Journals / Anadolu Üniversitesi Bilim ve Teknoloji Dergisi :A-Uygulamalı Bilimler ve Mühendislik / 2002 / Cilt: 3 - Sayı: 2

Su kalitesi eğilimlerinin istatistiksel analizi: Porsuk Çayı için bir uyarlama

Statistical analysis of water quality trends: An application to the Porsuk Stream

Pages
281–292
Publication Date
2022-10-11
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

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

It is found that the stream water quality has improved for suspended solids and the nitrogen species but become worse in terms of other water quality variables, indicating that the pollution of this important water course is continuing.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, nonparametric statistical trend analysis is conducted to assess trends in water quality time series.
📊
Key Findings & Data:Together with flow, seven water quality parameters are investigated and their trends from 1983 to 2000 are determined.
💡
Conclusion & Impact:It is found that the stream water quality has improved for suspended solids and the nitrogen species but become worse in terms of other water quality variables, indicating that the pollution of this important water course is continuing.
🔬Design:Research Article
📍Scope:2000 Verileri
⚙️Variables:Domain Parameters

Abstract

In this study, nonparametric statistical trend analysis is conducted to assess trends in water quality time series. For the analysis, the Seasonal Kendall Trend Test is used, together with other auxiliary statistical tests. The methodology is applied to water quality time series from the Beşdeğirmen monitoring station situated on the Porsuk Stream, the largest tributary of the Sakarya River. Together with flow, seven water quality parameters are investigated and their trends from 1983 to 2000 are determined. It is found that the stream water quality has improved for suspended solids and the nitrogen species but become worse in terms of other water quality variables, indicating that the pollution of this important water course is continuing.

Özet

Bu çalışmada, su kalitesi zaman serilerinde eğilimlerin saptanması için parametrik olmayan eğilim analizi uygulanmıştır. Analizler için, diğer istatistiksel testlerin yanısıra, Mevsimsel Kendall Eğilim Testi kullanılmıştır. Yöntem Sakarya nehrinin en büyük kolu olan Porsuk Sayı üzerinde bulunan Beşdeğirmen gözlem istasyonundan elde edilen su kalitesi zaman serilerine uygulanmıştır. Akım ile birlikte yedi su kalitesi parametresi incelenmiş ve 1983-2000 yılları arasındaki eğilimler saptanmıştır. Akarsuyun kalitesinin askıda katı maddeler ve azot türleri için daha iyiye gittiği, diğer parametreler için bozulduğu bulunmuştur. Bu da, bu önemli akarsuyun kirlenmesinin devam ettiğini göstermektedir.

🔖

Cite This Article

ALBEK, E. (2022). Su kalitesi eğilimlerinin istatistiksel analizi: Porsuk Çayı için bir uyarlama. Anadolu Üniversitesi Bilim ve Teknoloji Dergisi :A-Uygulamalı Bilimler ve Mühendislik, Cilt: 3 - Sayı: 2, 281–292. https://ajindex.com/articles/438474

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (14)

  1. Albek, E. (1999a). Seasonal and Long-term Trends in Sediment Transport of Turkish Streams, The Fourth International Conference on the Mediterane-an Coastal Environment, The Fourth International Conference on Environmental Management of Enclosed Coastal Seas (MEDCOAST-EMECS), Antalya, Türkiye,pp.49-60.
  2. Albek, E. (1999b). Identification of the Different Sources of Chlorides in Streams by Regression Analysis Using Chloride-Discharge Relationships. Wafer Environment Research 71(7), 1310-1319.
  3. Albek, E. (2000). Türkiye Akarsularmda Klorür Derişimlerinin Mevsimsel Bazda Yıllar Boyu Değişimleri, 1. Ulusal Çevre Kirliliği Kontrolü Sempozyumu, Orta Doğu Teknik Üniversitesi,
  4. Ankara, Türkiye, pp. 133-140.
  5. Behrendt, H., (1993). Separation of Point and Diffuse Loads of Pollutants Using Monitoring Data of Rivers. Wat. Sci. Tech. 28(3-5), 165-175.
  6. Cleveland, W.S. (1979). Robust Locally Weighted Regression and Smoothing Scatterplots. J. Am. Stat. Assoc. 74, 829-836.
  7. DSİ (1995). Porsuk Havzasında 1994
  8. Yılı Su Kalite Değerlendirmeleri, Teknik Araştırma ve Kaliıe Kontrol Şube Müdürlüğü. Drever, J.I. (1982).
  9. The Geochemistry of Natural Waters, Prentice- Hall, Inc., London. Helsel, D.R. and Hirsch, R.M. (1992). Statistical Methods in Water Resources, Elsevier, The Netherlands. Hirsch, R.M., Slack, J.R. and Smith, R.A. (1982). Techniques of Trend Analysis for Monthly Water Quality Data. Water Resources Research 18(1), 107-121.
  10. Hirsch, R.M. and Slack, J.R. (1984). A Nonparametric Trend Test for Seasonal Data with Serial Dependence. Water Resources Research 20(6), 727-732.
  11. Kahl, J.S., Haines, T.A., Norton, S.A., and Davis, R.B. (1993). Recent Trends in the Acid-Base Status of Surface Waters in Maine, USA. Water, Air and Soil Pollution 67, 281-300.
  12. McCuen, R.H., (1992). Microcomputer Applications. Statistical Hydrology. Prentice Hall, New Jersey. Peters, N.E., Bricker, O.P. and Kennedy, M.M. (Eds) (1997). Water Quality Trends and Geochemical Mass Balance, Wiley, England. Smith, R.A., Alexander, R.B. and Wolman, M.G. (1987). Analysis and Interpretation of water Quality Trends in Major US Rivers, 1974-81., United States Geologic Survey Water Supply Paper 2307. Gleick, Peter H. (2000). The World's Water, 2000-2001: The Biennial Report on Freshwater Resources, Island Press,
  13. Washington, D.C. United Nations Environment Programme (1995).
  14. Water Quality of World River Basins, Collaborating Centre for Freshwater Quality Monitoring and Assessment,Nairobi