**4. Conclusions**

This study described how ANN models are used to estimate yearly runoff for the Yerli sub-catchment of the upper Tapi basin. Runoff estimation was undertaken using NNTOOL and NNSTART. Adopting NNTOOL, two different models were developed, i.e., FFBPNN and CFBPNN networks, using several combinations of input data and then comparing their capability of flow estimation for the period 1981–2016. For estimating runoff using NNTOOL, two NNs are used, with the values of MSE, RMSE, and R calculated. For the transig function in FFBPNN, the most prominent model architecture is 6-4-1, which has an MSE value of 0.4982, an RMSE value of 0.7056, and a value of R of 0.96108. The 6-4-1 model architecture for the transig function is the most effective for CFBPNN, with MSE values of 0.8813, RMSE values of 0.9387, and R values of 0.96096. Using three different algorithms, LM, BR, and CGS, were used to predict runoff. Among the three, the LM-trained algorithm with 30 neurons is the best model, with MSE values of 0.7279, RMSE values of 0.8531, and R values of 0.95057. According to the findings, FFBPNN predicts better results than CFBPNN, and the LM algorithm stands out among the other algorithms.

**Supplementary Materials:** The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/ECWS-7-14232/s1, Table S1: Results of FFBPNN for Yerli station, Table S2: Results of CFBPNN for Yerli station, Table S3: Results of NNSTART for Yerli station.

**Author Contributions:** Conceptualization, U.M.; methodology, U.M.; software, U.M.; validation, U.M.; formal analysis, U.M. and S.B.M.; data curation, U.M.; writing—original draft preparation, U.M.; writing—review and editing, U.M. and S.B.M. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Unavailability of data due to ethical restrictions.

**Conflicts of Interest:** The authors declare no conflict of interest.
