Time series studies depend mostly on stochastic models for radon seasonal, annual or temporal variability explanations. Others solve radon transport steady state equation analytically to explain radon variability with soil depth. In order to understand radon variability comprehensively, there is the need for a model which encapsulates most required information about its seasonal variability from different aspects. In this paper, soil radon time series is modeled on the North Anatolian Fault Zone in Turkiye. The general PDE representing radon soil dynamics and boundary conditions is employed successfully through a hybrid regression model, which captures and forecasts radon seasonal anomaly as well as its depth profile. An efficient model can be used to estimate other radon-related variables like diffusion rate and velocity. The model evaluation criteria facilitated the forecast of almost 86% variation of radon concentration with an RMSE value of 9.4 Bqm⁻³, which is reasonable considering the nature of data used. This model is simple and can provide a realistic statistical outcome on any radon data. The relationship between Rn and soil temperature was also investigated. Radon seasonal anomaly is observed to attain its maximum and minimum values in summer and winter seasons. A solid correlation is obtained between radon and soil temperature at various depths. The radon anomaly in normal conditions is found to correlate strongly with the model. Monte Carlo simulation procedure is affected by taking the mean of 300 simulation paths within \(\pm \,2\sigma\) from the regression curve with practically acceptable results.

时间序列研究主要依赖于models模型的季节性，年度或时间变异性解释的随机模型。其他人则通过解析solve运输稳态方程来解释ra随土壤深度的变化。为了全面了解ra的变异性，需要一种模型，该模型从各个方面封装关于其季节性变异的最需要的信息。本文以Turkiye的北安那托利亚断层带为模型模拟了土壤ra时间序列。通过混合回归模型成功地采用了代表ra土壤动力学和边界条件的一般PDE，该模型可以捕获和预测ra的季节性异常及其深度剖面。一个有效的模型可以用来估计其他与ra有关的变量，例如扩散速率和速度。⁻³，考虑到所用数据的性质，这是合理的。该模型很简单，可以在任何ra数据上提供现实的统计结果。还研究了Rn与土壤温度之间的关系。summer的季节异常在夏季和冬季均达到最大值和最小值。在不同深度下，ra与土壤温度之间具有牢固的相关性。发现正常条件下的ra异常与模型密切相关。蒙特卡罗模拟程序受到回归曲线\（\ pm \，2 \ sigma \）内300条模拟路径平均值的影响，并获得了可接受的结果。