Comparison of Flow Measurement Techniques 139Sydney, and in a 1 m wide rectangular flume at the River Hydraulics and Hydrology Section of the Civil Engineering Research Institute of the
Trang 1Comparison of Flow Measurement Techniques 139
Sydney, and in a 1 m wide rectangular flume at the River Hydraulics and Hydrology Section of the Civil Engineering Research Institute of the Hokkaido Development Bureau in Japan Many of these tests were done over long periods involving a range of flows, and for all these tests the average error between the ADFM flow measurement and those of the laboratory rating or dye was less than 2 %
The ADFM has been found to be highly accurate in a wide range of tests without at-site calibration The disadvantage of the ADFM is moderately high cost (three to four times that of Doppler AVFMs) When choosing between AVFMs and the ADFM the potential cost of inaccurate measurements should be weighed against the extra cost of the ADFM One case where high accuracy was sought was the Thames Tideway Study of the large combined sewers from the London, UK, area that drain into the Thames River for which 18 ADFMs were deployed and have provided high
accuracy at sites with very complex hydraulics (Curling et al., 2003).
2.2.7 COMPARISON OF FLOW MEASUREMENT
TECHNIQUES
In 1995, the US Geological Survey (USGS) in cooperation with the Federal Highway Administration outfitted a 61 m length of straight, 137 cm diameter, 0.2 % slope, concrete storm-sewer pipe in Madison (WI, USA) with multiple instruments for the purpose of comparing these instruments The details and results of this study
are briefly summarized in Church et al (1999) However, additional details of this
field test were obtained as a written communication from D.W Owens of the USGS Wisconsin Water Science Center (D.W Owens, personal communication, 1998) Because this field test involved three of the previously discussed flow measurement techniques it is presented as a separate section
Owens (D.W Owens, personal communication, 1998) reported that the test site had the following characteristics that are typical of storm sewer locations where discharge monitoring may be desired:
(1) The concrete pipe sections had settled different depths creating pipe joints that acted as minor controls during lower flow conditions As the water level increased, the smaller controls were drowned out
(2) The flow conditions at the site change rapidly because of the small drainage area (77.7 ha), high amount of impervious surface, and intense summer rainstorms (3) Access to the pipe is limited creating a hazardous condition when the pipe is flowing
(4) Standard discharge measurements are nearly impossible to collect because of the access and rapidly changing flow
He also noted that the site was subject to relatively minor sediment loads
Trang 2140 Sewer Flow Measurement
The standard for judging the accuracy of the flows obtained from the various measurement techniques was a MPB flume (Kilpatrick and Kaehrle, 1986) that had been rated using 243 dye-dilution flow measurements over a flow range of 0.057 to 2.32 m3/s (hereafter referred to as ‘the measurement standard’) The average percent-age error in the dye dilution discharge calculations was estimated as 4 % with a range from 1 to 14 % (D.W Owens, personal communication, 1998) Fifty runoff events were monitored during a 6-month period and the resulting hydrographs and total storm runoff volumes obtained with the flow measurement techniques were com-pared with those obtained with the measurement standard The flow measurement techniques evaluated included:
(1) Critical-flow flumes in the form of the theoretical rating for the MPB flume (2) Manning’s equation applied at three locations in the study pipe
(3) AVFMs–Automated Data Systems (ADS), ISCO 4250, and American Sigma
950 Doppler AVFMs and Marsh–McBirney Flow-Tote electromagnetic AVFM
Data were collected at 1 min intervals for all meters except the ADS meter for which
a 2.5 min interval was used The meters were placed in series in the pipe
The comparisons of the measured hydrographs revealed the following (D.W Owens, personal communication, 1998):
(1) The hydrographs obtained from the AVFMs are noisier than hydrographs ob-tained with the measurement standard Inspection of the data showed that this resulted from erratic velocity measurements
(2) The AVFMs had periodic velocity dropouts wherein the velocity measurement dropped down to a value that was much lower than the previous and following measurements
(3) At higher flows (>0.4 m3/s), the Doppler AVFMs tended to underestimate the flow At lower stages, the Doppler signal tended to work better These results are indicative of the range bias for deeper flows that is common for the Doppler AVFMs
(4) The electromagnetic AVFM tended to be the closest to the measurement stan-dard Furthermore, the electromagnetic velocity measurements displayed less noise than the Doppler measurements
(5) The theoretical discharge for the MPB flume closely matched the measurement standard
(6) The Manning equation technique produced mixed results based on monitoring location in the pipe
Box plots were made of the percentage differences between the results of the various techniques/equipment and the measurement standard for the total storm
Trang 3Conclusions and Perspectives 141
runoff volume (Church et al., 1999) Table 2.2.1 was prepared using the same data used to prepare Figure 7 in Church et al (1999), which was provided by D.W Owens
of the USGS Wisconsin Water Science Center The comparison of the total storm volumes in Table 2.2.1 yielded the following results:
(1) The electromagnetic AVFM yielded the best overall results with a median error
of 0.4 % and an interquartile range of−9.4 to 4.4 %
(2) The theoretical rating of the MPB flume also yielded good results with a median error of+10.8 % and an interquartile range of 2.7 to 17.9 %
(3) All uncorrected Doppler AVFMs underestimated total storm volumes with me-dian errors ranging from−6.6 to −28.8 % and mean errors ranging from −10.1
to−30.5 % Again an indicator of the range bias for deeper flows
(4) One of the Manning’s equation sites was affected by backwater resulting in a median error of nearly 100 % Another Manning’s equation site was affected by drawdown resulting in 25 % of the storms having underestimates greater than
30 % The final Manning’s equation site was not affected by either backwater
or drawdown and had a median error of 24.4 % and an interquartile range of
−0.4 to 36.8 %
It is difficult to derive general results from measurement comparisons at one site,
but Church et al (1999) raised two important conclusions from this study The data
clearly indicate the need to calibrate the flow measurement device using measure-ments obtained with an independent method Further, although flow measurement techniques can be adjusted using verification data to minimize bias, the very large uncertainty in flow measurements exhibited by some of the flow measurement tech-niques is likely to remain after the adjustments
2.2.8 CONCLUSIONS AND PERSPECTIVES
Many methods are available for measurement of flow in sewerage systems Flumes have been available since the 1930s, and electromagnetic and acoustic methods for velocity measurement have been used since the 1970s and 1980s, respectively During these long periods of use, manufacturers and users have fine-tuned the equipment so that reliable measurements may be obtained in real-time by telephone line or radio transmission If real-time data are desired, users must pay special attention to the accessibility of the site to power and phone lines or radio transmission to a central station
All the flow measurement equipment is capable of yielding accurate discharges for the appropriate hydraulic conditions (although the range of appropriate conditions for Manning’s equation is quite limited) Flumes, electromagnetic flow meters and ADFMs have been found to yield high accuracy (within±5 %) for a wide range
of flow conditions However, flumes and electromagnetic meters may be difficult
Trang 4142
Trang 5References 143
to install at some locations ADFMs are easier to install, but are more costly than acoustic Doppler area–velocity flow meters Thus, users must consider site condi-tions, cost, use of the data, and desired accuracy when selecting the appropriate flow meter for the project at hand
Probes for measuring dissolved oxygen concentration, conductivity and temper-ature in real-time are commonly used in treatment plants and stream systems Their use in sewerage systems has been limited due to the possibility of damage by debris
in the confined space of the sewer pipe and the difficulty to keep the probes clean in the harsh sewer environment Other probes for measuring nutrients and other chem-ical constituents in real-time are in development As these probes are improved, development of ways to use them in sewerage systems could be very valuable and
is encouraged as a topic of future research and development
REFERENCES
Alley, W.M (1977) Guide for Collection, Analysis, and Use of Urban Stormwater Data: A Con-ference Report, Easton, MD, 28 Novembar–3 December 1976 ASCE.
Anon (1996) World Water Environ Eng., April, 36.
Baughen, A.J and Eadon, A.R (1983) J Inst Water Poll Cont., 82(1), 77–86.
B¨orzs¨onyi, A (1982) Advances in Hydrometry, IAHS Publ No 134, 19–23.
Church, P.E., Granato, G.E and Owens, D.W (1999) Basic Requirements for Collecting, Documenting, and Reporting Precipitation and Stormwater-Flow Measurements US Geo-logical Survey Open-File Report 99–255.
Curling, T., Leafe, M., and Metcalfe, M (2003) Avoiding the Pitfalls of Dynamic Hydraulic Con-ditions with Real-Time Data Available online at http://www.mgdinc.com/pdfs/Thames%20 Tideway%20Hydraulic%20Results.pdf.
Day, T.J (1996) Water Eng Manage., 143(4), 22–24.
Diskin, M (1977) J Irrig Drain Div., ASCE, 102(IR3), 383–387.
Doney, B (1999a) Water Eng Manage., 146(11), 32–34.
Doney, B (1999b) Water Eng Manage., 146(11), 11–12.
Drake, T (1994) Water Eng Manage., 141(12), 34.
Hager, W.H (1989) J Irrig Drain., ASCE, 114(3), 520–534.
Hughes, A.W., Longair, I.M., Ashley, R.M and Kirby, K (1996) Water Sci Technol., 33(1), 1–12 Hunter, R.M., Hunt, W.A., and Cunningham, A.B (1991) Water Environ Technol., 3(2), 47–51 Huth, S (1998) Water Technol., 21, 78–80.
Johnson, E.H (1995) Water SA, 21(2), 131–138.
Kilpatrick, F.A and Kaehrle, W.R (1986) Trans Res Rec., 1073, 1–9.
Lanfear, K.J and Coll, J.J (1978) Water Sewage Works, 125(3), 68–69.
Ludwig, R.G and Parkhurst, J.D (1974) J WPCF, 46(12), 2764–2769.
Marsalek, J (1973) Instrumentation for Field Studies of Urban Runoff Research Program for the Abatement of Municipal Pollution Under the Provisions of the Canada-Ontario Agreement on Great Lakes Water Quality, Ontario Ministry of the Environment, Project 73-3-12.
Melching, C S and Yen, B.C (1986) Slope influence on storm sewer risk In Stochastic and Risk Analysis in Hydraulic Engineering, B C Yen, ed Water Resources Publications, Littleton, CO,
pp 79–89.
Trang 6144 Sewer Flow Measurement
Metcalf, M.A and Edelh¨auser, M (1997) Development of a velocity profiling Doppler flow meter for use in the wastewater collection and treatment industry Paper Presented at WEFTEC
’97, available on-line at: http://www.mgdinc.com/pdfs/WEFTEC%20’97%20Velocity%20 Profiling%20for%20 Wastewater%20Collection%20and%20Treatment.pdf.
Newman, J.D (1982) Proc Int Symp Hydrometeorology, 15–26.
Palmer, H.K and Bowlus, F.D (1936) Adaptation of Venturi flumes to flow measurements in
conduit Trans ASCE, 101, 1195–1216.
Parr, A.D., Judkins, J.F., and Jones, T.E (1981) J WPCF, 53(1), 113–118.
Soroko, O (1973) Water and waste flow measurement TAPPI (Atlanta, GA) Engineering Confer-ence, Boston, MA, 9 October 1973 (Preprinted Proceedings), pp 187–203.
Valentin, F (1981) Water Sci Technol., 13(8), 81–87.
Waite, A.M., Hornewer, N and Johnson, G.P (2002) Monitoring and Analysis of Combined Sewer
Overflows, Riverside and Evanston, Illinois, 1997–99 US Geological Survey Water-Resources Investigations Report 01-4121.
Watt, I.A and Jefferies, C (1996) Water Sci Technol., 33(1), 127–137.
Wells, E.A and Gotaas, H.D (1958) Design of Venturi flumes in circular conduits Trans ASCE,
123, 749–771.
Wenzel Jr., H.G (1975) J Hydr Div., ASCE, 101(HY1), 115–133.
Weyand, M (1996) Water Sci Technol., 33(1), 257–265.
Wright, J.D (1991) Water Environ Technol., 3(9), 78–87.
Trang 7Monitoring in Rural Areas
Ann van Griensven and V´eronique Vandenberghe
2.3.1 Introduction
2.3.1.1 Monitoring for the European Union Water Framework Directive 2.3.1.2 Characterisation of Rural Areas and Pollution
2.3.1.3 Joint Use of Modelling and Monitoring 2.3.2 A Case Study
2.3.2.1 The Dender River in Flanders, Belgium 2.3.2.2 The Model Using ESWAT
2.3.2.3 Sensitivity Analysis 2.3.2.4 Uncertainty Analysis 2.3.2.5 Discussion
2.3.3 Automated Monitoring
2.3.3.1 Automated Monitoring Stations 2.3.3.2 The Control of the Station – GSM Communication 2.3.3.3 The Control of the Station – Internet Communication 2.3.3.4 Maintenance and Calibration
2.3.3.5 Discussion 2.3.4 Conclusions and Perspectives
References
Wastewater Quality Monitoring and Treatment Edited by P Quevauviller, O Thomas and A van der Beken
C
2006 John Wiley & Sons, Ltd ISBN: 0-471-49929-3
Trang 8146 Monitoring in Rural Areas
2.3.1 INTRODUCTION
2.3.1.1 Monitoring for the European Union Water
Framework Directive
Recently the European Union has approved the European Union Water Framework Directive (EU WFD) This directive claims that by the end of 2015 a ‘good status
of surface water’ and a ‘good status of groundwater’ should be achieved (European Union, 2000) To make sure that the new water policy will succeed, a profound analysis of the actual and future state of the water is necessary In this context, the evaluation of emissions into river water will be important
To that end, the EU WFD provides several guidelines for monitoring the water bodies, leaving the practical implementation to the local governments Since urban pollution has been strongly reduced in many western countries by collection and treatment of the urban wastewater, the remaining water quality problems require advanced management and optimisation techniques in an integrated manner ‘Inte-grated’ is a term with many interpretations, but also a dangerous term to be used Whereas ‘integrated water management’ at first referred to a holistic approach that linked the sewer–wastewater treatment plant–river systems, it soon became apparent that goals of good water quality were not reached, causing awareness that some other sources of pollution were involved Indeed, after large investments to reduce urban pollution, managers were confronted with pollution from rural areas (Figure 2.3.1)
Figure 2.3.1 Sources of pollution in a river basin
Trang 9Introduction 147
2.3.1.2 Characterisation of Rural Areas and Pollution
Rural areas should not necessarily be considered as pollutant areas Not-intensive grazing for instance has beneficial effects on erosion reduction and does not cause excessive nutrient loads to the receiving systems In Europe, evolution towards more intensive practices took place during the past decades and has caused an increase of nutrient release into the environment (Poirot, 1999) Under the Common Agricultural Policy of the EU, the Gross Value Added (GVA) of the agricultural sector has raised sharply over the last 25 years This was mainly due to increased investments giving
in increase in the volume of production (Barthelemy and Vidal, 1999) The measures have generally led to a reduction of permanent grassland in favour of wheat, maize, the appearance of oilseed and protein crops and annual crops as fodder Livestock production has also followed a trend to intensification, where small extensive hold-ings are replaced by modern and specialised ones These ‘nonland-bound’ farms
resulted in a considerable growth in the livestock sector (Boschma et al., 1999).
In particular, pig husbandry constitutes the most intensive type The intensification
in livestock production and crop culture has led to a high application of nutrients
to agricultural land Livestock manure is the second most important source in the
EU The Netherlands and Belgium had the highest input of nitrogen from manure per hectare coming mostly from pig production (Pau Val and Vidal, 1999) Within European soils, 115 million hectares suffer from water erosion and 42 million hectares from wind erosion (Montarella, 1999)
Most agricultural activities are considered to be nonpoint sources This is not the case for the large ‘nonland-bound’ farms that are agricultural enterprises where a large number of animals are kept and raised in confined areas The feed is generally brought to the animals, rather than the animals grazing or otherwise seeking feed in pastures, fields or rangeland Such activities are treated in a similar manner to other industrial sources of pollution Whereas point-source pollution can be measured by monitoring the discharge and the water quality, diffuse pollution sources are very difficult to monitor because the sources are distributed along the river
2.3.1.3 Joint Use of Modelling and Monitoring
An integrated approach with regard to the nonpoint and diffuse pollution creates new challenges for monitoring and modelling, but it also promotes the interaction between these two The water bodies are highly complex systems as they hold many unknowns and uncertainties due to the incomplete understanding of the processes,
to scaling aspects and to the high variability of the variables in time and space Consequently, it is not possible to develop one perfect model or to design an optimal monitoring network with present information and knowledge An adaptive approach
is therefore needed: besides linking available data and thereby improving the concep-tual understanding of the water system, models may indicate errors and inadequacies
in the monitoring network Conversely, the model is revised and updated as new data
Trang 10148 Monitoring in Rural Areas
become available The effects of a pollution load into the river can be evaluated using models, especially for diffuse pollution, coming from rural areas, because complete monitoring of diffuse pollution input is impossible Due to the characteristics of such
a pollution that comes from land use practices, fertiliser and pesticide use, these are subject to different processes like runoff, leakage to groundwater, uptake by plants, conversion in the soil and absorption by soil particles All these can be modelled, however, for several reasons those model outputs are uncertain (Beck, 1987) Model outcome uncertainties can become very large due to:
rinput uncertainty;
rmodel uncertainty;
runcertainty in the estimated model parameter values;
rmathematical uncertainty.
Therefore, estimating and calculating the diffuse pollution to a river can be subject
to large input uncertainties, so in this chapter we will focus on monitoring with a view to making the input uncertainties of a model that calculates diffuse pollution towards a river smaller To optimally allocate the efforts necessary to reduce those input uncertainties, it is useful to evaluate the sensitivity of the outputs, the water quality, to the different inputs needed for calculation of diffuse pollution
In this study we focus on the diffuse pollution of nitrate in the water due to fertiliser use With the use of an efficient Monte Carlo method based on Latin Hypercube sampling (McKay, 1988), the contribution to the uncertainty by each of the inputs is calculated The methodology is applied to the Dender basin in Flanders, Belgium The following sections give a description of the river basin for the case study, the model environment and the applied methodology, which consists of a sensitivity
and uncertainty analysis based on the studies performed by Vandenberghe et al (Vandenberghe et al., 2005).
2.3.2 A CASE STUDY
2.3.2.1 The Dender River in Flanders, Belgium
The catchment of the river Dender has a total area of 1384 km2 and has an average discharge of 10 m3/s at its mouth Figure 2.3.2 shows how the Dender basin is situated in Flanders As about 90 % of the flow results from storm runoff and the point sources make very little contribution, the flow of the river is very irregular with high peak discharges during intensive rain events and very low flows during dry
periods (Bervoets et al., 1989) The river Dender is heavily polluted Part comes from
point-pollution (e.g industry) but also from diffuse sources of pollution originating mainly from agricultural activity Although there is an unmistakable relation between intensive agricultural activity and the occurrence of high nutrient concentrations in