The doubt in the calculation algorithm of the standardized precipitation index (SPI), which is widely preferred in the evaluation and monitoring of drought, still remains up-to-date because its calculation process is performed in the form of standardization or normalization with a default probability distribution. Therefore, the success of this index is directly affected by the choice of the probability distribution model. This study is based on the effect of three different parameter estimation methods on the calculation process, as well as the comparison of the SPI results calculated based on the default Gamma distribution and the distribution with the best ability to represent the 3-and 12-month consecutive summed rainfall data among the 15 candidate distributions namely Gamma (GAM), Generalized Extreme Value (GEV), Pearson Type III (P III), Log Pearson Type III (LP III), two-parameter Lognormal (LN2), three-parameter Lognormal (LN3), Generalized Logistic (GLOG), Extreme Value Type I (EVI), Generalized Pareto (GPAR), Weilbul (W), Normal (N), Exponential (EXP), Logistic (LOG), four-parameter Wakeby (WK4), and five-parameter Wakeby (WK5) distributions. Approximately 68.4% and 18.4% of the 3-month data considered had the best fit to the Weibull and Pearson III distribution, while approximately 24% and 18% of the 12-month data had the best fit to the Weibull and Logistic distribution. On the other hand, it was found that the default Gamma distribution calculated the extreme drought categories significantly more than the best-fit distribution model. In terms of parameter estimation methods, L-moments for 3-month series and maximum likelihood approaches for 12-month series were most dominant.

中文翻译：

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土耳其 Yeşilırmak、Kızılırmak 和 Konya 封闭盆地常规假设下标准化降水指数 (SPI) 估算的准确性评估

在干旱评估和监测中广泛首选的标准化降水指数（SPI）的计算算法存在疑问，但由于其计算过程是以标准化或标准化的形式进行的，并且具有默认值，因此仍然保持最新状态概率分布。因此，该指标的成功与否直接受到概率分布模型选择的影响。本研究基于三种不同参数估计方法对计算过程的影响，以及基于默认 Gamma 分布计算的 SPI 结果与最能代表 3 个月和 12 个月的分布的比较15 个候选分布中的连续求和降雨数据，即 Gamma (GAM)、广义极值 (GEV)、Pearson Type III (P III)、Log Pearson Type III (LP III)、二参数对数正态分布 (LN2)、三参数对数正态分布 (LN3)、广义逻辑 (GLOG)、极值 I 型 (EVI)、广义帕累托 (GPAR)、Weilbul (W)、正态 (N)、指数 (EXP)、逻辑 (LOG)、四参数 Wakeby (WK4) 和五参数 Wakeby (WK5) 分布。大约 68.4% 和 18.4% 的 3 个月数据最符合 Weibull 和 Pearson III 分布，而大约 24% 和 18% 的 12 个月数据最适合 Weibull 和 Logistic 分布。另一方面，发现默认 Gamma 分布计算的极端干旱类别明显多于最佳拟合分布模型。在参数估计方法方面，