research article effects of el nino southern oscillation...

Hindawi Publishing CorporationAdvances in MeteorologyVolume 2013 Article ID 846397 7 pageshttpdxdoiorg1011552013846397

Research ArticleEffects of El Nino Southern Oscillation onthe Discharge of Kor River in Iran

Morteza Mohsenipour1 Shamsuddin Shahid1 and M J Nazemosadat2

1 Department of Hydraulics amp Hydrology Faculty of Civil Engineering Universiti Teknologi Malaysia (UTM)81310 Johor Bahru Malaysia

2 Department of Climate Research Center and Water Engineering Agriculture Faculty Shiraz University Shiraz 71946-84471 Iran

Correspondence should be addressed to Shamsuddin Shahid sshahidutmmy

Received 6 June 2013 Revised 21 September 2013 Accepted 7 October 2013

Academic Editor Qi Hu

Copyright copy 2013 Morteza Mohsenipour et al This is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited

The objective of the study was to investigate the El Nino forcing on the discharge of Kor River located inMaharloo-Bakhtegan basinin the Fars province of IranThirty-one-year (1965ndash1995) and twenty-year (1975ndash1995) monthly mean river discharge data recordedat two stations namely Chamriz and Dehkadeh-Sefid respectively were chosen in the present study Fourier analysis was used toextract harmonic information of time series data such as amplitude and phase angle to show the maximum effect and the time ofeffect of El Nino on river dischargeThe study revealed that El Nino events caused increase of discharge in Kor River by 15 to 20and the maximum influence was in the months of February and March in El Nino years

1 Introduction

In normal condition the temperature of ocean surface in theeast of southern Pacific Ocean is lower than the temperatureof surface water in the west of southern Pacific OceanTherefore a high pressure zone and a low pressure zonedominate in the east and the west of the southern PacificOcean respectively [1] The difference between high and lowpressure zones causes wind blowing namely trade wind oreasterlies The direction of wind is from the east to the westof Pacific OceanTherefore trade wind causes the movementof surface warm water in equatorial region from the east tothe west During El Nino period the temperature of surfacewater in the west is lower than the temperature of surfacewater in the east of southern Pacific Ocean This large-scale pressure seesaw in Pacific Ocean is called SouthernOscillation (SO) Therefore the direction of trade wind andalso warm water changes from the west to the east Existingwarm water pool in the coast of Peru and Southern Ecuadoris the sign of El Nino [1 2] The two phenomena El Ninoand Southern Oscillation together are known as ENSOThe relationship between El Nino and some parameterssuch as temperature rainfall and discharge was investigated

in different parts of the world Their results have showedthat El Nino causes floods and droughts on different partsaround the world [3 4] Cayan and Peterson [5] Kahyaand Dracup [6] Zhang et al [7] Ward et al [8] Cahoon[9] Osman and Abdellatif [10] Munoz-Salinas and Castillo[11] Wang and Eltahir [12] Simpson et al [13] Kahya andKarabork [14] and many other researchers conducted theimpact of El Nino on the discharge Cayan and Peterson [5]predicted discharge anomalies in the Western United Statesin two seasons by using Southern Oscillation Index (SOI)Zubair [15] investigated the relationship between ENSO andMahaweli River discharge in Sri Lanka and showed that ElNino caused declination of river discharge in the monthsfrom January to September Zhang et al [7] showed thatrelations between ENSO and yearly maximum dischargein the lower Yangtze River basin were in-phase in ChinaChandimala and Zubair [16] presented that the correlationcoefficient between ENSO and Kelani River discharge inSri Lanka was 119903 = minus041 It means that during El Ninoevents discharge was lower than normal periods Ward et al[8] investigated the sensitivity of river discharge to El NinoSouthern Oscillation and concluded that ENSO has a greater

2 Advances in Meteorology

Dehkadeh-Sefid

Chamriz

Figure 1 Location of two hydrometric stations on Kor River in Maharloo-Bakhtegan basin of Iran

impact on annual high-flow events than on mean annualdischarge especially in the extratropics Cahoon [9] studiedthe effect of ENSO on river flows in the lower Cape FearRiver watershed of North Carolina and reported significanteffects of ENSOon flows in several winter and springmonthsOsman and Abdellatif [10] assessed the links between ENSOand variability of the annual Blue Nile flows and concludedthe Blue Nile annual flow index (AFI) is negatively correlatedto the ENSO-SST index Munoz-Salinas and Castillo [11]assessed the factors controlling sediment and water dischargein the Santiago and Panuco Rivers of central Mexico Authorsreported that water discharge in Santiago River increasesduring El Nino and La Nina events and the discharge ofPanuco River was mostly affected by La Nina events

Therefore there is no doubt that El Nino changes pre-cipitation and river discharge which in turn cause floodsand droughts and damage to environment and economy [7]However the influence of El Nino on rivers discharge is notthe same all over the world A good understanding of El Ninoeffect on river discharge can help in mitigating hydrologicaldisaster as well as river basinmanagement and planningTheobjective of the present study was to investigate the effectof ENSO on discharge of Kor River located in Maharloo-Bakhtegan basin in the Fars province of Iran Thirty-one-year (1965ndash1995)monthlymean river discharge data recordedat Chamriz hydrometric station and twenty-one-year (1975ndash1995) monthly mean river discharge data at Dehkadeh-Sefidhydrometric stationwere used in the present studyHarmonicanalysis was used to understand the effect of El Nino on riverdischarge

2 Materials and Methods

21 Description of Study Area Kor River is located inMaharloo-Bakhtegan basin in the Fars province of IranMaharloo-Bakhtegan Basin lies between latitudes 28∘991015840ndash31∘251015840 N and longitudes 51∘821015840ndash54∘501015840 E It covers an area

of about 31874 million-meter2 which is 25 of the total areaof Fars province Kor River is the most important river inMaharloo-Bakhtegan basin The location of Kor River twohydrometric stations andMaharloo-Bakhtegan basin in Farsprovince are shown in Figure 1 Stream flow in Kor River isunreliable due to uneven distribution of annual precipitationin the basin Therefore Doroodzan Dam was built in KorRiver for optimum use of water The reservoir of dam isaround 960 million-meter3 which is used for the productionof 50 million KWhyear electric energy as well as to supplywater for farms covering 112000 hectares in Ramjerd Kam-firoz and Korbal regions industries like petrochemical anddrinking water to 22 million population in the capital of Fareprovince Shiraz and some areas Therefore Kor River playsan important role in agro-economy and peoplersquos livelihood inthe basin

Number of research has been conducted on variousaspects of Kor River [17ndash21] Keshavarzi and Nabavi [17]used stream flow data to predict the frequency of domi-nant discharge for flood plain management in Kor RiverDolatabadi et al [20] analysed the streamflowdata to identifythe percentage of groundwater contribution to stream flowin Maharloo-Bakhtegan Basin which contains the Kor RiverRazmkhah [19] employed flood frequency analysis methodfor flood forecasting in Kor River Jedari et al [18] assessedthe chemical quality of water of Kor River Khalifeh et al[21] used Entropy theory to assess the number and locationof hydrometric stations necessary for monitoring hydro-dynamics of Maharloo-Bakhtegan Basin The above studiesjustify the importance of Kor River in socioeconomy of theregion

22 Data Sets There are 52 hydrometric stations in KorRiver basin however only 24 hydrometric stations are activeChamriz and Dehkadeh-Sefid hydrometric stations wereselected for two important reasons first data in these stationswere unimpaired and second the duration of data records

Advances in Meteorology 3

0

40

80

120

160

200

1965 1973 1981 19891969 1977 1985 1993

Mea

n m

onth

ly d

ischa

rge

(m3s

)

(a)

0

20

40

60

1975 1979 1983 1987 1991 1995

Mea

n m

onth

ly d

ischa

rge

1977 1981 1985 1989 1993

(m3s

)

(b)

Figure 2 Time series mean monthly discharge at (a) Chamriz station from 1965 to 1995 and (b) Dehkadeh-Sefid station from 1975 to 1995

were longer than other stations Thirty-one-year (1965ndash1995)monthly mean river discharge data at Chamriz hydrometricstation and Twenty-one-year (1975ndash1995) monthly meanriver discharge data at Dehkadeh-sefid hydrometric recordedwere used in the present study As no recent long-termunimpaired river discharge data of Kor River is available dataat those two stations up to 1995 yearwere usedData after 1995was not available and therefore the study analysed data overthe time period of 1965ndash1995 only However several numberof El Nino events occurred over the time period of 1965ndash1995 therefore it can be expected that analysis of thirty-one-year data is enough to assess the effects of El Nino SouthernOscillation on the discharge of Kor River

The river discharge data were collected from the WaterResources Research Center of Iran Time series of meanmonthly discharge at Chamriz and Dehkadeh-Sefid stationsare shown in Figures 2(a) and 2(b) respectively El Nino eventyears during study period were collected from the AustralianBureau of Meteorology which was derived based on the sealevel pressure (Trouprsquos SOI) [22] According to Troup index ifSOIwas negative for four consecutivemonths it is consideredthat El Nino event happened in that year El Nino eventsduring the study period (1965ndash1995) occurred in the years1965 1966 1969 1972 1977 1980 1982 1987 1990 1991 1993and 1994

23 Methodology

231 Fitting Distribution Function In the present studynormal lognormal Gumbel and Gamma distributions arefitted over the river discharge data to find the best fitteddistribution function Easy fit professional software which isused for probability analysis was used to find the best fitteddistribution functionThe general formula for the probabilitydensity function of the normal distribution is

119891 (119909) =

1

120590radic2120587

119890minus(119909minus120583)

22120590

2

(1)

where120583 is the location parameter and120590 is the scale parameterThe mean is the location parameter 120583

Governing equation of the probability density function oflognormal distribution is

119891 (119909) =

1

119909120590119899(2120587)05

exp(minus12

(

ln119909 minus 120583119899

120590119899

)) 119909 ge 0 (2)

where 119909 is the raw monthly discharge the index 119899 inparameters indicates that mean and standard deviations arebased on the natural logarithms in the sample 120583

119899is the mean

of ln119909 and 120590119899is the standard deviation of ln119909

The general formula for the probability density functionof the Gumbel distribution is

119891 (119909) =

1

120573

119890(119909minus120583)120573

119890minus119890

(119909minus120583)120573

(3)

where120583 is the location parameter and120573 is the scale parameterThe mean is calculated as 120583 + 05772120573

The general formula for the probability density functionof the Gamma distribution is

119891 (119909)=

((119909 minus 120583) 120573)120574minus1 exp (minus ((119909 minus 120583) 120573))120573Γ (120574)

119909 ge 120583 120573 gt 0

(4)

where 120574 is the shape parameter 120583 is the location parameter 120573is the scale parameter and Γ is the Gamma function

24 Harmonic Analysis When periodicity in data does notclearly exist harmonic analysis is carried out for analysingthe periodic components of the data There are two mainways to calculate the mean curve of a period for harmonicanalysis namely polynomial regression and Fourier analysisHowever polynomial regression often shows humps in themean curve when scatter of points is too large Furthermoredifferentiation of such polynomial function can also producefalse results [23]TheFourier series is a sumof sine and cosinefunctions that describes a periodic signal It is representedin either the trigonometric form or the exponential formFourier analysis provides an easy way to calculate the meancurve of a periodic variable as well as to calculate the times ofmaxima and minima [24ndash26] Number of studies employedFourier analysis to understand harmonics of hydrological


data and the effect of large scale atmospheric phenomenaon hydrological data Kahya and Darcup [6] used Fourieranalysis to assess the effect of El Nino southern oscillation onthe streamflow in major rivers of the United States Fourieranalysis was applied to study the areal and temporal effectson precipitation in the North-Eastern United States by Scotteand Shulman [27] Therefore Fourier analysis was chosen inthe study to understand the effect of El Nino of Kor Riverdischarge

Harmonic analysis was carried out to understand theperiodic components in stream flow of Kor River as theperiodicity was not clearly visible It appeared that thereexists an oscillation in river discharge but its frequencyis unknown Therefore Fourier analysis is carried out toestimate the parameters of the oscillation Fourier analysisrevealed the orthogonality property of sinusoids with fre-quencies restricted to the Fourier frequencies According toFourier series any sine curve can be fitted to the curveof original data Each fitted sine curve has two featuresthat describe harmonic the amplitude which indicates thedifference between maximum and minimum data and thephase angle which indicates the time of the year when themaximum happens [27] Calculation of harmonics by fittingsine curves on data was done by using following equation

119883 = 119883 +

119894=1198732

sum

119894=1

[119860119894sin(360

119901

119894119905) + 119861119894cos(360

119901

119894119905)] (5)

where119883 represents the discharge at time 119905119883 is the arithmeticmean of discharge 119901 is the fundamental period 119873 is thenumber of observations 119894 is the number of the harmonics 119905 isthe phase angle and 119860

119894and 119861

119894are the coefficients of Fourier

series Coefficients 119860119894and 119861

119894 are the amplitude of the 119894th

harmonic (maximum departure from the mean) and can bewritten as follows

119860119894=

2

119873

sum[119883 sin(360119901

119894119905)] (6)

119861119894=

2

119873

sum[119883 cos(360119901

119894119905)] (7)

Equation (1) can be rewritten as

119883 = 119883 +

119894=1198732

sum

119894=1

119862119894cos [(360119894

119901

(119905 minus 119905119894))] (8)

where

119862119894= (119860119894+ 119861119894)05

(9)

119905119894=

119901

360119894

arcsin(119860119894

119862119894

) (10)

where 119862119894is the amplitude of the 119894th harmonic and 119905

119894is the

phase angle or the time of maximum influenceKahya and Dracup [6] recommended a two-year El Nino

composite for calculating duration Therefore 24-monthperiod starting from July before El Nino event to June of

Table 1 Best fitting distribution function for each month at twostations

Month Hydrometric stationChamriz Dehkadeh-Sefid

January Lognormal LognormalFebruary Lognormal LognormalMarch Normal LognormalApril Gumbel GammaMay Lognormal LognormalJun Lognormal GammaJuly Lognormal LognormalAugust Normal LognormalSeptember Lognormal LognormalOctober Lognormal GumbelNovember Gamma LognormalDecember Lognormal Lognormal

following El Nino event was used in the present study forcomputationMinus and plus signs were given for six monthsbefore and after the El Nino event respectively and zero signduring the El Nino event

The degree of significance for the amplitude can bewritten as

Prob = 1 minus exp[

[

minus(

119862119894

(119862119901radic119873)

)

2

]

]

(11)

where

119862119901= [

1

119873

(

119873

sum

119894=1

C2119894119901

)]

05

(12)

The goodness of fit of the sine curve on time series datawas computed by using the following equation

Goodness of fit =1198622

119894

21205752

(13)

where 120575 is the total standard deviation

3 Results and Discussion

31 Distribution Function The best fitted distribution func-tions in each month at two stations are shown in Table 1The table shows that the lognormal distribution was domainat Chamriz and Dehkadeh-Sefid hydrometric stations Thebest fitted distribution curves on river discharge data forthe month of September at Chamriz and Dehkadeh-Sefidstations are shown in Figures 3(a) and 3(b) respectivelyHigh-flow events usually cause positive skew in the frequencydistribution of discharge for most of the months As thelogarithmic transformation eliminates the skew it best fittedthe distribution of river discharge in most of the monthsAs the lognormal distribution was found to best fit themonthly river discharge at about 67 cases it was consideredto compute parameters for all months to make calculationeasy Therefore cumulative probabilities for monthly meandischarges were calculated using (2)


000

010

020

030

040

525

ndash825

825

ndash1125

1125

ndash1425

1425

ndash1725

1725

ndash2025

X

f(x)

HistogramLognormal

(a)

000

010

020

030

040

195

ndash315

315

ndash435

435

ndash555

555

ndash675

675

ndash795

X

HistogramLognormal

f(x)

(b)

Figure 3 Probability density function at (a) Chamriz station in September and (b) Dehkadeh-Sefid station in September

0

10

20

30

40

50

60

70

80

July

Mar

ch

May July

Mar

ch

May

Sept

embe

r

Nov

embe

r

Janu

ary

Sept

embe

r

Nov

embe

r

Janu

ary

Mon

thly

disc

harg

e (m

3s

)

Figure 4 Fitted second harmonic on discharge in El Nino eventyears at Chamriz station

32 Fitting Sine Curve Harmonics of time series data duringEl Nino years were fitted with sine curves First two harmon-ics of time series data were used to show the influence of ElNino reasonably because the progress of El Nino events arevery slow and happen in large scale [6]Therefore the ElNinoevent years were divided into two groups namely the firstharmonic domain and the second harmonic domain

A fitted sine curve on data is shown in Figure 4 Theamplitudes of the first and the second harmonics for El Ninoevent years were calculated using (9) Results showed thatcalculated amplitudes for the first harmonicwere greater thanthe calculated amplitudes for the second harmonics in 65cases at both stations The mean amplitudes for the first andsecond harmonics at both stations are shown in Table 2

The magnitude of the first harmonic represents themagnitude of the streamflow response to the ENSO events

Table 2 Calculated parameters of sine curves at two stations understudy

Harmonic Station

Chamriz Dehkadeh-Sefid

Amplitude First 01 012Second 014 010

Mean First 055 058Second 051 050

InfluenceFirst 01 + 05 = 015

or 15012 + 008 =

02 or 20

Second 014 + 001 =

015 or 1501 + 0 = 01

or 10Goodness offit ()

First 60 58Second 30 35

Significance First 65 85Second 48 60

[6] A discrepancy occurs in the magnitude of response ifthe mean and median of a composite are not equal In thatcase Kahya and Dracup [6] proposed that magnitude of theresponse can be correctly estimated by the summation of thecomputed amplitude and the difference between the meanand median For lognormal distribution data the mean isgreater than medianTherefore the difference between meanandmedianwas added to amplitude tomeasure the influenceThe means of data for the first and the second harmonics atboth stations are shown in Table 2 The difference betweenmean and median were 005 001 and 008 0 for the firstand the second harmonics at Chamriz and Dehkadeh-Sefidstations respectively Therefore the values were added tocalculated amplitudes and show the maximum influence ofEl Nino on discharge The maximum influences of El Ninoon discharges at two stations are shown in Table 2


0

20

40

60

80

100

120

El Nino years Normal years

Mar

ch

April

May

June July

Augu

st

Oct

ober

Janu

ary

Sept

embe

r

Nov

embe

r

Febr

uary

Dec

embe

r

Mon

thly

disc

harg

e (m

3s

)

Figure 5Monthlymean discharge during ElNino years and normalyears at Chamriz station

33 Goodness Fit and Degree of Significance Test Equations(13) and (11) were used to calculate the goodness of fitand degree of significance (DOS) of sine curves on datarespectively The results are shown in Table 2 It was foundthat the goodness fit for the first harmonic was much betterthan the second harmonic The significant test showed thatprobability of ElNino effect on discharge amplitudeswas highfor the first harmonic The probability was 65 for Chamrizand 85 for Dehkadeh-Sefid station

34 Time of Maximum Influence The phase angle or thetime of maximum influence was calculated for the first andthe second harmonics using (10) The maximum influencefor both stations was found to occur at 728th and 854thmonth from the beginning of 24-month period for the firstand the second harmonics respectively In other words themaximum influence occurred in the month of February andMarch of the El Nino year for the first and the secondharmonics The positive sign indicates that El Nino causedincreased discharge

35 Comparison of El Nino and Normal Periods Compar-isons between monthly mean discharge in El Nino yearsand normal years showed good agreement with the obtainedresults Figure 5 shows monthly mean discharge and 95confidence level of mean discharge for both El Nino yearsand normal years at Chamriz station It can be seen fromFigure 5 that monthly discharge in the months of March ismuch higher in El Nino years compared to normal years

4 Conclusions

Fourier analysis was used to extract harmonic informationof monthly river discharge data to understand the influenceof El Nino on the discharge of Kor River Amplitude andphase angle which are two characteristics of Fourier serieswere used to show the maximum influence and the time

influence of El Nino on river discharge The results showedthat probability of El Nino effect on discharge amplitudes washigh for the first harmonic and 65 and 85 for Chamriz andDehkadeh-Sefid stations respectively In average El Ninocaused increased discharge by 15 at Chamriz station and20atDehkadeh-Sefid stationThe time ofmaximum impactwas found in the months of February and March of theEl Nino year It can be expected that the results obtainedin the present study will help to understand the variationsof river discharge due to El Nino which in turn will helpwater managers dam operators and policy makers in waterresources planning and management as well as flood anddrought forecasting and mitigation

References

[1] S Vogel ldquoDeep-root disturbancerdquo Discover vol 10 no 7 pp26ndash29 1989

[2] N Nicholas ldquoThe El Nino-Southern oscillation phenomenonrdquoReport National Center for Atomic Research Boulder ColoUSA 1987

[3] S Jain and U Lall ldquoFloods in a changing climate does the pastrepresent the futurerdquo Water Resources Research vol 37 no 12pp 3193ndash3205 2001

[4] P Aceituno ldquoOn the functioning of the Southern Oscillationin the South American sector Part I surface climaterdquo MonthlyWeather Review vol 116 no 3 pp 505ndash524 1988

[5] D R Cayan and D H Peterson ldquoThe influence of North Pacificatmospheric circulation on streamflow in thewestrdquo inAspects ofClimate Variability in the Pacific and the Western of America DH Peterson Ed vol 55 ofGeophysicalMonograph pp 375ndash397American Geophysical Union

[6] E Kahya and J A Dracup ldquoUS streamflow patterns in relationto the El NinoSouthern OscillationrdquoWater Resources Researchvol 29 no 8 pp 2491ndash2503 1993

[7] Q Zhang C-Y Xu T Jiang and Y Wu ldquoPossible influence ofENSO on annual maximum streamflow of the Yangtze RiverChinardquo Journal of Hydrology vol 333 no 2ndash4 pp 265ndash2742007

[8] P J Ward W Beets L M Bouwer J C J H Aerts and HRenssen ldquoSensitivity of river discharge to ENSOrdquo GeophysicalResearch Letters vol 37 no 12 Article ID L12402 2010

[9] L Cahoon ldquoEl Nino-Southern oscillation effects on river flowsin the lower cape fear RiverWatershedNorthCarolinardquo Journalof North Carolina Academy of Science vol 128 no 34 pp 74ndash80 2012

[10] Y Z Osman and M E Abdellatif ldquoEl Nino Cycles andvariability of the Blue Nile annual flow in the Sudanrdquo inProceedings of the International Conference on Climate ChangeEffects Potsdam Germany May 2013

[11] E Munoz-Salinas and M Castillo ldquoSediment and water dis-charge assessment on santiago and Panuco rivers (CentralMexico) the importance of topographic and climatic factorsrdquoGeografiskaAnnaler A vol 95 no 2 pp 171ndash183 2013

[12] G Wang and E A B Eltahir ldquoUse of ENSO information inmedium- and long-range forecasting of the Nile floodsrdquo Journalof Climate vol 12 no 6 pp 1726ndash1737 1999

[13] H J Simpson M A Cane A L Herczeg S E Zebiak and JH Simpson ldquoAnnual river discharge in southeastern Australiarelated to El Nino-Southern Oscillation forecasts of sea surface


temperaturesrdquo Water Resources Research vol 29 no 11 pp3671ndash3680 1993

[14] E Kahya and M C Karabork ldquoThe analysis of El Nino and LaNina signals in streamflows of Turkeyrdquo International Journal ofClimatology vol 21 no 10 pp 1231ndash1250 2001

[15] L Zubair ldquoEl Nino-southern oscillation influences on theMahaweli streamflow in Sri Lankardquo International Journal ofClimatology vol 23 no 1 pp 91ndash102 2003

[16] J Chandimala and L Zubair ldquoPredictability of stream flow andrainfall based on ENSO for water resources management in SriLankardquo Journal of Hydrology vol 335 no 3-4 pp 303ndash312 2007

[17] A R Keshavarzi and S H Nabavi ldquoDominant discharge inthe kor river fars province Iranrdquo in Proceedings of the 10thInternationalWater TechnologyConference (IWTC rsquo10) pp 299ndash306 Assiut University Alexandria Egypt 2006

[18] J Jedari E Moghimi M Yamani H Mohammadi and AR Eisai ldquoEffect of eco-geomorphologic on water chemicalquality case study kor river Iranrdquo Journal Geographic andEnvironmental Management vol 37 no 1 pp 17ndash32 2009

[19] H Razmkhah ldquoPredict the discharge of flood using frequencyanalysis case study kor river Iranrdquo in Proceedings of the 1stNational Conference on Snow and Avalanche Iran 2010

[20] N Dolatabadi A Farid Hosseni K Davari and A MosaedildquoPredict base flow using recursive digital filter case studymaharloo-bakhtegan basin Iranrdquo in Proceedings of the 3rdInternational Conference on IntegratedWaterManagement Iran2011

[21] S Khalifeh S Karimi Goghari B Bakhteyari and E KhalifehldquoEffect of data categorization on data index to evaluationof hydrometric networkrdquo in Proceedings of the 11th NationalConference on Irrigation and Evaporation Iran 2011

[22] A J Troup ldquoThe Southern oscillationrdquo Quarterly Journal ofRoyal Meteorological Society vol 91 no 390 pp 490ndash506 1965

[23] D S G Pollock ldquoInvestigating economic trends and cyclesrdquo inPalgrave Handbook of Econometrics T C Mills and K Patter-son Eds vol 2 of Applied Econometrics Palgrave MacmillanLtd Houndmills UK 2008

[24] B-Y Qing Z-S Teng Y-P Gao and H Wen ldquoApproach forelectrical harmonic analysis based on nuttall window double-spectrum-line interpolation FFTrdquo Proceedings of the ChineseSociety of Electrical Engineering vol 28 no 25 pp 153ndash1582008

[25] B Zeng Z-S Teng H Wen and B-Y Qing ldquoApproach forharmonic analysis based on Rife-Vincent window interpolationFFTrdquo Proceedings of the Chinese Society of Electrical Engineeringvol 29 no 10 pp 115ndash120 2009

[26] H Wen Z Teng Y Wang and B Zeng ldquoAccurate algorithmfor harmonic analysis based on minimize sidelobe windowrdquoin Proceedings of the International Conference on MeasuringTechnology and Mechatronics Automation (ICMTMA rsquo10) pp386ndash389 March 2010

[27] CM Scott andM D Shulman ldquoAn areal and temporal analysisof precipitation in the northwestern United Statesrdquo Journal ofApplied Meteorology vol 18 no 5 pp 627ndash633 1979

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

EcologyInternational Journal of


EarthquakesJournal of


Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Mining


Journal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

OceanographyInternational Journal of


Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal ofPetroleum Engineering


GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Atmospheric SciencesInternational Journal of


OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Advances in


MineralogyInternational Journal of


MeteorologyAdvances in

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Geological ResearchJournal of


Geology Advances in


Dehkadeh-Sefid

Chamriz

Figure 1 Location of two hydrometric stations on Kor River in Maharloo-Bakhtegan basin of Iran

impact on annual high-flow events than on mean annualdischarge especially in the extratropics Cahoon [9] studiedthe effect of ENSO on river flows in the lower Cape FearRiver watershed of North Carolina and reported significanteffects of ENSOon flows in several winter and springmonthsOsman and Abdellatif [10] assessed the links between ENSOand variability of the annual Blue Nile flows and concludedthe Blue Nile annual flow index (AFI) is negatively correlatedto the ENSO-SST index Munoz-Salinas and Castillo [11]assessed the factors controlling sediment and water dischargein the Santiago and Panuco Rivers of central Mexico Authorsreported that water discharge in Santiago River increasesduring El Nino and La Nina events and the discharge ofPanuco River was mostly affected by La Nina events

Therefore there is no doubt that El Nino changes pre-cipitation and river discharge which in turn cause floodsand droughts and damage to environment and economy [7]However the influence of El Nino on rivers discharge is notthe same all over the world A good understanding of El Ninoeffect on river discharge can help in mitigating hydrologicaldisaster as well as river basinmanagement and planningTheobjective of the present study was to investigate the effectof ENSO on discharge of Kor River located in Maharloo-Bakhtegan basin in the Fars province of Iran Thirty-one-year (1965ndash1995)monthlymean river discharge data recordedat Chamriz hydrometric station and twenty-one-year (1975ndash1995) monthly mean river discharge data at Dehkadeh-Sefidhydrometric stationwere used in the present studyHarmonicanalysis was used to understand the effect of El Nino on riverdischarge

2 Materials and Methods

21 Description of Study Area Kor River is located inMaharloo-Bakhtegan basin in the Fars province of IranMaharloo-Bakhtegan Basin lies between latitudes 28∘991015840ndash31∘251015840 N and longitudes 51∘821015840ndash54∘501015840 E It covers an area

of about 31874 million-meter2 which is 25 of the total areaof Fars province Kor River is the most important river inMaharloo-Bakhtegan basin The location of Kor River twohydrometric stations andMaharloo-Bakhtegan basin in Farsprovince are shown in Figure 1 Stream flow in Kor River isunreliable due to uneven distribution of annual precipitationin the basin Therefore Doroodzan Dam was built in KorRiver for optimum use of water The reservoir of dam isaround 960 million-meter3 which is used for the productionof 50 million KWhyear electric energy as well as to supplywater for farms covering 112000 hectares in Ramjerd Kam-firoz and Korbal regions industries like petrochemical anddrinking water to 22 million population in the capital of Fareprovince Shiraz and some areas Therefore Kor River playsan important role in agro-economy and peoplersquos livelihood inthe basin

Number of research has been conducted on variousaspects of Kor River [17ndash21] Keshavarzi and Nabavi [17]used stream flow data to predict the frequency of domi-nant discharge for flood plain management in Kor RiverDolatabadi et al [20] analysed the streamflowdata to identifythe percentage of groundwater contribution to stream flowin Maharloo-Bakhtegan Basin which contains the Kor RiverRazmkhah [19] employed flood frequency analysis methodfor flood forecasting in Kor River Jedari et al [18] assessedthe chemical quality of water of Kor River Khalifeh et al[21] used Entropy theory to assess the number and locationof hydrometric stations necessary for monitoring hydro-dynamics of Maharloo-Bakhtegan Basin The above studiesjustify the importance of Kor River in socioeconomy of theregion

22 Data Sets There are 52 hydrometric stations in KorRiver basin however only 24 hydrometric stations are activeChamriz and Dehkadeh-Sefid hydrometric stations wereselected for two important reasons first data in these stationswere unimpaired and second the duration of data records


0

40

80

120

160

200

1965 1973 1981 19891969 1977 1985 1993

Mea

n m

onth

ly d

ischa

rge

(m3s

)

(a)

0

20

40

60

1975 1979 1983 1987 1991 1995

Mea

n m

onth

ly d

ischa

rge

1977 1981 1985 1989 1993

(m3s

)

(b)




23 Methodology


119891 (119909) =

1

120590radic2120587

119890minus(119909minus120583)

22120590

2

(1)



119891 (119909) =

1

119909120590119899(2120587)05

exp(minus12

(

ln119909 minus 120583119899

120590119899

)) 119909 ge 0 (2)


119899is the mean



119891 (119909) =

1

120573

119890(119909minus120583)120573

119890minus119890

(119909minus120583)120573

(3)



119891 (119909)=


119909 ge 120583 120573 gt 0

(4)






119883 = 119883 +

119894=1198732

sum

119894=1

[119860119894sin(360

119901

119894119905) + 119861119894cos(360

119901

119894119905)] (5)


119894and 119861





119860119894=

2

119873

sum[119883 sin(360119901

119894119905)] (6)

119861119894=

2

119873

sum[119883 cos(360119901

119894119905)] (7)


119883 = 119883 +

119894=1198732

sum

119894=1

119862119894cos [(360119894

119901

(119905 minus 119905119894))] (8)

where

119862119894= (119860119894+ 119861119894)05

(9)

119905119894=

119901

360119894

arcsin(119860119894

119862119894

) (10)


119894is the








Prob = 1 minus exp[

[

minus(

119862119894

(119862119901radic119873)

)

2

]

]

(11)

where

119862119901= [

1

119873

(

119873

sum

119894=1

C2119894119901

)]

05

(12)



119894

21205752

(13)





000

010

020

030

040

525

ndash825

825

ndash1125

1125

ndash1425

1425

ndash1725

1725

ndash2025

X

f(x)

HistogramLognormal

(a)

000

010

020

030

040

195

ndash315

315

ndash435

435

ndash555

555

ndash675

675

ndash795

X

HistogramLognormal

f(x)

(b)


0

10

20

30

40

50

60

70

80

July

Mar

ch

May July

Mar

ch

May

Sept

embe

r

Nov

embe

r

Janu

ary

Sept

embe

r

Nov

embe

r

Janu

ary

Mon

thly

disc

harg

e (m

3s

)






Harmonic Station





or 15012 + 008 =

02 or 20

Second 014 + 001 =

015 or 1501 + 0 = 01






0

20

40

60

80

100

120


Mar

ch

April

May

June July

Augu

st

Oct

ober

Janu

ary

Sept

embe

r

Nov

embe

r

Febr

uary

Dec

embe

r

Mon

thly

disc

harg

e (m

3s

)





4 Conclusions



References







































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


0

40

80

120

160

200

1965 1973 1981 19891969 1977 1985 1993

Mea

n m

onth

ly d

ischa

rge

(m3s

)

(a)

0

20

40

60

1975 1979 1983 1987 1991 1995

Mea

n m

onth

ly d

ischa

rge

1977 1981 1985 1989 1993

(m3s

)

(b)




23 Methodology


119891 (119909) =

1

120590radic2120587

119890minus(119909minus120583)

22120590

2

(1)



119891 (119909) =

1

119909120590119899(2120587)05

exp(minus12

(

ln119909 minus 120583119899

120590119899

)) 119909 ge 0 (2)


119899is the mean



119891 (119909) =

1

120573

119890(119909minus120583)120573

119890minus119890

(119909minus120583)120573

(3)



119891 (119909)=


119909 ge 120583 120573 gt 0

(4)






119883 = 119883 +

119894=1198732

sum

119894=1

[119860119894sin(360

119901

119894119905) + 119861119894cos(360

119901

119894119905)] (5)


119894and 119861





119860119894=

2

119873

sum[119883 sin(360119901

119894119905)] (6)

119861119894=

2

119873

sum[119883 cos(360119901

119894119905)] (7)


119883 = 119883 +

119894=1198732

sum

119894=1

119862119894cos [(360119894

119901

(119905 minus 119905119894))] (8)

where

119862119894= (119860119894+ 119861119894)05

(9)

119905119894=

119901

360119894

arcsin(119860119894

119862119894

) (10)


119894is the








Prob = 1 minus exp[

[

minus(

119862119894

(119862119901radic119873)

)

2

]

]

(11)

where

119862119901= [

1

119873

(

119873

sum

119894=1

C2119894119901

)]

05

(12)



119894

21205752

(13)





000

010

020

030

040

525

ndash825

825

ndash1125

1125

ndash1425

1425

ndash1725

1725

ndash2025

X

f(x)

HistogramLognormal

(a)

000

010

020

030

040

195

ndash315

315

ndash435

435

ndash555

555

ndash675

675

ndash795

X

HistogramLognormal

f(x)

(b)


0

10

20

30

40

50

60

70

80

July

Mar

ch

May July

Mar

ch

May

Sept

embe

r

Nov

embe

r

Janu

ary

Sept

embe

r

Nov

embe

r

Janu

ary

Mon

thly

disc

harg

e (m

3s

)






Harmonic Station





or 15012 + 008 =

02 or 20

Second 014 + 001 =

015 or 1501 + 0 = 01






0

20

40

60

80

100

120


Mar

ch

April

May

June July

Augu

st

Oct

ober

Janu

ary

Sept

embe

r

Nov

embe

r

Febr

uary

Dec

embe

r

Mon

thly

disc

harg

e (m

3s

)





4 Conclusions



References







































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in




119883 = 119883 +

119894=1198732

sum

119894=1

[119860119894sin(360

119901

119894119905) + 119861119894cos(360

119901

119894119905)] (5)


119894and 119861





119860119894=

2

119873

sum[119883 sin(360119901

119894119905)] (6)

119861119894=

2

119873

sum[119883 cos(360119901

119894119905)] (7)


119883 = 119883 +

119894=1198732

sum

119894=1

119862119894cos [(360119894

119901

(119905 minus 119905119894))] (8)

where

119862119894= (119860119894+ 119861119894)05

(9)

119905119894=

119901

360119894

arcsin(119860119894

119862119894

) (10)


119894is the








Prob = 1 minus exp[

[

minus(

119862119894

(119862119901radic119873)

)

2

]

]

(11)

where

119862119901= [

1

119873

(

119873

sum

119894=1

C2119894119901

)]

05

(12)



119894

21205752

(13)





000

010

020

030

040

525

ndash825

825

ndash1125

1125

ndash1425

1425

ndash1725

1725

ndash2025

X

f(x)

HistogramLognormal

(a)

000

010

020

030

040

195

ndash315

315

ndash435

435

ndash555

555

ndash675

675

ndash795

X

HistogramLognormal

f(x)

(b)


0

10

20

30

40

50

60

70

80

July

Mar

ch

May July

Mar

ch

May

Sept

embe

r

Nov

embe

r

Janu

ary

Sept

embe

r

Nov

embe

r

Janu

ary

Mon

thly

disc

harg

e (m

3s

)






Harmonic Station





or 15012 + 008 =

02 or 20

Second 014 + 001 =

015 or 1501 + 0 = 01






0

20

40

60

80

100

120


Mar

ch

April

May

June July

Augu

st

Oct

ober

Janu

ary

Sept

embe

r

Nov

embe

r

Febr

uary

Dec

embe

r

Mon

thly

disc

harg

e (m

3s

)





4 Conclusions



References







































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


000

010

020

030

040

525

ndash825

825

ndash1125

1125

ndash1425

1425

ndash1725

1725

ndash2025

X

f(x)

HistogramLognormal

(a)

000

010

020

030

040

195

ndash315

315

ndash435

435

ndash555

555

ndash675

675

ndash795

X

HistogramLognormal

f(x)

(b)


0

10

20

30

40

50

60

70

80

July

Mar

ch

May July

Mar

ch

May

Sept

embe

r

Nov

embe

r

Janu

ary

Sept

embe

r

Nov

embe

r

Janu

ary

Mon

thly

disc

harg

e (m

3s

)






Harmonic Station





or 15012 + 008 =

02 or 20

Second 014 + 001 =

015 or 1501 + 0 = 01






0

20

40

60

80

100

120


Mar

ch

April

May

June July

Augu

st

Oct

ober

Janu

ary

Sept

embe

r

Nov

embe

r

Febr

uary

Dec

embe

r

Mon

thly

disc

harg

e (m

3s

)





4 Conclusions



References







































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


0

20

40

60

80

100

120


Mar

ch

April

May

June July

Augu

st

Oct

ober

Janu

ary

Sept

embe

r

Nov

embe

r

Febr

uary

Dec

embe

r

Mon

thly

disc

harg

e (m

3s

)





4 Conclusions



References







































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


























Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in

research article effects of el nino southern oscillation...

Documents