Description Usage Format Source References Examples
A synthetic dataset for mean daily stream water temperature prediction. This data sets is made for testing all wateRtemp functionalities and has characteristics mimicking real world data.
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A data frame with 6851 rows and 10 variables:
Years as integer.
Months as integer.
Days as integer.
Daily mean discharge in m³/s at the gauging station of the test catchment.
Daily precipitation sums in mm, averaged over the whole catchment.
Daily minimum air temperature °C, averaged over the whole catchment.
Daily maximum air temperature °C, averaged over the whole catchment.
Daily mean air temperature °C, averaged over the whole catchment.
Daily mean stream water temperature in °C at the gauging station of the test catchment.
Daily mean global radiation in W/m², averaged over the whole catchment.
Feigl, M., Lebidzinski, K., Herrnegger, M. and Schulz, K.: Machine learning methods for stream water temperature prediction
Feigl, M., Lebidzinski, K., Herrnegger, M. and Schulz, K.: Machine learning methods for stream water temperature prediction
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