DOI: 10.4211/hs.27c93a3f4ee2467691a1671442e047b8
title: High frequency dataset for event-scale concentration-discharge analysis

description: This composite repository contains high-frequency data of discharge, electrical conductivity, nitrate-N, spectral absorbance at 254 nm and water temperature obtained in four neighboring catchments in the Harz mountains, Germany.
The repository contains four files - one for each catchment (WB - Warme Bode, RB - Rappbode, HS - Hassel, SK - Selke). Details on the catchments can be found here: WB - Kong et a.(2019), RV - Werner et al. (2019), HS and SK - Musolff et al. (2015)
Data for the SK catchment is part of the TERENO initiative (https://www.tereno.net/).
Each file states measurements for each timestep using the following columns: "index" (number of observation),"Date.Time" (timestamp in YYYY-MM-DD HH:MM:SS), "WT" (water temperature in degree celsius), "discharge.mm" (discharge in mm/d), "Q.smooth" ( discharge in mm/d smoothed using moving average),"EC.smooth" (electrical conductivity in µS/cm smoothed using moving average), "NO3.smooth" (NO3-N concentrations in mg N/L smoothed using moving average), "SAC.smooth" (spectral absorbance at 254 nm in 1/m, smoothed using moving average); NA - no data

Water quality data and discharge was measured at a high-frequency interval of 15 min in the time period between January 2013 and December 2014. Both, NO3-N and SAC were measured using in-situ UV-VIS probes (TRIOS ProPS, Trios Germany in WB, HS and SK; s::can spectrolyser, scan Austria in RB). EC was measured using in-situ probes (YSI6800, YSI, USA for WB, HS and SK; CTD Diver, Van Essen Canada for RB). Discharge measurements were provided by the state authorities [LHW, 2018] (for WB, HS and SK) or relied on an established stage-discharge relationship (RB, Werner et al. [2019]). Data loggers were maintained every two weeks, including manual cleaning of the UV-VIS probes and grab sampling for subsequent calibration and validation.

Data preparation included five steps: drift corrections, outlier detection, gap filling, calibration and moving averaging:
- Drift was corrected by distributing the offset between mean values one hour before and after cleaning equally among the two weeks maintenance interval as an exponential growth. 
- Outliers were detected with a two-step procedure. First, values outside a physically unlikely range were removed. Second, the Grubbs test, to detect and remove outliers, was applied to a moving window of 100 values. 
- Data gaps smaller than two hours were filled using cubic spline interpolation. 
- The resulting time series were globally calibrated against the lab measured concentration of NO3-N (all stations) and SAC254 (all stations but SK). Here, average probe values one hour before and after sampling were used. EC was calibrated against field values obtained with a handheld WTW probe (WTW Multi 430, Xylem Analytics Germany) for RB while YSI-probe values for WB, HS and SK have been regularly calibrated in field making later corrections obsolete.
- Noise in the signal of both discharge and water quality was reduced by a moving average between 2.5 and 6 hours.

References: 
Kong, X. Z., Q. Zhan, B. Boehrer, and K. Rinke (2019), High frequency data provide new insights into evaluating and modeling nitrogen retention in reservoirs, Water Res, 166, 115017.
LHW (2018), Datenportal Gewaesserkundlicher Landesdienst Sachsen-Anhalt (GLD),  Landesbetrieb fuer Hochwasserschutz und Wasserwirtschaft Sachsen-Anhalt. accessed 2018-08-15
Musolff, A., C. Schmidt, B. Selle, and J. H. Fleckenstein (2015), Catchment controls on solute export, Advances in Water Resources, 86, 133-146.
Werner, B. J., A. Musolff, O. J. Lechtenfeld, G. H. de Rooij, M. R. Oosterwoud, and J. H. Fleckenstein (2019), High-frequency measurements explain quantity and quality of dissolved organic carbon mobilization in a headwater catchment, Biogeosciences, 16(22), 4497-4516.