Wu et al. (2025) Assessing blue-green infrastructures for urban flood and drought mitigation under changing climate scenarios

Identification

• Journal: Journal of Hydrology Regional Studies
• Year: 2025
• Date: 2025-09-27
• Authors: Xuan Wu, Patrick Willems
• DOI: 10.1016/j.ejrh.2025.102798

Research Groups

• KU Leuven, Department of Civil Engineering, Belgium

Short Summary

This study evaluates the effectiveness of Blue-Green Infrastructures (BGIs) like green roofs, rain tanks, and permeable pavements in mitigating urban floods and droughts under present and future climate scenarios in a Belgian university campus. It found that BGIs significantly reduce discharge volumes and peak flows while substantially enhancing groundwater recharge, demonstrating their potential as a climate change adaptation solution.

Objective

• To integrate a fine-scale conceptual surface water balance (SWB) model with the MODFLOW groundwater model to simulate both surface runoff and groundwater levels in a small urban area.
• To assess the impact of BGIs on surface runoff and groundwater systems under both present and future climate scenarios using high-resolution, long-term hydrological simulations and extreme value analysis.

Study Configuration

• Spatial Scale: Arenberg III campus of KU Leuven and its neighboring area in Belgium, covering 0.64 km², with a horizontal discretization of 2.5 m × 2.5 m grid cells.
• Temporal Scale: Present climate conditions simulated for 30 years (1990–2019); future climate conditions simulated for the horizon 2100 based on perturbed 30-year data. Model calibration and validation used data from 2015–2022.

Methodology and Data

• Models used:
  • Fine-scale conceptual Surface Water Balance (SWB) model (developed in Python).
  • MODFLOW-NWT (groundwater model).
  • Conceptual rainfall-runoff model (for river water level estimation).
  • Continuous Soil Conservation Service Curve Number (SCS-CN) method.
  • Linear reservoir function for runoff routing.
  • Flopy (Python package for MODFLOW-NWT).
• Data sources:
  • Meteorological data (rainfall, potential evapotranspiration): Waterinfo, Royal Meteorological Institute of Belgium.
  • Catchment characteristics (soil map, Digital Elevation Model, land use): Geopunt, KU Leuven Technical Services.
  • River water levels: Waterinfo.
  • Groundwater level observations: Databank Ondergrond Vlaanderen (DOV).
  • Aquifer information and parameters: Regional groundwater model by De Watergroep.
  • Future climate projections: Ensemble of 30 EURO-CORDEX regional climate model runs (CMIP5 Representative Concentration Pathways), statistically downscaled using the quantile perturbation method.

Main Results

• BGIs significantly reduce monthly average total discharge volume and lower peak discharge rates across all climate scenarios.
• BGIs substantially enhance groundwater recharge, leading to increases in both monthly average and low groundwater levels under various climate conditions.
• Under present climate conditions, BGIs result in an approximate 0.2 m increase in monthly average groundwater levels.
• BGIs effectively prevent overflow problems, with the maximum discharge capacity reached only under the most severe climate conditions associated with a 30-year return period, compared to the current system exceeding it at approximately a 2.5-year return period under certain climate change projections.
• Future climate projections for Belgium indicate a trend towards wetter conditions in winter (increased runoff, enhanced groundwater recharge) and drier summer periods (decreased runoff, groundwater depletion).
• The effectiveness of BGIs in mitigating peak discharges declines under future wet climate scenarios and long return periods, and their impact on peak runoff reduction becomes more sensitive to climate variability under extreme conditions.
• Low groundwater levels in the BGIs scenario are more sensitive to climate variations, and their effectiveness in increasing groundwater levels appears to decline under extremely dry conditions, though they generally remain higher than in the current campus scenario.

Contributions

• Developed and applied a novel loosely coupled fine-scale SWB-MODFLOW model that balances computational efficiency with flexible integration of various BGIs and local datasets.
• Advanced the understanding of BGI performance by comprehensively capturing both surface runoff dynamics and subsurface groundwater levels at high spatial and temporal resolutions, addressing a gap in previous research primarily focused on surface runoff.
• Provided a combined evaluation of BGIs' effectiveness in mitigating both urban flood and drought risks under an ensemble of 30 future climate change scenarios.
• Offered critical guidance for urban planners and policymakers by illustrating how local-scale BGI interventions can inform the development of scalable solutions for sustainable urban development and enhanced regional water management in response to climate change.

Funding

• KU Leuven (CELSA/21/014 & Internal funding Technical Services)
• CSC Scholarship No. 202107650049
• Province of Vlaams-Brabant (Slimme Regio call: project RainBrain)

Citation

@article{Wu2025Assessing,
  author = {Wu, Xuan and Willems, Patrick},
  title = {Assessing blue-green infrastructures for urban flood and drought mitigation under changing climate scenarios},
  journal = {Journal of Hydrology Regional Studies},
  year = {2025},
  doi = {10.1016/j.ejrh.2025.102798},
  url = {https://doi.org/10.1016/j.ejrh.2025.102798}
}