Fernández-Nóvoa, Diego · Barreiro-Fonta, Helena · Gonzalez-Cao, Jose · et al.
hybrid · semantic + lexical · 4 datasets ranked · 1.23s
Fernández-Nóvoa, Diego · Barreiro-Fonta, Helena · Gonzalez-Cao, Jose · et al.
This dataset provides a high-resolution climate database developed to support the assessment of climate change impacts on the hydrological regime of the international Miño-Limia river basins. The database contains two key atmospheric variables governing the hydrological cycle: precipitation and 2 m air temperature. The dataset includes historical climate conditions for the period 1985-2014 and future climate projections for 2020-2100 under the SSP2-4.5 and SSP5-8.5 scenarios. The atmospheric fields were obtained from dynamically downscaled CMIP6 climate simulations using the Weather Research and Forecasting (WRF) model. The WRF configuration, including model domains and physical parameterizations, follows the methodology described in the associated studies: Forecasting offshore wind energy in Atlantic Europe using CMIP6 dynamically downscaled data and Neural network approach for modeling future natural river flows: Assessing climate change impacts on the Tagus River . For the development of this database, precipitation and temperature fields were extracted at the grid points covering the Miño-Limia river basins, providing a spatially consistent climate dataset specifically tailored for hydrological and climate change impact assessments in the study area. The dataset is provided in NetCDF format, with a spatial resolution of 0.1° × 0.1° and a daily temporal resolution. This database was developed within the framework of the RISC_PLUS project (0031_RISC_PLUS_6_E), co-funded by the European Regional Development Fund (ERDF) through the Interreg VI-A Spain-Portugal Cross-Border Cooperation Programme (POCTEP) 2021-2027. The dataset supports the assessment of future climate and hydrological conditions in the international Miño-Limia river basins, contributing to the analysis of climate change impacts on water availability, droughts, floods, and other hydrological extremes. The computational resources required for generating and processing the climate simulations were provided by the Galician Supercomputing Centre (CESGA). Users of this dataset are encouraged to cite both this Zenodo repository and the associated publications describing the atmospheric downscaling methodology and its application to climate change impact assessment.
Cahyarini, Sri Yudawati · Zinke, Jens · Watanabe, Takaaki K. · et al.
1 files · 132 KB · xlsxdeclared
The data content: coral proxy data d18O, recconstructed d18O seawater and also historical SSS data, runoff data, measured rainfall data, which are data paper accepted in Journal Geophysical Research Ocean -date 07-July-2026
Lumbroso, Darren · Davison, Mark
1 files · 6.5 MB · xlsxdeclared
A process-based monthly water balance model was developed to simulate changes in Caspian Sea water levels under both historical and future climate conditions. The model represents the Caspian Sea and the connected Kara-Bogaz-Göl (KBG) lagoon as coupled storage elements linked by a hydraulic exchange term. At each monthly time step, river inflows, direct precipitation, evaporation, groundwater and residual exchange fluxes, Volga Delta losses, and KBG exchange are converted into volume changes. The updated storage volume is then translated into water level using interpolated hypsometric area-volume-elevation relationships. The model incorporates historical river flow data from the basins draining into the Caspian Sea, together with time series of precipitation and evaporation.
Lumbroso, Darren · Davison, Mark
2 files · 27 MB · xlsxdeclared
The hydrological model of the Volga River basin runs on a monthly time step. For each month, net precipitation is calculated as precipitation minus evaporation and converted to runoff using a delay function that includes contributions from the current month and up to four antecedent months. This formulation represents the aggregate effects of snow and ice storage, soil retention, groundwater contribution and river travel time using a small number of calibrated parameters. Runoff was separated into a rapid surface component, representing 80% of runoff, and a delayed groundwater component, representing 20%. The model was used to provide inflows to a Caspian Sea water balance model. Flows in the Volga River Basin are regulated by the Volga-Kama hydropower cascade which comprises 12 large dams and reservoirs constructed between the 1930s and 1980s The hydrological routing model of the River Volga can be used to route flow through the Volga-Kama hydropower reservoir cascade using a monthly flow routing model that represents constant minimum releases for hydropower and environmental flows, and spillway discharge when storage capacity is exceeded. Reservoir inflows were estimated based on the contributing catchment areas and simulated runoff volumes.