Evaluation of long-term satellite-based precipitation products for developing intensity-frequency (IF) curves of daily precipitation

Abstract

Iran is one of the most flood-prone countries in the world. It experiences much damage from floods, leading to economic challenges in the country. One of the most important strategies for flood risk management is an accurate estimation of design flood for water infrastructures construction. It is estimated based on the intensity-duration-frequency (IDF) curves. Traditionally, the IDF curves are generated by the gauged-based rainfall data. But, recently, the application of satellite-based rainfall estimates is evaluating by a few researchers around the world. In this study, four satellite-based precipitation products (MSWEP, CHIRPS, PERSIANN-CDR, and PERSIANN-CCS-CDR) were used to evaluate the performance of the individual and ensemble of the products for developing the Intensity-Frequency (IF) curves for daily precipitation in Iran. The investigation was conducted in 14 stations with different climatic conditions. The evaluation metrics (ME (mean error), RMSE, PCC (Pearson correlation coefficient), and RE (relative error)) show that CHIRPS (ME<-1 mm/h, RMSE<1.5 mm/h, PCC > 0.85, RE < 30%) performs better than the other products for all return periods. However, the other products may provide reasonable IF curves if the bias of the data is corrected. The ensemble of the bias-corrected products leads to the most accurate estimation of the IF curve (ME<0.1 mm/h, RMSE<0.5 mm/h, PCC > 0.85, RE < 7%); however, the ensemble of the unadjusted products provides a reliable estimation (ME<-0.5 mm/h, RMSE<1.7 mm/h, PCC > 0.5, RE < 10%). Accordingly, for the ungauged regions, where the measured data is not available for bias correction, the unadjusted CHIRPS or the ensemble of the unadjusted products can be applied.