RAINFALL TREND ANALYSIS BY MANN- KENDALL TEST FOR VAMANAPURAM RIVER BASIN, KERALA

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1 Interntionl Journl of Civil Engineering nd Technology (IJCIET) Volume 9, Issue 13, December 218, pp , Article ID: IJCIET_9_13_156 Avilble online t ISSN Print: nd ISSN Online: IAEME Publiction Scopus Indexed RAINFALL TREND ANALYSIS BY MANN- KENDALL TEST FOR VAMANAPURAM RIVER BASIN, KERALA Mrs. Anie John. S * Reserch Scholr, Deprtment of Civil Engineering, Kruny Institute of Technology nd Sciences, Coimbtore Dr. J. Brem Professor, Deprtment of Civil Engineering, Kruny Institute of Technology nd Sciences, Coimbtore *corresponding uthor ABSTRACT The rinfll trend nlysis study helps to ssess the monsoon pttern of the selected river bsin so s to predict chnces of occurrence of flood. This study ims to nlyse the rinfll trend in Vmnpurm River bsin, South Kerl, Indi. Thirty yers ( ) of monthly rinfll dt hs been nlysed using Mnn-Kendll test nd Sen s slope estimtion methods. The nlysis hs been done by the use of XLSTAT 217 softwre. Sen s Slope fctor (Q) hs lso been estimted in the study. In Mnn- Kendll test, the test sttistics (Zc) for Mrch, April, June, July, September, October, November nd December shows rising trend while Zc vlues corresponding to the months, Jnury, Februry, My nd August re showing negtive trend during the study period. Key words: Trend nlysis, Mnn-Kendll test, Sen s Slope fctor Cite this Article: Mrs. Anie John. S nd Dr. J. Brem, Rinfll Trend Anlysis by Mnn-Kendll Test for Vmnpurm River Bsin, Kerl, Interntionl Journl of Civil Engineering nd Technology, 9(13), 218, pp INTRODUCTION The erth s climte hs chnged over the pst century in terms of vrition of rinfll nd temperture. Min impct of climte chnge is the chnging precipittion ptterns. Chnges in rinfll due to globl wrming will influence the hydrologicl cycle nd the pttern of stremflows nd demnds (prticulrly griculturl), requiring review of hydrologic design nd mngement prctices. Urbniztion is lso leding to climte chnge with chnging lnduse editor@ieme.com

2 Mrs. Anie John. S nd Dr. J. Brem from the impct of griculturl nd irrigtion prctices [1]. Chnges in run-off nd its distribution will depend on likely future climte scenrios [2]. Any chnges in precipittion ptterns will hve n impct of strem flow s they re directly proportionl. The rinfll received in n re is n importnt fctor in determining the mount of wter vilble to meet vrious demnds, such s griculturl, industril, domestic wter supply nd for hydroelectric power genertion. The vrition of South West monsoon in mny prt of the country is directly ffecting the griculturl production nd thus the overll economy got ffected. It hs been shown in vrious studies [3] tht hevy rinfll occurs in monsoon seson nd the scrcity is observed in non- monsoon seson. The hevy rinfll leds to flood nd the other seson exhibits insufficiency of wter to fulfill the requirement especilly irrigtion requirement. The recent flood occurred in Kerl especilly in Vmnpurm river cused life thret to mny lives nd the griculturl lnd. Mny reserchers studied the rinfll trend in vrious prts of the country. Trend nlysis of rinfll for the period t 11 sttions in Himchl Prdesh indicted incresing trend in nnul rinfll t 8 sttions [4]. Kothwle et l. [5] studied the ssocition between El Niño Southern Oscilltion (ENSO) nd monsoon rinfll over Indi nd reported strong ssocition between El Niño events nd deficient monsoon rinfll. Decresing trends, prticulrly for sttions in the hilly terrin, were found in nnul extreme rinfll over Kerl [6]. In view of ll bove problems, the present study hd done s n ttempt to find out the trend of most importnt climtic vrible, rinfll. Trend nlysis of monthly nd nnul rinfll of the selected river bsin will helpful to mnge the storm wter nd flood in the ctchment. In the present study, trend nlysis of rinfll dt from four rin guges situted within the bsin, for selected 3 yers ( ) is used. Mnn-Kendll test nd Sen s slope estimtion methods re used to study the trend by the use of XLSTAT 217 softwre. 2. MATERIALS AND METHODS 2.1. Study re Figure 1 Loction Mp of the Vmnpurm River Bsin editor@ieme.com

3 Rinfll Trend Anlysis by Mnn-Kendll Test for Vmnpurm River Bsin, Kerl The Vmnpurm river is the longest perennil river (length 88 km) in south Kerl with ctchment re of 787 sq. km. is locted minly in Thiruvnnthpurm district nd smll prt flls in Kollm district of Kerl Stte. Fig.1 shows the loction mp of the Vmnpurm River Bsin. Vmnpurm River Bsin is bounded by ltitudes of N nd N nd longitudes of E nd E. The Vmnpurm River Bsin is bounded by Nedumngd Tluk of Thiruvnnthpurm district in the South, Kottrkkr Tluk of Kollm districts in the North, Tmil Ndu in the Est nd Arbin se in the West. The re forms prt of the midlnd terrin of the stte, chrcterized by lteritic uplnds with undulting topogrphy nd intermittent vlleys. The min strem origintes from the foothills of the Ponmudi hills (174 m bove msl) nd the tributries from the surrounding hills like Kllr. The river then flows through Vmnpurm town nd two-brnch strems join t Attrmoodu nd t this loction the minstrem is clled s Kilimnur river. The min strem then flows nd joins the Kdinmkulm bckwter t the northern extremity. It debouches into the Arbin Se t Mudlpllipozhi ner Perumthur, 25 km north of Thiruvnnthpurm city. The mjor portion of the Vmnpurm River flows through midlnd terrin nd the remining through highlnd nd lowlnd res. The river bsin consists of high to moderte nd low flood risk res Dt Collection The mjor dt utilized for the study is rinfll dt comprising of rinfll durtions nd intensities in Vmnpurm River Bsin, Kerl. Thirty (3) yers of monthly rinfll dt rnging from 1984 to 213 from the four rin guge sttions nmely Nedumngd, Thiruvnnthpurm, Punlur nd Vrkl. The dt were obtined from Indin Meteorologicl Deprtment (IMD), Thiruvnnthpurm, Kerl Trend Anlysis Trend nlysis of time series consists of the mgnitude of trend nd its sttisticl significnce. This is sttisticl method which is being used for studying the sptil vrition nd temporl trends of hydroclimtic series. The uthors [7] hve discussed the chnge detection methodologies for hydrologic dt. The mgnitude of trend in time series is determined either using regression nlysis (prmetric test) or using Sen s estimtor method (non-prmetric method) [8]. Both these methods ssume liner trend in the time series. Regression nlysis is conducted with time s the independent vrible nd rinfll s the dependent vrible. The regression nlysis cn be crried out directly on the time series or on the nomlies (i.e. devition from men). A liner eqution, y = mt + c, defined by c (the intercept) nd trend m (the slope), cn be fitted by regression. The liner trend vlue represented by the slope of the simple lest-squre regression line provided the rte of rise/fll in the vrible. Sen s estimtor hs been widely used for determining the mgnitude of trend in hydrometeorologicl time series. In this method, the slopes (T i ) of ll dt pirs re first clculted by 1 Where xj nd xk re dt vlues t time j nd k (j > k) respectively. The medin of these N vlues of Ti is Sen s estimtor of slope which is clculted s editor@ieme.com

4 Mrs. Anie John. S nd Dr. J. Brem T N β = 1 T 2 N 2 + T N N is odd, N is even, (2) A positive vlue of β indictes n upwrd (incresing) trend nd negtive vlue indictes downwrd (decresing) trend in the time series Significnce of trend To scertin the presence of sttisticlly significnt trend in hydrologic climtic vribles such s temperture nd precipittion with reference to climte chnge, non-prmetric Mnn Kendll (MK) test hs been employed [9 14]. The MK test checks the null hypothesis of no trend versus lterntive hypothesis of the existence of incresing or decresing trend. Mnn- Kendll test is preferred when vrious sttions re tested in single study [15]. Mnn-Kendll test hd been formulted by [16] s non-prmetric test for trend detection nd the test sttistic distribution hd been given by [17 ]for testing non-liner trend nd turning point. The sttistics (S) is defined s S = N 1 N sgn ( x j x i ), i= 1 j= i+ 1 (3) Where N is the number of dt points. Assuming (xj xi) = θ, the vlue of sgn(θ) is computed s follows: 1 if θ > sgn( θ ) = if θ > 1 if θ >, (4) This sttistics represents the number of positive differences minus the number of negtive differences for ll the differences considered. For lrge smples (N > 1), the test is conducted using norml distribution, with men nd vrince s follows: E[ S] = N ( N 1)(2 N + 5) tk ( t k = 1 vr( S) = 18 n k 1)(2t k + 5), (6) where n is the number of tied (zero difference between compred vlues) groups nd tk the number of dt points in the kth tied group. The stndrd norml devite (Z-sttistics) is then computed s Z = S 1 vr( S) S + 1 vr( S) if if if S > S = S < (5) (7) editor@ieme.com

5 Rinfll Trend Anlysis by Mnn-Kendll Test for Vmnpurm River Bsin, Kerl If the computed vlue of Z > zα/2, the null hypothesis (H) is rejected t α level of significnce in two-sided test. In this nlysis, the null hypothesis ws tested t 95% confidence level. 3. RESULTS AND DISCUSSION Fig. 2 shows the nnul totl rinfll vrition nd it is shown tht the mximum rinfll of mm occurred in 26 nd minimum rinfll occurred in 212 of mm. The yer 26 is referred s wet yer nd 212 dry yer mong the study period. Figure 2 Annul Rinfll of 3 yers for Vmnpurm river bsin R i n Yer Jnury februry Mrch April Figure 3 Rinfll vrition of 3 yers -Jnury, Februry, Mrch nd April months It is lso shown tht the verge rinfll for the selected study period of 3 yers is mm. The October month observed mximum verge rinfll of mm nd June month shows the second highest of mm for the study period of 3 yers. The lowest rinfll observed during Jnury which is mm. It is due to the onset of South West monsoon nd North-Est monsoon in the month of June nd October respectively. Figs. 3, 4 & 5 shows the yerly rinfll vrition for selected study period of 3 yers for individul months. In the non-prmetric Mnn-Kendll test, trend of rinfll for 3 yers from Jnury to December hs been clculted for ech month individully together with the Sen s mgnitude editor@ieme.com

6 Mrs. Anie John. S nd Dr. J. Brem of slope (Q) by the use of XLSTAT 217 softwre. The results shows tht in the Mnn-Kendll test the Zc sttistics reveled the trend of the series for 3 yers for individul 12 months from Jnury to December which re -.24, -.11,.33,.36, -.89,.412,.196, -.65,.22,.44,.93 nd.169 respectively. R i n f l Yer My June Figure 4 Rinfll vrition of 3 yers -My, June, July nd August months July August R i n f l l September October November December Yer Figure 5 Rinfll vrition of 3 yers - September, October, November nd December months. Fig. 6 shows the vrition in Zc vlues for different months. Highest positive trend is observed during the month of June which is.412. The highest negtive trend (-.24) is shown in the month of Jnury. These re the implictions of the effect of South West monsoon. Tble 1 showed the Sen s slope estimtion fctor nd Kendll test sttistics (Zc) for the study period for individul months. There is negtive trend in the month of Februry, My nd August nd the other months showed the positive trend. The positive trend of rinfll is due to the onset of S-W monsoon nd N-E monsoon in Kerl especilly in the month of June editor@ieme.com

7 Rinfll Trend Anlysis by Mnn-Kendll Test for Vmnpurm River Bsin, Kerl Rinfll Trend by Mnn-Kendll for 3 yers Z c Stti stics Month Zc vlues Figure 6 Trend of Z c for Individul Months for 3 Yers ( ). Tble 1 Estimted Sen s Slope nd Kendll s test sttistics ( Z c) vlues from 1984 to 213. Months Men Stndrd Kendll s test Sen s Slope Devition sttistics(z c) Jnury Februry Mrch April My June July August September October November December CONCLUSIONS In the non-prmetric Mnn-Kendll test, the Zc sttistics reveled the trend of the series for 3 yers ( ) for individul 12 months from Jnury to December which re -.24, -.11,.33,.36, -.89,.412,.196, -.65,.22,.44,.93 nd.169 respectively. For Mrch, April, June, July, September, October, November nd December there is n evidence of rising rinfll trend while Zc vlue is showing negtive trend in Jnury, Februry, My nd August. Thus Zc vlues for eight months show positive trend nd for other four months it shows negtive trend representing lmost non-significnt condition. Similrly in the cse of Sen s Slope fctor, there is positive trend for Jnury, Mrch, April, June, July, September, October, November nd December months. The three months showed negtive trend. The trend nlysis for rinfll helped to understnd the monsoon pttern of the Vmnpurm river bsin nd thus nticipte flood sitution in the monsoon seson editor@ieme.com

8 Mrs. Anie John. S nd Dr. J. Brem ACKNOWLEDGEMENT The required dischrge, rinfll nd toposheet provided by the Centrl Wter Commission (CWC), Indin Meteorologicl Deprtment (IMD) nd Survey of Indi re gretly cknowledged. REFERENCES [1] Klny, E. nd Ci, M. Impct of urbniztion nd lnd-use chnge on climte. Nture 423, 23, pp [2] IPCC, Summry for policymkers. In Climte Chnge 27: The Physicl Science Bsis (eds Solomon, S. D. et l.). Cmbridge University Press, Cmbridge, UK, 27. [3] Jin, S.K. nd Kumr, V. Trend nlysis of rinfll nd temperture dt for Indi, Current Science (Bnglore), 12 (1), 212, pp [4] Kumr, V., Singh, P. nd Jin, S. K., Rinfll trends over Himchl Prdesh, Western Himly, Indi. Conference on Development of Hydro Power Projects A Prospective Chllenge, Shiml, 2 22 April 25. [5] Kothwle, D. R., Munot, A. A. nd Krishn Kumr, K. Surfce ir temperture vribility over Indi during , nd its ssocition with ENSO. Climte Res, 42, 21, pp [6] Somn, M. K., Krishn Kumr, K. nd Singh, N. Decresing trend in the rinfll of Kerl. Curr. Sci, 57, 1988, pp [7] Kundzewicz, Z. W. Chnge detection in hydrologicl records review of the methodology. Hydrol. Sci., J, 49(1), 24, pp [8] Sen, P. K. Estimtes of the regression coefficient bsed on Kendll s tu. J. Am. Stt. Assoc, 63, 1968, pp [9] Burn, D. H., Cunderlik, J. M. nd Pietroniro, A. Hydrologicl trends nd vribility in the Lird river bsin. Hydrol. Sci. J, 49, 24, pp [1] Dougls, E. M., Vogel, R. M. nd Knoll, C. N. Trends in flood nd low flows in the United Sttes: impct of sptil correltion. J. Hydrol, 24, 2, pp [11] Sls, J. D. Anlysis nd modeling of hydrologic time series. In Hndbook of Hydrology (ed. Midment, D. R.), McGrw-Hill, New York, 1993, pp [12] Singh, P., Kumr, V., Thoms, T. nd Aror, M. Chnges in rinfll nd reltive humidity in different river bsins in the northwest nd centrl Indi. Hydrol. Process, 22, 28, pp [13] Yu, Y. S., Zou, S. nd Whittemore, D. Non-prmetric trend nlysis of wter qulity dt of rivers in Knss. J. Hydrol, 15, 1993, pp [14] Yue, S., Pilon, P. nd Phinney, B. Cndin stremflow trend detection: impcts of seril nd cross-correltion. Hydrol. Sci.J, 48, 23, pp [15] Hirsch, R.M., Alexnder, R.B. nd Smith, R.A. Selection of methods for the detection nd estimtion of trends in wter qulity. Wter Resources Reserch, 27, 1991, pp [16] Mnn, H.B. Non-prmetric test ginst trend. Econometric, 13, 1945, pp [17] Kendll, M.G. Rnk Correltion Methods, 4th edition. Chrles Griffin, London, U.K, editor@ieme.com