COMPARISON OF DEMAND DRIVEN AND PRESSURE DEPENDENT HYDRAULIC APPROACHES FOR MODELLING WATER QUALITY IN DISTRIBUTION NETWORKS

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1 11 th Internatonal Conference on Computng and Control for the Water Industry, Exeter UK, 5-7 September 211 COMPARISON OF DEMAND DRIVEN AND PRESSURE DEPENDENT HYDRAULIC APPROACHES FOR MODELLING WATER QUALITY IN DISTRIBUTION NETWORKS Alemtsehay G. Seyoum, Tku T. Tanymboh and Calvn Sew Unversty of Strathclyde, Glasgow, Scotland, UK 1 alemtsehay.seyoum@strath.ac.uk, 2 tku.tanymboh@strath.ac.uk, 3 calvn.sew@strath.ac.uk Abstract Water dstrbuton hydraulc models have been used as a bass for water qualty modellng n dstrbuton networks. Experts recognzed that a realstc hydraulc model s requred to accurately smulate water qualty. The am of ths paper s to compare Demand Drven Analyss (DDA) and Pressure Dependent Analyss (PDA) based hydraulc models for smulatng water qualty n networks for future enhancement of water qualty models. The well known EPANET 2 and the newly developed (pressure dependent extenson) have been used as the DDA and PDA models respectvely. Water qualty analyss was performed for normal and pressure defcent hydraulc condtons on a sample network from lterature. The models provde dentcal results for normal pressure condtons, but dfferent results for pressure defcent condtons. The dfferences for the case of pressure defcent condton are sgnfcant at the farthest nodes from the source durng hgh pressure defcency stuaton wth low demand satsfacton condton. Keywords Demand drven analyss, pressure drven analyss, EPANET 2,, water qualty modellng, water dstrbuton network 1. INTRODUCTION One of the man concerns n drnkng water ndustry today s on mantanng water qualty n dstrbuton networks. Water qualty deterorates because of varous complex chemcal and mcrobologcal actvtes takng place n the dstrbuton system. One of the health concerns assocated wth water qualty problem for nstance s formaton of potentally carcnogenc dsnfecton by products (DBPs) due to reacton of dsnfectant wth organc and norganc substances n water. In order to predct and control water qualty the use of water qualty models has become vtal for water utltes. Water dstrbuton hydraulc models have been ntegrated wth water qualty models to smulate dfferent water qualty parameters. Nevertheless hydraulc models need to be hghly accurate before beng used n conjuncton wth water qualty models [1] and [2]. Demand Drven Analyss (DDA) and Pressure Dependent Analyss (PDA) are the two approaches to hydraulc modellng of a network. DDA assumes nodal flows are always satsfed at all demand nodes regardless of the avalable pressures at demand nodes [3]. Conversely PDA takes nto consderaton the pressure at demand nodes [4]. Several researchers emphaszed the robustness of PDA for ts capablty n provdng realstc results under dfferent pressure condtons [4], [5], [6] and [7] and crtczed the DDA approach due to ts lack of accuracy under pressure defcent condtons such as ppe bursts, pump falures, temporary demand ncrease and system mantenance and repar restrctons. The man purpose of ths paper s to compare DDA and PDA approaches for modellng water qualty n a network for future enhancement of water qualty models. The paper s part of a recently started research on Water Qualty Management and Optmzaton of Water Dstrbuton Systems. The well-known EPANET 2 and the newly developed [5] were used as DDA and PDA models respectvely. To exemplfy the capablty of DDA and PDA approaches a water qualty analyss was performed on a

2 sample network under dfferent pressure condtons. Durng the analyss effect of leakage was not consdered. Results from the two models are compared and presented heren. 2. HYDRAULIC AND WATER QUALITY APPROCHES EPANET 2 and are the two models used n the study as a DDA and PDA respectvely. EPANET- PDX s an extenson of EPANET 2 wth a contnuous nodal Pressure Dependent Demand Functon [8] ntegrated nto the Gradent Method [9] to form a model for both hydraulc and water qualty modellng of a network under dfferent pressure condtons durng extended tme perods. The Pressure Dependent Demand Functon [8] whch was ntegrated nto s: req exp( α + β Hn ) Qn ( Hn ) = Qn (1) 1+ exp( α + β Hn ) where Qn and Hn are the flow and head at node respectvely. Qn req s demand at node. α and β are parameters determned usng relevant feld data. The bass for ths functon, as descrbed n Fgure 1, s nodal demand s satsfed n full when nodal head s equal to or greater than the desred head and zero when the nodal head s equal to or lower than the mnmum head [4]. The demand satsfacton rato (DSR) s Qn (Hn )/Qn req DSR Nodal head ( m ) Fgure 1. Pressure dependent demand functon (node elevaton =45 m, desred head=6m) The governng equatons for EPANET 2 water qualty solver are based on the prncple of conservaton of mass coupled wth reacton knetcs [1]. follows the same prncple as t s developed n EPANET 2 envronment; however, the bass for ts hydraulc data needed for water qualty analyss s the ntegrated pressure dependent demand functon. The expressons for the conservatons of mass durng transport n ppes, mxng at junctons and mxng n storages facltes can be found n [1] and [12]. Detals on reacton rate expressons for modellng decay and growth of substances can be found n [1]. A Lagrangan tme based approach s used by EPANET 2 s water qualty solver to trace concentraton of a seres of segments of water n the dstrbuton network [1]. The concentraton of the segments s updated for any reacton that may have taken place over a tme step. The accuracy of the Lagrangan tme based approach s dependent on the choces of qualty tme step and concentraton tolerance [12]. The concentraton tolerance refers to the smallest change n concentraton that wll cause generaton of new segments of water n a ppe [1]. 62

3 3. EXAMPLE, RESULTS AND DISCUSSIONS Ths secton presents water qualty results obtaned from EPANET 2 and models for a steady state condton consderng both normal and pressure defcent hydraulc condtons. A sample network [13] whch s shown n Fgure 2 s used for demonstratng the results. The network conssts of a sngle source, 8 ppes of length 1m and 6 demand nodes. The requred resdual head for all nodes was predetermned to be 15 m. The mnmum heads for all nodes are taken to be equal to ther respectve elevatons; the desgn heads are equal to elevaton plus the requred resdual head of 15m. The source head was fxed at 9 m for normal pressure condton. Varous source heads (6m, 65 m, 7m and 75m) were consdered for pressure defcent condtons. Node Elevaton Demand (m) (l/s) Ppe Dameter (mm) C Fgure 2. Sample network The output of the water qualty analyss comprsed of water age [hrs], chlorne [ mg / L ] and Trhalomethane (THM) [ µ g / L ]. For reactons n bulk soluton and at ppe walls, the bulk and wall coeffcents were assumed 1[day -1 ] and 1.5[m/day] respectvely based on lterature [1]. For estmatng chlorne decay, a constant chlorne dose of 1[mg/L] was appled at the source. For estmatng THM concentraton, the lmtng concentraton was assumed to be 8[ µ g / L ] and the ntal concentratons at all nodes were taken to be equal to 2[ µ g / L ]. A 5 mnute qualty tme step, whch s much shorter than the mnmum travel tme n the network, was chosen for accurate smulaton. A zero concentraton tolerance has also been selected for accurate network smulaton. As the network used here s of small sze, consderng zero concentraton tolerance dd not affect the network computaton tme. Water qualty analyss was carred out usng EPANET 2 and models under normal pressure condton. The models provde dentcal results for all water qualty parameters,.e. water age, chlorne resdual and THM concentratons as ndcated n Fgures 3 and 4 below. 621

4 Age [hrs] EPANET 2 Fgure 3. Water age for normal pressure condton Chlorne [mg / L] EPANET 2 THM [ ug/l] EPANET 2 Fgure 4. Chlorne resduals and THM concentratons for normal pressure condton Pressure defcent condtons were created by reducng the source water level from 9 m to 75 m, 7 m, 65 m and 6 m to make the network satsfy only 92 %, 83%, 71% and 56 % of the total demand respectvely. Water qualty analyss for pressure defcent condtons ndcates that EPANET 2 gves the same result as ts normal pressure condtons. Ths llustrates EPANET 2 s ncapable of handlng the dfferent pressure condtons realstcally. By contrast consders the dfferent pressure condtons and provdes dfferent results for normal and pressure defcent condtons. The overall comparson of the models for pressure defcent condtons s ndcated n Fgures 5, 6 and 7 below. Results from show hgher values of water age, lower chlorne resdual and hgher THM concentraton n all nodes compared to EPANET 2. Ths s because of the occurrence of low flow condton n the system (Fgure 8) owng to the pressure defcency. The low flow condton creates longer resdence tme n the network and ultmately contrbutes to more chlorne depleton and hgh THM growth. It s worthwhle to see n Fgures 5, 6 and 7 that the dfferences n the model results of EPANET 2 and are sgnfcant at the farthest nodes from the source durng hgh pressure defcency wth low demand satsfacton condton. In fact nodes whch are far from the sources have normally long resdence tme n the network and thus requre accurate model predcton. Long resdence tme contrbutes to deteroraton of mcrobal and chemcal water qualty n the dstrbuton network. To verfy the accuracy of results for pressure defcent condton a hydraulc feasblty [14] check was carred out usng the actual nodal flows from as a new demand nput nto EPANET 2. Smulatons for source heads rangng from 4m to 8m were performed. Nodal heads obtaned from EPANET 2 were compared wth those of. A correlaton between the heads gves R 2 value of as t s shown n Fgure 9. Ths evdently confrms that results are accurate. 622

5 1 8 Age [hr] Fgure 5. Water age for pressure-defcent condtons Chlorne [mg/l] THM [ug/l] Fgure 6. Chlorne resduals for pressure-defcent condtons Fgure 7. THM concentratons for pressure-defcent condtons 75 Flow (l/s) Ppe ID Nodal heads (m)_ 7 R 2 = Nodal heads (m)_ EPANET 2 Fgure 8. Ppe flows for pressure-defcent condtons Fgure 9. Hydraulc feasblty check for source heads from 4m to 8m 623

6 4. CONCLUSIONS Comparson of EPANET 2 (DDA) and (PDA) models was performed for water qualty analyss of a network under normal and pressure defcent hydraulc condtons. The performance of the models was tested on a sample network and the study shows that both EPANET 2 and provde dentcal results under normal pressure condton but dfferent results durng pressure defcent condtons. The dfferences durng the pressure defcent condtons are sgnfcant at the farthest nodes from the source durng hgh pressure defcency stuaton wth low demand satsfacton condton. Acknowledgements The authors are grateful to the Brtsh Government (Overseas Research Students Awards Scheme) and the Unversty of Strathclyde for fundng the frst and thrd authors PhD programmes. References [1] P.M.R. Jonkergouw, S.-T. Khu, Z.S. Kapelan, and D.A. Savc, Water Qualty Model Calbraton under Unknown Demands, Journal of Water Resources Plannng and Management, vol. 134, no. 4, Jul. /Aug. 28, pp [2] J. Powell et al., Predctve Models for Water Qualty n Dstrbuton Systems. Denver, Colorado: AWWA Research Foundaton, 24. [3] P.R. Bhave and R. Gupta. Analyss of Water Dstrbuton Networks. 1st ed., Oxford, U.K: Alpha Scence Internatonal Ltd, 26. [4] T.T. Tanymboh and A.B Templeman, Seamless Pressure-Defcent Water Dstrbuton System Model, Journal of Water Management, vol. 163, no. 8, 21, pp [5] C. Sew and T.T. Tanymboh, Pressure-Dependent Epanet Extenson: Pressure-Dependent Demands, n Proc. 12 th Annual Water Dstrbuton Systems Analyss Conference, Tucson, Arzona, 21. [6] C.W. Baek, H.D. Jun, and J.H. Km, Development of a PDA Model for Water Dstrbuton Systems Usng Harmony Search Algorthm, KSCE Journal of Cvl Engneerng, vol. 14, no. 4, 21, pp [7] Z.Y. Wu, R.H. Wang, T. Walsk, S.Y. Yang, and D. Bowlder, Effcent Pressure Dependent Demand Model for Large Water Dstrbuton System Analyss, n Proc. 8 th Annual Internatonal Symposum on Water Dstrbuton System Analyss, Cncnnat, Oho, 26. [8] T.T. Tanymboh and A.B. Templeman, A New Nodal Outflow Functon for Water Dstrbuton Networks, n Pro. 4 th Internatonal Conf. on Eng. Computatonal Technology, Strlngshre, UK: Cvl-Comp Press, 24, pp. 12. [9] E. Todn and S. Plat, A gradent algorthm for the analyss of ppe networks, Computer Applcatons n Water Supply, Vol. 1, [1] L.A. Rossman, EPANET 2 Users Manual, Water Supply and Water Resources Dvson, Natonal Rsk Management Research Laboratory, Offce of Research and Development, U.S. Envronmental Protecton Agency, Cncnnat, Oho, 2. [11] T.T. Tanymboh, B. Tahar, and A.B. Templeman, Pressure-Drven Modellng of Water Dstrbuton Systems, Water Scence and Technology Water Supply, vol. 3, no. 1-2, 23, pp [12] L.A. Rossman and P.F. Boulos, Numercal Methods for Modellng Water Qualty n Dstrbuton Systems: A Comparson, Journal of Water Resources Plannng and Management, vol. 122, no 2, 1996, pp [13] O. Fujwara and T. Ganesharajah, Relablty Assessment of Water Supply Systems wth Storage and Dstrbuton Networks, Water Resources Research, vol. 29, no. 8, 1993, pp [14] J.R.L Ackley, T.T. Tanymboh, B. Tahar, and A.B. Templeman, Head Drven Analyss of Water Dstrbuton Systems, Water Software Systems: Theory and Applcatons, vol. 1, 21, Chapter 3: