Improving surface-subsurface water budgeting using high resolution satellite imagery applied on a brownfield

Area of Science:

• Environmental science
• Hydrology
• Remote sensing

Background:

• Surface-subsurface water interactions are complex and variable, especially in urban areas due to intricate land-cover patterns.
• Urban groundwater pollution is closely linked to land-use patterns, necessitating detailed land-cover characterization.

Purpose of the Study:

• To develop and apply an integrated modeling and remote sensing approach for estimating water fluxes in urban environments.
• To simulate contaminant fluxes from polluted urban sites, specifically brownfields, into groundwater.

Main Methods:

• An object-oriented classification of high-resolution satellite data was used for detailed land-cover mapping (Kappa = 0.86).
• The WetSpass model simulated spatially distributed groundwater recharge, and MODFLOW simulated subsurface water flow.
• The methodology was applied to a brownfield site in Vilvoorde, Brussels, Belgium.

Main Results:

• The detailed land-use map significantly impacted groundwater recharge, leading to high spatial variability.
• Simulated groundwater contaminant fluxes from the brownfield to the River Zenne were validated through independent measurements and thermal gradient analysis.
• The study demonstrated the strong influence of land cover on water flux dynamics.

Conclusions:

• Integrating remote sensing imagery into modeling procedures can operationally improve the quantification of total contaminant fluxes from urban brownfields into groundwater.
• Accurate land-cover characterization is crucial for understanding and managing urban hydrological processes and contaminant transport.