Runoff for Russia (RFR v1.0): The Large-Sample Dataset of Simulated Runoff and Its Characteristics
Global warming challenges communities worldwide to develop new adaptation strategies that are required to be based on reliable data. As a vital component of life, river runoff comes into particular focus as a determining and limiting factor of water-related hazard assessment. Here, we present a data...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Data |
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| Online Access: | https://www.mdpi.com/2306-5729/8/2/31 |
| _version_ | 1797621490557911040 |
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| author | Georgy Ayzel |
| author_facet | Georgy Ayzel |
| author_sort | Georgy Ayzel |
| collection | DOAJ |
| description | Global warming challenges communities worldwide to develop new adaptation strategies that are required to be based on reliable data. As a vital component of life, river runoff comes into particular focus as a determining and limiting factor of water-related hazard assessment. Here, we present a dataset that makes it possible to estimate the influence of projected climate change on runoff and its characteristics. We utilize the HBV (in Swedish, Hydrologiska Byråns Vattenbalansavdelning) hydrological model and drive it with the ISIMIP (The Inter-Sectoral Impact Model Intercomparison Project) meteorological forcing data for both historical (1979–2016) and projected (2017–2099) periods to simulate runoff and the respective hydrological states and variables, i.e., state of the soil reservoir, snow water equivalent, and predicted amount of melted water, for 425 river basins across Russia. For the projected period, the bias-corrected outputs from four General Circulation Models (GCM) under three Representative Concentration Pathways (RCPs) are used, making it possible to assess the uncertainty of future projections. The simulated runoff formed the basis for calculating its characteristics (191 in total), representing the properties of water regime dynamics. The presented dataset also comprises two auxiliary parts to ensure the seamless assessment of inter-connected hydro-meteorological variables and characteristics: (1) meteorological forcing data and its characteristics and (2) geospatial data. The straightforward use of the presented dataset makes it possible for many interested parties to identify and further communicate water-related climate change issues in Russia on a national scale. |
| first_indexed | 2024-03-11T08:57:41Z |
| format | Article |
| id | doaj.art-29278b41aeec4c209fba5a3b5ae1148b |
| institution | Directory Open Access Journal |
| issn | 2306-5729 |
| language | English |
| last_indexed | 2024-03-11T08:57:41Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Data |
| spelling | doaj.art-29278b41aeec4c209fba5a3b5ae1148b2023-11-16T19:58:48ZengMDPI AGData2306-57292023-01-01823110.3390/data8020031Runoff for Russia (RFR v1.0): The Large-Sample Dataset of Simulated Runoff and Its CharacteristicsGeorgy Ayzel0State Hydrological Institute, 199004 Saint Petersburg, RussiaGlobal warming challenges communities worldwide to develop new adaptation strategies that are required to be based on reliable data. As a vital component of life, river runoff comes into particular focus as a determining and limiting factor of water-related hazard assessment. Here, we present a dataset that makes it possible to estimate the influence of projected climate change on runoff and its characteristics. We utilize the HBV (in Swedish, Hydrologiska Byråns Vattenbalansavdelning) hydrological model and drive it with the ISIMIP (The Inter-Sectoral Impact Model Intercomparison Project) meteorological forcing data for both historical (1979–2016) and projected (2017–2099) periods to simulate runoff and the respective hydrological states and variables, i.e., state of the soil reservoir, snow water equivalent, and predicted amount of melted water, for 425 river basins across Russia. For the projected period, the bias-corrected outputs from four General Circulation Models (GCM) under three Representative Concentration Pathways (RCPs) are used, making it possible to assess the uncertainty of future projections. The simulated runoff formed the basis for calculating its characteristics (191 in total), representing the properties of water regime dynamics. The presented dataset also comprises two auxiliary parts to ensure the seamless assessment of inter-connected hydro-meteorological variables and characteristics: (1) meteorological forcing data and its characteristics and (2) geospatial data. The straightforward use of the presented dataset makes it possible for many interested parties to identify and further communicate water-related climate change issues in Russia on a national scale.https://www.mdpi.com/2306-5729/8/2/31dischargefloodwaterclimate changeglobal warming |
| spellingShingle | Georgy Ayzel Runoff for Russia (RFR v1.0): The Large-Sample Dataset of Simulated Runoff and Its Characteristics Data discharge flood water climate change global warming |
| title | Runoff for Russia (RFR v1.0): The Large-Sample Dataset of Simulated Runoff and Its Characteristics |
| title_full | Runoff for Russia (RFR v1.0): The Large-Sample Dataset of Simulated Runoff and Its Characteristics |
| title_fullStr | Runoff for Russia (RFR v1.0): The Large-Sample Dataset of Simulated Runoff and Its Characteristics |
| title_full_unstemmed | Runoff for Russia (RFR v1.0): The Large-Sample Dataset of Simulated Runoff and Its Characteristics |
| title_short | Runoff for Russia (RFR v1.0): The Large-Sample Dataset of Simulated Runoff and Its Characteristics |
| title_sort | runoff for russia rfr v1 0 the large sample dataset of simulated runoff and its characteristics |
| topic | discharge flood water climate change global warming |
| url | https://www.mdpi.com/2306-5729/8/2/31 |
| work_keys_str_mv | AT georgyayzel runoffforrussiarfrv10thelargesampledatasetofsimulatedrunoffanditscharacteristics |