12107

11093

كارشناسي ارشد

منابع آب

اصفهان: دانشگاه صنعتي اصفهان، دانشكده كشاورزي

1395

چهارده، 106ص.: مصور، جدول، نمودار

ص. ع. به فارسي و انگليسي

سعيد اسلاميان

رضا مدرس

منوچهر حيدرپور، سعيد سلطاني

1395/11/17

كتابنامه

كشاورزي

مهندسي كشاورزي

ID11093

108Application of Wavelet Transformation in Forecasting Low Flow Time Series for Some Hydrometric Stations in Iran Sheyda Mohammadi Fard mohammadifard sh@gmail com January 16 2017 Department of Water Engineering College of Agriculture Isfahan University of Technology Isfahan 84156 83111 IranDegree M Sc Language FarsiSupervisor Saeid Eslamian saeid@cc iut ac irAbstract One of the most important and fundamental issues that Iran has faced in recent years is water crisis This problem mostly hits the country in years with drought The minimum water flow in the river in factis the low flow Environmentally the shrinkage of low flow to its minimum value Increases the relatedcontamination and lowers the dissolved oxygen in water which causes the death of aquatics in the rivers As directorial view this minimum of low flow has special importance for study the fields of urban industrial and agricultural water supply Therefore prediction of low flow in the water field andenvironmental issues must be heeded In this study prediction of 7 day and 30 day low flow has beenconsidered which data of daily flows came from staions Ghale Shahrokh and Eskandari in Isfahanprovince and Chamriz and Chenarsookhte in Fars province was used For this purpose two methods ofusual time series modeling and modeling of time series using wavelet wavelet series were used Theapproached presented by Box and Jenkins was considered for the modeling of time series which consistsof three steps namely model parameter estimation and goodness of fit test or time independency For theprediction of low flow modeling of time series was done for main logarithmic and seasonal series Theresults indicated the advantage of logarithmic series in all of the stations One of the procedures whichrecently has been considered in hydrologic field is utilizing wavelet as an innovative and effective methodin time series analysis In the wavelet time series modeling with Haar wavelet theory the consideredseries was decomposed According to the considered series decomposition was performance at levels 5and 6 in mentioned stations In data there are results of analyzing wavelet including A approximationwhich has main essence of data and details containing white noise Then the time series modeling stepswere performed for the approximate Finally the series analysis has done simply with use of by obtainingcorrelation coefficient mean rooted squared error and mean absolute deviation in modeling andpredicting for two methods and also by considering that wavelet decomposition simplifies the serieswhich simplifies the analysis of the series the wavelet time series method was proved to be the mostappropriate method to predict the amount of low flow Keywords Box and Jenkins forecast Haar low flow time series Wavelet

سعيد اسلاميان

رضا مدرس

منوچهر حيدرپور، سعيد سلطاني