Evaluation of Satellite Rainfall Products in the Caribbean Region

Abstract

Abstract Obtaining rainfall data in many countries around the world, especially in remote areas and mountainous river basins, is one of the major challenges encountered in natural resource monitoring, conservation, and management. Due to the inaccessibility of those areas and the non-existence of in-situ gaging stations, accurate and consistent measurement of rainfall data is rare in these regions. In this study, high spatial resolution satellite precipitation products are evaluated using the U.S. Army Corps of Engineers (USACE) – Hydrologic Engineering Center - Hydrologic Modeling System (HEC-HMS) (USACE, 2022). A comparison of ground-based estimates from pluviometry data in Puerto Rico is used to verify the satellite-based estimates. Satellite rainfall data products will be selected from a list of the latest satellite precipitation technology models for implementation, such as PERSIANN-CDR (NCAR, 2022) which is an estimation of precipitation from remotely sensed information using artificial neural networks, the Climate Hazards Group Infra-Red Precipitation with Stations (CHIRPS; Funk et al., 2015), which provides resolutions between 0.05° and 0.25°, and the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA; Huffman et al., 2007) for streamflow simulation with a daily temporal and spatial resolution of 0.25° x 0.25°. The objective is to identify which of these different satellite precipitation products provide better estimates of rainfall for hydrological applications and the performance of satellite rainfall satellite precipitation estimates for hydrological modeling in different regions of the Caribbean. An uncertainty analysis will be done to determine the most appropriate product. The first phase of this investigation is identifying the study area in Puerto Rico and creating the hydrological model, calibrating and validating it. The experience obtained with Puerto Rico‘s calibrated model will be transferred to the Republic of Haiti attempting to develop flood-prone area maps on the north side of the country. Satellite precipitation estimates always suffer from uncertainties due to random and systematic errors associated with the observations, sampling, retrieval algorithms, and bias correction processes, which must be eliminated or minimized before they can be used in the simulation using HEC-Hydrologic Modeling System (HMS. Satellite spatial precipitation estimates are a promising alternative for the simulation of HEC-HMS hydrological models in regions where on-site rain gages are non-existent.