RFmerge

May 22, 2020 · 2 min read
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rpackages
RFmerge R package.

RFmerge R package.

Description

RFmerge is an R package (currently not on CRAN, but working with the terra package on Github) designed to generate more reliable environmental datasets by combining information from gridded datasets and ground-based observations. It implements the Random Forest Merging Procedure (RF-MEP) (Baez-Villanueva et al., 2020), a machine-learning approach developed to improve the spatial and temporal representation of environmental variables—particularly precipitation—by leveraging the complementary strengths of different data sources.

The package addresses a persistent challenge in hydrology and Earth system sciences: no single dataset provides a complete and unbiased representation of environmental conditions. Rain gauges offer accurate point measurements but limited spatial coverage, while satellite products provide broad spatial information that may contain systematic errors. By integrating these sources within a unified statistical framework, RFmerge produces merged datasets that better capture variability, reduce bias, and enhance the reliability of environmental analyses, especially in data-scarce regions.

Built with operational applications in mind, RFmerge provides a transparent and reproducible workflow for dataset merging that can be adapted to a wide range of variables beyond precipitation, including temperature, soil moisture, or other gridded datasets. It is particularly well suited for researchers and practitioners who require spatially consistent datasets to support hydrological modelling, climate analysis, and water resources assessment.

Grounded in peer-reviewed research and real-world applications, RFmerge offers a technically robust and methodologically sound foundation for transforming heterogeneous environmental observations into coherent, analysis-ready datasets.

Reference

R Package Gridded Datasets Hydrology Merging Data Fusion
Dr. Mauricio Zambrano-Bigiarini
Authors
Dr. Mauricio Zambrano-Bigiarini (he/him)
Associate Professor

I am an Associate Professor in the Department of Civil Engineering at the University of La Frontera. I hold a PhD in Environmental Engineering from the University of Trento (Italy) and completed postdoctoral training at the European Commission’s Joint Research Centre. I have more than 20 years of experience in water resources research and have previously served as an Associate Researcher at the Center for Climate and Resilience Research (CR)2 and as a member of the Earth Sciences Assessment Group of the Chilean National Research and Development Agency (ANID).

My research lies at the interface of hydrology, data science, and environmental sciences, with a particular focus on the use of gridded datasets and open-source tools to investigate droughts, extreme events, and water-related impacts of global change.

I work across spatial and temporal scales to improve the understanding of catchment-scale hydrological processes and to translate this knowledge into operational modelling, forecasting, and early-warning systems that support robust environmental decision-making.

Please reach out to collaborate 😃