*2.4. Model Certification and Verification*

This study built a computational cell based on the hydrological and physiographic data of the case area. The computational cell covers an area of 2046 km2, with a total of 9804 cells, as shown in Figure 4.

This study took the heavy rain event from June 2016 as a certification case of the PHD model and used the Nash-Sutcliffe efficiency (NSE) coefficient and root mean square error (RMSE) for checking the value of the model accuracy. Another heavy rain event from May 2019 was taken as a verification case, and the simulation results of both events are as shown in Figure 5. The NSE and RMSE values of the heavy rain event in June 2016 are 0.78 and 0.15 m, and the heavy rain event in May 2019 has values of 0.68 and 0.47 m, respectively. As the NSE values of both events exceeded 0.5, we concluded that the PHD model can reasonably simulate the phenomenon of runoff in the case area.

**Figure 4.** Computational cells.

**Figure 5.** The comparison between simulated and observed water level. (**a**) Heavy rain event from June 2016; (**b**) Heavy rain event from May 2019.
