Flood durations and potential natural vegetation distribution on the floodplains of River Rhine and River Elbe, Germany
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| Format: | Dataset Open Access |
| Langue: | en |
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PANGAEA
2022
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| _version_ | 1867172343946674176 |
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| author | Weber, Arnd |
| author_facet | Weber, Arnd |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | Floodplains are morphologically highly heterogeneous environments with dynamically in- and decreasing water levels and flows. Strong environmental filtering through floodplain inundation creates favorable conditions for highly specialized organisms leading to high biodiversity and conservation value of floodplains. With hyd1d and hydflood we provide two R packages for simplified hydrologic modelling in two large central European floodplains – along River Rhine and River Elbe in Germany. We applied the R function hydflood::flood3 on both active floodplains covering a timespan from 1960 to 2021 and computed annual flood durations for 61 years. For two timespans (1960-1989 and 1990-2019) we aggregated the annual flood durations statistically by mean and standard deviation. Finally, we predicted potentially natural vegetation based on the mean flood duration from 1990 to 2019 and a simple reclassification model implemented in the R function hydflood::classifyToPNV. The datasets consist of 67 different raster layers (62 annual layers, 4 statistically aggregated layers and 1 layer of potential natural vegetation). They are tiled into 40 tiles along River Rhine and 49 tiles along River Elbe, resulting in a total of 5963 individual raster datasets stored in GeoTiff file format. All raster have a spatial resolution of 1 m and are stored in the coordinate reference systems ETRS 1989 UTM Zone 32 N (EPSG: 25832) for River Rhine and ETRS 1989 UTM Zone 33 N (EPSG: 25833) for River Elbe. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_948042 |
| institution | PANGAEA |
| language | en |
| publishDate | 2022 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | Flood durations and potential natural vegetation distribution on the floodplains of River Rhine and River Elbe, Germany Weber, Arnd Code (EPSG); DATE/TIME; e001_SCHOENA1; e002_SCHOENA2; e003_PIRNA1; e004_PIRNA2; e005_DRESDEN1; e006_DRESDEN2; e007_MEISSEN1; e008_MEISSEN2; e009_RIESA1; e010_RIESA2; e011_MUEHLBERG1; e012_MUEHLBERG2; e013_TORGAU1; e014_TORGAU2; e015_PRETZSCH; e016_ELSTER; e017_WITTENBERG; e018_COSWIG; e019_VOCKERODE; e020_DESSAU; e021_AKEN1; e022_AKEN2; e023_BARBY1; e024_BARBY2; e025_SCHOENEBECK1; e026_SCHOENEBECK2; e027_MAGDEBURG; e028_MAGDEBURG; e029_NIEGRIPP; e030_ROGAETZ1; e031_ROGAETZ2; e032_ROGAETZ3; e033_TANGERMUENDE; e034_STORKAU; e035_SANDAU1; e036_SANDAU2; e037_SCHARLEUK; e038_WITTENBERGE; e039_MUEGGENDORF; e040_SCHNACKENBURG; e041_LENZEN; e042_GORLEBEN; e043_DOEMITZ; e044_HITZACKER; e045_NEU_DARCHAU; e046_BLECKEDE; e047_BOIZENBURG; e048_HOHNSTORF; e049_ARTLENBURG; ElBiota; ElBiota - Lateral connectivity and biodiversity of the Elbe floodplains; Event label; Germany; Latitude of event; Latitude of event 2; Longitude of event; Longitude of event 2; Model; Model output, GeoTIFF format; Model output, GeoTIFF format (File Size); Model output, GeoTIFF format (MD5 Hash); r001_IFFEZHEIM; r002_PLITTERSDORF1; r003_PLITTERSDORF2; r004_PLITTERSDORF3; r005_MAXAU1; r006_MAXAU2; r007_MAXAU3; r008_PHILIPPSBURG; r009_SPEYER; r010_MANNHEIM; r011_WORMS1; r012_WORMS2; r013_WORMS3; r014_NIERSTEIN; r015_MAINZ; r016_OESTRICH; r017_BINGEN; r018_KAUB; r019_SANKT; r020_BOPPARD; r021_KOBLENZ1; r022_KOBLENZ2; r023_ANDERNACH1; r024_ANDERNACH2; r025_OBERWINTER; r026_BONN1; r027_BONN2; r028_KOELN1; r029_KOELN2; r030_KOELN3; r031_KOELN4; r032_DUESSELDORF1; r033_DUESSELDORF2; r034_DUISBURG; r035_DUISBURG; r036_WESEL1; r037_WESEL2; r038_REES1; r039_REES2; r040_REES3; Type; UTM Easting, Universal Transverse Mercator; UTM Northing, Universal Transverse Mercator Floodplains are morphologically highly heterogeneous environments with dynamically in- and decreasing water levels and flows. Strong environmental filtering through floodplain inundation creates favorable conditions for highly specialized organisms leading to high biodiversity and conservation value of floodplains. With hyd1d and hydflood we provide two R packages for simplified hydrologic modelling in two large central European floodplains – along River Rhine and River Elbe in Germany. We applied the R function hydflood::flood3 on both active floodplains covering a timespan from 1960 to 2021 and computed annual flood durations for 61 years. For two timespans (1960-1989 and 1990-2019) we aggregated the annual flood durations statistically by mean and standard deviation. Finally, we predicted potentially natural vegetation based on the mean flood duration from 1990 to 2019 and a simple reclassification model implemented in the R function hydflood::classifyToPNV. The datasets consist of 67 different raster layers (62 annual layers, 4 statistically aggregated layers and 1 layer of potential natural vegetation). They are tiled into 40 tiles along River Rhine and 49 tiles along River Elbe, resulting in a total of 5963 individual raster datasets stored in GeoTiff file format. All raster have a spatial resolution of 1 m and are stored in the coordinate reference systems ETRS 1989 UTM Zone 32 N (EPSG: 25832) for River Rhine and ETRS 1989 UTM Zone 33 N (EPSG: 25833) for River Elbe. |
| title | Flood durations and potential natural vegetation distribution on the floodplains of River Rhine and River Elbe, Germany |
| topic | Code (EPSG); DATE/TIME; e001_SCHOENA1; e002_SCHOENA2; e003_PIRNA1; e004_PIRNA2; e005_DRESDEN1; e006_DRESDEN2; e007_MEISSEN1; e008_MEISSEN2; e009_RIESA1; e010_RIESA2; e011_MUEHLBERG1; e012_MUEHLBERG2; e013_TORGAU1; e014_TORGAU2; e015_PRETZSCH; e016_ELSTER; e017_WITTENBERG; e018_COSWIG; e019_VOCKERODE; e020_DESSAU; e021_AKEN1; e022_AKEN2; e023_BARBY1; e024_BARBY2; e025_SCHOENEBECK1; e026_SCHOENEBECK2; e027_MAGDEBURG; e028_MAGDEBURG; e029_NIEGRIPP; e030_ROGAETZ1; e031_ROGAETZ2; e032_ROGAETZ3; e033_TANGERMUENDE; e034_STORKAU; e035_SANDAU1; e036_SANDAU2; e037_SCHARLEUK; e038_WITTENBERGE; e039_MUEGGENDORF; e040_SCHNACKENBURG; e041_LENZEN; e042_GORLEBEN; e043_DOEMITZ; e044_HITZACKER; e045_NEU_DARCHAU; e046_BLECKEDE; e047_BOIZENBURG; e048_HOHNSTORF; e049_ARTLENBURG; ElBiota; ElBiota - Lateral connectivity and biodiversity of the Elbe floodplains; Event label; Germany; Latitude of event; Latitude of event 2; Longitude of event; Longitude of event 2; Model; Model output, GeoTIFF format; Model output, GeoTIFF format (File Size); Model output, GeoTIFF format (MD5 Hash); r001_IFFEZHEIM; r002_PLITTERSDORF1; r003_PLITTERSDORF2; r004_PLITTERSDORF3; r005_MAXAU1; r006_MAXAU2; r007_MAXAU3; r008_PHILIPPSBURG; r009_SPEYER; r010_MANNHEIM; r011_WORMS1; r012_WORMS2; r013_WORMS3; r014_NIERSTEIN; r015_MAINZ; r016_OESTRICH; r017_BINGEN; r018_KAUB; r019_SANKT; r020_BOPPARD; r021_KOBLENZ1; r022_KOBLENZ2; r023_ANDERNACH1; r024_ANDERNACH2; r025_OBERWINTER; r026_BONN1; r027_BONN2; r028_KOELN1; r029_KOELN2; r030_KOELN3; r031_KOELN4; r032_DUESSELDORF1; r033_DUESSELDORF2; r034_DUISBURG; r035_DUISBURG; r036_WESEL1; r037_WESEL2; r038_REES1; r039_REES2; r040_REES3; Type; UTM Easting, Universal Transverse Mercator; UTM Northing, Universal Transverse Mercator |
| url | https://doi.org/10.1594/PANGAEA.948042 |