scholarly journals Assessing dry weather flow contribution in TSS and COD storm events loads in combined sewer systems

2011 ◽  
Vol 63 (12) ◽  
pp. 2983-2991 ◽  
Author(s):  
M. Métadier ◽  
J. L. Bertrand-Krajewski
Keyword(s):  
Time Series ◽  
Oxygen Demand ◽  
Seasonal Effect ◽  
Storm Events ◽  
Combined System ◽  
Time Step ◽  
Urban Catchment ◽  
Sewer Systems ◽  
Continuous Discharge

Continuous high resolution long term turbidity measurements along with continuous discharge measurements are now recognised as an appropriate technique for the estimation of in sewer total suspended solids (TSS) and Chemical Oxygen Demand (COD) loads during storm events. In the combined system of the Ecully urban catchment (Lyon, France), this technique is implemented since 2003, with more than 200 storm events monitored. This paper presents a method for the estimation of the dry weather (DW) contribution to measured total TSS and COD event loads with special attention devoted to uncertainties assessment. The method accounts for the dynamics of both discharge and turbidity time series at two minutes time step. The study is based on 180 DW days monitored in 2007–2008. Three distinct classes of DW days were evidenced. Variability analysis and quantification showed that no seasonal effect and no trend over the year were detectable. The law of propagation of uncertainties is applicable for uncertainties estimation. The method has then been applied to all measured storm events. This study confirms the interest of long term continuous discharge and turbidity time series in sewer systems, especially in the perspective of wet weather quality modelling.

From mess to mass: a methodology for calculating storm event pollutant loads with their uncertainties, from continuous raw data time series

2011 ◽  
Vol 63 (3) ◽  
pp. 369-376 ◽  
Author(s):  
M. Métadier ◽  
J. -L. Bertrand-Krajewski
Keyword(s):  
Time Series ◽  
Oxygen Demand ◽  
Software Tool ◽  
Large Data ◽  
Sensor Calibration ◽  
Storm Event ◽  
Storm Events ◽  
Time Step ◽  
Raw Data ◽  
Sewer Systems

With the increasing implementation of continuous monitoring of both discharge and water quality in sewer systems, large data bases are now available. In order to manage large amounts of data and calculate various variables and indicators of interest it is necessary to apply automated methods for data processing. This paper deals with the processing of short time step turbidity time series to estimate TSS (Total Suspended Solids) and COD (Chemical Oxygen Demand) event loads in sewer systems during storm events and their associated uncertainties. The following steps are described: (i) sensor calibration, (ii) estimation of data uncertainties, (iii) correction of raw data, (iv) data pre-validation tests, (v) final validation, and (vi) calculation of TSS and COD event loads and estimation of their uncertainties. These steps have been implemented in an integrated software tool. Examples of results are given for a set of 33 storm events monitored in a stormwater separate sewer system.

Modelling of overflow emissions in flanders

1998 ◽  
Vol 38 (10) ◽  
pp. 41-48 ◽  
Author(s):  
G. Vaes ◽  
J. Berlamont
Keyword(s):  
Time Series ◽  
Storm Events ◽  
Short Time Series ◽  
Hydrodynamic Simulations ◽  
Sewer Systems ◽  
Linear Behaviour ◽  
Long Time ◽  
Short Time ◽  
Different Characteristics

Ideally, for emission calculations long term hydrodynamic simulations should be performed, but this requires long calculation times. Simplifications are consequently necessary. Due to the non-linear behaviour of sewer systems, hydrodynamic simulations using single storm events often will not lead to a good probability estimation of the overflow emissions. Simplified models using long time simulations give better results if they are well calibrated. To increase the accuracy hydrodynamic simulations with short time series can be used. The short time series are selected from the long time historical rainfall series using a simplified model. To test the accuracy of these three methods, hydrodynamic long term simulations were performed for several (small) sewer systems with different characteristics to compare with.

scholarly journals Evaluating Simple Methodology for Piezoelectric Level Sensors Protection

Proceedings ◽  
2019 ◽  
Vol 48 (1) ◽  
pp. 30
Author(s):  
Luis Hamilton Pospissil Garbossa ◽  
Argeu Vanz ◽  
Matias Guilherme Boll ◽  
Hamilton Justino Vieira
Keyword(s):  
Water Level ◽  
Flood Control ◽  
Low Cost ◽  
Solid Particles ◽  
Storm Events ◽  
Sewer Systems ◽  
Continuous Monitor ◽  
Level Monitoring ◽  
Water Level Monitoring

The increasing frequency of extreme storm events has implications for the operation of sewer systems, storm water, flood control monitoring and tide level variations. Accurate and continuous monitor water level monitoring is demanded in different environments. Piezoelectric sensors are widely used for water level monitoring and work submerged in waters subject to the presence of solid particles, biological fouling and saltwater oxidation. This work aimed to develop a simple, low-cost methodology to protect sensors over long-term deployment. The results show that simple actions, costing less than 2 EUR, can protect and extend the lifecycle of equipment worth over 2000 EUR, ensuring continuous monitoring and maintaining quality measurements.

scholarly journals The Analogue Method for Precipitation Forecasting: Finding Better Analogue Situations at a Sub-Daily Time Step

2016 ◽  
Author(s):  
Pascal Horton ◽  
Charles Obled ◽  
Michel Jaboyedoff
Keyword(s):  
Time Series ◽  
Atmospheric Circulation ◽  
Time Window ◽  
Heavy Precipitation ◽  
Seasonal Effect ◽  
Precipitation Series ◽  
Time Step ◽  
Analogue Method ◽  
The Impact ◽  
Daily Time

Abstract. The Analogue Method (AM) aims at forecasting local weather variables (predictands), such as precipitations, by means of a statistical relationship with predictors at a synoptic scale. The analogy is generally assessed in the first place on the geopotential field by mean of a comparison of the gradients, in order to sample the days with a similar atmospheric circulation. The search for candidate situations, for a given target day, is usually undertaken by comparing the state of the atmosphere at fixed hours of the day, for both the target day and the candidate analogues. The constraint being the use of daily time series, due to the length of available archives they provide, and the unavailability of equivalent archives at a finer time step. However, it is unlikely that the best analogy happens at the very same hour, but it may occur at a different time of the day. In order to assess the potential of finding better analogues at a different hour, a moving time window (MTW) has been introduced on a reduced archive of hourly precipitation totals. The MTW resulted in a better analogy in terms of the atmospheric circulation, with improved values of the analogy criteria on the whole distribution of analogue dates. The improvement was found to grow with the analogue ranks due to an accumulation of more similar situations in the selection. Moreover, the improvement is even more important for days with heavy precipitation events, which are generally related to more dynamic atmospheric situations, where timing is more specific. A seasonal effect has also been identified, with larger improvements in winter than in summer, supposedly due to the stronger effect of the diurnal cycle in summer, which favors predictors at the same hour for target and analogues. The impact of the MTW on the prediction performance has been assessed by means of a sub-daily precipitation series transformed into moving 24 h-totals at a 6-hourly time step. This resulted in an improvement of the prediction skills, which were even larger after recalibrating the AM parameters. However, attempts to reconstruct longer precipitation series of running 24 h-totals by means of simple methods failed. It emphasized the need to use time series with an appropriate chronology. These should be available in a near future, either by means of growing observed archives, or by the establishment of precipitation reanalyses through regional modeling. Then, the use of a MTW in the AM should be considered for any application, especially when the prediction quality of extreme events is important.

Dissolved Oxygen Balance Model for Neris

2001 ◽  
Vol 6 (1) ◽  
pp. 105-131 ◽  
Author(s):  
Gaudenta
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Dissolved Oxygen ◽  
Biochemical Oxygen Demand ◽  
Oxygen Demand ◽  
Point Sources ◽  
Balance Model ◽  
Oxygen Balance ◽  
Source Data

We consider a dissolved oxygen balance model for Neris, which includes biochemical oxygen demand, nitrification, sedimentation, algae respiration and photosynthesis. The load from point sources, tributaries and distributed sources are taken into account. Long-term systematic components such as drift and seasonal components are analysed by applying time series analysis. The model is adapted according to the State Environmental Monitoring, and source data of controlled pollution covering the period 1978-1998.

Seventy-seven years of natural disturbances in a mountain forest area — the influence of storm, snow, and insect damage analysed with a long-term time series

2008 ◽  
Vol 38 (8) ◽  
pp. 2249-2261 ◽  
Author(s):  
Marc Hanewinkel ◽  
Johannes Breidenbach ◽  
Till Neeff ◽  
Edgar Kublin
Keyword(s):  
Time Series ◽  
Forest Structure ◽  
Forest Damage ◽  
Mountain Forest ◽  
Natural Disturbances ◽  
Storm Events ◽  
Insect Outbreaks ◽  
Planted Forests ◽  
Risk Processes

We investigated the effects of site properties, forest structure, and time on snow breakage, insect outbreaks, windthrow, and total damage for predominantly planted forests. A time series of forest damage in southwestern Germany spanning 77 years, from 1925 to 2001, was available along with a database on site properties and forest structure. The statistical modeling procedure successively addressed (i) probability of damage occurrence, (ii) timber loss in damaging events, and (iii) interaction among damage agents over time. Logistic and linear regressions were combined with multivariate autoregressive techniques. Natural disturbances were responsible for a total timber loss of 3.0 m3· ha–1· year–1. The distribution of the timber loss values over the years and over sites and stands with different properties was modeled with a standard error of 6.7 m3· ha–1· year–1. Disturbances are more likely to occur in previously damaged stands. Storm events typically provoke subsequent insect outbreaks between 2 and 6 years later. Large windthrow and snow breakage events tend to occur periodically, once every 10th, 11th, or 15th year. Analysis of disturbances as a time series significantly enhances understanding of forest risk processes.

Modelling Stormwater Quality of an Arid Urban Catchment

2015 ◽  
Vol 735 ◽  
pp. 215-219 ◽  
Author(s):  
A.O. Hussein ◽  
Shamsuddin Shahid ◽  
K.N. Basim ◽  
Shreeshivadasan Chelliapan
Keyword(s):  
Treatment Plan ◽  
Sewage Treatment ◽  
Oxygen Demand ◽  
Urban Catchment ◽  
Storm Water Management Model ◽  
Pollution Loading ◽  
Stormwater Pollution ◽  
Very High

Understanding quality of stormwater is important for effective urban rainwater treatment planning and management. In this study, the quality of stormwater runoff from an arid urban residential catchment located in the Karbala city of Iraq, draining through stormwater sewers was investigated. The Storm Water Management Model (SWMM) was used to estimate the concentrations of pollutants in stormwater and wastewater in the sewer networks. The results showed that the concentrations of the Biological Oxygen Demand (BOD5) and Total Suspended Solids (TSS) increased significantly after rain in the study area. The increase of TSS was very high compared to the BOD5. It is expected that the long-term simulations of stormwater pollution loading will help to compare the benefits of different scenarios of the sewage treatment plan for the reduction of the pollution in the storm discharge area.

scholarly journals Impact of Combined Sewer Systems on the Quality of Urban Streams: Frequency and Duration of Elevated Micropollutant Concentrations

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 850 ◽  
Author(s):  
Ulrich Dittmer ◽  
Anna Bachmann-Machnik ◽  
Marie A. Launay
Keyword(s):  
Aquatic Organisms ◽  
Urban Streams ◽  
Base Flow ◽  
Storm Events ◽  
Urban Catchment ◽  
Mixing Ratios ◽  
Sewer Systems ◽  
Wwtp Effluent ◽  
Wide Range ◽  
Combined Sewer

Water quality in urban streams is highly influenced by emissions from WWTP and from sewer systems particularly by overflows from combined systems. During storm events, this causes random fluctuations in discharge and pollutant concentrations over a wide range. The aim of this study is an appraisal of the environmental impact of micropollutant loads emitted from combined sewer systems. For this purpose, high-resolution time series of river concentrations were generated by combining a detailed calibrated model of a sewer system with measured discharge of a small natural river to a virtual urban catchment. This river base flow represents the remains of the natural hydrological system in the urban catchment. River concentrations downstream of the outlets are simulated based on mixing ratios of base flow, WWTP effluent, and CSO discharge. The results show that the standard method of time proportional sampling of rivers does not capture the risk of critical stress on aquatic organisms. The ratio between average and peak concentrations and the duration of elevated concentrations strongly depends on the source and the properties of the particular substance. The design of sampling campaigns and evaluation of data should consider these characteristics and account for their effects.

scholarly journals Building long-term and high spatio-temporal resolution precipitation and air temperature reanalyses by mixing local observations and global atmospheric reanalyses: the ANATEM method

2015 ◽  
Vol 12 (1) ◽  
pp. 311-361 ◽  
Author(s):  
A. Kuentz ◽  
T. Mathevet ◽  
J. Gailhard ◽  
B. Hingray
Keyword(s):  
Time Series ◽  
Temporal Resolution ◽  
Air Temperature ◽  
Large Scale ◽  
Precipitation Time Series ◽  
Time Step ◽  
Spatial Homogeneity ◽  
Temperature And Precipitation ◽  
Spatio Temporal

Abstract. Improving the understanding of past climatic or hydrologic variability has received a large attention in different fields of geosciences, such as glaciology, dendrochronology, sedimentology or hydrology. Based on different proxies, each research community produces different kind of climatic or hydrologic reanalyses, at different spatio-temporal scales and resolution. When considering climate or hydrology, numerous studies aim at characterising variability, trends or breaks using observed time-series of different regions or climate of world. However, in hydrology, these studies are usually limited to reduced temporal scale (mainly few decades, seldomly a century) because they are limited to observed time-series, that suffers from a limited spatio-temporal density. This paper introduces a new model, ANATEM, based on a combination of local observations and large scale climatic informations (such as 20CR Reanalysis). This model allow to build long-term air temperature and precipitation time-series, with a high spatio-temporal resolution (daily time-step, few km2). ANATEM was tested on the air temperature and precipitation time-series of 22 watersheds situated on the Durance watershed, in the french Alps. Based on a multi-criteria and multi-scale diagnostic, the results show that ANATEM improves the performances of classical statistical models. ANATEM model have been validated on a regional level, improving spatial homogeneity of performances and on independent long-term time-series, being able to capture the regional low-frequency variabilities over more than a century (1883–2010).

Influence of local calibration on the quality of online wet weather discharge monitoring: feedback from five international case studies

2014 ◽  
Vol 71 (1) ◽  
pp. 45-51 ◽  
Author(s):  
Nicolas Caradot ◽  
Hauke Sonnenberg ◽  
Pascale Rouault ◽  
Günter Gruber ◽  
Thomas Hofer ◽  
...  
Keyword(s):  
Online Monitoring ◽  
Oxygen Demand ◽  
Storm Events ◽  
Local Calibration ◽  
Combined Sewer Overflows ◽  
Measured Concentration ◽  
Representative Sampling ◽  
Sewer Systems ◽  
Wet Weather

This paper reports about experiences gathered from five online monitoring campaigns in the sewer systems of Berlin (Germany), Graz (Austria), Lyon (France) and Bogota (Colombia) using ultraviolet–visible (UV–VIS) spectrometers and turbidimeters. Online probes are useful for the measurement of highly dynamic processes, e.g. combined sewer overflows (CSO), storm events, and river impacts. The influence of local calibration on the quality of online chemical oxygen demand (COD) measurements of wet weather discharges has been assessed. Results underline the need to establish local calibration functions for both UV–VIS spectrometers and turbidimeters. It is suggested that practitioners calibrate locally their probes using at least 15–20 samples. However, these samples should be collected over several events and cover most of the natural variability of the measured concentration. For this reason, the use of automatic peristaltic samplers in parallel to online monitoring is recommended with short representative sampling campaigns during wet weather discharges. Using reliable calibration functions, COD loads of CSO and storm events can be estimated with a relative uncertainty of approximately 20%. If no local calibration is established, concentrations and loads are estimated with a high error rate, questioning the reliability and meaning of the online measurement. Similar results have been obtained for total suspended solids measurements.

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