Resumo:
Satellite-based precipitation products can be an important alternative for developing
IDF equations in ungauged regions, in search for more flood-resilient hydraulic
systems. This study evaluated precipitation estimates from the product CHIRPS for
developing IDF equations in the Southern Bahia Mesoregion. The statistical metrics
used were Percent Bias (PBIAS), Root Mean Square Error (RMSE), Mean Absolute
Error (MAE), and the Nash-Sutcliffe Efficiency coefficient (NSE). The results indicate
that CHIRPS does not perform satisfactorily in its original state (PBIAS 21.54%; RMSE
43.56 mm/h; MAE 42.74 mm/h; NSE -2.78), but it can provide reasonable IDF
equations if the data bias is corrected (PBIAS -4.75%; RMSE 10.09 mm/h; MAE 9.03
mm/h; NSE 0.78). Based on a linear regression model, a bias correction method was
proposed, which can be applied, with some limitations, in ungauged areas of the
studied region, using only geographic coordinates (PBIAS -3.77%; RMSE 15.46 mm/h;
MAE 14.41 mm/h; NSE 0.45). Using CHIRPS data corrected by the proposed method
showed higher performance when compared to IDF curves provided by the Plúvio 2.1
software (PBIAS 13.56%; RMSE 28.25 mm/h; MAE 26.84 mm/h; NSE -0.55), which is
commonly used by engineers/designers. Finally, non-stationary models for frequency
analysis proved to be more appropriate when a trend condition in the series is
identified. Furthermore, based on the AIC, BIC criteria, and the likelihood ratio test,
models with fewer parameters were preferred over more complex models, with the
Gumbel distribution outperforming the GEV distribution.
