hydroTSM
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Description
hydroTSM is an R package designed to support the practical workflow of hydrologists and environmental scientists who routinely work with time series data. It provides a comprehensive and coherent set of tools for the management, quality control, analysis, interpolation, and visualization of hydrological and environmental time series, with particular emphasis on tasks commonly encountered in hydrological modelling and water resources assessment.
hydroTSM prioritises reliability, transparency, and functional breadth, reflecting the operational realities of applied hydrology, where reproducible data handling and robust diagnostics are often more critical than marginal computational gains. Its functions are built to integrate naturally into analytical pipelines, facilitating consistent preprocessing and exploration of observational datasets prior to modelling or decision-making.
Developed with the daily needs of practitioners in mind, hydroTSM has been widely used in research, teaching, and professional applications. It is especially suitable for users who require dependable, well-documented tools to support routine hydrological analysis while maintaining full control over data processing steps within the R environment.
hydroTSM R package.
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 😃