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dc.contributor.authorMasimin
dc.contributor.authorHarun, Sobri
dc.date.accessioned2012-09-06T07:59:07Z
dc.date.available2012-09-06T07:59:07Z
dc.date.issued2011-05
dc.identifier.citationAdamowski, K., Alila, J. & Pilon, P.J. (1996). ”Regional rainfall distribution for Canada.” Atmospheric Research 42, 75-88. Adamowski, K. and Bougadis, J. (2003). “Detection of trends in annual extreme rainfall.” Hydrol. Processs. 17, 3547-3560. Berndtsson, R. & Niemczynowics, J. (1986). “Spatial and temporal characteristics of high-intensive rainfall in northern Tunisia.” Journal of Hydrology, 87, 285-298. Burn, D.H. (1990). “Evaluation of regional flood frequency analysis with a region of influence approach.” Water Resources Research, 26(10), 2257-2265. Chow, V.T. (1964). Handbook of applied hydrology, McGraw- Hill Book Co., New York. Cunnane, C. (1988). “Methods and merits of regional flood frequency analysis.” J. Hydrology, 100, 269-290. Dinpashoh, Y., Fakheri-Fard, A., Moghaddam, M., Jahanbakhsh, S. & Mirnia, M. (2004). “Selection of variables for the purpose of regionalization climate using multivariate methods.” J. Hydrology, 297, 109-123. Daud, Z.M., Mohd Kassim, A.M., Mohd Desa, M.N., & Nguyen, V.T.V. (2002). “Statistical analysis of at-site extreme rainfall process in Peninsular Malaysia.” Proc. of 4th Int. Conference of FRIEND, Cape Town, March 2002, IAHS Publication (274), 1-8. Durrans, S.R. & Kirby, J.T. (2004). “Regionalization of extreme precipitation estimates for the Alabama rainfall atlas.” Journal of Hydrology, 295,101-107. Fill, H.D. & Stedinger, J.R. (1995). “Homogeneity tests based upon Gumbel distribution and a critical appraisal of Dalrymple’s test.” J. Hydrology, 166, 81-105. Greenwood, J.A., Landwehr, J.M., Matalas, N.C., & Wallis, J.R. (1979). “Probability weighted moments: Definition and relation to parameters of several distributions expressable in inverse form.” Water Resources Research, 15(5), 1049-1054. Hosking, J.R.M., Wallis, J.R. & Wood, E.F. (1985). “Estimation of the generalized extreme-value distribution by the method of probability-weighted moments.” Technometrics, 27(3), 251-261.Hosking, J.R.M. & Wallis, J.R. (1987). “An ‘index flood’ procedure for regional rainfall frequency analysis.” Eos Trans. Am. Geophys. Un., 68, 312. Hosking, J.R.M. & Wallis, J.R. (1987). “Parameter and quantile estimation for the generalized Pareto distribution.” Technometrics, August 1987, 29 (3), 339-349. Hosking, J.R.M, (1990). “L-moments: Analysis and estimation of distributions using liner combinations of order statistics.” J. R. Stat. Society, 52 (1), 105-124. Hosking, J.R.M. & Wallis, J.R. (1993). “Some statistics useful in regional frequency analysis.” Water Resources Research, 29(2), 271-281. Hosking, J.R.M. (1996). Fortran routines for use with the method of L-moments. RESEARCH REPORT, IBM Research Division, Yorktown Heights, NY 10598. Kottegoga, N.T. & Rosso, R. (1997) Statistics, probability, and reliability for civil and environmental engineers, The Mc Graw-Hill Companies, Inc., New York, USA. Kumar, R. & Chatterjee, C. (2005). “Regional flood frequency analysis using L-moments for North Brahmaputra region of India.” J. Hydrol. Engg., 10(1), 1- 7. Lettenmaier, D.P., Matalas, N.C. &Wallis, J.R. (1987). “Estimation of parameters and quantiles of Wakeby distribution, part 1 and 2.” Water Resources Research, 15(6), 1361-1379. Lu, L.H. & Stedinger, J.R. (1992). “Sampling variance of normalized GEV/PWM quantile estimators and a regional homogeneity test.” J. Hydrology, 138, 223-245. Lu, L.H. & Stedinger, J.R (1992). “Variance of two and threeparameter GEV/PWM quantile estimators: formulae, confidenceintervals, and a comparison.” J. Hydrology, 138, 247-267. Masimin & Harun, S. (2006). “Analysis for annual maximum pre-cipitation series for State of Selangor using probability weigh-ted moments.” Proc. of Hydrological Sciences for Managing Water Resources in the Asian Developing World Con-ference, Guangzhou, P.R. China. Mohd. Kasim, A.H., & Way, L.K. (1995). Frequency analysis of annual maximum rainfall for the Klang river basin using GEV distribution. Faculty of Civil Engineering, Universiti Teknolo-gi Malaysia, Johor Bahru, Malaysia. Rao, A.R & Hamed, K.H. (1997). ”Regional frequency analysis of Wabash river flood data by L-Moments.” J. Hydrol. Engg., 2(4), 160-179. Rao, A.R & Hamed, K.H. (2000). Flood frequency analysis. CRC Press, New York, USA. Rao, A.R. & Srinivas, V.V. (2006). “Regionalization of watersheds by fuzzy cluster analysis.” J. Hydrology, 318, 57-79. Smithers, J.C. & Schulze, R.E. (2001). “A methodology for the estimation of short duration design storms in South Africa using regional approach based on L-moment.” J Hydrology, 241, 42-52. Sosrodarsono, S. & Takeda T. (1980). Hidrologi untuk Pengairan, Pradnya Paramita, Jakarta. Sveinsson, O.G.B., Salas, J.D. & Boes, D.C. (2002). “Regional frequency analysis of extreme precipitation in Northeastern Colorado and Fort Collins flood of 1997.” J. Hydrol Engg., 7(1), 49-63. Viessman, W. & Lewis, G.L. (2003). Introduction to hydrology, (5th ed) Prentice Hall, New York.en_US
dc.identifier.issn1411-8904
dc.identifier.urihttp://hdl.handle.net/11617/1959
dc.description.abstractData hujan tiap 5 menit yang diambil dari 5 stasiun yang tersebar di wilayah barat daya Johor dianalisis untuk mem-pelajari intensitas-dirasi-frekuensi (IDF) yang berhubungan dengan pengembangan perancangan badai. Penelitian ini mencakup analisis hujan regional, penentuan distribusi probabilitas, estimasi parameter dan quantil distribusi, pe-ngembangan IDF, dan studi perbandingan untuk estimasi IDF berdasarkan hujan harian. Dalam penenlitian ini pola durasi diatur dalam 15-, 30-menit, 1-, 2-, 4-, 8-, 16-jam, dan 1-hari. Pengujian X10 digunakan untuk analsisi regio-nal untuk menentukan keseragaman regional dan probabilitas berat momen (PWM) digunakan untuk nanlisis fre-kuensi. Untuk melihat munculnya tren, metoda Kendall digunakan. Hasil analisis menunjukkan bahwa wilayah yang diteliti adalah wilayahyang seragam. Berdasarkan analisis frekuensi, data cenderung mengikuti nilai akstrim yang u-mum (GEV) dan distribusi logistik umum (GLOG). Pada analisis regresi, kurva IDF pada periode 2-, 5-, 10-, 20-, 50-,100-, 200-, dan 500-tahun cenderung mengukuti persamaan power. Kurva famili IDF berdasarkan data harian memberikan over estimasi sekitar 10% dibandingkan dengan data yang dihitung berdasarkan data hujan tiap 5 menit.en_US
dc.subjectKeseragaman wilayahen_US
dc.subjectperancangan badaien_US
dc.subjectanalisis frekuensien_US
dc.titleEVALUASI DURASI HUJAN PENDEK DALAM PENGEMBANGAN PERANCANGAN BADAIen_US
dc.title.alternativeSHORT RAINFALL DURATION EVALUATION IN DESIGN STORMS DEVELOPMENTen_US
dc.typeArticleen_US


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