Time series analysis case of gash river at Kassala Station
مقدم أطروحة جامعية
مشرف أطروحة جامعية
Bashshar, Kamal al-Din al-Sadiq
الجامعة
جامعة أم درمان الإسلامية
الكلية
كرسي اليونسكو للمياه
دولة الجامعة
السودان
الدرجة العلمية
ماجستير
تاريخ الدرجة العلمية
2012
الملخص الإنجليزي
Time series analysis is an importance to detect patterns embedded in a time series and enables the generation and forecast of future values.
The hydrological time series analysis is also important in operation and design of water structures. Time series modeling is mainly useful in providing reservoir sizing, planning studies of future reservoir operation, planning capacity expansions of water supply systems, determining the risk of failure (or reliability) of water supply for irrigation systems.
In this study annual flow data of the gash river from 1907 to 2003 is used to calibrate and fit time series models of Autoregressive of order 1, 2, 3 and Autoregressive-Moving Average (ARMA(1,1)).
Model parameters were estimated using method of moments and stationarity and goodness of fit were applied to each model.
The model performance test was applied to select the best model. It was found that AR (3) model showed the best performance based on AIC (3,0) test.
Thus this model was used to generate synthetic data.
The generated data conserved well the first and second moments of the historical data. Kassala state lies in eastern Sudan, between latitudes 14° 13'–17° 10' north and longitudes 34° 10'-37° east.
It shares borders with Gedarif state in south west.
Nile state from the west and Red Sea state from the north. Along the east borders extents the hill series from the south east corner to the Red Sea hills.
The available data from 1907 to 2003, the main goal in this study is to analyze time series to obtain optimizing models to forecast the future values and to generate synthetic flow.
Analysis of the historical data for stationarity was done.
Results showed that the data is stationary.
Annual trend analysis was also performed on the historical data with results showing various outcomes. ARMA model was fitted to historical data.
It was found that ARMA (1,1) best fits the data.
The AR (3) was fitted and used to regenerate historical record.
Results showed complete agreement between the observed and generated flows.
التخصصات الرئيسية
الموضوعات
عدد الصفحات
86
قائمة المحتويات
Table of contents.
Abstract.
Chapter One : Introduction.
Chapter Two : Literature review.
Chapter Three : Methodology.
Chapter Four : Application, result and discussion.
Chapter Five : Summary, conclusion and recommendations.
References.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Janw, Azizah Musa Hamid. (2012). Time series analysis case of gash river at Kassala Station. (Master's theses Theses and Dissertations Master). Omdurman Islamic University, Sudan
https://search.emarefa.net/detail/BIM-364036
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Janw, Azizah Musa Hamid. Time series analysis case of gash river at Kassala Station. (Master's theses Theses and Dissertations Master). Omdurman Islamic University. (2012).
https://search.emarefa.net/detail/BIM-364036
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Janw, Azizah Musa Hamid. (2012). Time series analysis case of gash river at Kassala Station. (Master's theses Theses and Dissertations Master). Omdurman Islamic University, Sudan
https://search.emarefa.net/detail/BIM-364036
لغة النص
الإنجليزية
نوع البيانات
رسائل جامعية
رقم السجل
BIM-364036
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر