Journals / Ekoloji / 2008 / Cilt: 17 - Sayı: 67

Porsuk Barajı'ndaki su miktarının istatistiksel olarak modellenmesi

Statistical modelling of water quantity in the Porsuk Dam

Journal
Ekoloji
Pages
52–59
Publication Date
2022-10-17
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In November 2005, monthly average water quantity reaching was 244.270 m3, and it is forecasted to be 206.560 m3.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, daily water quantity data in the Porsuk Dam which is taken from State Hydraulic Works (SHW) 3rd Regional Directorate, reaching during January 1992-November 2005 was examined.
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Key Findings & Data:ARIMA (1,1,1) model was found appropriate to forecast the amount of water in the Porsuk Dam.A forecast related to water quantity which comes to the dam for 12-months is realized.
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Conclusion & Impact:In November 2005, monthly average water quantity reaching was 244.270 m3, and it is forecasted to be 206.560 m3.
🔬Design:Modeling & Simulation
📍Scope:2005 Verileri
⚙️Variables:Domain Parameters

Abstract

In this study, daily water quantity data in the Porsuk Dam which is taken from State Hydraulic Works (SHW) 3rd Regional Directorate, reaching during January 1992-November 2005 was examined. Then, monthly average values were determined by using these daily data and analyzed through Box-Jenkins method. ARIMA (1,1,1) model was found appropriate to forecast the amount of water in the Porsuk Dam.A forecast related to water quantity which comes to the dam for 12-months is realized. In December 2004, monthly average water quantity reaching to the Dam was 256.000 m3 and it is forecasted as 360.590 m3. In November 2005, monthly average water quantity reaching was 244.270 m3, and it is forecasted to be 206.560 m3.

Özet

Bu çalışmada 1992 Ocak- 2005 Kasım dönemi için Porsuk Barajı'na günlük gelen su miktarı verileri Devlet Su İşleri 3. Bölge Müdürlüğü'nden elde edilmiştir. Daha sonra günlük verilerin aylık ortalamaları alınmış ve veriler Box-Jenkins yöntemiyle analiz edilmiştir. Porsuk Barajı'na gelen su miktarına ilişkin öngörüde bulunmak için ARIMA (1,1,1) modeli uygun bulunmuştur. Baraja gelen aylık ortalama su miktarına ilişkin 12 aylık öngörü yapılmıştır. 2004 yılının Aralık ayında baraja gelen aylık ortalama su miktarı 256,000 m3'e ulaşmış ve bu dönem için 360,590 m3 olarak öngörülmüştür. 2005 Kasım ayında aylık ortalama su miktarı 244,270 m3 olarak gerçekleşmiş ve 206,560 m3 olarak öngörülmüştür.

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Cite This Article

ÖZAYDIN, Ö., CEMREK, F., ALTIN, A. (2022). Porsuk Barajı'ndaki su miktarının istatistiksel olarak modellenmesi. Ekoloji, Cilt: 17 - Sayı: 67, 52–59. https://ajindex.com/articles/499211

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References (20)

  1. Akgul I (2003) Zaman Serilerinin Analizi ve ARIMA Modelleri. Der Press,
  2. Istanbul. Bowerman BL, O'Connell RT (1993) Forecasting and Time Series: An Applied Approach. Third ed., Duxbury Press,
  3. Belmont. Georgakarakos S, Koutsoubas D, Valavanis V (2006) Time series analysis and forecasting techniques applied on loliginid and ommastrephid landings in Greek waters. Fisheries Research 78, 1, 55-71.
  4. Gujarati D (2004)
  5. Basic Econometrics. Fourth ed., The McGraw-Hill Companies, New York. Irvine KN, Eberhardt AJ (1992) Multiplaticative Seasonal ARIMA Models for Lake and Lake Ontario Water Levels. Journal of Water Resources Association 28, 2, 385-396.
  6. Kadilar C (2005) SPSS Uygulamalý Zaman Serileri Analizine Giriþ. Bizim Buro Kitabevi,
  7. Ankara.
  8. Koutroumanidis T, Iliadis L, Georgios KS (2006) Time-Series Modelling of Fishery Landings Using ARIMA Models and Fuzzy Expected Intervals Software. Environmental Modelling & Software 21, 1711-1721.
  9. Kurunc A, Yurekli K, Cevik O (2005) Performance of two stochastic approaches for forecasting water quality and stream-flow data from Yesilirmak River, Turkey. Environmental Modelling and Software, 20, 1195-1200.
  10. Kutlar A (2005) Uygulamalı Ekonometri. 2. Baskı,
  11. Nobel Kitabevi,
  12. Ankara.
  13. Niu X-F, Edmiston HL, Bailey GO (1998) Time Series Models for Salinity and Other Environmental Factors in the Apalachicola Estuarine System. Estuarine, Coastal and Shelf Science 46, 549-563.
  14. Ozmen A (1989) Mevsimsel Dalgalanmalar İçermeyen Zaman Serilerinde Kısa Dönem Öngörü Amaçlı Box-Jenkins (ARIMA) Modellerinin Kullanımı. Journal of Faculty of Art and Science, Anadolu University in Eskişehir in Turkey 2, 1, 105-120.
  15. Papamichail DM, Georgiou PE (2001) Seaonal ARIMA Inflow Models for Reservoir Sizing. Journal of Water Resources Association 37, 4, 877-885.
  16. Priestley MB (1991) Non-Linear and Non-Stationary Time series Analysis. Academic Press,
  17. London. Sevuktekin M, Nargelecekenler M (2005) Zaman Serileri Analizi. Nobel Yayınevi,
  18. Ankara.
  19. Steelea, BM, Reddya SK, Nemani, RR (2005) A regression strategy for analyzing environmental data generated by spatio-temporal processes. Ecological Modelling 181, 93-108.
  20. Sun H, Koch M (2001) Case Study: Analysis and Forecasting of Salinity in Apalachicola Bay, Florida, Using Box-Jenkins ARIMA Models. Journal of Hydraulic Engineering 127, 9, 718-727.