Assessment of Water Quality Modelling Capabilities of EPANET Multiple Species and Pressure-Dependent Extension Models

Transcription

1 Assessment of Water Qualty Modellng Capabltes of EPANET Multple Speces and Pressure-Dependent Extenson Models Alemtsehay G. Seyoum, Tku T. Tanymboh and Calvn Sew Department of Cvl Engneerng, Unversty of Strathclyde Glasgow, John Anderson Buldng, 17 Rottenrow, Glasgow G4 NG, UK (Emal: Ths artcle was publshed n Water Scence and Technology: Water Supply. The fnal publcaton s avalable at: Assessment of water qualty modellng capabltes of EPANET multple speces and pressure-dependent extenson models Alemtsehay G. Seyoum, Tku T. Tanymboh, Calvn Sew Water Scence and Technology: Water Supply (213), 13(4), pages , DOI: /ws

2 Assessment of Water Qualty Modellng Capabltes of EPANET Multple Speces and Pressure Dependent Extenson Models Alemtsehay G. Seyoum, Tku T. Tanymboh and Calvn Sew Department of Cvl Engneerng, Unversty of Strathclyde Glasgow, John Anderson Buldng, 17 Rottenrow, Glasgow G4 NG, UK (Emal: Abstract The need for accurately predctng water qualty through models has ncreasngly been crucal n meetng rgorous standards and customer expectatons. There are several endeavours on developng robust water qualty models for water dstrbuton systems. In ths paper, two varants of the EPANET 2 water qualty model have been assessed to nform future research. The models are the multple speces extenson EPANET-MSX and the pressure dependent extenson EPANET-PDX. Water qualty analyss was conducted on a hypothetcal network consderng varous operatng pressure condtons. Dfferent knetc models were employed to smulate water qualty. Frst order, lmted frst order and zero order models were used for predctng chlorne resdual, dsnfecton by-products and water age respectvely. Generally, EPANET-MSX and EPANET-PDX provded dentcal water qualty results for normal operatng condtons wth adequate pressure but dfferent results for pressure defcent networks. Also, a parallel frst order model wth fast and slow reactng components was used for chlorne decay and dsnfecton by-products usng the EPANET- MSX model for a network operatng under normal pressure condtons. Keywords EPANET, pressure-defcent water dstrbuton system, water qualty modellng, dsnfecton by-products INTRODUCTION Research ndcates that the qualty of water n water dstrbuton systems (WDSs) may deterorate due to several changes that take place durng transport n the dstrbuton system (Rossman, 1993). These changes nclude: loss of dsnfecton resduals that can lead to bacteral re-growth (Clark and Haught, 25); formaton of potentally carcnogenc dsnfecton by-products (DBPs) due to the reactons of the dsnfectant wth organc and norganc substances n water (Rodrguez et al., 24); development of taste and odour; and corroson. The water qualty concerns n combnaton wth the rgorous standards set by regulatory bodes have pressed water companes to depend ncreasngly on models n the quest to understand and control the dynamcs of water qualty processes. Several computer models are avalable to smulate water qualty processes n WDSs. EPANET 2, a publc doman hydraulc and water qualty model, s among the most wdely used. The model enables smulaton of non-reactve tracer materals, chlorne decay, DBPs growth and water age (Rossman, 2). Prmarly EPANET 2 s a sngle speces model and lmted to model the dynamcs of chlorne resdual, trhalomethane (THM) or water age that does not permt smulaton of multple nteractng speces (Shang et al., 28). The frst order knetc decay model of EPANET 2 depends on the concentraton of only one reactant. The model for chlorne decay, for example, depends only on the concentraton of chlorne. Ths prevents the chlorne decay model from ncludng other potental reactants such as natural organc matter. Another drawback of EPANET 2 stems from the hydraulc analyss approach used. There are two hydraulc analyss approaches, vz the tradtonal demand drven analyss (DDA) and pressure

3 dependent analyss (PDA) (Wu et al. 29; Tanymboh and Templeman 21; Sew and Tanymboh, 211). DDA assumes demand s satsfed n full rrespectve of the network pressure. Ths assumpton s vald only f the network performs under normal pressure condtons wth adequate pressures at all nodes (Wu et al. 29). However, n the presence of network rregulartes such as ppe breaks, pump falures, temporary demand ncrease e.g. for fre fghtng purposes, and system mantenance and repar restrctons, DDA provdes unrealstc hydraulc and water qualty results. By contrast, PDA based models take nto account the pressure dependent nature of nodal flows and thus the models provde results that are more realstc (Chandaplla 1991; Gupta & Bhave 1996; Tanymboh et al. 1999). EPANET 2 s a DDA based model. There have been great research efforts to enhance the EPANET 2 model. Shang et al. (28) developed a multspeces extenson model called EPANET-MSX. The model enables smulaton of multple chemcal speces n bulk water as well as the ppe wall. EPANET-MSX can assst modellers to nvestgate any speces and chemcal reactons of nterest. Also, the model takes nto account the reactvty of water from dfferent sources. It mantans wholly the exstng EPANET 2 capablty of smulatng water qualty for extended perods. A recent achevement on mprovng EPANET 2 has also been reported n Sew and Tanymboh (212). The researchers have developed a pressure dependent extenson known as EPANET-PDX. The model s an extenson that has a logstc pressure dependent demand functon (Tanymboh and Templeman, 21). The model has full EPANET 2 modellng functonalty and can perform hydraulc, water qualty and extended perod smulaton of a network under normal and pressure defcent condtons n a seamless way. The am of ths paper s to compare the water qualty modellng capabltes of the multspeces and pressure dependent EPANET 2 extenson models to nform future research on pressure dependent water qualty modellng. We used a smple network from the lterature n ths study. METHODS To evaluate the capabltes of EPANET-PDX and EPANET-MSX dfferent water qualty analyses were conducted on a smple network n Fujwara and Ganesharajah (1993). The analyses comprsed of smulaton of water age, chlorne resdual and THM concentratons. Varous reacton rate models and network hydraulc condtons were consdered. The equatons used heren for the knetc reactons nclude frst order, lmted frst order and parallel frst order models. The frst order (Equaton 1) and lmted frst order (Equaton 2) knetc models were used for the smulaton of chlorne decay and THM concentraton n bulk water respectvely. dc dt = k C (1) b where C = chlorne concentraton; t = tme; k b = bulk water reacton rate constant. dc dt = k ( C C) b L (2) where C = THM concentraton; t = tme; k b = bulk water reacton rate constant; and C L = maxmum THM concentraton. For modellng water age, a zero order reacton s used,.e. dc/dt = 1. The parallel frst order model n Equaton 3 was used for modellng of chlorne decay.

4 C t = C[( F exp( k1t) + (1 F)exp( k2t)] (3) where C t = chlorne concentraton at tme t; C = ntal chlorne concentraton; k 1 & k 2 = fast and slow decay rate constants; F = fracton of chlorne reactng rapdly; (1-F) = fracton of chlorne reactng slowly. Helblng and Van Bresen (29) evaluated dfferent knetc models and concluded that the parallel frst order model provded the best results among dfferent models. The model has two components that descrbe rapd and slow reactons. Sohn et al. (24) developed a two-phase THM knetc model (Equaton 4) based on a parallel frst order model. The model explctly consders chlorne decay n the reacton knetcs. THM = C{ A(1 exp( k1t)) + B(1 exp( k2t))} (4) where C = chlorne concentraton; k 1 & k 2 = chlorne decay rate constants as n Equaton 3; A & B = parameters of the THM model that represent the fast and slow reactng components, respectvely. For pressure dependent modellng EPANET-PDX ncorporates the Tanymboh and Templeman (21) logstc pressure dependent demand functon nto the system of hydraulc equatons. The functon s descrbed as follows. Qn ( Hn ) = Qn req exp( α + β Hn ) 1+ exp( α + β Hn ) (5) req where Qn and Hn are the flow and head at node respectvely. Qn s demand at node. α and β are parameters to be calbrated wth relevant feld data. In the absence of feld data, Tanymboh and Templeman (21) suggested that default values for α and β could be taken as α = 4.595Hn Hn des des 6.97Hn Hn mn mn (6) β = des Hn Hn mn (7) des where Hn s the nodal head above whch whch Qn =. RESULTS AND DISCUSSIONS req Qn = Qn and mn Hn s nodal head below The smple two-loop network shown n Fgure 1 n whch C HW represents the Hazen-Wllams roughness coeffcent was selected for demonstraton purposes (Fujwara and Ganesharajah 1993). The network conssts of a sngle source, 8 ppes of length 1 m and 6 demand nodes. The requred resdual head for all nodes s 15 m. 24-hour extended perod water qualty smulatons of the network were conducted.

5 Node Elevaton Demand (m) (l/s) Ppe Dameter (mm) C HW Fgure 1. Layout of the demonstraton network We consdered three cases (Cases 1 to 3) to evaluate the models. Values of the bulk water reacton rate used prevously n the lterature were consdered. Carrco and Snger (29) and Helblng and Van Bresen (29) summarzed the reported values of bulk water reacton rates. The values range from.1 to 4.52/day. For ths work, a bulk water reacton rate of 1/day was selected. A constant chlorne dose of 1mg/L was appled at the source. A maxmum THM concentraton of 1µg/L n the network has been assumed accordng to the Water Supply (Water Qualty) Regulatons (21) n England and Wales. Also, a 5-mnute water qualty tme step was specfed. All smulatons were carred out on a personal computer (Intel Core 2 Duo, 3.2 GHz, 3.21 GB RAM, Mcrosoft Wndows XP operatng system). Case 1 In Case 1, the water level at the source was fxed at 9 m to ensure the network operates wth suffcent pressure to satsfy all demands and acheve a 1% demand satsfacton rato (DSR). The frst order, lmted frst order and zero order knetc models were used to predct chlorne resdual, THM concentraton and water age respectvely. Fgure 2 shows that both EPANET-MSX and EPANET-PDX provde essentally dentcal results when pressure n the system s suffcent. Due to the mult-speces capablty of EPANET-MSX, ths model can predct all the 3 speces (water age, chlorne and THM) n a sngle smulaton. EPANET-MSX requred an average CPU tme of.265 seconds to complete the analyss for a 24-hour operatng cycle. On the other hand, to smulate a sngle speces, EPANET-MSX requred an average CPU tme of.93 seconds. EPANET-PDX, however, whch s a sngle speces model, performed the same analyss by smulatng only one speces at a tme. To carry out the water age analyss for a 24-hour perod of operaton, EPANET-PDX requred an average CPU tme of.38 seconds. Ths s almost 2.5 tmes faster than EPANET-MSX. Case 2 In case 2 pressure defcent condtons were created by reducng the source water level from 9 m to 65 m and 6 m n Stages I and II respectvely. Ths resulted n the network satsfyng only 7% and 56% of the total demand n Stages I and II respectvely. Cases 1 and 2 are dentcal n all other respects. For modellng the pressure defcent network, the head below whch Qn = was taken as the nodal elevaton whle the head above whch Qn = Qn req was taken as the elevaton plus the

6 mnmum requred resdual head of 15 m. Default values for α and β were obtaned usng Equatons 6 and 7 respectvely. Rather unexpectedly, EPANET-MSX provded dentcal water qualty results to Case 1 (n whch there s enough pressure to satsfy all demands). In practcal terms, a pressuredefcent network cannot satsfy demands n full. In ths regard, EPANET-MSX results are unrealstc. Ths lmtaton s attrbutable to the underlyng DDA modellng approach. EPANET-PDX that has PDA functonalty provded dfferent water qualty results that reflected the actual pressure n the network (Fgure 3). Fgure 3 shows that when the pressure n the system decreases, the THM concentraton and water age ncrease whle the chlorne resdual decreases. Ths evdently reflects the fact that when the pressure n the network s low, the flow wll correspondngly be low and the hydraulc resdence tme (water age) wll be greater. An ncrease n resdence tme wll enable the THM concentraton to ncrease and the chlorne concentraton to decrease. It s noted that low pressure condtons produced sgnfcant changes at dstant nodes such as Nodes 5 and 6 as llustrated n Fgure 3. Case 3 In Case 3 the parallel frst order model for chlorne decay and THM producton was used. The source water level was fxed at 9 m and thus the network was operatng under normal pressure condtons wth 1% DSR. The multspeces capablty of EPANET- MSX allows smulaton of the rapdly and slowly reactng components of the chlorne and THM. It should be noted, however, that EPANET-PDX cannot perform these smulatons owng to ts sngle speces attrbute. Water age (hrs) Chlorne resdual (mg/l) THM (ug/l) EPANET-PDX (a) EPANET-MSX EPANET-PDX (b) EPANET-MSX EPANET-PDX (c) EPANET-MSX Fgure 2. Comparson of water qualty results for normal pressure condtons For smulaton of chlorne decay, Helblng and Van Bresen (29) developed general-purpose emprcal equatons relatng the ntal concentraton to each parameter of the parallel frst order model. Accordngly we used F =.87, k 1 =.31/hr and k 2 =.2/hr. Sohn et al. (24) developed emprcal equatons for estmatng the parameters for THM producton; we used A = 16 and B = 34.7.

7 It should be noted that EPANET-MSX can smulate all the speces nvolved usng the dfferent knetc models n a sngle smulaton run. To smulate the seven speces (chlorne decay, THM, water age, and the rapdly and slowly reactng fractons of chlorne and THM) at once, EPANET- MSX requred an average CPU tme of.69 seconds. Ths s approxmately 16 tmes the CPU tme requred by EPANET-PDX to smulate a sngle speces. The chlorne resdual and THM concentratons predcted usng the parallel frst order model have been compared wth the values derved prevously usng the frst order (Fgure 4) and lmted frst order (Fgure 5) models. Slght dfferences between the models can be observed n the results shown n each of Fgures 4 and 5. Water Age ( hrs ) Chlorne resdual (mg/l) DSR=1% DSR=7% DSR= 56% (a) Although there seems to be reasonable agreement between these alternatve formulatons, n practce more accurate calbraton of the two canddate models may be consdered, whch may nvolve feldwork and laboratory tests. The man objectve heren, however, s to demonstrate that EPANET-MSX can model both the chlorne resdual and THM concentratons usng parallel knetc models whereas EPANET- PDX cannot. Conversely EPANET-MSX cannot smulate subnormal pressure condtons realstcally whle EPANET-PDX does so seamlessly. THM (ug/l) DSR=1% DSR=7% DSR= 56% (b) DSR=1% DSR=7% DSR= 56% (c) Fgure 3. EPANET-PDX water qualty results for normal and subnormal pressures CONCLUSIONS In ths paper, the multple speces and pressure dependent EPANET extensons have been assessed. EPANET-MSX can model multple nteractng speces but t s lmted to networks operatng under normal pressure condtons. On the other hand, EPANET-PDX, whch s a pressure dependent model, can smulate both normal and pressure defcent networks seamlessly. However, the model s restrcted to the dynamcs of just a sngle speces. Ths precludes smulaton of reactons between two or more speces accurately. The respectve shortcomngs of the two models provde nspraton to develop a holstc mult-speces pressure dependent water qualty model that can more accurately smulate the reactons between multple speces for approprate and tmely decson-makng. The research descrbed n ths artcle s stll n progress.

8 1.2 Chlorne resdual (mg/l) Frst order model Parallel frst order model Fgure 4. EPANET-MSX chlorne resduals under normal pressure 6 THM (ug/l) Lmted frst order model Parallel frst order model ACKNOWLEDGEMENT Fgure 5. EPANET-MSX THM concentratons under normal pressure 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. Ths project was funded n part by the UK Engneerng and Physcal Scences Research Councl (EPSRC Grant Reference EP/G55564/1). REFERENCES Carrco B. and Snger P.C. (29). Impact of booster chlornaton on chlorne decay and THM producton: smulated analyss. J. Envronmental Engneerng, 135(1), Chandaplla J. (1999). Realstc smulaton of water dstrbuton system. J. Transportaton Engneerng. 117 (2), Clark R.M. and Haught R.C. (25). Characterzng ppe wall demand: mplcatons for water qualty modellng. J. Water Resources Plannng and Management, 31(3), Fujwara O. and Ganesharajah T. (1993). Relablty assessment of water supply systems wth storage and dstrbuton networks. J. Water Resources Research, 29(8),

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