Lake Erken High Frequency Monitoring data used for EU Water JPI project PROGNOS

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Created: Aug 12, 2019 at 9:38 a.m.
Last updated: Aug 27, 2019 at 7:14 p.m.
DOI: 10.4211/hs.2dead0d54fe74ee7943e89ae4159aab1
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The European Union Water JPI ( has funded the project PROGNOS (Predicting In-Lake Responses to Change Using Near Real Time Models PROGNOS developed an integrated approach that couples high frequency (HF) lake monitoring data to dynamic lake water quality models to forecast short-term changes in lake water quality. Here we provide an archive the the HF monitoring data sets that were used by PROGNOS project Partner Uppsala Universtiy to calibrate and verify the performance of the GOTM ( SELMA models that are coupled by the frame work for aquatic biogeochemical models ( All data were collected from Lake Erken the site of the Uppsala University Limnology field station ( HF data is from 2015, 2016, 2017, and 2018, years when there was good coverage of the three main categories of data that are needed for water quality modeling: 1) meteorological data; 2) water temperature data; and 3)lake biogeochemical data. These data are in the format routinely collected,and can contain additional measurements that are not actually used in the model simulations.

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Resource Level Coverage


Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees


Start Date:
End Date:


Meteorlogical Data

_ErkenMalmaIslanMetData_2015-2018.csv _

This is data collected from an automated monitoring station located on Malma Island, a small island 500 m offshore from the Erken Laboratory (59.83909N 18.629558W). The measured parameters as listed in the file header are

  • SW_Rad_Avg Shortwave radiation (watts m-2)
  • PAR_Rad_Avg Photosythetically available radiation (400-700nm moles-6 m-2 s-1)
  • Air_Temp_HS_Avg Air temperature measured by humidity sensor passive shield (C)
  • Air_Temp_AS_Avg Air temperature measured by an aspirated sensor (C)
  • RelHumidity_Avg Relative Humidity (percent)
  • Vapor_Pressure_Avg Vapor pressure (h Pa)
  • Water_Temp_1m_Avg Water Temperature at 1 m depth (C)
  • Water_Temp_3m_Avg Water Temperature at 3 m depth (C)
  • Water_Temp_15m_Avg Water Temperature at 15 m depth (C)
  • MeanWS Mean wind speed (m s-1)
  • WindVector Vector calculated mean wind speed (m s-1)
  • WindDir Wind direction (degree 0-360)
  • StdDevWindDir Standard deviation of wind direction
  • WindSpeed_Max Maximum wind speed recorded during the hour
  • WindSpeed_TMx Time the maximum wind speed was recorded
  • WindSpeed3_Avg Cube of the mean wind speed
  • Water_Level_Avg Level of the lake surface water meters above sea level
  • Rain_Total Total rain in the last hour (mm)
  • AirPressure_hPa_Avg Air pressure (hPa)

The data logger measures every minute and data are saved at 1 hour interval. Mean valuse are that of the 60 minute measurements. To force the Lake model the following values are used: SW_Rad_Avg, Air_Temp_AS_Avg, RelHumidity_Avg, MeanWS, Rain_Total, and AirPressure_hPa_Avg. To check the lake water balance Water_Level_Avg is used and the 3 water temperature are used for model calibration and verification.

Data are also obtained from the SMHI meteorological station at Svanberga (59.83232N 18.654550W),stations=all,stationid=98490

Cloud cover data are only available from this station, and precipitation data are generally more reliable from the Svanberga station. There is a longer data record of humidity and air pressure from Svanberga so these data are used when they are not available for the Malma Island station. Each parameter is downloaded as s separate file

Water Temperature Data

During ice free conditions full profiles of water temperature are automatically recorded at the Eastern end of Lake Erken approximately 500 m to the NE of the Malma island meteorological station at a depth of 15.5 m (59.84297N 18.635433W). During the PROGNOS project 2 different systems were used both based on thermocouple sensors. Between 2015-2016 temperatures were measured every 30 min at 30 depths between 0.5 and 15 meters depth. Starting in 2016 an upgraded system measured temperatures at 50 depths between 1.0 and 15.5 m depth at hourly intervals. This system was designed to be operate year round and is moored underwater below the depth of ice formation.

Each file line contains:

  • Time stamp
  • An ID or record number
  • Data logger multiplexer reference temperature(s)
  • Water temperature measurements in the remaining columns. Depths are given in the column header.


  • 2015_ErkenWaterTempProfile.csv------------2015 temperature profiles old system
  • 2016_ErkenWaterTempProfile.csv------------2016 temperature profiles old system
  • 2017_ErkenWaterTempProfile.csv------------2017 temperature profiles old system up until time of new system deployment
  • 2017-2018_ErkenWaterTempProfile.dat-------2017-2017 temperature profiles from new system, which operate year round.

Water Quality Data Files

HF water quality measurements collected by a YSI EXO2 sonde ( that was deployed on a profiling system ( were used to calibrate the GOTM/SELMA model. Data used were dissolved oxygen, and chlorophyll fluorescence. This system was also deployed near Malma Island in the main basin of the lake the exact location (and maximum depth) varied from year to year. The present location is at 59.84530N 18.624217W and at depth of 18.0 meters. Profiles are collected every hour at 0.5 meter intervals. Separate yearly files are provided for each of the water quality parameters. Each row is a profile, the first column is time, followed by measurement at depth as specified in the file header.


Funding Agencies

This resource was created using funding from the following sources:
Agency Name Award Title Award Number
European Union ERA-NET WaterWorks2014 Cofunded Call PROGNOS
FORMAS Predicting in-lake responses to change using near real time models (PROGNOS) 2016-00006
Swedish Infrastructure for Ecosystem Science (SITES)

How to Cite

Pierson, D. (2019). Lake Erken High Frequency Monitoring data used for EU Water JPI project PROGNOS, HydroShare,

This resource is shared under the Creative Commons Attribution CC BY.


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