Design of a retention tank: comparison of stormwater quality models with various levels of complexity

2006 ◽  
Vol 54 (6-7) ◽  
pp. 231-238 ◽  
Author(s):  
M. Mourad ◽  
J.-L. Bertrand-Krajewski ◽  
G. Chebbo
Keyword(s):  
Simulation Models ◽  
Data Sets ◽  
Calibration Data ◽  
Storm Events ◽  
Stormwater Quality ◽  
Event Mean Concentration ◽  
Transport Modelling ◽  
Detention Tank ◽  
Systems Modelling ◽  
Mean Concentration

Stormwater quality simulation models are useful tools for the design and management of sewer systems. Modelling results are highly sensitive to experimental data used for calibration. This sensitivity is examined for three modelling approaches of various complexities (site mean concentration approach, event mean concentration approach and build-up, washoff and transport modelling approach) applied to a typical case study (design of a dry detention tank), accounting for the variability of calibration data and their effect on simulation results. Calibrated models with different calibration data sets were used to simulate 3 years of rainfall with different retention tank specific volumes. Annual pollutant load interception efficiencies were determined. Simulations results revealed i) that there is no advantage in using the EMC model compared to the SMC model and ii) that the BWT model resulted in higher design ratios than those given by the SMC/hydraulic approach. For both EMC and BWT models, using an increasing number n of events for calibration leads to narrower confidence intervals for the design ratios. It is crucial for design ratios to account for successive storm events in chronological order and to account for the maximum allowable flow to be transferred to the downstream WWTP.

Calibration and validation of multiple regression models for stormwater quality prediction: data partitioning, effect of dataset size and characteristics

2005 ◽  
Vol 52 (3) ◽  
pp. 45-52 ◽  
Author(s):  
M. Mourad ◽  
J.-L. Bertrand-Krajewski ◽  
G. Chebbo
Keyword(s):  
Multiple Regression ◽  
Regression Models ◽  
Data Partitioning ◽  
Data Sets ◽  
Calibration Data ◽  
Stormwater Quality ◽  
Calibration And Validation ◽  
Multiple Regression Models ◽  
Dataset Size ◽  
Few Data

Two main issues regarding stormwater quality models have been investigated: i) the effect of calibration dataset size and characteristics on calibration and validation results; ii) the optimal split of available data into calibration and validation subsets. Data from 13 catchments have been used for three pollutants: BOD, COD and SS. Three multiple regression models were calibrated and validated. The use of different data sets and different models allows viewing general trends. It was found mainly that multiple regression models are case sensitive to calibration data. Few data used for calibration infers bad predictions despite good calibration results. It was also found that the random split of available data into halves for calibration and validation is not optimal. More data should be allocated to calibration. The proportion of data to be used for validation increases with the number of available data (N) and reaches about 35% for N around 55 measured events.

scholarly journals Quantifying the Effects of Residential Infill Redevelopment on Urban Stormwater Quality in Denver, Colorado

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 988
Author(s):  
Kyle R. Gustafson ◽  
Pablo A. Garcia-Chevesich ◽  
Kimberly M. Slinski ◽  
Jonathan O. Sharp ◽  
John E. McCray
Keyword(s):  
Water Quality ◽  
Green Infrastructure ◽  
Stormwater Quality ◽  
Dry Period ◽  
Event Mean Concentration ◽  
Fecal Indicator ◽  
Water Quality Regulations ◽  
First Flush Effect ◽  
Urban Stormwater Quality ◽  
Mean Concentration

Stormwater quality in three urban watersheds in Denver that have been undergoing rapid infill redevelopment for about a decade was evaluated. Sampling was conducted over 18 months, considering 15 storms. Results: (1) The first-flush effect was observed for nutrients and total suspended solids (TSS) but not for total dissolved solids (TDS), conductivity, pH, and fecal indicator bacteria; (2) though no significant differences on event mean concentration (EMC) values were found among the three basins, local-scale EMCs were higher than traditional city-wide standards, particularly some metals and nutrients, most likely because of the significantly higher imperviousness of the studied urban basins compared to city averages; (3) peak rainfall intensity and total rainfall depth showed significant but weak correlations with some nutrients and metals, and TDS; (4) antecedent dry period were not correlated with water quality, except for phosphorus and lead; (5) contrary to what was expected, total coliforms and Escherichia coli were not correlated with TSS; and (6) no significant correlations between water quality and land-use or zoning categories were found. It was concluded that locally focused stormwater monitoring can aid data-driven decision-making by city planners where redevelopment is occurring at local “neighborhood scales”, particularly for the implementation and management related to green infrastructure and water-quality regulations.

Stormwater pollutant loads modelling: epistemological aspects and case studies on the influence of field data sets on calibration and verification

2007 ◽  
Vol 55 (4) ◽  
pp. 1-17 ◽  
Author(s):  
Jean-Luc Bertrand-Krajewski
Keyword(s):  
Case Studies ◽  
Model Calibration ◽  
Current Practice ◽  
Data Sets ◽  
Stormwater Quality ◽  
Quality Models ◽  
Pollutant Loads ◽  
Detention Tank ◽  
Software Packages ◽  
Calibration And Verification

In urban drainage, stormwater quality models have been used by researchers and practitioners for more than 15 years. Most of them were initially developed for research purposes, and have been later on implemented in commercial software packages devoted to operational needs. This paper presents some epistemological problems and difficulties with practical consequences in the application of stormwater quality models, such as simplified representation of reality, scaling-up, over-parameterisation, transition from calibration to verification and prediction, etc. Two case studies (one to estimate pollutant loads at the outlet of a catchment, one to design a detention tank to reach a given pollutant interception efficiency), with simple and detailed stormwater quality models, illustrate some of the above problems. It is hard to find, if not impossible, an “optimum” or “best” unique set of parameters values. Model calibration and verification appear to dramatically depend on the data sets used for their calibration and verification. Compared to current practice, collecting more and reliable data is absolutely necessary.

Development of statistical linear regression model for metals from transportation land uses

2009 ◽  
Vol 59 (12) ◽  
pp. 2495-2501 ◽  
Author(s):  
Marla C. Maniquiz ◽  
Soyoung Lee ◽  
Eunju Lee ◽  
Lee-Hyung Kim
Keyword(s):  
Linear Regression ◽  
Urban Areas ◽  
Point Sources ◽  
Storm Events ◽  
Simple Linear Regression ◽  
Event Mean Concentration ◽  
Management Policies ◽  
Term Monitoring ◽  
Mean Concentration

The transportation landuses possessing impervious surfaces such as highways, parking lots, roads, and bridges were recognized as the highly polluted non-point sources (NPSs) in the urban areas. Lots of pollutants from urban transportation are accumulating on the paved surfaces during dry periods and are washed-off during a storm. In Korea, the identification and monitoring of NPSs still represent a great challenge. Since 2004, the Ministry of Environment (MOE) has been engaged in several researches and monitoring to develop stormwater management policies and treatment systems for future implementation. The data over 131 storm events during May 2004 to September 2008 at eleven sites were analyzed to identify correlation relationships between particulates and metals, and to develop simple linear regression (SLR) model to estimate event mean concentration (EMC). Results indicate that there was no significant relationship between metals and TSS EMC. However, the SLR estimation models although not providing useful results are valuable indicators of high uncertainties that NPS pollution possess. Therefore, long term monitoring employing proper methods and precise statistical analysis of the data should be undertaken to eliminate these uncertainties.

scholarly journals Determination of NPS Pollutant Unit Loads from Different Landuses

2021 ◽  
Vol 13 (13) ◽  
pp. 7193
Author(s):  
Jiyeon Choi ◽  
Baekyung Park ◽  
Jinsun Kim ◽  
Soyoung Lee ◽  
Jichul Ryu ◽  
...  
Keyword(s):  
Environmental Changes ◽  
Oxygen Demand ◽  
Runoff Coefficient ◽  
Forest Land ◽  
Event Mean Concentration ◽  
Rainfall Events ◽  
Total Phosphorous ◽  
Mean Concentration

This study aimed to estimate pollutant unit loads for different landuses and pollutants that reflected long-term runoff characteristics of nonpoint source (NPS) pollutants and recent environmental changes. During 2008–2014, 2026 rainfall events were monitored. The average values of antecedent dry days, total rainfall, rainfall intensity, rainfall duration, runoff duration, and runoff coefficient for each landuse were 3.8–5.9 d, 35.2–65.0 mm, 2.9–4.1 mm/h, 12.5–20.4 h, 12.4–27.9 h, and 0.24–0.45, respectively. Uplands (UL) exhibited high suspended solids (SS, 606.2 mg/L), total nitrogen (TN, 7.38 mg/L), and total phosphorous (TP, 2.27 mg/L) levels, whereas the runoff coefficient was high in the building sites (BS), with a high impervious surface ratio. The event mean concentration (EMC) for biological oxygen demand (BOD) was the highest in BS (8.0 mg/L), while the EMC was the highest in BS (in the rainfall range <10 mm) and UL and forest land (in the rainfall range >50 mm). The unit loads for BOD (1.49–17.76 kg/km2·d), TN (1.462–10.147 kg/km2·d), TP (0.094–1.435 kg/km2·d), and SS (15.20–327.70 kg/km2·d) were calculated. The findings can be used to manage NPS pollutants and watershed environments and implement relevant associated management systems.

scholarly journals EVALUATION OF THE INFLUENCE OF SOCIAL AND ECONOMIC DETERMINANTS ON THE STATE OF PUBLIC HEALTH ON THE BASIS OF MICROIMITATION MODELING

2017 ◽  
pp. 79-90
Author(s):  
Dmytro Shushpanov ◽  
Volodymyr Sarioglo
Keyword(s):  
Research Policy ◽  
Synthetic Data ◽  
Simulation Models ◽  
The State ◽  
Data Sets ◽  
Economic Determinants ◽  
Micro Simulation ◽  
State Employment ◽  
Health Research Policy ◽  
Main Determinants

In the article the essence and peculiarities of microimitational modeling are considered. The advantages of microimitational models over the statistics models are substantiated. Micro-simulation models, that prognosticate somehow dynamic changes in health and which are most appropriate to use in development and health research policy, such as POHEM, CORSIM and Sife Paths, are outlined. It is proposed to use elements of statistical and dynamic microimitation modeling, agent modeling and the concept of a life course for the estimation of the influence social and economic determinants. The synthetic model of population which has been formed on the basis of representative data sets of sample surveys of living conditions of households and economic activity of the population of the State Employment Service of Ukraine, as well as microdata of the Multicultural Survey of the Population of Ukraine (2012) and the Medical and Demographic Survey (2013). The generalized scheme of the method of microimulation modeling of the influence of social and economic determinants on the health status of the population of Ukraine has been developed. The influence of the main determinants on the health of certain age, gender and social and economic groups of the population is estimated on the basis of the methodology of synthetic data.

scholarly journals From pole to pole: 33 years of physical oceanography onboard R/V <i>Polarstern</i>

2017 ◽  
Vol 9 (1) ◽  
pp. 211-220 ◽  
Author(s):  
Amelie Driemel ◽  
Eberhard Fahrbach ◽  
Gerd Rohardt ◽  
Agnieszka Beszczynska-Möller ◽  
Antje Boetius ◽  
...  
Keyword(s):  
Data Collection ◽  
Water Cycle ◽  
Heat Budget ◽  
Ocean Dynamics ◽  
The Arctic ◽  
Sensor Calibration ◽  
Data Sets ◽  
Calibration Data ◽  
Data Set ◽  
Different Characteristics

Abstract. Measuring temperature and salinity profiles in the world's oceans is crucial to understanding ocean dynamics and its influence on the heat budget, the water cycle, the marine environment and on our climate. Since 1983 the German research vessel and icebreaker Polarstern has been the platform of numerous CTD (conductivity, temperature, depth instrument) deployments in the Arctic and the Antarctic. We report on a unique data collection spanning 33 years of polar CTD data. In total 131 data sets (1 data set per cruise leg) containing data from 10 063 CTD casts are now freely available at doi:10.1594/PANGAEA.860066. During this long period five CTD types with different characteristics and accuracies have been used. Therefore the instruments and processing procedures (sensor calibration, data validation, etc.) are described in detail. This compilation is special not only with regard to the quantity but also the quality of the data – the latter indicated for each data set using defined quality codes. The complete data collection includes a number of repeated sections for which the quality code can be used to investigate and evaluate long-term changes. Beginning with 2010, the salinity measurements presented here are of the highest quality possible in this field owing to the introduction of the OPTIMARE Precision Salinometer.

Exploring Earth's space environment with the GRACE-FO mission

2020 ◽  
Author(s):  
Claudia Stolle ◽  
Ingo Michaelis ◽  
Chao Xiong ◽  
Guram Kervalishvili ◽  
Lucas Schreiter ◽  
...  
Keyword(s):  
Space Environment ◽  
Local Times ◽  
Electron Content ◽  
Data Sets ◽  
Similar Data ◽  
Storm Events ◽  
Solar Cycles ◽  
Scientific Application ◽  
Total Electron ◽  
Orbit Control

&lt;p&gt;As part of its attitude and orbit control system, the GRACE-FO satellites carry vector magnetometers. After appropriate calibration and characterisation of artificial magnetic disturbances, the mean residual to the high precision magnetic models is below 1 nT during times of geomagnetic quiet conditions. Furthermore, navigational GPS observations are used to derived data of the total electron content integrated over the upper ionosphere and KBR data are used to derive in situ electron density. These observations are valuable assets to characterize the natural variability of Earth's magnetic field and its space environment. The performance of GRACE-FO magnetic and plasma data is discussed on selected scientific examples. E.g., during magnetic storm events, GRACE-FO, in a constellation with other satellites, reveals the local time dependence of the magnetospheric ring current signature, and monitors significant plasma density enhancements at low and high latitudes. It is further demonstrated that the dual-satellite constellation of GRACE-FO is most suitable to derive the persistence of auroral field-aligned currents with scale lengths of 180 km or longer.&lt;/p&gt; &lt;p&gt;The data derived from non-dedicated observations extends the scientific application areas of the GRACE-FO to space weather and monitoring. Together with similar data sets such as from CHAMP, GRACE, GOCE, and Swarm among others, magnetic and ionospheric monitoring over nearly two solar cycles is available at LEO for different local times or altitudes.&lt;/p&gt;

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