5268

4938

كارشناسي ارشد

آبياري و زهكشي

اصفهان: دانشگاه صنعتي اصفهان، دانشكده كشاورزي

1388

نه،117ص.:مصور،جدول،نمودار

ص.ع.به فارسي و انگليسي

فرهاد موسوي،سعيد اسلاميان

جواد عسگري،عليرضا مامن پوش

22/3/89

جهانگير عابدي كوپايي،مجيد افيوني

1396/10/02

كتابنامه

مهندسي كشاورزي

ID4938

به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي

Application of Localization in Estimating Groundwater Level using Deterministic Ensemble Kalman Filter Mohammad Mehdi Bateni mm bateni@ag iut ac ir Date of Submission 2010 03 13 Water Engineering Department Isfahan University of Technology Isfahan 8415683111 Iran Degree M Sc Language FarsiSupervisors Sayed Farhad Mousavi mousavi@cc iut ac ir Saeid Eslamian saeid@cc iut ac irAbstract The most important quantity in groundwater resources management is groundwater level at various locations of the aquifer This quantity has been obtained by means of quantitative groundwater modeling The main problem to develop such a model is determining exactly its parameters particularly hydrogeologic coefficients which in most cases inexact ones result in unsatisfactory model results In this thesis after a survey on system theory key definitions of this theory and their examples in literature of groundwater modeling was expressed Then subsequent to a review on data assimilation methods various versions of Kalman filter as a sequential data assimilation method was explained Kalman filters for large scale systems like large plain aquifers are discussed Ensemble Kalman filters as the most common version of Kalman filter in natural sciences were explained After that Kalman filter was applied to the groundwater system Then Deterministic Ensemble Kalman Filter DEnKF which is a square root of mean preserving EnKF is explained Then methods of improving filter performance with focus on localization were discussed and finally a type of localization within the framework of DEnKF was applied Najafabad aquifer in Isfahan province with area of approximately 150 km2 in timeframe of Mehr 1379 Oct 2000 to Shahrivar 1386 Sept 2007 with monthly time steps was modeled Water table level of unit hydrograph of this aquifer within 1379 80 water year has a downtrend and after that changes to uptrend are studied and their stochastic and square root versions are explained The least amount 1697 m above mean sea level was in Oct 2001 By division of the aquifer into 5 zones the first 54 months values of hydrogeologic coefficients for each zone were calibrated with the help of monthly data of 32 observation wells Then the model was verified over the last 30 months It showed a good performance in comparison with monthly data of other 17 observation wells of the aquifer The result of this calibrated model is assumed to be true and at some points after adding a Gaussian noise considered as observation data DEnKF was combined with 45 observations of true run with inexact hydrogeologic parameters 2 5 and 10 times of calibrated values of hydraulic conductivity and specific yield This filter was run with and without localization with 3 range parameters of 2500 3500 and 5000 m Results showed that application of this new filter with inexact model parameters has greatly improved the results of inexact model Major error reduction has occurred at first few time steps and at most cases because of creation of false correlations in covariance matrix of error and then it followed an upward trend By localization this upcoming trend changed to a downward trend or for the case of inexact specific yield which model is more sensitive to it this trend is attenuated The amount of improvement due to localization based on range parameters is different and shows no obvious relationship to exactness of the model Keywords Groundwater Data Assimilation Localization Ensemble Kalman Filter

فرهاد موسوي،سعيد اسلاميان

جواد عسگري،عليرضا مامن پوش

جهانگير عابدي كوپايي،مجيد افيوني