SavedAdd your journal

Journals / Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi / 2018 / Cilt: 8 Sayı: 1

Long Years Precipitation Parameters by CLIGEN Precipitation Model in Tokat Province

Tokat İlin’deki Uzun Yıllar Yağış Parametrelerinin CLIGEN Yağış Modeli ile Değerlendirilmesi

Saniye Demir0000-0003-3908-7070
İrfan Oğuz0000-0002-1576-333X
Ömer Faruk Ciba0000-0001-8297-2855
Pages
319–328
Publication Date
2018-03-31
🏛️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)

The results showed no significant difference between observed and simulated values for rainfall parameters.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, by using CLIGEN, between 2005-2015 long years historical daily precipitation records were simulated from Tokat weather stations.
📊
Key Findings & Data:The basic statistics of daily, monthly and annual precipitations (mean, standart deviation, skewness) were compared with those derived from the observed and generated by CLIGEN weather series.
💡
Conclusion & Impact:The results showed no significant difference between observed and simulated values for rainfall parameters.
🔬Design:Araştırma Makalesi
📍Scope:2005-2015 Verileri
⚙️Variables:CLIGEN · İklimsel değişiklikler · Tokat yağış

Abstract

In this study, by using CLIGEN, between 2005-2015 long years historical daily precipitation records were simulated from Tokat weather stations. The basic statistics of daily, monthly and annual precipitations (mean, standart deviation, skewness) were compared with those derived from the observed and generated by CLIGEN weather series. The results showed no significant difference between observed and simulated values for rainfall parameters. Especially, CLIGEN estimations tend to underestimate the observed data in spring and winter months. CLIGEN exhibited higher performance in simulation of monthly and annual rainfall.

Özet

Bu çalışmada, Tokat meteoroloji istasyonundan 2005-2015 yıllarına ait günlük yağış verileri,

🔖

Cite This Article

Demir, S., Oğuz, İ., Ciba, Ö. F., *, S. D. (2018). Long Years Precipitation Parameters by CLIGEN Precipitation Model in Tokat Province. Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi, Cilt: 8 Sayı: 1, 319–328. https://doi.org/10.21597/jist.407892

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (15)

  1. Anonim. 2015. Tokat iklim verileri. Metereoloji Genel Müdürlüğü. 2015.
  2. Elliot WJ, Arnold, CD, 2001. Validation of the weather generator CLIGEN with precipitation data from Uganda. Trans. ASAE 44 (1):53-58.
  3. Fan JC, Yang CH, Li, CH, Huang, HY,2013. Assessment and validation of CLIGEN-simulated rainfall data for Northern Taiwan. Paddy Water Environ 11:161-173.
  4. Headrick MG, Wilson B N, 1997. An evaluation of stochastic weather parameters for Minnesota and their impact on WEPP. ASAE paper no. 972230. St. Joseph, Mich: ASAE.
  5. Johnson GL, CL, Hanson SP, Ballard BE, 1996. Stochastic weather simulation: Overview and analysis of two commonly used models. J. Appl. Meteorol., 35(1), 1878-1896.
  6. Jones JW, Hoogenboom G, Porter CH, Boote KH and 6 others, 2003. The DSSAT cropping system model. Eur. J. Agron., 18, 235-265.
  7. Kou XG, Jianping Y, Wang CZ, 2007. Validation of the weather generator CLIGEN with daily precipitation data from the Loess Plateau. J. Hydrol. 347(3-4), 347-357.
  8. Mann HB, 1945. Nonparametric tests against trend. Econometrica 13:245–259.
  9. Min YM, Kryjov VN, An KH, Hameed, SN Sohn SJ, Lee WJ, Oh JH, 2011. Evaluation Of the weather generator CLIGEN with daily precipitation characteristics in Korea. The Korean Meteorological Society And Springer, 47(3), Pp.255–263.
  10. Nearing MA, Foster GR, Lane LJ and Finkner SC, 1989. A process-based soil erosion model for USDA-Water Erosion Prediction Project technology. (ın press) Transactions of the ASAE.
  11. Nicks AD, Lane LJ, Gander GA, 1995. USDA-Water Erosion Prediction Project: Hillslope profile and watershed model documentation. 2.1-2.22. NSERL report no. 10. Flanagan, D.C., Nearing, M.A (ed) West Lafayette Ind: USDA-ARS National Soil Erosion Reserach Laboratory.
  12. Soil Survey Staff, 2009. R. Burt (ed.). Soil survey field and laboratory methods manual. Ver. 1.0. USDA/NRCS, Soil Survey Investigations Report No. 51. Available online at http://www.soils.usda.gov/technical/ (verified January 24, 2011).
  13. Wilks DS, 1999. Multisite downscaling of daily precipitation with a stochastic weather models. Prog. Phys. Geog. 23, 329-357.
  14. Zhang XC, Garbrecht JD, 2003. Evaluation of CLIGEN precipitation parameters and their implication on WEPP runoff and erosion prediction. Trans. ASAE, 46, 311-320.
  15. Zhang XC, Garbrecht JD, 2007. A comparision of explicit and implicit spatial downscaling of GCM output for soil erosion and crop production assaessments. Climatic Change, 84, 337-363.