TY - JOUR T1 - Nakagami Distribution for Modeling Monthly Precipitations in Van, Türkiye AU - Bağcı, Kübra PY - 2024 DA - September Y2 - 2024 DO - 10.30897/ijegeo.1434719 JF - International Journal of Environment and Geoinformatics JO - IJEGEO PB - Istanbul University WT - DergiPark SN - 2148-9173 SP - 19 EP - 23 VL - 11 IS - 3 LA - en AB - 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. KW - Drought KW - Precipitation KW - Nakagami distribution KW - Van CR - 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 CR - 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 CR - 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 CR - 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 CR - Evans, M., Hastings, N., Peacock, B. (2001). Statistical distributions. IOP Publishing. CR - 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 CR - 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 CR - 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 CR - 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 CR - 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 CR - 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 CR - 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 CR - 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 CR - 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 CR - 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 CR - 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 CR - 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 CR - 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 CR - 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. UR - https://doi.org/10.30897/ijegeo.1434719 L1 - https://dergipark.org.tr/en/download/article-file/3719177 ER -