Jansen, Femke; Uijlenhoet, Remko; Jacobs, Cor; Teuling, Adriaan J. (2022): Open water evaporation of Lake IJssel, scripts and data used for regression analyses in the study 'Evaporation from a large lowland reservoir – observed dynamics during a warm summer'. Version 2. 4TU.ResearchData. dataset. https://doi.org/10.4121/16913308.v2

Dataset

x choose version: version 3 - 2023-11-22 (latest) version 1 - 2021-11-02

• Land and Water Management
• Atmospheric Sciences

data driven approach, eddy covariance, Evaporation, Hydrology, IJsselmeer, Lake IJssel, Open water evaporation, Regression analysis

2019-2020, only the summer periods taken as 1st of May - 31st of August.

CC BY-NC-SA 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Femke Jansen , Remko Uijlenhoet , Cor Jacobs , Adriaan J. Teuling

Scripts in the programming language R and accompanying datasets that are used for regression analysis in the study 'Evaporation from a large lowland reservoir – observed dynamics during a warm summer'. The analysis provides insight in which variables can explain open water evaporation of Lake IJssel, the Netherlands, measured at two locations for the years 2019 and 2020. There are 4 scripts for each location (i.e. Stavoren and Trintelhaven): for (1) the hourly and (2) daily temporal scale, and for analysis based on (3) our own observations (doi: 10.4121/16601675), and (4) routinely measured data by the Royal Netherlands Meteorological Institute (KNMI -https://www.knmi.nl/nederland-nu/klimatologie/uurgegevens (last access: 01-11-2021)) and the Directorate-General for Public Works and Water Management (Rijkswaterstaat - https://waterinfo.rws.nl/#!/kaart/watertemperatuur/ (last access: 01-11-2021)). The datasets consist of evaporation data, and five possible explanatory variables: global radiation, wind speed, vertical vapour pressure gradient,vapour pressure deficit, and water temperature. The datasets of the routinely measured data consist of combined data that is sourced from KNMI (global radiation, wind speed, vapour pressure gradient, vapour pressure deficit) and Rijkswaterstaat (water temperature). For more information about the datasets that are based on our own observations, have a look at doi:10.4121/16601675 (related dataset).

• 2021-11-02 first online

• 2022-05-20 published, posted

4TU.ResearchData

.R and .txt

• https://doi.org/10.4121/16601675

• SWM-EVAP: Smart Water Management in a complex environment: improving the monitoring and forecasting of surface evaporation (grant code ALWTW.2016.049) [more info...] Dutch Research Council

Hydrology and Quantitative Water Management, Wageningen University & Research