determination of standard target water quality in the nakdong river basin for the total maximum...

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KSCE Journal of Civil Engineering (2013) 17(2):309-319 10.1007/s12205-013-1893-5 309 www.springer.com/12205 Environmental Engineering Determination of Standard Target Water Quality in the Nakdong River Basin for the Total Maximum Daily Load Management System in Korea Ayeon Lee*, Seonju Cho**, Moo Jong Park***, and Sangdan Kim**** Received January 16, 2012/Accepted May 30, 2012 ··································································································································································································································· Abstract This study suggests methods to improve the total maximum daily loads management system currently being regulated in Korea. The TANK model which is a conceptual rainfall-runoff model including the river routing function and the evapotranspiration process is adapted to simulate daily stream flows, and the 7-parameter log-linear model combined with the minimum variance unbiased estimator is used to calculate daily stream contaminant loads. Based on these methods, Load Duration Curves (LDCs) for each unit watershed are constructed. Using LDCs of all unit watersheds, representative specific LDC of Nakdong River is derived to indicate the average contaminant status of the whole river basin in terms of water quality items. Using representative specific LDCs, appropriate target water qualities with respect to reference flow conditions are assigned to all of unit watersheds, and point sources or non-point sources priority management areas of 40 unit watersheds of the Nakdong River basin are identified. Keywords: Biochemical Oxygen Demand (BOD), contaminant loads, hydrologic flux, Total Maximum Daily Load (TMDL), Total Organic Carbon (TOC), Total Phosphorus (TP) ··································································································································································································································· 1. Introduction The Total Maximum Daily Loads (TMDLs) management system has been executed in Korea since 2004 under the definition that “this system is to set a target water quality of each unit watershed with scientific grounds, to calculate allowable contaminant loads to achieve and maintain the target water quality, and to restrain and manage the total amount of contaminant loads discharged from unit watersheds to meet the target water quality” (Korean Ministry of Environment, 2004). Korea has adapted the system since 2004 under the condition that the target substance is Biochemical Oxygen Demand (BOD) and the standard stream flow is 10-year average low flow. Currently the total maximum daily load management system in Korea has the target BOD water quality and assigns allowable loads to each unit watershed. However, target water quality allocated somewhat unfairly has been facing a strong backlash from local governments, which becomes a serious threat to a plan of including Total Phosphorus (TP) and Total Organic Carbon (TOC) as additional water quality items of the system in the foreseeable future. Therefore, more reasonable target water quality is required to improve the previous method. In this case, the target water quality by unit watershed should consider the current water quality to some extent to be effective as a target standard but, before this, regardless of the current water quality, the target water quality should be determined under the fairer standards. This study defines it as the standard target water quality. After setting such a target water quality under the fairer standards, it should go through negotiations between regions and between upstream and downstream areas and reflect socioeco- nomic factors in order to get a finally agreed target water quality, which is a way to prevent a backlash from the local government in advance and by following this way, we can expect a coop- erative mode in the regional management. In addition, since the current target water quality is based on the 10-year average low flow, TMDL system could be effective in managing point sources but not in the case of non-point sources management (Novotny, 2004). In Korea, since TMDL management system assigns and manages allowable loads of both point and non-point sources in each unit watershed at the same time, the total stream flow conditions should be included with low flow, the current standard stream flow. In other words, we need information on daily stream flows and daily water quality from the long term perspective that considering the ****Research Scientist, Nakdong River Environment Research Center, National Institute of Environmental Research, Gyeongbuk 717-873, Korea (E-mail: [email protected]) ****Graduate Student, Dept. of Environmental Engineering, Pukyong National University, Busan 608-737, Korea (E-mail: [email protected]) ****Member, Professor, Dept. of Civil Engineering, Hanseo University, Chungnam 356-706, Korea (E-mail: [email protected]) ****Member, Associate Professor, Dept. of Environmental Engineering, Pukyong National University, Busan 608-737, Korea (Corresponding Author, E- mail: skim@ pknu.ac.kr)

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KSCE Journal of Civil Engineering (2013) 17(2):309-31910.1007/s12205-013-1893-5

− 309 −

www.springer.com/12205

Environmental Engineering

Determination of Standard Target Water Quality in the Nakdong River Basin for the Total Maximum Daily Load Management System in Korea

Ayeon Lee*, Seonju Cho**, Moo Jong Park***, and Sangdan Kim****

Received January 16, 2012/Accepted May 30, 2012

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Abstract

This study suggests methods to improve the total maximum daily loads management system currently being regulated in Korea.The TANK model which is a conceptual rainfall-runoff model including the river routing function and the evapotranspiration processis adapted to simulate daily stream flows, and the 7-parameter log-linear model combined with the minimum variance unbiasedestimator is used to calculate daily stream contaminant loads. Based on these methods, Load Duration Curves (LDCs) for each unitwatershed are constructed. Using LDCs of all unit watersheds, representative specific LDC of Nakdong River is derived to indicatethe average contaminant status of the whole river basin in terms of water quality items. Using representative specific LDCs,appropriate target water qualities with respect to reference flow conditions are assigned to all of unit watersheds, and point sources ornon-point sources priority management areas of 40 unit watersheds of the Nakdong River basin are identified.Keywords: Biochemical Oxygen Demand (BOD), contaminant loads, hydrologic flux, Total Maximum Daily Load (TMDL), TotalOrganic Carbon (TOC), Total Phosphorus (TP)

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1. Introduction

The Total Maximum Daily Loads (TMDLs) managementsystem has been executed in Korea since 2004 under thedefinition that “this system is to set a target water quality of eachunit watershed with scientific grounds, to calculate allowablecontaminant loads to achieve and maintain the target waterquality, and to restrain and manage the total amount ofcontaminant loads discharged from unit watersheds to meet thetarget water quality” (Korean Ministry of Environment, 2004).Korea has adapted the system since 2004 under the conditionthat the target substance is Biochemical Oxygen Demand (BOD)and the standard stream flow is 10-year average low flow.

Currently the total maximum daily load management systemin Korea has the target BOD water quality and assigns allowableloads to each unit watershed. However, target water qualityallocated somewhat unfairly has been facing a strong backlashfrom local governments, which becomes a serious threat to aplan of including Total Phosphorus (TP) and Total OrganicCarbon (TOC) as additional water quality items of the system inthe foreseeable future. Therefore, more reasonable target waterquality is required to improve the previous method. In this case,

the target water quality by unit watershed should consider thecurrent water quality to some extent to be effective as a targetstandard but, before this, regardless of the current water quality,the target water quality should be determined under the fairerstandards. This study defines it as the standard target waterquality. After setting such a target water quality under the fairerstandards, it should go through negotiations between regions andbetween upstream and downstream areas and reflect socioeco-nomic factors in order to get a finally agreed target water quality,which is a way to prevent a backlash from the local governmentin advance and by following this way, we can expect a coop-erative mode in the regional management.

In addition, since the current target water quality is based onthe 10-year average low flow, TMDL system could be effectivein managing point sources but not in the case of non-pointsources management (Novotny, 2004). In Korea, since TMDLmanagement system assigns and manages allowable loads ofboth point and non-point sources in each unit watershed at thesame time, the total stream flow conditions should be includedwith low flow, the current standard stream flow. In other words,we need information on daily stream flows and daily waterquality from the long term perspective that considering the

****Research Scientist, Nakdong River Environment Research Center, National Institute of Environmental Research, Gyeongbuk 717-873, Korea (E-mail:[email protected])

****Graduate Student, Dept. of Environmental Engineering, Pukyong National University, Busan 608-737, Korea (E-mail: [email protected])****Member, Professor, Dept. of Civil Engineering, Hanseo University, Chungnam 356-706, Korea (E-mail: [email protected])****Member, Associate Professor, Dept. of Environmental Engineering, Pukyong National University, Busan 608-737, Korea (Corresponding Author, E-

mail: skim@ pknu.ac.kr)

Ayeon Lee, Seonju Cho, Moo Jong Park, and Sangdan Kim

− 310 − KSCE Journal of Civil Engineering

various stream flows occurred by the rainfall-runoff process of anatural phenomenon and the artificially controlled stream flowscaused by water use of multipurpose dams located at theupstream. Therefore, more acceptable target water quality isrequired to improve the previous system, and the improved targetwater quality should be based on the full range of stream flowvariation.

This study aims to suggest alternatives against the twoproblems specified above among other various problems relatedto the TMDL management system. In other words, the studyfocuses on the establishment of the fair target water qualityapplicable to the subject region and the solution of setting atarget water quality that can cover all scales of stream flowincluding dry periods and wet periods. All of the methods thisstudy followed are only based on data available and applicablefor the TMDL management system in order to increase theapplicability of the research. The target area of the study is theNakdong River basin in the southeastern Korea, adapting theTANK model which is a conceptual rainfall-runoff modelincluding the river routing function to simulate daily stream flowof the 40 unit watersheds in the Nakdong River area. Assesseddaily stream flow is used to simulate the daily stream contaminantloads through the stream flow-water quality relation curveswhich are created by the 7-parameter log-linear model combinedwith the Minimum Variance Unbiased Estimator (MVUE). Basedon the data, the representative specific load duration curves ofNakdong River can be drawn by water quality item (BOD, TP,TOC). As a result depending on the scale of stream flow, targetwater qualities of all unit watersheds are assessed. Also, therepresentative specific load duration curves apply to prioritizationof management areas by point sources and non-point sources inthe 40 unit watersheds in the Nakdong River basin.

2. Methods

2.1 Daily Stream Flow SimulationThe TANK model (Sugawara, 1995) which is a conceptual

rainfall-runoff model including the Muskingum river routingfunction is applied to simulate daily stream flows of theNakdong river basin in southeastern Korea. The Nakdong riverbasin has an area of 23,300 km2 dividing into 44 small basins andthe daily stream flows are simulated by basin. The main structureof the TANK model applied to indicate the rainfall-runoffprocess is expressed in Fig. 1 as below. Precipitation is put intothe top tank, and evaporation is subtracted from the top tank. Ifthere is no water in the top tank, evaporation is subtracted fromthe second tank, if there is no water in both the top and thesecond tank, evaporation is subtracted from the next tank and soon. The outputs from the side outlets are the calculated runoffs.The output from the top tank is considered as surface runoff,output from the second tank as intermediate runoff, from thethird tank as sub-base runoff and output from the fourth tank asbase flow. The modified TANK model with the river routingfunction added is a successful model that was adapted to the

Nakdong river basin in the assessment of climate change impactson stream flow (Kim and Kim, 2007) and the establishment ofvarious water environment plans (Kim et al., 2009; Han et al.,2009).

The TANK model is based on data of daily precipitation, airtemperature, relative humidity, wind speed, solar radiation,sunshine duration and others collected from 19 meteorologicalstations in the southeast area of Korea, which data are availablefrom the Korea Meteorological Administration website (www.kma.go.kr). Potential evapotranspiration data required to run theTANK model is previously calculated by the Penman methodand inputted.

According to the TMDL management plan, the NakdongRiver basin is divided into 41 unit watersheds. However NB-Nlocated at the exit basin is excluded in the study because flow ofthis unit watershed is always artificially controlled except wetperiod. Also to consider effect of dam some unit watersheds arere-divided on the bias of the dam. Only four dams (AD dam, IHdam, HC dam and NG dam) which are located in the level ofnational rivers and seriously affect the main stream areconsidered. As a result, finally 44 unit watersheds of theNakdong River basin are analyzed, which are described in Fig. 2.The rainfall-runoff model is calibrated by using the 8-dayinterval stream flow data collected in 40 gauging stations in theNakdong River basin during 2004~2009. Daily stream flow datais also applied for four large dam stations. According to theguideline of total maximum daily load management system, the

Fig. 1. Structure of daily rainfall-runoff model TANK

Fig. 2. Subbasins for TANK-Nakdong River Model

Determination of Standard Target Water Quality in the Nakdong River Basin for the Total Maximum Daily Load Management System in Korea

Vol. 17, No. 2 / March 2013 − 311 −

Ministry of Environment conducts the survey on water qualityand stream flow at the end of unit watershed every eight days.Water quality and stream flow measurement data can besearched and managed through the web system (http://water.nier.go.kr). The meteorological stations and gauging stations of studyarea are described in Fig. 3. Meaning of circle is unit watershedand triangle is dam.

Based on the long term daily stream flow simulation dataextracted from the model above, flow duration curves of eachunit watershed can be drawn out, and this flow duration curvescan be a measure to indicate the scale of stream flow dependingon the number of applicable days in a year or a ranking percent,providing a method of statistical understanding of total streamflow conditions in a basin (Dingman, 2002; Vogel and Fenessey,1994).

2.2 Daily Stream Contaminant Loads SimulationRegarding the estimation of contaminant loads that are trans-

ported through the river, various methods have been studied.These studies generally focused on estimating contaminant loadstransported from a certain point of the river, and they are basedon the relations between observed stream flow Q, concentrationC or contaminant loads L. This study is to calculate daily loads ofBOD, TP, TOC based on the 7-parameter log-linear model(Cohn et al., 1992; Cohn, 2005) which is a model to calculateriver contaminant loads in USGS. And the minimum varianceunbiased estimator (Han et al., 2007) is adapted to estimateparameters of the 7-parameter log-linear model.

The 7-parameter log-linear model’s basic formula is ex-pressed as below. If the seven parameters are appropriatelyassessed, the effect of steam flow changes, the effect of seasonchanges and the effect of time changes on the contaminants’concentration level could be figured out, which is a reason toselect this model.

(1)

where Q is a stream flow, β is a parameter to be estimated and Tis a daily percentage (ex, Jan. 1 means 1/365, Jan. 2 means 2/365etc). ε is a model’s tolerance and and are as below:

(2)

(3)

and are also explained similarly.Load L is defined as the amount of contaminants transported

through a certain aspect of a river during time intervals and the formula is expressed as below:

(4)

Here, C is a concentration level, Ku is a unit conversioncoefficient. It is possible to estimate relatively accurate streamflow Q(t) from the observation or simulation data however waterquality C(t) has no continuous observation data but having Ndata during the discontinuous time intervals . Therating curve is broadly used to clarify the relation betweenconcentration’s logarithm value and stream flow’s logarithmvalue (Miller, 1951; Colby, 1956; Cohn, 1995), and C(t) iscalculated from Q(t) and in general it is expressed in a linearmodel as below:

(5)

Here, means predictive vectorsand is regression coefficient. If Eq.(4) is substituted by Eq. (5), the result is shown as below:

(6)

Equation (6) is determined by continuous observation variableslike stream flow. If Eq. (5) uses In(Q) as an expectation variable,the model defined by Eq. (5) can be expressed simpler.

(7)

(8)

It is proved that Eqs. (6) and (8) become completely the samemodels by using Eq. (9).

InC β0 β1In Q/Q[ ] β2 In Q/Q[ ]{ }2+ +=

β3 T T–[ ] β4 T T–[ ]2 β5sin 2πT[ ] β6cos 2πT[ ] ε++ + + +

T T

T TΣi 1=

nTi T–( )

3

2Σi 1=n

Ti T–( )2

----------------------------------+=

T 14---Σi 1=

nTi=

Q Q

ta tb,{ }

L L t( ) tdta

tb

∫ Ku C t( )Q t( ) tdta

tb

∫= =

t1 … tN, ,{ }

Y* In C t( )( ) X t( )β* ε t( )+= =

X t( ) X0 t( ) X1 t( ) … XK t( ), , ,{ }=β* β0

* β1* … βK

*, , ,{ }= K 1+

L Ku C t( )Q t( ) tdta

tb

∫ Ku exp X t( )β* In Q t( )( )+( )ta

tb

∫= =

exp ε t( )( ) td⋅

In L t( )( ) X t( )β ε t( )+=

L exp X b( )β( )exp ε t( )( ) tdta

tb

∫=

Fig. 3. Study Area and Locations of Calibration Catchments

Ayeon Lee, Seonju Cho, Moo Jong Park, and Sangdan Kim

− 312 − KSCE Journal of Civil Engineering

(9)

When observation data vectors (Eq. (10)) and the correspondingexpectation variable matrixes (Eq. (11)) are prepared, the least-squares regression estimation to estimate parameters would becalculated by Eqs. (12) and (13).

(10)

(11)

(12)

(13)

Here, ‘ ’ means an estimate. Loads of the rating curve can be defined as Eq. (14) but

since it tends to show retransformation bias, it is not ideal fromthe statistical perspective.

(14)

In other words, if stream flow is given, an expectationvalue of loads becomes Eq. (15) but ’s expectation value canbe written as Eq. (16).

(15)

(16)

Here,

(17)

Along with the increasing size of a sample, it is hardly possiblethat an expectation value of is converged to an expectationvalue of . If the N value has a high number, the expectationvalue rate of for will be converged to .

Finney (1941) suggests the MVUE in a way to remove thesebiases, and its formula is shown below. It may sound a little morecomplex than other estimators, but it is widely known to removebiases completely.

(18)

Here,

(19)

(20)

As described above, the minimum variance unbiased estimatoris applied to the 8-day interval stream flow data provided byNational Institute of Environment Research’ water quality andstream flow networks and other DBs and web system (http://

β β*

In Ku( )

10…0

+=

YY1

…YN

Y t1( )

…YN

≡ ≡

In L t1( )( )

…In L tN( )( )

XX1

…XN

X t1( )

…XN

≡ ≡

1 In Q t1( )( ) X2 t( ) … XK t1( )… … … … …1 In Q tN( )( ) … … XK tN( )

β XC′XC( )1–XC′Y=

s2 Y XC β–( )′ Y XC β–( )/ N K 1+( )–( )=

LRC

LRC exp X t( )β( ) exp β 0 β 1In Q t( )(+( ) …+= =

Q t( )LRC

E L t( ) Q t( )[ ] exp X t( )β σ2/2+( )=

E LRC t( )[ ] E exp X t( )β( )[ ] exp X t( )β hE t( )σ2/2+( )= =

hE t( ) X t( ) XC′XC( )1–X′ t( )=

LRC

L t( )LRC E L[ ] exp σ2–( )

LMVUE LRC Gm 1 hE t( ))s2/2–(( )⋅=

Gm t( ) 1 t mm 2+------------ t2

2!----- m2

m 2+( ) m 4+( )---------------------------------- t3

3!----- …+ + + +=

m N K 1+( )–( )=

Fig. 4. Procedure Diagram of this Study

Determination of Standard Target Water Quality in the Nakdong River Basin for the Total Maximum Daily Load Management System in Korea

Vol. 17, No. 2 / March 2013 − 313 −

water.nier.go.kr) and the BOD, TP and TOC simultaneousobservation data in order to complete the stream flow-waterquality relation formula. In addition to the formula, the dailystream flow data previously simulated by the TANK model islinked to simulate the daily stream flow contaminant loads.Based on the simulated daily stream flow contaminant loads,load duration curves can be drawn out as the stream flowduration curves did before. If the load duration curves aredivided by effective area, the specific load duration curves wouldbe drawn, which make the comparisons of each basin available.Fig. 4 indicates procedure diagrams of the stream flow durationcurve, water quality-steam flow curve, load duration curve andspecific load duration curve.

3. Results

3.1 Daily Stream FlowTo estimate parameters of the model, it is required to collect

daily precipitation, daily potential evapotranspiration, dailywater withdrawal rate from water supply facilities, and dailydischarge rate from wastewater treatment plants of 44 unitwatersheds in the Nakdong River basin. The calibration ofTANK model is sequentially carried out along with river routingfrom upstream to downstream. For more quantitative decision ofobservation data’s reproduction, statistic correlations betweensimulation data and observation data are analyzed through thedeterminant coefficient R2 extracted from the regression analysis

result between the two data and through the model efficiencycoefficient suggested by Nash and Sutcliffe (1970). As a result, itis confirmed that, on average the determinant coefficient is 0.84,the model efficiency coefficient is 0.77, which show relativelyexcellent reproducing results of observation stream flow data.Fig. 5, as an example of simulation result shows observationstream flow and simulation stream flow at point NB-C and NB-Iin the Nakdong River mainstream. In the first figure, P meansdaily precipitation, and the dotted line means potential evapo-transpiration, the line means actual evapotranspiration in thesecond figure. In the third one, Q indicates daily stream flow andthe line is simulated stream flow and the dot means observedstream low.

Daily steam flows over the last 10 years (2000~2009) aresimulated and flow duration curves of each unit watershed aredrawn as well. Fig. 6 shows the flow duration curves at NB-Cand NB- I.

3.2 Daily Contaminant Loads7-parameter log-linear model is established by using the

stream flow and water quality data accumulated since 2004 in 40unit watersheds of the Nakdong River basin. Target water qualityitems are BOD which is a target substance of the TMDL

Fig. 5. Stream Flow Simulation Results: (a) Nakdong River Main-stream-C, (b) Nakdong River Mainstream-I

Fig. 6. Flow Duration Curves: (a) Nakdong River Mainstream-C,(b) Nakdong River Mainstream-I

Ayeon Lee, Seonju Cho, Moo Jong Park, and Sangdan Kim

− 314 − KSCE Journal of Civil Engineering

management system in Korea, TP and TOC which are expectedto be added soon. Fig. 7 indicates the simulation resultsconducted at NB-I. When the accuracy of 7-parameter log-linearmodel is examined through a determinant coefficient R2, devia-tions exist depending on each unit watershed but the averageaccuracy shows relatively high numbers such as 0.88 for BOD,0.89 for TP and 0.96 for TOC.

Based on the results, stream flow contaminant loads over thelast 10-year are simulated by linking with the 10-year dailystream flow data which is simulated by the TANK modelestablished in advance. And load duration curves are created inthe same way that stream flow duration curves are drawn outwith simulation data. In addition to this, the load duration curveis divided by effective area in order to make the specific loadduration curves (unit: kg/day/km2) which are load duration

curves per unit area. When the specific load duration curves areprepared by unit watershed and by water quality item, one cancalculate an arithmetic mean of the specific load duration curvesin 40 unit watersheds by water quality item in order to get therepresentative specific load duration curve in the Nakdong Riverbasin. Fig. 8 indicates the specific load duration curves collectedfrom the 40 unit watersheds and the representative specific loadduration curve in the Nakdong River basin.

Fig. 7. Results for 7-Parameter Log Linear Model (Nakdong rivermainstream-I): (a) BOD, (b) TP, (c) TOC

Fig. 8. Representative Specific Load Duration Curves: (a) BOD,(b) TP, (c) TOC

Determination of Standard Target Water Quality in the Nakdong River Basin for the Total Maximum Daily Load Management System in Korea

Vol. 17, No. 2 / March 2013 − 315 −

4. Discussions

4.1 Stream FlowThis study simulates natural stream flow of the Nakdong River

basin by using the TANK model and tries to understand thespatial flow condition of the basin. Natural stream flow means,under the current hydrologic condition in the basin, the streamflow that is not affected at all by the stream flow control effectoccurred by multipurpose dams and outflow discharge, intakedischarge performed by environment facilities. In other words,without changing the model’s parameters, the inflow dischargeof multipurpose dams become the outflow discharge of thedams, and the model is executed in the case of considering theoutflow discharge and intake discharge of environment facilitiesand agricultural intake discharge as 0. Fig. 9 shows stream flowchanges in high flow, median flow, low flow and drought flow inthe Nakdong River mainstream from upstream (NB-A) todownstream(NB-M). The drought flow means the 355th largeststream flow (Q355) among daily stream flows in a year, the lowflow is the 275th largest one (Q275), the median flow is the 185th

largest one (Q185) and the high flow is the 95th largest one(Q95). In the figure, “present” stands for a simulation result ofNakdong river mainstream, and “natural” means a simulationresult of natural stream flow.

In comparison with natural stream flow, it is confirmed thatartificially controlled stream flow of the current Nakdong Riveris relatively larger than natural stream flow. Noticeable increase

of the stream flow is detected from the NB-C where AD dam andIH dam control the stream flow. This increasing effect tends tocontinue down to the end of Nakdong River possibly because ofthe outflow discharge effect occurred by environment facilitiesin Daegu city located in the middle of the Nakdong River basinand the stream flow control effect caused by large-sized damslocated at tributaries combining into Nakdong River at the NB-Hand NB-I. However the K-L section, the downstream sectionunder the NB-I shows slightly decreased stream flow, whichmight be caused by the intensive intake discharge performed byBusan city, another big city and it is evidently proved by the factof the decreased stream flow at the Nakdong River mainstream-L in which Mulgeum intake station is located, a largest watersource in Busan city.

4.2 Standard Target Water Quality Based on simulation data related to long-term daily stream

flow and water quality, the standard target water quality by unitwatershed including the Nakdong river mainstream areas isdetermined as follows:

1) On the representative specific load duration curve, specificdaily loads of drought flow periods, low flow periods,median flow periods and high flow periods are assessedrespectively. In this case, the specific daily load of droughtflow periods means the 355th largest specific daily load(sL355) among specific daily loads in a year. And sL275 forlow flow periods, sL185 for median flow periods and sL95

Fig. 9. Comparison between Present and Natural Stream Flow in Nakdong River Main Stream: (a) High Flow Condition (Q95), (b) MedianFlow Condition (Q185), (c) Low Flow Condition (Q275), (d) Drought Flow Condition (Q355)

Ayeon Lee, Seonju Cho, Moo Jong Park, and Sangdan Kim

− 316 − KSCE Journal of Civil Engineering

for high flow periods. 2) Multiply an assessed specific daily load by an effective area

of each unit watershed in order to calculate the specificdaily load (L355) of drought flow periods, the one (L275) oflow flow periods, the one (L185) of median flow periodsand the one (L95) of high flow periods.

3) As shown in Eq. (21), calculate the standard target waterquality of each unit watershed and stream flow period bydividing the loads of each unit watershed by the streamflows of each unit watershed.

(21)

The stands for standard target water quality duringthe low flow periods. Like this method, the standard target waterquality can be assessed by unit watershed, water quality item andstream flow period.

Figures 10-12 indicate the standard target water quality ofBOD, TP and TOC during the high flow, median flow, low flowand drought flow periods in the Nakdong River mainstream fromupstream to downstream and its current water quality condition.The current water quality is calculated by applying the specificload duration curves, instead of the representative specific loadduration curves, to the target water quality calculation method.

Regardless of water quality parameters and reference flows, itis confirmed that the standard target of water quality get worse asit went down from NB-G to NB-M. Because most of outflow

discharge released from environment facilities in Daegu city areflown into the NB-G unit watershed. It was already remarked inthe Han et al. (2009), and the water quality status of Nakdongriver downstream largely depend on how to treat the pointsources discharged from Daegu-city located in the middle ofNakdong River basin.

In the Nakdong River upstream, BOD and TP of the currentwater quality are better than the standard target of water quality,but in terms of TOC. It is indicated that the current TOC waterquality in the NB-C is worse than the standard target of waterquality. The NB-C is an area where the stream flow controllingeffect is doubled by AD dam in the Nakdong River mainstreamand IH dam located in the Banbyeon River, a tributary flowinginto the mainstream. This create the same effect of having twolarge-sized lakes in the upstream of NB-C, which can beanalyzed that biological degradable organic matters are treated tosome extent due to the reinforcement of environment facilitiesbut refractory organic matters are not treated properly. Also dueto the changes in the rainfall patterns caused by the recentclimate change, there are more frequent heavy rains and therainfall intensity is getting stronger as a result, the large-scale soilloss happens more frequently, which might be raise the concernthat this is a main external source of refractory organic mattersaccumulated in the Nakdong river basin. Thus it is required tomanage TOC values of unit watersheds in the upstream ofNakdong river basin, including unit watersheds in the downstream.

Ctarget 275, L275/Q275=

Ctarget 275,

Fig. 10. Target Water Quality (BOD): (a) High Flow Condition (BOD95), (b) Median Flow Condition (BOD185), (c) Low Flow Condition(BOD275), (d) Drought Flow Condition (BOD355)

Determination of Standard Target Water Quality in the Nakdong River Basin for the Total Maximum Daily Load Management System in Korea

Vol. 17, No. 2 / March 2013 − 317 −

Fig. 11. Target Water Quality (TP): (a) High Flow Condition (TP95), (b) Median Flow Condition (TP185), (c) Low Flow Condition (TP275),(d) Drought Flow Condition (TP355)

Fig. 12. Target Water Quality (TOC): (a) High Flow Condition (TOC95), (b) Median Flow Condition (TOC185), (c) Low Flow Condition(TOC275), (d) Drought Flow Condition (TOC355)

Ayeon Lee, Seonju Cho, Moo Jong Park, and Sangdan Kim

− 318 − KSCE Journal of Civil Engineering

4.3 Prioritizing for Managing Point or Non-Point SourcesWith the representative specific load duration curves, 40 unit

watersheds of the Nakdong river basin under the TMDLmanagement system can be categorized by conditions that ifspecific load duration curve of a certain unit watershed is locatedin a lower side than the representative specific load durationcurve, it is ‘OK’, if it is located in the upper side, it is ‘NG’, if itis located in the lower side only when the loads are smaller thanthat of low flow periods, it is ‘NP’ (means a river basin havingnon-point source as a main contaminant source) and if it islocated in the lower side only when the loads are larger than thatof median flow periods, it is ‘P’ (means a river basin havingpoint source as a main contaminant source). River basinclassification results in terms of BOD, TP and TOC based onthese data are specified in Fig. 13. Regardless of water qualityitems, in the case of unit watersheds in the Nakdong Riverupstream, there are many ‘OK’ areas but more and more ‘NG’unit watersheds are gathered in the downstream. Especially inthe unit watersheds including NB-G located in the downstream,it is confirmed that the specific load duration curves are locatedin the upper side of the representative specific load durationcurve. As a result, one can explain that when contaminant loadsreleased from Daegu city located in the middle of NakdongRiver basin flow into the mainstream, the water quality iscompletely different from that of the Nakdong River upstream.In addition, it is also confirmed that almost all tributaries flowinginto the lower part of Nakdong River such as the Geumho River(GH-C), Nam River (NG-A,B,D,E), Hwang River (HG-A,B)and Milyang River (MY-A,B) have relatively worse waterquality. And in the case of unit watershed NB-A which is theuppermost stream of Nakdong river, it is found that TP pointsources are the main contaminant source and in the case of NB-Fwhich is in the midstream, BOD non-point sources are blamedfor the main contaminant source.

Interesting result is the NB-C’s result about TOC. As mentionedabove, the NB-C is an area being affected by the doubled streamflow control effect created by two large multipurpose dams,

strongly showing a lake-like characteristic. Considering the factthat BOD and TP’s results are different from TOC result, it isassumed that refractory organic matters released from AD andIH dam should be treated. Furthermore, as for TOC, it is requiredto manage non-point contaminant sources in the HG-A and NG-G unit watersheds, and near the upstream there is Jiri Mountain,the largest mountain having relatively well-preserved ecologicalenvironment. As a result, it is decided that this region releases arelatively large amount of refractory organic matters that exist ina natural state in the rain.

5. Conclusions

This study aims to determine the proper target of water qualityapplicable to river basins assigned by the TMDL managementsystem and to find alternatives to set the target of water qualityfor all flow conditions regardless of wet periods and dry periods.All methods adapted in this study are based on data available forthe TMDL management system in order to improve theapplicability of this study. This study suggests a method toevaluate the current river basin status roughly by reflecting thetotal flow conditions and corresponding water quality conditions,and applies the method to the Nakdong River basin to figure outspatial distributions in terms of BOD, TOC and TP loads.

The TANK model, a conceptual rainfall-runoff model includinga river routing function was adapted to simulate daily streamflows of 44 unit watersheds in the Nakdong river basin. Accordingto model-calibrating results, the average coefficient of determinationwas 0.84, and the average model efficiency coefficient was 0.77.It was confirmed that high reproducibility between the simulatedsteam flows and observed stream flows was found. Daily streamcontaminant loads were simulated through the stream flow-waterquality relation curves which were established by the 7-parameterlog-linear model combined with the minimum variance unbiasedestimator. As a result, deviations from observations existed ineach unit watershed, but based on the average coefficient ofdetermination by unit watershed, the relatively high accuracy

Fig. 13. Management Prioritization: (a) BOD, (b) TP, (c) TOC

Determination of Standard Target Water Quality in the Nakdong River Basin for the Total Maximum Daily Load Management System in Korea

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were found in all water quality parameters. With the result, therecent 10-year daily stream contaminant loads were calculatedby linking with previously simulated stream flow data. Loadduration curves were created from daily stream contaminantloads regardless of wet and dry periods, and specific loadduration curves of 44 unit watersheds for each water quality itemwere drawn out by dividing into the load duration curve of eachunit watersheds for each water quality item and its effective area.The representative load duration curve for each water qualityitem was constructed by calculating an arithmetic mean of 44specific load duration curves. Using the representative loadduration curve for each water quality item, the target waterquality of each unit watershed was determined and the generalstatus of water quality management of the Nakdong Rivermainstream was reviewed by comparing with the current waterquality.

Specific load duration curves created by this study haveadvantages not only in stochastic understanding of general waterquality in a certain area but also in making the data as visualdiagrams. Since it is possible to set target water quality by streamflow period, it is also expected that the specific load durationcurves can be used as basic data to determine the fairer standardtarget water quality.

Acknowledgement

This work was supported by the Korea Research Foundation(KRF) grant funded by the Korea government (MEST) (NRF-2009-0071549).

Referencess

Cohn, T. A. (1995). “Recent advances in statistical methods for theestimation of sediment and nutrient transport in rivers.” Reviews ofGeophysics, Vol. 33, No. S1, pp. 1117-1124.

Cohn, T. A. (2005). “Estimating contaminant loads in rivers: ANapplication of adjusted maximum likelihood to type 1 censoreddata.” Water Resources Research, Vol. 41, No. 7, pp. W07003.1-W07003.13.

Cohn, T. A., Caulder, D. L., Gilroy, E. J., Zynjuk, L. D. and Summers,

R. M. (1992). “The validity of a simple statistical model forestimating fluvial constituent loads: An empirical study involvingnutrient loads entering Chesapeake Bay.” Water Resources Research,Vol. 28, No. 9, pp. 2353-2364.

Colby, B. R. (1956). The relationship of sediment discharge to stream-flow, Technical Report, U.S. Geol, Surv., Reston, Va.

Dingman, S. L. (2002). Physical hydrology, 2nd edition, Prentice Hall,New Jersey.

Finney. D. J. (1941). “On the distribution of a variate whose logarithmnormally distributed.” J. R. Stat. Soc. Suppl., Vol. 7, No. 2, pp. 155-161.

Han, S., Kim, E., and Kim, S. (2009). “The water quality management inthe Nakdong river watershed using multivariate statistical techniques.”KSCE Journal of Civil Engineering, KSCE, Vol. 13, No. 1, pp. 95-105.

Han, S., Shin, H. S., and Kim, S. (2007). “Applicability of load durationcurve to Nakdong River watershed management.” Journal ofKorean Society on Water Quality, Vol. 23, No. 5, pp. 620-627.

Kim, J. C. and Kim, S. (2007). “Flow duration curve analysis forNakdong River basin using TMDL flow data.” Journal of KoreanSociety on Water Quality, Vol. 23, No. 3, pp. 332-338.

Kim, M. S., Shin, H. S, Park, J. H., and Kim, S. (2009). “Empiricalequation for pollutant loads delivery ratio in Nakdong River TMDLunit watersheds.” Journal of Korean Society on Water Quality, Vol.25, No. 4, pp. 580-588.

Korean Ministry of Environment (2004). Guideline of Korean totaldaily maximum loads, Ministry of Environment in Korea, Seoul,Korea.

Miller, C. R. (1951). Analysis of flow-duration, sediment-rating curvemethod of computing sediment yield, US Department of Interior,Bureau of Reclamation.

Nash, J. E. and Sutcliffe, J. V. (1970). “River flow forecasting throughconceptual models part 1-A discussion of principles.” Journal ofHydrology, Vol. 10, No. 3, pp. 282-290.

Novotny, V. (2004). “Simplified databased total maximum daily loads,or the world is log-normal.” Journal of Environmental Engineering,ASCE, Vol. 130, No. 6, pp. 674-683.

Sugawara, M. (1995). Tank model in computer models of watershedhydrology, Water Resources Publications, pp. 164-214.

Vogel, R. M. and Fenessey, N. M. (1994). “Flow-duration curves, 1:New interpretation and confidence intervals.” Journal of WaterResources Planning and Management, ASCE, Vol. 120, No. 4, pp.485-504.