Variable physical drivers of near-surface turbulence in a regulated river

• Main Author: Guseva, S (via Mendeley Data)
• Language: unknown
• Published: 2021
• Subjects: Interdisciplinary sciences; Kitinen; Tower The; Northern Finland
• Online Access: http://nbn-resolving.org/urn:nbn:nl:ui:13-k3-vh74; https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:225105

This dataset is used to analyze the drivers of near-surface turbulence in large rivers. The data were collected during the measurement campaign conducted at the River Kitinen in Northern Finland (67.3665º N, 26.6230º E) in the summer of 2018. At the study site, the river is 181 m wide, and its flow is regulated by two hydropower stations. These unique data include results of measurements in the river and the atmosphere collected at different locations: a floating platform in the middle of the river, the river bottom, a meteorological mast at the river bank, and a land meteorological tower located at a small distance to the east of the river bank. The river data contain continuous measurements of flow velocity (ADCP, bottom; ADV, platform), water temperature (thermistor chain, river middle), water level (wave recorder, river bank), and photosynthetically active radiation (PAR sensor, platform). The atmospheric data contain continuous measurements of wind speed and direction, air temperature and relative humidity, and incoming shortwave and longwave radiation (river bank mast and land tower). The detailed information about the measurement instruments can be found in the corresponding article “Variable physical drivers of near-surface turbulence in a regulated river”.Rivers are an important source of the greenhouse gases to the atmosphere. The gas exchange at the air-water interface is largely controlled by the near-surface turbulence, which has not been studied in details for large rivers. The idea behind the analysis of these data is to determine the main drivers of the near-surface turbulence in large rivers and their relative importance. To that end, we computed the dissipation rate of turbulent kinetic energy and compared it with the estimates provided by bulk scaling relations and a one-dimensional numerical turbulence model. The results are two-fold. First, all estimation methods are able to accurately predict the dissipation rate. Second, the two main drivers of the near-surface turbulence, namely the ...