*3.2. NNSTART*

In this study, three different algorithms, namely Levenberg–Marquardt (trainlm), Bayesian Regularization (trainbr), and Scaled Conjugate Gradient (trainscg), were used for model development. Table S3 shows the Yerli station results for the ANN trained by LM, BR, and CGS. The study compares ANN models that were trained with LM, BR, and CGS. LM-trained algorithm with 30 neurons is the best model with an MSE value of 0.7279, an RMSE value of 0.8531, and an R value of 0.95057. Figure 6 shows the best regression plot for the LM algorithm with 30 neurons.

**Figure 6.** Regression plot for LM algorithm with 30 neurons.
