What is it about?

We developed a novel precipitation dataset RAIN4PE for Peru and Ecuador by merging multi-source precipitation data (satellite, reanalysis, and ground-based precipitation) with terrain elevation using the random forest method. Furthermore, RAIN4PE was hydrologically corrected using streamflow data in watersheds with precipitation underestimation through reverse hydrology. The results of a comprehensive hydrological evaluation showed that RAIN4PE outperformed state-of-the-art precipitation datasets such as CHIRP, ERA5, CHIRPS, MSWEP, and PISCO in terms of daily and monthly streamflow simulations, including extremely low and high flows in almost all Peruvian and Ecuadorian catchments. This underlines the suitability of RAIN4PE for hydrometeorological applications in this region. Furthermore, our approach for the generation of RAIN4PE can be used in other data-scarce regions.

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Why is it important?

The overall good performance of the RAIN4PE highlights its utility as an important new gridded precipitation dataset, which opens new possibilities for numerous hydrometeorological applications throughout Peru and Ecuador. Examples are streamflow simulations, estimation of the water budget and its evolution, water resources management, understanding spatiotemporal variations of droughts and floods, and exploring spatial variations and regimes of precipitation.


Our future investigations will focus on the analysis of the water budget at the national scale of Peru, as well as climate change impacts on water resources using RAIN4PE as the basis for bias adjustment, and trends in frequency and intensity of meteorological and hydrological droughts.

Universitat Potsdam

Read the Original

This page is a summary of: A novel high-resolution gridded precipitation dataset for Peruvian and Ecuadorian watersheds – development and hydrological evaluation, Journal of Hydrometeorology, December 2021, American Meteorological Society,
DOI: 10.1175/jhm-d-20-0285.1.
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