000			03734cas a2200409 a 4500
005			20260817171312.0
008			111010s1992 th uu|m rtt 0| a1eng d
035			_a.b10111049
099		9	_aAIT Thesis no.AE-92-50
100	1		_aAfzal, Chaudri Sohail
245	1	0	_aBest fitting distribution function for floods in the Upper Indus Basin (Pakistan)
260			_aBangkok : _bAsian Institute of Technology, _c1992
300			_a71 leaves : _bill.
490	1		_aThesis ; _vno. AE-92-50
502			_aThesis (M.Eng.) - Asian Institute of Technology
500			_aA thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering.
520			_aThe results offlood frequency analysis can be used for the design of dams, culverts, flood control structures and to determine the economic value of projects etc,. A variety ofdistributions have been used in hydrology in fitting the hydrologic random variables of annual stream flows. So, the selection of a distribution plays an important role in the design of structure and its economic condition. In Pakistan the use of the Gumbel (EYl) distribution is a common practice. However there is no investigation on the proper use of statistical distributions for annual maximum flood frequency analysis in Pakistan. Therefore the upper Indus basin which is the largest one in Pakistan was selected for this study. A flood frequency analysis of the upper Indus basin was carried out for 20 unregulated stream flow stations located on various rivers with each data set having at least 20 observations. The Wald-Wolfowitz test of independence and Grubbs & Beck test for detection of outliers were applied. Extreme value type 1 (EYl), General extreme value (GEY), Lognormal 2 (LN2), and Pearson Type 3 (P3) distributions were used as the parent models. The Probability Weighted Moments (PWM), and Maximum Likelihood (ML) methods were taken for parameter estimation. Commonly considered criteria to evaluate the performance of distributions such as statistical measures, goodness of fit test, and probability plots using appropriate probability papers were employed. The results of the study conclude that for flood frequency analyses of the upper Indus basin, GEY (EY2 and EY3) distribution should be applied because it gives a good fit on GEY probability paper with less RMSE, BIAS, and K-S statistics. Moreover, for this distribution, the PWM method should be used because it is less biased and more efficient. The EYl, LN2, P3 distributions can not satisfactorily represent the flood data in a large number of cases. As such, they are not suitable for flood frequency analyses of the upper Indus basin.
650		0	_aHydrology _xStatistical methods
650		0	_aFloods _zPakistan _zIndus Basin
700	1		_aLoof, Rainer, _eChairperson
700	0		_aNophadol In-na, _eExamination committee
700	1		_aPaudyal, Guna N., _eExamination committee
700	1		_aNielsen, J. M., _eExamination committee
710	2		_aDAAD, _eScholarship donor
810	2		_aAsian Institute of Technology. _tThesis ; _vno. AE-92-50
856			_3Full-Text _uhttp://203.159.5.9/ait-thesis/detail.php?q=B16509
907			_a.b10111049 _bmnait _cs
902			_a240411
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