Application of QUAL2Kw for water quality modeling in the Tunggak River, Kuantan, Pahang, Malaysia

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1 Research Journal of Recent Scences ISSN Res.J.Recent Sc. Applcaton of QUAL2Kw for water qualty modelng n the Tunggak Rver, Kuantan, Pahang, Malaysa Abstract Hossan M.A., Sujaul I.M. and Nasly M.A. * Faculty of Cvl Engneerng and Earth Resources, Unversty Malaysa Pahang, Kuantan, MALAYSIA Avalable onlne at: Receved 2 nd September 203, revsed 20 th November 203, accepted th December 203 The Tunggak Rver receves waste water from the Gebeng ndustral estate (GIE) and from some agrcultural and homestead areas n Kuantan, Malaysa. Dscharges of ndustral effluents contanng conventonal and non-conventonal pollutant wth degradable organcs and nutrents are the major cause of water qualty deteroraton n ths rver. Degradable organc and nutrents have resulted n decrease n DO concentratons along the rver. Wth the objectve of modelng of the water qualty of the rver a one- dmensonal rver and stream water qualty model QUAL2Kw was calbrated and confrmed usng the data for the perod of Wth some exceptons t represented the collected data qute good. Smulaton of varous water qualty consttuents was done applyng the model durng dry and wet season. The result shows that the DO concentraton was very low n all parts of the rver. BOD and COD was very hgh compare to standard level of Malaysa. Due to ndustral wastewater the polluton was hgh and wthout takng mprove management based on the smulated results, the scenaro wll not change. Keywords: QUAL2kw, Tunggak rver, smulaton, dssolved oxygen, calbraton, water qualty. Introducton The anthropogenc actvtes lke ndustralzaton homestead and agrcultural practces ntroduces sgnfcant amount of organc matters and nutrents nto the rver flow that resulted contamnaton of surface water. Pollutants n degradable wastewater caused decrease n dssolved oxygen due to ther metabolsm by the acton of mcroorgansm and other bota; chemcal oxdaton of reduced pollutant and plant respraton also results reducton n DO concentraton 2,3, 4. Water flow s nfluencng the avalablty and reducton of dssolved oxygen too; decreasng s clearly vsble durng low flow perods. It s essental to mantan the threshold level of the key parameters lke dssolved oxygen (DO), carbonaceous bochemcal oxygen demands (CBOD), ammonacal ntrogen (NH 3 -N), ntrate ntrogen (NO 3 -N), norganc phosphorus (PO 4 3- ), temperature and ph for a better rver health 2. To mantan the mnmum standard of the water qualty, effcent water management ncludng montorng and research s necessary 5. Nowadays, surface water management ncludes some mathematcal models for evaluatng the mpact of pollutant. Water qualty models are beng used for water management as an mportant tools; whch are able to predct long and short term varaton of water qualty parameters 5-6. Among the water qualty models, QUAL2E was the wdely used mathematcal model for rver and stream water qualty to evaluate the conventonal pollutant mpact 2,7,3. However, due to some lmtatons t was modfed by Park and Lee 8 and they developed QUAL2K, 2000, whch ncluded the addton of new water qualty nteractons. It was further developed by Chapra and Pelleter 9 wth the name QUAL2K, By modfyng the QUAL2K, 2003, Pelleter et al. 0 developed QUAL2Kw, whch s the modernzed verson of QUAL2E 2. QUAL2Kw has many new features, ncludng Software Envronment and Interface, Model segmentaton, carbonaceous BOD specaton and others. Smlar to QUAL2K, t s a onedmensonal, steady flow stream water qualty model and useful even n data lmted condton 2. The software of QUAL2Kw s freely avalable and can be used for both small and bg rver 5. It can smulate a number of consttuents ncludng temperature, ph, carbonaceous bochemcal demand, sedment oxygen demand, dssolved oxygen, organc ntrogen, ammona ntrogen, ntrte and ntrate ntrogen, organc phosphorus, norganc phosphorus, total ntrogen, total phosphorus, phytoplankton and bottom algae. Kannel et al. 2 appled the model for Bagmat Rver, Nepal and the model represented the feld data qute well. Gardner et al. 2 also used the model for better understandng of the water qualty status n Ro Blanco watershed n Jalsco, Mexco. As a tool for water qualty management of small rver basn, Olvera et al. 3 used ths QUAL2Kw n Portugal. In Malaysa, QUAL2K model was used by Zanudn et al. 4 for Sunga Tebrau and found as an outstandng tool n managng the rver basn. Regardng the present study, Tunggak Rver s a small rver havng no trbutary. It s beng polluted due to the vcnty of ndustral zone of Gebeng, Kuantan, Malaysa. Gebeng ndustral areas dschargng ther wastewater to the rver flow that causng heavy polluton; t act as an mportant factor to Internatonal Scence Congress Assocaton 6

2 contrbute DO reducton as well as ncreasng of other water qualty parameters n the rver water. In ths study QUAL2Kw model s calbrated and confrmed wth the observed data. The objectve of the study s to calbrate the QUAL2Kw model wth water qualty data of Tunggak Rver and to smulate the water envronment of the rver for better water management. Materal and Methods Study area: The study was conducted n the Tunggak Rver basn and surroundng surface water of Gebeng Industral Estate (GIE), located n the eastern part of pennsular Malaysa. The Tunggak rver basn s under contnuous degradaton process due to rapd ndustralzaton and urbanzaton 5. Ths study covered lower 7.5 km length of the rver where, the md-zone s densely populated ndustralzed and resdental areas and the lower part s wth mangrove plantaton (fgure ). In the ndustral zone wastewater dscharge lne are drectly connected wth the rver flow. The water qualty of the rver s deteroratng due to low DO concentraton, presence of other toxc parameters and metal contamnaton 6. for wet season; as these two seasons are prevalng n the area. In ths study observed water qualty parameters were: water flow, temperature, ph, electrcal conductvty (EC),dssolved oxygen (DO), total suspended solds (TSS), norganc phosphorus(po4-p), ammonacal ntrogen (NH4-N), ntrate ntrogen (NO3-N), 5 days bochemcal oxygen demand as mgo2/l (CBOD or BOD) and chemcal oxygendem and as mgo2/l (COD). Durng collecton, transportaton, preservaton and analyss of water samples the methods of the Amercan Publc Health Assocaton 7 and HACH 8 were followed. For BOD, water samples were collected n separatee black bottles (300 ml) and were stored n ce-boxes. The data of physcal parameters: water flow, temperature, ph, EC and DO were collected n-stu usng YSI and other portable devces. Flow was observed usng current meter and other physcal parameters were measured usng YSI. All other data were measured n the envronment laboratory. TSS determnaton was done by gravmetrc method usng temperature controlled oven. The concentraton of BOD was measured by readng out the DO concentraton before and after the ncubaton. BOD samples were ncubated for 5 days at 20±30C n BOD bottle and after the ncubaton perod BOD5 was calculated wth the fnal readng of DO. COD determnaton was done n reactor dgeston method usng HACH spectrometer Ntrogen (NH4) was measured n nessler method; ntrate was estmated n cadmum reducton method, PO4-P was determned n ascorbc acd method. In those determnaton calormetrc method (APHA, 2005) was used. Modelng tool: In the study a one dmensonal mathematcal model QUAL2Kw was used. It can be used for rver water qualty smulaton when the rver water flow s steady but non- nto t reman roughly unform and the polluton loadng constant 3,9. It consders the nfluence of pont source and non- pont source polluton loads durng smulaton 9. Moreover, the model has a number of new elements that make t usable for shallow and small rver besdes relatvely large rver basn 8-2. Fgure- Map of the study area ndcatng montorng staton on Tunggak Rver Montorng statons and data collecton: For ths study seven montorng statons was selected along the rver namely: Eastman chemcal (EC); Brtsh petroleum (BPL); AsturSdn. Bhd. (Ast); Meco Manufacturng (MF); Taman balo 9k makmur (TBM); Seberang balok (SB) and Lower stream (LS). The detal summary of the montorng statons s gven n table- were done. The montorng, water samples and data collecton on March-August for dry season and on September- February The QUAL2Kw model has a general mass balance equaton for all consttuent concentraton(fg. 2) n the water column (except bottom algae) of a reach ( excludng hyporhec) s wrtten as 0 : dc Q Q ab, E E W = c c + ( c c ) + ( c+ c ) + + S () dt V V V V V Where, c = consttuent concentraton, Q =flow at reach (m3/d), V =volume of reach (m3/d), Qab, = abstracton flow at reach (m3/d), E = bulk dsperson coeffcent between reaches (m3/d), E, E are bulk dsperson coeffcents between reaches & and & +, W =external loadng of the consttuent (mg/day) and S= sources and snks of the consttuent due to reactons and mass transfer mechansms (mg/l/day). The detal descrpton of nteractng water qualty state varables process s descrbed n Pelleter and Chapra. Internatonal Scence Congress Assocaton 7

3 For auto calbraton QUAL2Kw maxmze the goodness of ft of the model results compared wth measured data by usng genetc algorthm (GA). It s the recprocal of the weghted average of the normalzed root mean squared error (RMSE) of the dfference between the model predctons and the observed data Model calbraton and confrmaton: Rver segmentaton: The total 7.5 km length of the lower part of the Tunggak Rver was segmented nto 7 reaches that are shown n Fg. 3. The fgure shows the reaches of the rver along wth the locatons of pont sources of polluton loads. for water qualty consttuents. The GA maxmzes the ftness functon f(x) as: Input data: The nput data of water qualty parameters were m n n ( = O j= j m) flow, temperature, conductvty (EC), ph, DO, BOD, COD (as f ( x) w = = w 2 [ ( ) pj Oj / ] generc consttuent), ammonacal ntrogen, ntrate ntrogen, m 2 (2) norganc phosphorus, norganc suspended sold (ISS). Regardng phytoplankton and pathogen, those data were not Where, Oj = observed values, Pj = predcted values, measured. The bottom plants were assumed 40%. These dment/ m=number of pars of predcted and observed values, w = hyporhec zone thckness was assumed 0 cm. The water weghtng factors, and n =number of dfferent state varables qualtes for the pont and dffuse source of pollutons were ncluded n the recprocal of the weghted normalzed RMSE. other nput to the model. The data were collected for one tme n Pelleter et al. 0 descrbed detals about auto-calbraton method a day of each month both n wet and dry season. Average data n ther publcaton, QUAL2Kw A framework for modelng for the dry season and wet season were used as the nput data. water qualty n streams and rvers usng a genetc algorthm for calbraton. Table Water qualty montorng statons n the Tunggak Rver Dstance from Staton Name of Statons upper stream No. (km) Locaton. Upper Stream (US) 0.00 Near the brdge on JalanGebeng 2/6 2. Eastman (EC).27 Besdes Eastman Chemcal sdn.bhd 3. Brtsh Petroleum (BPL).7 50 meters from BP Chemcals Sdn. Bhd 4. Astro (Ast) 0.87 Near AstroSdn. Bhd. 5. Meco Factory (MF) 0.90 Near the brdge on JalanPntasanKuantan 6. Taman Balok (TBM) meters from Taman BalokMakmur 7. SeberangBalok (SB) 0.85 Near PerumahanSeberangBalok 8. Lower Stream (LS).60 Besdes the brdge on JalanGebeng 2 (Port road) Fgure- 2 Mass balance n a reach segment. Internatonal Scence Congress Assocaton 8

4 Fgure- 3 QUAL2Kw segmentaton scheme wth locaton of polluton sources along Tunggak Rver System parameters: The system parameters requred by QUAL2 Kw for calbraton are shown n table-2. These parameters were obtaned from a numbers of studes and lteratures ncludng: Envronment Protecton Agency (EPA) gudance document 22, user manual of QUAL2Kw and documentaton for the enhanced stream water qualty model QUAL2E and QUAL2E-UNCAS 7. Internal calculaton method was used to calculate re-aeraton rate; whch was also appled by Zhang et al. 9. Exponental model was chosen for oxygen nhbton of CBOD oxdaton, ntrfcaton and phyto-respraton; and also for oxygen enhance of de-ntrfcaton and bottom algae respraton. The range of CBOD oxdaton rate was assumed as 0 5, whch was also used by Olvera et.al 3 ; Cho and Ha 2 and Camargo et al. 23 for small rver. The other parameters were set as default value n QUAL2Kw. Model mplementaton: Model calbraton was run wth the measured data of dry season. To avod nstablty n the model calbraton, the calculaton step was set at mn 2,24. Euler s method was set for the soluton of ntegraton; Newton Raphson method was used for ph modelng. The sedment dgeness smulaton was done for level I opton. To perform goodness of ft dfferent weghtng factors were gven to dfferent parameters. The weght 50 was gven for DO as t s the most nfluental parameter 2,23. Weght 2 was gven for temperature, ph, CBOD and COD; and for other parameters was gven as weghtng factor. Model was run for a populaton sze of 00 wth 50 generatons n the evoluton (model runs n a populaton). It was because, accordng to Pelleter et al. 0 a populaton sze of 00 performs better than smaller numbers and as nearly as a populaton sze of 500. Results and Dscusson Calbraton and confrmaton: Fgure 4 shows the calbraton and fgure 5 shows the confrmaton results of modelng respectvely. Fgure 4 denotes that, calbraton result of temperature, ph and DO were n accordance wth the observed values and other parameters were lttle bt dfferent. The studed rver water qualtes were hard to reach the mnmum DO requrement n all reaches of the rver (fgure 4). The low DO concentraton that was below 3.0 mg/l n all reaches s an ndcaton of enterng wastewater from dfferent pont sources through wastewater drans and channels from the ndustral areas; those wastewater add hgh organc and norganc materals resulted low DO 5. Internatonal Scence Congress Assocaton 9

5 Table 2 Calbrated parameters for the Tunggak Rver n 202 Parameters Values Unts Autocalbraton Mn. value Max. value Carbon 40 gc No Ntrogen 7.2 gn No 3 9 Phosphorus gp No Dry weght 00 gd No Chlorophyll ga No ISS settlng velocty 0.0 m/day Yes 0 2 O2 reaeraton model Internal No Slow CBOD hydrolyss rate day Yes 0 5 Slow CBOD oxdaton rate day Yes Fast CBOD oxdaton rate day Yes 0 5 Organc N hydrolyss day Yes 0 5 Organc N settlng velocty m/day Yes 0 2 Ammonum ntrfcaton day Yes 0 0 Ntrate dentrfcaton day Yes 0 2 Sed. dentrfcaton transfer coeffcent m/day Yes 0 Organc P hydrolyss 2.2 day Yes 0 5 Organc P settlng velocty m/day Yes 0 2 Inorganc P settlng velocty m/day Yes 0 2 Sed. P oxygen attenuaton half sat constant.8956 mgo2/l Yes 0 2 Bottom plant Growth model zero-order Max Growth rate mga/m2/day Yes 0 00 Frst-order model carryng capacty 00 mga/m2 No Basal Respraton rate day Yes Excreton rate day Yes Death rate day Yes External ntrogen half sat constant ugn/l Yes External phosphorus half sat constant ugn/l Yes 0 00 Inorganc carbon half sat constant.3e-04 moles/l Yes.30E-06.30E-04 Lght model Half saturaton Lght constant langleys/day Yes 00 Ammona preference ugn/l Yes 00 Subsstence quota for ntrogen mgn/gd Yes Subsstence quota for phosphorus mgp/gd Yes Max. uptake rate for ntrogen mgn/gd/d Yes Max. uptake rate for phosphorus mgp/gd/d Yes Internal ntrogen half sat rato Yes.05 5 Internal phosphorus half sat rato Yes.05 5 Detrtus dssoluton rate.4653 day Yes 0 5 Detrtus settlng velocty m/day Yes 0 5 COD decay rate 0.8 day Yes COD settlng velocty m/day Yes The concentratons of CBOD, COD was hgher and beyond the standard level n all reaches. These two parameters decreased steadly up to 6.5 km from downstream boundary (Fg. 4). The head water was relatvely better regardng BOD and COD. Ths was because of the amount ndustral wastewater ncreased wth the dstance due to the dense of ndustres at the md regon of the rver (after km from upstream) 6.The concentraton of ammonacal-n decreasedsteadly and sharply ncreased after 6 km from downstream. On the contrary norganc phosphorus was almost smlar up to 5 km and after that t ncreased sharply. Wth some excepton, the outcomes of the model calbraton were n well agreement wth the observed data. Table-3 shows the root mean square errors (RMSE) between the smulated and Internatonal Scence Congress Assocaton 0

6 observed values of water qualty parameters n calbraton (dry season) and confrmaton (wet season). The table also shows the dfference of RMSE from calbraton to confrmaton (%). Calbraton and confrmaton had smlar RMSE value, f the dfference s less than 20%; t ndcated the good matchng between the observed and predcted values 23. Durng calbraton, the RMSE of temperature, ph, DO, CBOD, COD,NH 4 -N, PO 4 -P and ISS were 2.67, 0.69,.55, 34.58, 37.93, and 2.8%, respectvely (table 3). In the confrmaton, the RMSE for temperature, ph, DO, CBDO, COD, NH 4 -N, PO 4 -P and ISS were observed 3.07, 0.56,.20, 33.0, 32.48, 0.56, 0.39 and 7.5% respectvely (Table 3). On the bass of the dfference of RMSE (%) temperature, ph, CBOD, COD NH 4 -N and PO 4 -P had very good match between observed and predcted values. The more dfference ndcated that, the envronmental condton especally for those parameters was dfferent between the two perods 23. In spte of some errors, as some errors n ths modelng are nevtable due to tme varaton of sample collecton; the smulaton results were qute good and acceptable to acheve modest management goals. Nevertheless, more accuracy could be attaned through addng varous nput varables ncludng bottom algae, sedment oxygen demand, organc ntrogen, total and organc phosphorus, etc. n montorng program; and also sophstcated 2D or 3D models can be appled to acheve the better management. Fgure-4 Model calbraton of water qualtes n Tunggak Rver for dry season s data Internatonal Scence Congress Assocaton

7 Fgure-5 Model confrmaton of water qualtes n Tunggak Rver for wet season s data Table 3 Root mean squared errors (RSME) between predcted and measured values of water qualty parameters durng calbraton (dry) and confrmaton (wet season) RMSE (%) SL No. Parameters Dfference (%) Calbraton Confrmaton. Temperature ph DO CBOD COD NH 4 -N Inorganc Phosphorus ISS Internatonal Scence Congress Assocaton 2

8 Concluson Rver and stream water qualty QUAL2Kwwas calbrated usng the data n dry season of 202 and confrmed wth wet season s (202-3) data. RMSE showed good match between observed and predcted value of maxmum parameters except ISS. The model was appled to smulate varous water qualty parameters. The result shows that, the water qualty parameters dd not dffer greatly from dry season to wet season. RMSE denoted that, the ISS dffered sgnfcantly and t was due to runoff at wet season. However, the model QUAL2Kw adequately represented the feld data of Tunggak Rver and the modeled data (Smulaton) expressed that, the DO concentraton was very low and due to ncrease amount of waste water t cannot be fxed wthout takng mproved management based on the smulated results. Acknowledgments Authors are grateful to the unversty Malaysa Pahang and the Faculty of Cvl Engneerng and Earth Resources for ther supportng and fundng through the research project RDU 0354 and GRS Reference. S.S., A. and B.N., S. Effect of Anthropogenc Actvtes on Zooplankton Populaton of Sogal Pond, Belgaum Dstrct, Karnataka, Inda, Res.J.Recent Sc., 2, 8 83 (203) 2. Kannel P.R., Lee S., Lee Y.S., Kanel S.R. and Pelleter G.J., Applcaton of automated QUAL2Kw for water qualty modelng and management n the Bagmat Rver, Nepal, Ecol.Model., 202, (2007) 3. Drolc A. and Končan J.Z., Water qualty modellng of the rver Sava, Slovena, Water Res., 30, (996) 4. Harbhau M.G., Trace Metals Contamnaton of Surface Water Samples n and Around Akot Cty n Maharashtra, Inda, Res.J.Recent Sc.,, 5 9 (202) 5. Bottno F., Ferraz I.C., Mendondo E.M. and Caljur M.D.C., Calbraton of QUAL2K model n brazlan mcro watershed: effects of the land use on water qualty, Acta Lmnologca Braslensa, 22, (200) 6. Sardnha D. and Conceção F., Evaluaton of the water qualty and auto-purfcaton from the meo stream, Leme (SP), Engenhara Santara e Ambental, 3, (2008) 7. Brown L. and Barnwell, T., The enhanced stream water qualty models QUAL2E and QUAL2E-UNCAS: documentaton and user manual. (U. S. Envronmental Protecton Agency, Athens, GA, 987). 8. Park, S. S. and Lee, Y. S., A water qualty modelng study of the Nakdong Rver, Korea. Ecol.Mode., 52, (2002) 9. Chapra S. and Pelleter G., QUAL2K: A Modelng Framework for Smulatng Rver and Stream Water Qualty: Documentaton and Users Manual, (Cvl and Envronmental Engneerng Dept., Tufts Unversty, Medford, MA., 2003) 0. Pelleter G.J., Chapra S.C. and Tao H., QUAL2Kw A framework for modelng water qualty n streams and rvers usng a genetc algorthm for calbraton, Envron. Model. Soft., 2, (2006). Pelleter G. and Chapra S., QUAL2Kw theory and documentaton A modelng framework for smulatng rver and stream water qualty, (Envronmental Assessment Program Olympa, Washngton , (2008) 2. Gardner S., Grggs B., Handy J., Lemme N. and Paudel M.A, Qual2k water qualty analyss of the Blanco watershed near Jalsco, Mexco, Department of Cvl and Envronmental Engneerng, Brgham Young Unversty (2007) 3. Olvera B., Bola J., Quntero P., Nadas H. and Arroja L., Applcaton of Qual2Kw model as a tool for water qualty management: Cértma Rver as a case study, Envron. Mont. Assess., 84, (202) 4. Zanudn Z., Rahman N., Abdullah N. and Mazlan N.F., Development of water qualty model for Sg. Tebrau usng QUAL2K, Journal of Appled Scences, 0, (200) 5. Sujaul I., Hossan M., Nasly M.A. and Sobahan M.A., Effect of Industral Polluton on the Spatal Varaton of Surface Water Qualty, Am. J. Envron. Sc., 9, (203) 6. Nasly M., Hossan M. and Islam M., Water Qualty Index of Sunga Tunggak: An Analytcal Study, n 3rd Internatonal Conference on Chemcal, Bologcal and Envronment Scences (ICCEBS 203) (203) 7. Andrew D., Standard methods for the examnaton of water and wastewater, 200, Amercan Publc Health Assocaton, (2005) 8. HACH, Water analyss gude (2005) 9. Zhang R., Qan X., Yuan X., Ye R., Xa B. and Wang Y., Smulaton of water envronmental capacty and polluton load reducton usng QUAL2K for water envronmental management, Int. J. Envron. Res. Publc Health, 9, (202) 20. Anh D.T., Bonnet M.P., Vachaud G., Van Mnh C., Preur N., VU DUC L., and LAN ANH L., Bochemcal modelng of the Nhue Rver (Hano, Vetnam): Practcal dentfablty analyss and parameters estmaton, Ecol.model., 93, (2006) 2. Cho J.H. and Ha S.R., Parameter optmzaton of the QUAL2K model for a multple-reach rver usng an Internatonal Scence Congress Assocaton 3

9 nfluence coeffcent algorthm, Sc. Total Envron., 408, (200) 22. Bowe G.L., Mlls W.B., Porcella D.B., Campbel Carre L., Pagenkop, James R., Rupp, Gretchen L., Johnson, Kay M., Chan, Peter W.H., Ghern, Steven A., Chamberln and Charles E., Rates, constants, and knetcs formulatons n surface water qualty modelng, EPA (U. S. Envronmental Protecton Agency, Athens, GA, 985) 23. Camargo R.D.A., Caljur M.L., Santago A.D.F., Couto E.D.A. De and Slva M.D.F.M.E., Water qualty predcton usng the QUAL2Kw model n a small karstc watershed n Brazl, Acta Lmnologca Braslensa, 22, (200) 24. Zhang, R., Qan, X., L, H., Yuan, X. and Ye, R., Selecton of optmal rver water qualty mprovement programs usng QUAL2K: a case study of Tahu Lake Basn, Chna, Sc. Total Envron., 43, (202) Internatonal Scence Congress Assocaton 4