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'.
Datacite citation style
Jansen, Femke; Uijlenhoet, Remko; Jacobs, Cor; Teuling, Adriaan J. (2021): 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 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/16913308.v1
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Dataset
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Categories
Geolocation
Lake IJssel
Time coverage 2019-2020, only the summer periods taken as 1st of May - 31st of August.
Licence CC BY-NC-SA 4.0
Interoperability
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).
History
- 2021-11-02 first online, published, posted
Publisher
4TU.ResearchDataFormat
.R and .txtReferences
Funding
- 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
Organizations
Hydrology and Quantitative Water Management, Wageningen University & ResearchDATA
Files (25)
- 4,733 bytesMD5:
2b7724eab2cc266c6c0820f23a3407a1README.txt - 7,718 bytesMD5:
f1fffa8c8bd1cf0f52631a3dff1e5315Regression_Stavoren_daily.R - 7,551 bytesMD5:
ec85b12145992310155eee4ce11018dfRegression_Stavoren_daily_routine.R - 7,248 bytesMD5:
6ada66496bfc3cbd2dfc07d39105daaeRegression_Stavoren_hourly.R - 7,541 bytesMD5:
4ff38ee9886c5d893ae8de6f0be35386Regression_Stavoren_hourly_routine.R - 7,273 bytesMD5:
3be2a079ede66b14945edfe715f1f6d8Regression_Trintelhaven_daily.R - 7,291 bytesMD5:
9f2f8baddd0cf0a3822189ead5dbb04aRegression_Trintelhaven_daily_routine.R - 7,287 bytesMD5:
f7b548d158ea033f5014cdcb8766fcb8Regression_Trintelhaven_hourly.R - 7,764 bytesMD5:
c63e1e0fdeb9bab3233d9b1f9220b8c2Regression_Trintelhaven_hourly_routine.R - 39,048 bytesMD5:
c3b25318976b7df497fe2d510021c48cStavoren_daily_2019.txt - 42,534 bytesMD5:
04de361534fd7c11ffde07416bdf83e8Stavoren_daily_2019_routine.txt - 27,950 bytesMD5:
b1cef6456b3583681e0db9039c0d3964Stavoren_daily_2020.txt - 31,340 bytesMD5:
23f254975f6534891c4cf65358005b6fStavoren_daily_2020_routine.txt - 254,614 bytesMD5:
d18354fc7c32c2ae17b6b546783bcfb9Stavoren_hourly_2019.txt - 392,096 bytesMD5:
2e8af6194cfc63279a8d543f9a5c9800Stavoren_hourly_2019_routine.txt - 172,289 bytesMD5:
8f9101934e8872fa7fec7515f7ae1f80Stavoren_hourly_2020.txt - 254,914 bytesMD5:
6cf08def32d0158e5890f7cc4b7f4830Stavoren_hourly_2020_routine.txt - 35,376 bytesMD5:
c0ed962ca0b42857879d5dc6e0f4453aTrintelhaven_daily_2019.txt - 54,283 bytesMD5:
2cbb89580da2efdf2b2800753fd69cf1Trintelhaven_daily_2019_routine.txt - 43,337 bytesMD5:
9b6eed348a826d93715c23fe13c95368Trintelhaven_daily_2020.txt - 58,191 bytesMD5:
dcf9fdce51c1c45ea7581ad4298eca7fTrintelhaven_daily_2020_routine.txt - 404,513 bytesMD5:
ed97898601c44354d48db31dd7dbb928Trintelhaven_hourly_2019.txt - 748,281 bytesMD5:
40c3b2b085bb5f0382744c8bea1adf6eTrintelhaven_hourly_2019_routine.txt - 540,606 bytesMD5:
c499e400c29b4ba08e8545f43347c84bTrintelhaven_hourly_2020.txt - 998,015 bytesMD5:
aceaadc805f937c34a12eb9044e93428Trintelhaven_hourly_2020_routine.txt -
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