DOI: 10.6084/m9.figshare.15178107.v5
title: A 500-year runoff reconstruction for European catchments

description: Runoff is an important hydrological variable for determining past hydrological pattern and extremities but the hydrological variables are available for short time period. This paper reconstructs runoff series from European catchment since 1500 AD. The study used basin average precipitation and temperature that were estimated from the reconstructed forcing by averaging the grid cells covering the specific catchment boundary. Similarly, we calculated the average catchment PDSI from the OWDA, and selected the raw proxy data from inside the catchment or within a 100km buffer around the catchment.<br><br><br>** (1) Content *<br>At each folder, files are saved with the station river names, which correspond to the station identifiers (GRDCno) listed below.<br> GRDCno station_river1 6123100 Montjean_Loire2 6123300 Blois_Loire3 6335020 Rees_Rhine4 6335060 Koeln_Rhine5 6335301 Neuerhafen_Main6 6335500 Weurzburg_Main7 6337200 Intschede_Wesser8 6337400 HannMuenden_Wesser9 6337514 Bodenwerder_Wesser10 6340120 Dresden_Elbe11 6343100 Wasserburg_Inn12 6742200 Orsova_Danube13 6935051 Basel Rheinhalle_Rhine14 6935052 Basel Schifflaende_Rhine<br><br><br><br>** (1.1) Folder "Input_data"**<br>Each files contains such fields<br><br>1 GRDCno GRDC station ID2 station_river Station name corresponding to river ( e.g Blois_Loire)3 long Longitude of station4 lat Latitude of station5 time Time period between 1500 to 2000 6 pdsi Average of scPDSI from Old World drought Atlas across each basin7 ljun_(no) Columns were extracted precipitation and temperature related European proxies from Ljungqvist et al., 2016. Twenty precipitation and seventeen temperature proxies were found inside Europe. More information are available at the Excel sheet ****proxies metadata.csv********** The number of proxy columns varies depending on the catchment within a 100-kilometer buffer zone. "NA" character was used to represent missing value.<br>8 gPR Average of Gridded seasonal precipitation (mm) at individual catchment 9 gTAS Average of Gridded seasonal temperature (degree C) at individual catchment 10 R Observed runoff (mm) from Global runoff dataset (GRDC). NA represent that the values are missing at some years<br><br><br><br>** (1.2) Folder "Runoff_recons"**<br><br>Each .csv contain runoff reconstruction for one of 14 catchments 1 "Year" column indicate the year between 1500 and 2000. 2 "Simulated Runoff" represent the reconstructed runoff (in mm) with the best model 3 "Observed Runoff" includes the observed GRDC runoff (in mm) series The .rds files with the same structure are available for R users (to be read with the readRDS function). Runoff reconstructions are developed using the input data set (precipitation, temperature, proxies, and drought index ( scPDSI) ) as referenced below. While , comparative data were derived from the Global Historical Climatology Network (GHCN) and the global runoff data (GRDC) center. <br> ** (1.3) Folder "Shape_Catchments"** Station boundaries are available in the next folder 'Shape_Catchments'<br>* STRUCTURE:Each GRDC station is associated with a catchment boundary; these files were named as GRDCnos.Each catchment is represented by four separate files with the same name (e.g. station_river) but different file extensions:<br>(1) '.shp': provides geometry of the catchment polygon. (2) '.shx': provides shape index position.(3) '.dbf': provides attribute table assoaciated to a specific catchment.(4) '.prj': provides the metadata associated with the shapefiles coordinate and projection system<br><br><br><br>***************proxies_metadata.csv*******************There are two.csv files here (tem_proxies and precip_proxies) that provide related information about selected proxies used in our analysis (e.g longitute,latitute, proxy, season, ID, references, name)<br><br><br>