Evaluation of TRMM Multisatellite Precipitation Analysis (TMPA) and Its Utility in Hydrologic Prediction in the La Plata Basin

TLDR

Satellite‑based precipitation estimates offer an alternative forcing source for hydrological models where in‑situ data are scarce, and the La Plata basin exemplifies this need. To assess TMPA’s suitability, this study evaluates nine years of TRMM Multisatellite Precipitation Analysis against gauged observations and a VIC semidistributed hydrology model for the La Plata basin. The evaluation compares basin‑wide TMPA estimates with gauge data and applies the VIC model to simulate hydrologic responses. TMPA matches gauge data at monthly scales but underperforms at daily scales, especially for intense rainfall; nevertheless, it drives the VIC model to capture daily floods and low flows with modest peak‑flow bias, reproduces seasonal and interannual streamflow variability, and demonstrates potential for hydrologic forecasting in data‑sparse regions.

Abstract

Abstract Satellite-based precipitation estimates with high spatial and temporal resolution and large areal coverage provide a potential alternative source of forcing data for hydrological models in regions where conventional in situ precipitation measurements are not readily available. The La Plata basin in South America provides a good example of a case where the use of satellite-derived precipitation could be beneficial. This study evaluates basinwide precipitation estimates from 9 yr (1998–2006) of Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA; 3B42 V.6) through comparison with available gauged data and the Variable Infiltration Capacity (VIC) semidistributed hydrology model applied to the La Plata basin. In general, the TMPA estimates agreed well with the gridded gauge data at monthly time scales, most likely because of the monthly adjustment to gauges performed in TMPA. The agreement between TMPA and gauge precipitation estimates was reduced at daily time scales, particularly for high rain rates. The TMPA-driven hydrologic model simulations were able to capture the daily flooding events and to represent low flows, although peak flows tended to be biased upward. There was a good agreement between TMPA-driven simulated flows in terms of their reproduction of seasonal and interannual streamflow variability. This analysis shows that TMPA has potential for hydrologic forecasting in data-sparse regions.