hydroTSM v0.6-0 on CRAN

Mar 11, 2020·
Dr. Mauricio Zambrano-Bigiarini
Dr. Mauricio Zambrano-Bigiarini
· 1 min read
blog

Following a request made by CRAN regarding compatibility issues with the upcoming version of R, the new version of hydroTSM (v0.6-0) was released today March 11th 2020, and it is available on CRAN now https://cran.r-project.org/package=hydroTSM

Among its new features stand out:

  • Package tested against R Under development (unstable) (2020-03-10 r77920) – “Unsuffered Consequences”, following an imperative request made by CRAN.

  • Vignette on Introductory Analysis of Daily Precipitation was moved from Sweave to Knitr and now includes a climograph example.

  • subdaily2daily: new argument start to allow daily observations start at any time different from 00:00:00 UTC.

  • time2season : class of objects is now tested in a way compatible with the upcoming R 4.0.0

  • dm2seasonal : class of objects is now tested in a way compatible with the upcoming R 4.0.0

  • matrixplot : class of objects is now tested in a way compatible with the upcoming R 4.0.0

I hope you enjoy it !.

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Dr. Mauricio Zambrano-Bigiarini
Authors
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 😃