Find research datasets worth reusing

opencc-by-4.0Feb 2021View details →

The Surface Water Chemistry (SWatCh) database

This is the dataset presented in the following manuscript: The Surface Water Chemistry (SWatCh) database: A standardized global database of water chemistry to facilitate large-sample hydrological research, which is currently under review at Earth System Science Data. Openly accessible global scale surface water chemistry datasets are urgently needed to detect widespread trends and problems, to help identify their possible solutions, and determine critical spatial data gaps where more monitoring is required. Existing datasets are limited in availability, sample size/sampling frequency, and geographic scope. These limitations inhibit the answering of emerging transboundary water chemistry questions, for example, the detection and understanding of delayed recovery from freshwater acidification. Here, we begin to address these limitations by compiling the global surface water chemistry (SWatCh) database. We collect, clean, standardize, and aggregate open access data provided by six national and international agencies to compile a database containing information on sites, methods, and samples, and a GIS shapefile of site locations. We remove poor quality data (for example, values flagged as “suspect” or “rejected”), standardize variable naming conventions and units, and perform other data cleaning steps required for statistical analysis. The database contains water chemistry data for streams, rivers, canals, ponds, lakes, and reservoirs across seven continents, 24 variables, 33,722 sites, and over 5 million samples collected between 1960 and 2022. Similar to prior research, we identify critical spatial data gaps on the African and Asian continents, highlighting the need for more data collection and sharing initiatives in these areas, especially considering freshwater ecosystems in these environs are predicted to be among the most heavily impacted by climate change. We identify the main challenges associated with compiling global databases – limited data availability, dissimilar sample collection and analysis methodology, and reporting ambiguity – and provide recommended solutions. By addressing these challenges and consolidating data from various sources into one standardized, openly available, high quality, and trans-boundary database, SWatCh allows users to conduct powerful and robust statistical analyses of global surface water chemistry.

opencc-by-4.0Apr 2022View details →

The true colour of water at Upper Penticton Creek -- data and scripts

These files contain data and scripts used in the analysis for an article titled " Streamwater colour in snow-dominated headwater catchments: natural variability and the effects of forest harvesting," by R.D. Moore, R.D. Winkler and G.D. Hope, to be published in Hydrological Processes. The file upc_water_colour.csv contains the colour data as expressed in true colour units (TCU). The first line is a comment that should be skipped, noting that entries of "creek dry" have been manually edited out of this version of the data. All other editing was performed in the script named 0_wrangle_data.r. The columns are  as follows: <ul> <li>Year - year of observation as four-digit value (e.g., 2005)</li> <li>Date - date as dd-Mmm (e.g., 15-May)</li> <li>Day - day of year (e.g., 1-Jan = 1)</li> <li>Cut241 - cumulative area harvested in 241 Creek as a percentage of catchment area</li> <li>Cut242 - cumulative area harvested in 241 Creek as a percentage of catchment area</li> <li>wc_240 - water colour (TCU) in 240 Creek</li> <li>wc_241 - water colour (TCU) in 241 Creek</li> <li>wc_242 - water colour (TCU) in 242 Creek</li> </ul> The scripts are numbered in the order of dependency. For example, a script beginning 0_ should be run before running a script beginning 1_. The scripts are set up to be run within an R project on the local hard drive. The project directory should contain a folder named data that contains upc_water_colour.csv. All other data sets are accessed programmatically within the scripts. Brief descriptions of the scripts follow: <ul> <li>0_wrangle_data.r - Uses functions in the tidyhydat package to access streamflow data; corrects some erroneous entries for the water colour data; merges streamflow and colour data sets for further analysis.</li> <li>0_wrangle_spatial_data.r - Accesses digital elevation models (DEMs) catchment boundaries and soil map from the Upper Penticton Creek data repository (zenodo); computes various topographic indices from the DEMS; saves processed files on the local hard drive in a folder named dem, located within the project root folder.</li> <li>1_soil_maps.r - Generates a map of the gleyed soil units (Figure 2).</li> <li>1_q_pca_trimonthly.r - Performs a paired-catchment analysis of the streamflow response to logging using a tri-monthly time step; generates plots of observed and predicted streamflow for 241 and 242 Creeks (Figure 3).</li> <li>1_wc_analysis_post_140.r - Analyses water colour variations and response to logging; generates figures used in the article; analysis focuses on days 145 and on each year due to lack of data for earlier dates in the pre-harvest period.</li> <li>1_catchment_characteristics.r - Computes topographic indices for each catchment and generates a table (Table 1) that contains a summary of catchment characteristics.</li> <li>ch_saga_functions.r - Contains functions that use RSAGA package to process the digital elevation models to remove sinks and calculate contributing area grids.</li> </ul>

opencc-by-4.0May 2022View details →

Data for Li et al., Coupling remote sensing and particle tracking to estimate trajectories in large water bodies, International Journal of Applied Earth Observation and Geoinformation, 2022

This data set contains four parts: 1) compressed folder with input parameters and results for the hydrodynamic model 2) compressed folder with input parameters and results for the particle tracking 3) compressed folder with satellite data  4) code used in the article for hydrodynamic model, particle tracking and image processing Each folder contains a readme file,

opencc-by-4.0Mar 2022View details →

Water conformation at three-phases contact lines

This dataset contains detailed trajectories obtained from molecular dynamics simulations performed using GROMACS. The simulated system consists in a quasi-2-dimensional SPC/E water meniscus confined between solid substrates composed by silica quadrupoles. Details on the molecular model and the simulation technique can be found in the references article. The data collected in this dataset are utilized in a ongoing project aimed to demystify the motion of three-phases contact lines over hydrophilic surfaces.

opencc-by-4.0May 2022View details →

Supplemental data and code for "Global patterns in water flux partitioning: Irrigated and rainfed agriculture drives asymmetrical flux to vegetation over runoff"

This dataset provides all data compiled and generated for the manuscript entitled "Global patterns in water flux partitioning: Irrigated and rainfed agriculture drives asymmetrical flux to vegetation over runoff" (https://doi.org/10.1016/j.oneear.2023.08.002). This includes the boundaries for 3614 hydrological catchments, the curated data used for analysis and modelling, the developed machine learning model, shapley values and area of applicability results, and data for global extrapolation It also contains a markdown file ('code.html') which shows how to access and use the data, and generic sample codes used to generate these results.

opencc-by-4.0May 2022View details →

WaterGAP2.2d model derived Potential evapotranspiration and Renewable water resources variables with standard and modified PET calculation methods

This data set is produced as a part of the ''Improving the quantification of climate change hazards by hydrological models: A simple ensemble approach for considering the uncertain effect of vegetation response to climate change on potential evapotranspiration" journal publication (in preparation). WaterGAP2.2d global hydrological model with two different settings; 1) with standard PET method Priestley-Taylor (PT) and 2) with modified approach (PT-MA) (please refer to the publication for more details on the method) used to derive the data set. The bias-adjusted GCM-derived (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, and MIROC5) climate data under RCP2.6 and RCP8.5 emission scenarios were used as the input. The model-derived potential evapotranspiration and the renewable water resources variables are available from 1981 to 2099 on the monthly scale for each land grid cell (spatial resolution: 0.5 degrees x 0.5 degrees). The data files are in the netCDF format (.nc4).

Streamflow drought hazard indicators for monitoring drought risk for human water supply and river ecosystems at the global scale

1) Indicators of streamflow drought hazard (SDHI) as computed by WaterGAP 2.2d (climate data WFDEI-GPCC) for the whole globe except Antarctica, spatial resolution: 0.5°, monthly data for the reference period 1986-2015: Indicators of drought magnitude: SPI12, SPEI12, SSI1, SSI12, EP1, RDQI1 Indicators of drought severity: CDQI1-Q50, CDQI1-Q80, CDQI1-Q80-HS, CDQI1-WUs, CDQI1-WUs-EFR, CDQI1-Q50_f, CDQI1-Q80_f, CDQI1-WUs_f, CDQI1-WUs-EFR_f, CEP1(20%)_f, CRDQI1(-50%)_f 2) WaterGAP grid cell IDs ("arcid") with longitude and latitude (WaterGAP_ArcID_lon_lat.txt) 3) Streamflow observations and SDHI (based on observations) for two GRDC gauging stations: Input_Figure_2_Little_Colorado_River.txt (station near Cameron) and Input_Figure_2_Danube_River.txt (station at Hofkirchen) 4) WaterGAP output: Mean monthly surface water abstractions in km3 per month: Mean_monthly_WUs_km3_per_month_WFDEI_GPCC_ant_22d_1986_2015.txt 5) Input data for computing Pearson correlation between SSI1 based on observations and each of the five indicators SSI1 (simulated), SPI3, SPI6, SPI9, and SPI12. Indicators computed for 218 out of 220 GRDC gauging stations with continuous streamflow observations between 1986 and 2015. The folder also contains a list of the 220 GRDC station numbers and the related WaterGAP grid cell ID ("arcid").

Crop-specific salinity and irrigation data for river sub-basin water scarcity analyses in the US and AU

This dataset contains observed monthly and annual salinity (EC) data for surface water (river) respectively groundwater, spatially averaged over sub-basins within the Central Valley, CA and the Murray Darling basin, AU, used for salinity-inclusive water scarcity assessments. The data also includes crop-specific irrigated area, irrigation withdrawals and salinity thresholds and other parameters specified, as well as example codes for analyses related to the manuscript: Thorslund et al., Salinity impacts on irrigation water-scarcity in food bowl regions of the US and Australia.

Reservoir water quality deterioration due to deforestation emphasizes the indirect effects of global change

This repository contains the dataset linked to the following publication: Article title: Reservoir water quality deterioration due to deforestation emphasizes the indirect effects of global change Journal title: Water Research Article Number: WR_118721 doi: https://doi.org/10.1016/j.watres.2022.118721 Abstract: Deforestation is currently a widespread phenomenon and a growing environmental concern in the era of rapid climate change. In temperate regions, it is challenging to quantify the impacts of deforestation on the catchment dynamics and downstream aquatic ecosystems such as reservoirs and disentangle these from direct climate change impacts, let alone project future changes to inform management. Here, we tackled this issue by investigating a unique catchment-reservoir system with two reservoirs in distinct trophic states (meso‑ and eutrophic), both of which drain into the largest drinking water reservoir in Germany. Due to the prolonged droughts in 2015–2018, the catchment of the mesotrophic reservoir lost an unprecedented area of forest (exponential increase since 2015 and ca. 17.1% loss in 2020 alone). We coupled catchment nutrient exports (HYPE) and reservoir ecosystem dynamics (GOTM-WET) models using a process-based modeling approach. The coupled model was validated with datasets spanning periods of rapid deforestation, which makes our future projections highly robust. Results show that in a short-term time scale (by 2035), increasing nutrient flux from the catchment due to vast deforestation (80% loss) can turn the mesotrophic reservoir into a eutrophic state as its counterpart. Our results emphasize the more prominent impacts of deforestation than the direct impact of climate warming in impairment of water quality and ecological services to downstream aquatic ecosystems. Therefore, we propose to evaluate the impact of climate change on temperate reservoirs by incorporating a time scale-dependent context, highlighting the indirect impact of deforestation in the short-term scale. In the long-term scale (e.g. to 2100), a guiding hypothesis for future research may be that indirect effects (e.g., as mediated by catchment dynamics) are as important as the direct effects of climate warming on aquatic ecosystems.   Data description by Xiangzhen Kong (xiangzhen.kong@ufz.de; xzkong@niglas.ac.cn) 2022-06-20 1. Discharge in the streams from 2010 to 2021 at YRZ site, and from 2010 to 2020 at YHZ_Q site. <ul> <li>File name: dat_discharge_stream_YRZ_YHZ_2010_2021_daily.csv</li> <li>Note: The data is at daily basis but also available at 15-min high frequency basis, which can be requested from the authors.</li> </ul> 2. Nitrate concentration in the streams from 2011 to 2019 at both YRZ and YHZ_Q sites. <ul> <li>File name: dat_nitrate_stream_YRZ_YHZ_2011_2019_daily.csv</li> <li>Note: The data is at daily basis but also available at 15-min high frequency basis, which can be requested from the authors.</li> </ul> 3. Water quality data in the inflows from 2010 to 2021 at biweekly basis, from YRZ and YHZ_WQ sites. <ul> <li>File name: dat_waterquality_stream_YRZ_YHZ_2010_2021_biweekly.csv</li> <li>Note: The data is at biweekly basis, measured at the depth of 0.5m under water surface, from both probe and lab.</li> </ul> 4. Water quality data in the predams from 2010 to 2021 at biweekly basis, from YR1 and YH1 sites. <ul> <li>File name: dat_waterquality_predams_YR1_YH1_2010_2021_biweekly.csv</li> <li>Note: The data is at biweekly basis, measured at the depth of 0.5m under water surface, from both probe and lab.</li> </ul> 5. Water quality data in the predams from 2010 to 2015 at biweekely basis, from YR3 and YH3 sites. <ul> <li>File name: dat_waterquality_predams_YR3_YH3_2010_2015_biweekly.csv</li> <li>Note: The data is at biweekly basis, measured at various water depth, only from lab.</li> </ul> 6. CTD and BBE probe profile data in the predams from 2010 to 2015 at biweekely basis, from YR3 and YH3 sites. <ul> <li>Note: Data stored in the folder "probe_profiles_predam_YR3_YH3_2010_2015_biweekly". The data is at biweekly basis, measured at various water depths. The measurements include water temperature (Celcius), DO (mg/L), Chl-a (mg/m3), bluegreen, green and diatom (all in Chl-a, mg/m3)</li> </ul>

Harvesting the Value of Data: A Data Architectural Smart Solutions Approach for Enabling Digital Water - Dataset

This database includes the test data used to produce the results for the following article: Harvesting the Value of Data: A Data Architectural Smart Solutions Approach for Enabling Digital Water  by S. Seshan, D. Vries, M. Zandvoort, A. W. C. van der Helm, J. Poinapen, Smart Water - WaterAge Magazine, February 16-23

Data on submerged aquatic vegetation and its water environment in Lake Saint-Pierre, Saint Lawrence River, from 2012 to 2016

This dataset is the result of a large collaborative work lead by the GRIL from 2012 to 2015 on a submerged aquatic vegetation meadow located downstream of two agricultural tributaries (Saint-François and Yamaska rivers) in Lake Saint-Pierre, a fluvial lake of the Saint Lawrence River. The data describe plants (as rake biomass and echosounding) and their environment, including water chemistry, current velocity as well as light, temperature and instantaneous meteo. Only echosounding data are available in 2016 and sediments were collected in 2015.  Data are organized as a relational database and the GRIL_LSP_database.png provides keys and links between tables as well as data format. Data are in the tables mesure_integree, mesure_spatiale, mesure_verticale, plante_biomass_taxon, plante_recolte, plante_in_situ. The other tables are metadata about spatiotemporal locations and reported measures. Additional data (e.g. zooplankton, sediments) should eventually be made available and associated to this overall GRIL dataset.

opencc-by-nc-nd-4.0Jul 2022View details →

Icing Wind Tunnel Measurements of Supercooled Large Droplets Using the 12 mm Total Water Content Cone of the Nevzorov Probe: Measurement Data

This repository contains the measurement data that was used for the publication "Icing Wind Tunnel Measurements of Supercooled Large Droplets Using the 12 mm Total Water Content Cone of the Nevzorov Probe".

Datasets for investigation of the impact of afforestation on the atmospheric water cycle over the Loess Plateau

These datasets are the processed and refined data that support and lead to the described results and allow other readers to assess the conclusions in the paper, entitled “Large-scale Afforestation Enhances Precipitation by Intensifying the Atmospheric Water Cycle over the Chinese Loess Plateau”.

Water and chlorine in the Martian subsurface along the traverse of NASA's Curiosity rover: DAN measurement profiles along the traverse

This dataset contains a water map and a table of water and chlorine content in shallow Martian subsurface derived from the DAN instrument data from a landing site up to MSL sol 3333. DAN is a neutron spectrometer onboard the NASA’s Curiosity rover (see Mitrofanov, I. G., et al., (2012). Dynamic Albedo of Neutrons (DAN) experiment onboard NASA’s Mars Science Laboratory. Space Science Reviews, 170(1–4), 559–582. <a href="https://doi.org/10.1007/s11214-012-9924-y">https://doi.org/10.1007/s11214-012-9924-y</a>). The DAN instrument consists of two separate units: the DAN DE is the detector and electronics block, the DAN PNG is pulsed neutron generator. The DAN DE contains two proportional counters filled with 3He gas for recording thermal and epithermal neutrons up to energy of 100 eV (CTN detector) and epithermal neutrons from 0.4 eV up to 100 eV (CETN detector). DAN provides two types of measurements: active and passive. When DAN DE operates in the passive mode, its detectors record the local neutron background. In the active mode the DAN PNG unit generates short pulses of 14 MeV neutrons, and DAN DE record additional counts of post-pulse emission of moderated neutrons after their interactions with nuclei of shallow subsurface. The results of active and passive DAN measurements along the traverse are assigned to two independent types of pixels: Pixel with Active Data (PAD) and Pixels of Passive Data (PPD). The content of water reported as Water Equivalent Hydrogen (WEH) for both kinds of pixel. The content of absorption equivalent chlorine (AEC) reported only for PAD. Statistical errors are given in each pixel. Method of active data analysis is described in Lisov, D. I., et al., (2018). Data Processing Results for the Active Neutron Measurements by the DAN Instrument on the Curiosity Mars Rover. Astronomy Letters, 44(7), 482–489. <a href="https://doi.org/10.1134/S1063773718070034">https://doi.org/10.1134/S1063773718070034</a>. The "Method of Referencing by Active Data" (MRAD) to analyze passive data was described in Nikiforov, S. Y., et al., (2020). Assessment of water content in Martian subsurface along the traverse of the Curiosity rover based on passive measurements of the DAN instrument. Icarus, 346, 113818. <a href="https://doi.org/10.1016/j.icarus.2020.113818">https://doi.org/10.1016/j.icarus.2020.113818</a>. PPD pixels are presented as squares in the water map, PAD are presented as circles. Table of water and chlorine contains seven values for each pixel: (1) is the successive number of pixel, (2) is a mark of its type, either PAD or PPD, (3) is longitude and (4) is latitude coordinates of the center of the pixel, (5) is the associated member of the MSL stratigraphic column, and (6) is estimated WEH values (wt.%) in PAD or PPD and (7) is estimated AEC value in PAD (wt.%).

Datasets of titrations of mineral water hardness monitored using SERS

These datasets contains the spectral information used in a publication regarding the implementation of complexometric titrations of water hardness monitored using Surface Enhanced Raman Spectroscopy (SERS). The data consists of two csv files with semi-column separators. « MD150 to 155_Master_df_638_corrected_mod_v02.csv » and « MD150 to 155_Master_df_785_corrected_mod_v02.csv » correspond to spectral data acquired under 638 and 785 nm irradiation respectively. The data are organised as row vectors. Each dataset has 432 rows corresponding to 3 water samples (Evian, Volvic, Contrex), 3 replicate titration series + 1 blank titration per batch of NPs, 2 batches of NPs and 18 titration steps per titration series: . The row vectors consist of a first sub-vector of spectral descriptors (identity of spectra, identity and composition of measurement samples and conditions of spectral acquisition), followed by a sub-vector of baseline-substracted spectral intensities. In both datasets, the first 14 columns consists of the spectral descriptors. In the « MD150 to 155_Master_df_638_corrected_mod_v02.csv » dataset, the spectra section consists of 1010 columns which names are the values of the Raman shifts at which the intensities have been recorded. In the « MD150 to 155_Master_df_785_corrected_mod_v02.csv » dataset, the spectra section consists of 1746 columns which names are the values of the Raman shifts at which the intensities have been recorded.

Planktonic Mg/Ca-derived IPWP upper ocean temperature, heat content and sea water δ18O over the last 360 ka

This dataset contains planktonic foraminifera Mg/Ca-derived temperature estimates, age control points and sea water δ18O (δ18Osw) of cores ODP807, KX21-2, MD10-3340, SO18480-3 and MD98-2162 from the Indo-Pacific Warm Pool (IPWP) over the last 360 ka. It also includes reconstructed IPWP stacks of SST, TWT, upper OHC and δ18Osw, and numerical simulated upper OHC, δ18Osw (sea water) and δ18Op (rainfall) from the CESM model and GISS-ModelE2-R model.

Raw Data - Photo-Responsive Doped 3D-Printed Copper Electrodes for Water Splitting: Refractory One-Pot Doping Dramatically Enhances the Performance

The dataset contains raw data that complements the article: Photo-Responsive Doped 3D-Printed Copper Electrodes for Water Splitting: Refractory One-Pot Doping Dramatically Enhances the Performance Christian Iffelsberger, Daniel Rojas, and Martin Pumera* https://doi.org/10.1021/acs.jpcc.1c10686 Related to the MSCA Project: 888797 LoCatSpot

opencc-by-4.0Dec 2021View details →

Supporting data of: Hydrography and food distribution during a tidal cycle above a cold-water coral mound

This file contains the raw data and data analyses scripts to: Hydrography and food distribution during a tidal cycle above a cold-water coral mound Evert de Froe, Sandra R. Maier, Henriette G. Horn, George A. Wolff, Sabena Blackbird, Christian Mohn, Mads Schultz, Anna-Selma van der Kaaden, Chiu H. Cheng, Evi Wubben, Britt van Haastregt, Eva Friis Moller, Marc Lavaleye, Karline Soetaert, Gert-Jan Reichart, Dick van Oevelen. Deep Sea Research Part I: Oceanographic Research Papers, 2022, ISSN 0967-0637, https://doi.org/10.1016/j.dsr.2022.103854. Abstract: Cold-water corals (CWCs) are important ecosystem engineers in the deep sea that provide habitat for numerous species and can form large coral mounds. These mounds influence surrounding currents and induce distinct hydrodynamic features, such as internal waves and episodic downwelling events that accelerate transport of organic matter towards the mounds, supplying the corals with food. To date, research on organic matter distribution at coral mounds has focussed either on seasonal timescales or has provided single point snapshots. Data on food distribution at the timescale of a diurnal tidal cycle is currently limited. Here, we integrate physical, biogeochemical, and biological data throughout the water column and along a transect on the south-eastern slope of Rockall Bank, Northeast Atlantic Ocean. This transect consisted of 24-hour sampling stations at four locations: Bank, Upper slope, Lower slope, and the Oreo coral mound. We investigated how the organic matter distribution in the water column along the transect is affected by tidal activity. Repeated CTD casts indicated that the water column above Oreo mound was more dynamic than above other stations in multiple ways. First, the bottom water showed high variability in physical parameters and nutrient concentrations, possibly due to the interaction of the tide with the mound topography. Second, in the surface water a diurnal tidal wave replenished nutrients in the photic zone, supporting new primary production.  Third, above the coral mound an internal wave (200 m amplitude) was recorded at 400 m depth after the turning of the barotropic tide. After this wave passed, high quality organic matter was recorded in bottom waters on the mound coinciding with shallow water physical characteristics such as high oxygen concentration and high temperature. Trophic markers in the benthic community suggest feeding on a variety of food sources, including phytodetritus and zooplankton. We suggest that there are three transport mechanisms that supply food to the CWC ecosystem. First, small phytodetritus particles are transported downwards to the seafloor by advection from internal waves, supplying high quality organic matter to the CWC reef community. Second, the shoaling of deeper nutrient-rich water into the surface water layer above the coral mound could stimulate diatom growth, which form fast-sinking aggregates. Third, evidence from lipid analysis indicates that zooplankton faecal pellets also enhance supply of organic matter to the reef communities. This study is the first to report organic matter quality and composition over a tidal cycle at a coral mound and provides evidence that fresh high-quality organic matter is transported towards a coral reef during a tidal cycle.

opencc-by-4.0Sep 2022View details →

Data set for "The annual-hydrogen-yield-climatic-response ratio: evaluating the real-life performance of integrated solar water splitting devices"

This data set was used for the modelling in the article M. Kölbach, O. Höhn, K. Rehfeld,  M. Finkbeiner,  J. Barry, and M. M. May, “The annual-hydrogen-yield-climatic-response ratio: evaluating the real-life performance of integrated solar water splitting devices”, Sustainable Energy Fuels, 2022, 6, 4062-4074, <a href="https://doi.org/10.1039/D2SE00561A">https://doi.org/10.1039/D2SE00561A</a>. It contains the External Quantum Efficiency (EQE) data of a wafer-bonded AlGaAs//Si dual-junction solar cell for several top absorber compositions, angle of incidences, and temperatures modelled using the OPTOS formalism (see <a href="https://doi.org/10.1364/OE.24.0A1083">https://doi.org/10.1364/OE.24.0A1083</a> , <a href="https://doi.org/10.1364/OE.23.0A1720">https://doi.org/10.1364/OE.23.0A1720</a> , and <a href="http://doi.org/10.1109/JPHOTOV.2021.3064562"> https://doi.org/10.1109/JPHOTOV.2021.3064562</a>). Moreover, the data set includes hourly resolved direct and diffuse solar spectra for a location near the Neumayer station in Antarctica (-70.67°/-8.28°) that were modelled using the libRadtran software package for the year 2021 (see  <a href="https://doi.org/10.1140/epjconf/e2009-00912-1">https://doi.org/10.1140/epjconf/e2009-00912-1</a> and <a href="http://doi.org/10.5194/acp-5-1855-2005">https://doi.org/10.5194/acp-5-1855-2005</a>). The modelling of the spectra was performed employing the predefined “subarctic summer” and  “subarctic winter” atmosphere datasets assuming a tilt angle of 70° and 1-axis tracking. For the sake of simplicity, no cloud cover was assumed over the course of the whole year. Finally, the input files required for modelling the climatic response of solar water splitting devices for the selected location in Antarctica using the “climatic_response_function” of YaSoFo (see <a href="http://doi.org/10.5281/zenodo.5257492">https://doi.org/10.5281/zenodo.5257492</a> for an extended example) are included in the data set.

Wastewater Treatment Plant Inflow Rate, Network Water Levels and Rain Rate for Koeln Weiden, Germany

wtp_network_rain.csv contains time series data of measured wastewater treatment plant inflow rates, water levels from multiple locations within the wastewater sewer network and rain rate measured from a rain recorder located at the wastewater treatment plant.