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005			20260818133457.0
008			190598 th eng
035			_a.b1033046x
099		9	_aAIT Thesis no. WA-84-15
100	0		_aChalinee Prajakthum
245	1	0	_aHeuristic relation between point rainfall and meteorological factors
260			_aBangkok : _bAsian Institute of Technology, _c1983
300			_a119 p.
490	1		_aThesis ; _vno. WA-84-15
500			_aA thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Engineering and Technology
502			_aThesis (M.Eng.) - Asian Institute of Technology, 1983
520			_aThe point-rainfall calibrating and forecasting models are developed and applied for Khonkhan station by using the empirical GMDH (Group Method of Data Handling) model. It is considered as a semi-causal model in a deterministic sense , though the actual times of occurance are defined as a day or duration of day , it emphasizes on magnitude at that actual time than to predict in a probabilistic sense in tension probability of occurance or in a stochastic sense with emphasis on the probability of the sequences of events. The causal input variables are acquired by other meteorological parameters at the same station, The accuracy of the model performance on calibration and forecasting is tested by applying them to perform rainfall calibration for daily , 5 , 6 , and 7 days and rainfall forecasting for those duration 5, 6 and 7 days during the years 1970-1980. The accuracy of the model performance depends mainly upon, i) rainfall condition: such as distribution, fluctuation and variation etc. ii) the relationship between rainfall and each meteorological input variables, and iii) the numerical technique applied to solve the problems. The accuracy of the models are evaluated by means of root mean square error, percentage of error and coefficient of correlation. The analysis of the model signified the acceptable performance of the model in calibration of those duration 5 , 6, and 7 days. In case of daily calibration the insignificant results are due to the rather wider fluctuation. That is the coefficients of variation are more than 1.0 . The basic heuristics considered in this study and also limitation of the empirical models impose difficulties in forecasting the nonstationary phenomena of rainfall.
650		0	_aRain and rainfall
700	0		_aPrida Thimakorn, _eChairperson
700	1		_aHoshi, Kiyoshi, _eExamination Committee
700	1		_aHuynh, Ngoc Phien, _eExamination Committee
710	2		_aSelf--support, _eScholarship Donor
810	2		_aAsian Institute of Technology. _tThesis ; _vno. WA-84-15
856			_3Full-Text _uhttp://203.159.5.9/ait-thesis/detail.php?q=B21031
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