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Nakagami Distribution for Modeling Monthly Precipitations in Van, Türkiye

Year 2024, , 19 - 23, 28.09.2024
https://doi.org/10.30897/ijegeo.1434719

Abstract

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.

References

  • 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
  • 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
  • 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
  • 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
  • Evans, M., Hastings, N., Peacock, B. (2001). Statistical distributions. IOP Publishing.
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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.
Year 2024, , 19 - 23, 28.09.2024
https://doi.org/10.30897/ijegeo.1434719

Abstract

References

  • 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
  • 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
  • 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
  • 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
  • Evans, M., Hastings, N., Peacock, B. (2001). Statistical distributions. IOP Publishing.
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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.
There are 19 citations in total.

Details

Primary Language English
Subjects Physical Geography and Environmental Geology (Other)
Journal Section Research Articles
Authors

Kübra Bağcı 0000-0002-6679-9738

Early Pub Date August 31, 2024
Publication Date September 28, 2024
Submission Date February 13, 2024
Acceptance Date August 31, 2024
Published in Issue Year 2024

Cite

APA Bağcı, 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