Claro et al. (2026) Near-Future Climate Change Impacts on Sado River (Southern Portugal) Flow Rates Using CMIP6-HSPF Modelling

Identification

• Journal: Water
• Year: 2026
• Date: 2026-02-07
• Authors: André Claro, André R. Fonseca, António Fernandes, Christoph Menz, Carina Almeida, Hélder Fraga, João A. Santos
• DOI: 10.3390/w18040442

Research Groups

• Centre for the Research and Technology of Agro-Environmental and Biological Sciences (CITAB), University of Trás-os-Montes e Alto Douro (UTAD), Portugal
• Institute for Innovation, Capacity Building and Sustainability of Agri-Food Production (Inov4Agro), Portugal
• Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Germany
• Institute of Environmental Science and Geography, University of Potsdam, Germany

Short Summary

This study assesses the near-future (2041–2060) climate change impacts on Sado River flow rates in Southern Portugal using CMIP6-HSPF modeling, projecting significant decreases in flow rates and riverine water volume, particularly under higher emission scenarios, due to increased temperatures and reduced autumn/spring precipitation.

Objective

• To project climate change impacts on near-future Sado River flow rates and surface-water volumes in the Sado River Basin (SRB) by performing hydrological model simulations using the latest generation of future-climate datasets and socioeconomic scenarios.

Study Configuration

• Spatial Scale: Sado River Basin (SRB), Southwest Portugal (6529 km²). Climate data downscaled to 1 km spatial resolution, then resampled to 10 km for bias adjustment. HSPF model delineated into 17 subbasins.
• Temporal Scale:
  • Reference period: 1995–2014 (20 years)
  • Near-future period: 2041–2060 (20 years)
  • Model warm-up periods: 1994 and 2040 (1 year each)
  • Calibration/Validation: 2002, 2003, 2018, 2021 (within 2001–2022 period)

Methodology and Data

• Models used:
  • Hydrological Simulation Program—FORTRAN (HSPF)
  • General Circulation Models (GCMs) from CMIP6 ensemble (9 models: CanESM5, CNRM-CM6-1, CNRM-ESM2-1, EC-Earth3, IPSL-CM6A-LR, MIROC6, MPI-ESM1-2-HR, MRI-ESM2-0, UKESM1-0-LL)
  • Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3b) protocol for downscaling and bias adjustment
  • Climatologies at High resolution for the Earth’s Land Surface Areas (CHELSA) approach for further downscaling
  • Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) framework
• Data sources:
  • CMIP6 GCM ensemble projections (SSP1-2.6, SSP3-7.0, SSP5-8.5 scenarios)
  • W5E5 reanalysis dataset
  • ERA5-Iberia (10 km resolution ERA5-Land reanalysis, bias-adjusted with Iberia01 observed weather data)
  • European Digital Elevation Model version 1.1 (EU-DEM) (25 m resolution)
  • Harmonised World Soil Database v2.0 (HWSD)
  • Portuguese General-Directorate of Territory (land use data)
  • Portuguese Hydrological Resources National Information System (SNIRH) (observed flow rates, meteorological station data)
  • Instituto Português do Mar e da Atmosfera (IPMA) (climatological normals)

Main Results

• Sado River flow rates (FRs) are projected to decrease across all seasons and scenarios (2041–2060 vs. 1995–2014), with the most significant reductions under SSP3-7.0.
• Yearly accumulated riverine water volume is projected to decrease by 13% (SSP1-2.6), 29% (SSP3-7.0), and 33% (SSP5-8.5) compared to the historical period (1192 hm³).
• The fulfillment of yearly surface water needs could be delayed by up to 22 days under SSP3-7.0.
• Riverine water surplus (primarily during December–January–February and March–April–May) is expected to decrease, with a 38% drop under SSP3-7.0.
• Summertime (June–July–August) and autumn (September–October–November) riverine water deficit is projected to increase by up to 31% under SSP3-7.0, and the period of river dryness in late summer/early autumn is expected to lengthen.
• Overall temperature increases are projected, ranging from 0.8 °C (minimum temperature, SSP1-2.6) to 2.5 °C (maximum temperature, SSP3-7.0), with higher increases in northern and northeastern areas.
• Annual precipitation is projected to decrease under all SSPs, with changes ranging from -30 to -110 mm/year, most notably under SSP3-7.0. Seasonal precipitation decreases are expected, with autumn and spring showing the highest reductions (up to -60 mm/season).
• The winter (December–January–February) precipitation range is projected to increase under SSP1-2.6 and SSP3-7.0, suggesting a concentration of yearly precipitation in winter months. The percentage of total precipitation from heavy events (P95TOT) is expected to increase by 1% to 6%.

Contributions

• First study to assess climate change impacts on Sado River flow rates using bias-adjusted and downscaled CMIP6 ensemble projections (ISIMIP3b-Sado) as input for hydrological simulations of the entire Sado River Basin.
• Developed an innovative, highly spatially resolved (1 km) climate dataset for southwest Portugal based on state-of-the-art global climate ensemble projections.
• Provides critical near-future (2041–2060) projections for agricultural stakeholders and decision-makers in the Sado region to inform water management strategies.
• Validates and reinforces previous findings on water availability reductions in the Sado River Basin and demonstrates coherence with projections for other Mediterranean basins.

Funding

• FCT—Portuguese Foundation for Science and Technology (projects UID/04033/2025; LA/P/0126/2020)
• MIT Portugal Partnership 2030 (MPP2030-FCT), grant number PRT/BD/154652/2023
• European Regional Development Fund (ERDF) through the Northern Regional Programme 2021-2027 [NORTE2030] (project STrengthS4WineChaiN NORTE2030-FEDER-01786100, project ReFOOD4North NORTE2030-FEDER-02654300)
• Horizon Europe (project LivingSoiLL GA 101157502)

Citation

@article{Claro2026NearFuture,
  author = {Claro, André and Fonseca, André R. and Fernandes, António and Menz, Christoph and Almeida, Carina and Fraga, Hélder and Santos, João A.},
  title = {Near-Future Climate Change Impacts on Sado River (Southern Portugal) Flow Rates Using CMIP6-HSPF Modelling},
  journal = {Water},
  year = {2026},
  doi = {10.3390/w18040442},
  url = {https://doi.org/10.3390/w18040442}
}