ measurements from quasi-Lagrangian studies conducted on six cruises in the California Current Ecosystem. Broad patterns observed in in situ measurements, including decreasing C:234Th ratios with depth and a strong correlation between sinking C:234Th and the ratio of vertically-integrated particulate organic carbon (POC) to vertically-integrated total water column 234Th, were accurately recovered by models assuming either a power law distribution of sinking speeds or a double log normal distribution of sinking speeds. Simulations suggested that the observed decrease in C:234Th with depth may be driven by preferential remineralization of carbon by particle-attached microbes. However, an alternate model structure featuring complete consumption and/or disaggregation of particles by mesozooplankton (e.g. no preferential remineralization of carbon) was also able to simulate decreasing C:234Th with depth (although the decrease was weaker), driven by 234Th adsorption onto slowly sinking particles. Model results also suggest that during bloom decays C:234Th ratios of sinking particles should be higher than expected (based on contemporaneous water column POC), because high settling velocities minimize carbon remineralization during sinking.

Evaluation of reanalysis and satellite-based sea surface winds using in situ measurements from Chinese Antarctic Expeditions

2013 ◽  
Vol 24 (3) ◽  
pp. 147
Author(s):  
Ming LI ◽  
Qinghua YANG ◽  
Jiechen ZHAO ◽  
Lin ZHANG ◽  
Chunhua LI ◽  
...  
Keyword(s):  
In Situ Measurements ◽  
Sea Surface ◽  
Surface Winds ◽  
Sea Surface Winds

In Situ Measurements of Coherent Structures and Turbulence

2009 ◽  
Author(s):  
W. R. Geyer ◽  
John Trowbridge
Keyword(s):  
Coherent Structures ◽  
In Situ Measurements

scholarly journals Development of the Statistical Model for Monitoring Salinization in the Mekong Delta of Vietnam Using Remote Sensing Data and In-Situ Measurements

Proceedings ◽  
2018 ◽  
Vol 2 (10) ◽  
pp. 565
Author(s):  
Nguyen Nguyen Vu ◽  
Le Van Trung ◽  
Tran Thi Van
Keyword(s):  
Statistical Model ◽  
Mekong Delta ◽  
Remote Sensing Data ◽  
Principal Component ◽  
Measured Data ◽  
In Situ Measurements ◽  
Landsat 8 ◽  
Spectral Bands ◽  
Component Band

This article presents the methodology for developing a statistical model for monitoring salinity intrusion in the Mekong Delta based on the integration of satellite imagery and in-situ measurements. We used Landsat-8 Operational Land Imager and Thermal Infrared Sensor (Landsat- 8 OLI and TIRS) satellite data to establish the relationship between the planetary reflectance and the ground measured data in the dry season during 2014. The three spectral bands (blue, green, red) and the principal component band were used to obtain the most suitable models. The selected model showed a good correlation with the exponential function of the principal component band and the ground measured data (R2 > 0.8). Simulation of the salinity distribution along the river shows the intrusion of a 4 g/L salt boundary from the estuary to the inner field of more than 50 km. The developed model will be an active contribution, providing managers with adaptation and response solutions suitable for intrusion in the estuary as well as the inner field of the Mekong Delta.

Reviewing Fundamental CO2 Adsorption Characteristics of Zeolite and Activated Carbon by In-situ Measurements With Radioactively Labelled CO2

2021 ◽  
pp. 1-12
Author(s):  
Yimin Deng ◽  
Jonathan Peter Kyle Seville ◽  
Sarah Dawn Bell ◽  
Andrew Ingram ◽  
Huili Zhang ◽  
...  
Keyword(s):  
Activated Carbon ◽  
Co2 Adsorption ◽  
In Situ Measurements ◽  
Adsorption Characteristics

scholarly journals Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation

2021 ◽  
Author(s):  
Mark D. Risser ◽  
Michael F. Wehner ◽  
John P. O’Brien ◽  
Christina M. Patricola ◽  
Travis A. O’Brien ◽  
...  
Keyword(s):  
Climate Variability ◽  
Extreme Precipitation ◽  
Southern Oscillation ◽  
Statistical Significance ◽  
In Situ Measurements ◽  
Climate Indices ◽  
Natural Climate Variability ◽  
Modes Of Variability ◽  
Natural Climate

AbstractWhile various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of how these physical phenomena simultaneously influence precipitation in the observational record across the contiguous United States. In this work, we introduce a single framework for characterizing the historical signal (anthropogenic forcing) and noise (natural variability) in seasonal mean and extreme precipitation. An important aspect of our analysis is that we simultaneously isolate the individual effects of seven modes of variability while explicitly controlling for joint inter-mode relationships. Our method utilizes a spatial statistical component that uses in situ measurements to resolve relationships to their native scales; furthermore, we use a data-driven procedure to robustly determine statistical significance. In Part I of this work we focus on natural climate variability: detection is mostly limited to DJF and SON for the modes of variability considered, with the El Niño/Southern Oscillation, the Pacific–North American pattern, and the North Atlantic Oscillation exhibiting the largest influence. Across all climate indices considered, the signals are larger and can be detected more clearly for seasonal total versus extreme precipitation. We are able to detect at least some significant relationships in all seasons in spite of extremely large (> 95%) background variability in both mean and extreme precipitation. Furthermore, we specifically quantify how the spatial aspect of our analysis reduces uncertainty and increases detection of statistical significance while also discovering results that quantify the complex interconnected relationships between climate drivers and seasonal precipitation.

scholarly journals Mapping High Spatiotemporal-Resolution Soil Moisture by Upscaling Sparse Ground-Based Observations Using a Bayesian Linear Regression Method for Comparison with Microwave Remotely Sensed Soil Moisture Products

2021 ◽  
Vol 13 (2) ◽  
pp. 228
Author(s):  
Jian Kang ◽  
Rui Jin ◽  
Xin Li ◽  
Yang Zhang
Keyword(s):  
Soil Moisture ◽  
Large Scale ◽  
Spatial Scales ◽  
Microwave Remote Sensing ◽  
In Situ Measurements ◽  
Spatial Density ◽  
Linear Regression Method ◽  
Spatiotemporal Resolution ◽  
Pixel Scale

In recent decades, microwave remote sensing (RS) has been used to measure soil moisture (SM). Long-term and large-scale RS SM datasets derived from various microwave sensors have been used in environmental fields. Understanding the accuracies of RS SM products is essential for their proper applications. However, due to the mismatched spatial scale between the ground-based and RS observations, the truth at the pixel scale may not be accurately represented by ground-based observations, especially when the spatial density of in situ measurements is low. Because ground-based observations are often sparsely distributed, temporal upscaling was adopted to transform a few in situ measurements into SM values at a pixel scale of 1 km by introducing the temperature vegetation dryness index (TVDI) related to SM. The upscaled SM showed high consistency with in situ SM observations and could accurately capture rainfall events. The upscaled SM was considered as the reference data to evaluate RS SM products at different spatial scales. In regard to the validation results, in addition to the correlation coefficient (R) of the Soil Moisture Active Passive (SMAP) SM being slightly lower than that of the Climate Change Initiative (CCI) SM, SMAP had the best performance in terms of the root-mean-square error (RMSE), unbiased RMSE and bias, followed by the CCI. The Soil Moisture and Ocean Salinity (SMOS) products were in worse agreement with the upscaled SM and were inferior to the R value of the X-band SM of the Advanced Microwave Scanning Radiometer 2 (AMSR2). In conclusion, in the study area, the SMAP and CCI SM are more reliable, although both products were underestimated by 0.060 cm3 cm−3 and 0.077 cm3 cm−3, respectively. If the biases are corrected, then the improved SMAP with an RMSE of 0.043 cm3 cm−3 and the CCI with an RMSE of 0.039 cm3 cm−3 will hopefully reach the application requirement for an accuracy with an RMSE less than 0.040 cm3 cm−3.

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