International Journal of Environment and Geoinformatics

GÖNDERBİLGİ
EnglishTürkçe

Araştırma Makalesi


DOI :10.30897/ijegeo.1434719   IUP :10.30897/ijegeo.1434719    Tam Metin (PDF)

Nakagami Distribution for Modeling Monthly Precipitations in Van, Türkiye

Kübra Bağcı Genel

Precipitation patterns are intricately influenced by geographic factors and local environmental conditions. Statistical distributions are one of the methods that help investigate precipitation characteristics at different sites. Van is a province that ranks among the provinces with the lowest precipitation in the Eastern Anatolia region of Türkiye, receiving an annual rainfall of around 400 mm. In this study, 63 years of monthly average precipitation data from Van, are modeled employing various well-known statistical distributions including the Nakagami distribution. The Nakagami distribution is one of the flexible distributions used in describing data from various fields. In estimating the parameters of the considered distributions maximum likelihood estimation method is utilized. Comparisons are made using various goodness of fit criteria including root mean squared error, coefficient of determination, and Kolmogorov-Smirnov test. According to the results, the Nakagami distribution is found to be the most suitable statistical distribution for modeling precipitations in Van province. Additionally, precipitation values for 10, 25, 50, and 100-year return periods are obtained. 

Anahtar Kelimeler: Drought, Precipitation, Nakagami distribution, Van

PDF Görünüm

Referanslar

  • Alam, M. A., Emura, K., Farnham, C., Yuan, J. (2018). Best-Fit Probability Distributions and Return Periods for Maximum Monthly Rainfall in Bangladesh. Climate, 6(1). doi.org/10.3390/cli6010009 google scholar
  • Angelidis, P., Maris, F., Kotsovinos, N., Hrissanthou, V. (2012). Computation of Drought Index SPI with Alternative Distribution Functions. Water Resources Management, 26(9), 2453–2473. doi.org/ 10.1007/s11269-012-0026-0 google scholar
  • Choi, S. C., Wette, R. (1969). Maximum Likelihood Estimation of the Parameters of the Gamma Distribution and Their Bias. Technometrics, 11(4), 683–690. doi.org/10.1080/00401706.1969.10490731 google scholar
  • Cohen, A. C. (1965). Maximum Likelihood Estimation in the Weibull Distribution Based On Complete and On Censored Samples. Technometrics, 7(4), 579–588. doi.org/10.1080/00401706.1965.10490300 google scholar
  • Evans, M., Hastings, N., Peacock, B. (2001). Statistical distributions. IOP Publishing. google scholar
  • Galoie, M., Zenz, G., Eslamian, S. (2013). Application of L-moments for IDF determination in an Austrian basin. International Journal of Hydrology Science and Technology, 3(1), 30–48. doi.org/10.1504/ IJHST.2013.055231 google scholar
  • Ghiaei, F., Kankal, M., Anilan, T., Yuksek, O. (2018). Regional intensity–duration–frequency analysis in the Eastern Black Sea Basin, Türkiye, by using L-moments and regression analysis. Theoretical and Applied Climatology, 131(1), 245–257. doi.org/ 10.1007/s00704-016-1953-0 google scholar
  • Guenang, G. M., Komkoua, M. A. J., Pokam, M. W., Tanessong, R. S., Tchakoutio, S. A., Vondou, A., Tamoffo, A. T., Djiotang, L., Yepdo, Z., Mkankam, K. F. (2019). Sensitivity of SPI to Distribution Functions and Correlation Between its Values at Different Time Scales in Central Africa. Earth Systems and Environment, 3(2), 203–214. doi.org/10.1007/s41748-019-00102-3 google scholar
  • Hinis, M. A., Geyikli, M. S. (2023). Accuracy Evaluation of Standardized Precipitation Index (SPI) Estimation under Conventional Assumption in Yeşilırmak, Kızılırmak, and Konya Closed Basins, Turkey. Advances in Meteorology, 2023(1), 5142965. doi.org/10.1155/2023/5142965 google scholar
  • Kassem, Y., Gökçekuş, H., Gökçekuş, R. (2021). Identification of the most suitable probability distribution models for monthly and annual rainfall series in Güzelyurt Region, Northern Cyprus. Desalination and Water Treatment, 215, 427–451. doi.org/10.5004/dwt.2021.26904 google scholar
  • Moccia, B., Mineo, C., Ridolfi, E., Russo, F., Napolitano, F. (2021). Probability distributions of daily rainfall extremes in Lazio and Sicily, Italy, and design rainfall inferences. Journal of Hydrology: Regional Studies, 33, 100771. doi.org/10.1016/j.ejrh.2020.100771 google scholar
  • Moccia, B., Mineo, C., Ridolfi, E., Russo, F., Napolitano, F. (2022). SPI-Based Drought Classification in Italy: Influence of Different Probability Distribution Functions. Water, 14(22). doi.org/10.3390/ w14223668 google scholar
  • Ozonur, D., Pobocikova, I., & de Souza, A. (2021). Statistical analysis of monthly rainfall in Central West Brazil using probability distributions. Modeling Earth Systems and Environment, 7(3), 1979–1989. doi.org/10.1007/s40808-020-00954-z google scholar
  • Schwartz, J., Godwin, R. T., Giles, D. E. (2013). Improved maximum-likelihood estimation of the shape parameter in the Nakagami distribution. Journal of Statistical Computation and Simulation, 83(3), 434–445. doi.org/10.1080/00949655.2011.615316 google scholar
  • Seckin, N., Haktanir, T., Yurtal, R. (2011). Flood frequency analysis of Turkey using L-moments method. Hydrological Processes, 25(22), 3499–3505. doi.org/10.1002/hyp.8077 google scholar
  • Spinoni, J., Barbosa, P., Bucchignani, E. Et al., (2020) . uture global meteorological drought hot spots: a study based on CORDEX data, J. Clim., 33, 3635-3661, 10.1175/JCLI-D-19-0084.1 google scholar
  • Stagge, J. H., Tallaksen, L. M., Gudmundsson, L., Van Loon, A. F., Stahl, K. (2015). Candidate Distributions for Climatological Drought Indices (SPI and SPEI). International Journal of Climatology, 35(13), 4027–4040. doi.org/10.1002/joc.4267 google scholar
  • Tosunoglu, F., Gurbuz, F. (2019). Mapping spatial variability of annual rainfall under different return periods in Turkey: The application of various distribution functions and model selection techniques. Meteorological Applications, 26(4), 671–681. doi.org/10.1002/met.1793 google scholar
  • Tramblay Y, Koutroulis A, Samaniego L, et al. (2020). Challenges for drought assessment in the Mediterranean region under future climate scenarios. Earth-Sci Rev. 2020;210:103348. google scholar

Atıflar

Biçimlendirilmiş bir atıfı kopyalayıp yapıştırın veya seçtiğiniz biçimde dışa aktarmak için seçeneklerden birini kullanın


DIŞA AKTAR



APA

Bağcı Genel, K. (2024). Nakagami Distribution for Modeling Monthly Precipitations in Van, Türkiye. International Journal of Environment and Geoinformatics, 11(3), 19-23. https://doi.org/10.30897/ijegeo.1434719


AMA

Bağcı Genel K. Nakagami Distribution for Modeling Monthly Precipitations in Van, Türkiye. International Journal of Environment and Geoinformatics. 2024;11(3):19-23. https://doi.org/10.30897/ijegeo.1434719


ABNT

Bağcı Genel, K. Nakagami Distribution for Modeling Monthly Precipitations in Van, Türkiye. International Journal of Environment and Geoinformatics, [Publisher Location], v. 11, n. 3, p. 19-23, 2024.


Chicago: Author-Date Style

Bağcı Genel, Kübra,. 2024. “Nakagami Distribution for Modeling Monthly Precipitations in Van, Türkiye.” International Journal of Environment and Geoinformatics 11, no. 3: 19-23. https://doi.org/10.30897/ijegeo.1434719


Chicago: Humanities Style

Bağcı Genel, Kübra,. “Nakagami Distribution for Modeling Monthly Precipitations in Van, Türkiye.” International Journal of Environment and Geoinformatics 11, no. 3 (Dec. 2024): 19-23. https://doi.org/10.30897/ijegeo.1434719


Harvard: Australian Style

Bağcı Genel, K 2024, 'Nakagami Distribution for Modeling Monthly Precipitations in Van, Türkiye', International Journal of Environment and Geoinformatics, vol. 11, no. 3, pp. 19-23, viewed 23 Dec. 2024, https://doi.org/10.30897/ijegeo.1434719


Harvard: Author-Date Style

Bağcı Genel, K. (2024) ‘Nakagami Distribution for Modeling Monthly Precipitations in Van, Türkiye’, International Journal of Environment and Geoinformatics, 11(3), pp. 19-23. https://doi.org/10.30897/ijegeo.1434719 (23 Dec. 2024).


MLA

Bağcı Genel, Kübra,. “Nakagami Distribution for Modeling Monthly Precipitations in Van, Türkiye.” International Journal of Environment and Geoinformatics, vol. 11, no. 3, 2024, pp. 19-23. [Database Container], https://doi.org/10.30897/ijegeo.1434719


Vancouver

Bağcı Genel K. Nakagami Distribution for Modeling Monthly Precipitations in Van, Türkiye. International Journal of Environment and Geoinformatics [Internet]. 23 Dec. 2024 [cited 23 Dec. 2024];11(3):19-23. Available from: https://doi.org/10.30897/ijegeo.1434719 doi: 10.30897/ijegeo.1434719


ISNAD

Bağcı Genel, Kübra. “Nakagami Distribution for Modeling Monthly Precipitations in Van, Türkiye”. International Journal of Environment and Geoinformatics 11/3 (Dec. 2024): 19-23. https://doi.org/10.30897/ijegeo.1434719



ZAMAN ÇİZELGESİ


Gönderim13.02.2024
Kabul31.08.2024
Çevrimiçi Yayınlanma28.09.2024

LİSANS


Attribution-NonCommercial (CC BY-NC)

This license lets others remix, tweak, and build upon your work non-commercially, and although their new works must also acknowledge you and be non-commercial, they don’t have to license their derivative works on the same terms.


PAYLAŞ




İstanbul Üniversitesi Yayınları, uluslararası yayıncılık standartları ve etiğine uygun olarak, yüksek kalitede bilimsel dergi ve kitapların yayınlanmasıyla giderek artan bilimsel bilginin yayılmasına katkıda bulunmayı amaçlamaktadır. İstanbul Üniversitesi Yayınları açık erişimli, ticari olmayan, bilimsel yayıncılığı takip etmektedir.