Chinese cities and megacities occupy large areas with high population densities. These urban sectors have extensive impervious surfaces and import large amounts of water from pristine sources, putting pressure on the urban drainage systems during storms. To reduce flood risk and tackle water scarcity, the Chinese government promulgated the Sponge City concept: an ensemble of absorbing features, including permeable pavements and green roofs, to reduce urban runoff and increase water storage. We evaluate the benefits of merging the urban aquifer with conventional Sponge City features by simulating stormwater storage in aquifers with a groundwater model (MODFLOW) and a stormwater management model (SWMM). The urban aquifers of an ideal district, characterized by high-density housing and a flat morphology, collect and dissipate extreme rains (200 mm in 6 h) when the hydraulic conductivity of the subsoil is higher than 1·10⁻⁵ m/s, roughly corresponding to a medium productive aquifer. Economic and ecological benefits at the catchment scale are also discussed. Suitable shallow aquifers are individuated and discussed throughout China via a hydrogeological and geomorphological approach. The proposed method increases the percentage of water that can be controlled above that obtained through conventional Sponge City features.

Rapid urbanization has exacerbated urban-stormwater challenges, highlighting the critical need for coordinated surface-water and groundwater management through rainfall recharge. However, current sponge city construction methods often overlook the crucial role of underground aquifers in regulating the water cycle and mostly rely on simplified engineering approaches. To address these limitations, this study proposes a spatial optimization framework for urban-scale sponge systems that integrates a hydrodynamic model (FVCOM), geographic information systems (GIS), and Monte Carlo simulations. This framework establishes a comprehensive evaluation system that synergistically integrates surface water inundation depth, geological lithology, and groundwater depth to quantitatively assess sponge city suitability. The FVCOM was employed to simulate surface water inundation processes under extreme rainfall scenarios, while GIS facilitated spatial analysis and data integration. The Monte Carlo simulation was utilized to optimize the spatial layout by objectively determining factor weights and evaluate result uncertainty. Using Shenzhen City in China as a case study, this research combined the “matrix-corridor-patch” theory from landscape ecology to optimize the spatial structure of the sponge system. Furthermore, differentiated planning and management strategies were proposed based on regional characteristics and uncertainty analysis. The research findings provide a replicable and verifiable methodology for developing sponge city systems in high-density urban areas. The core value of this methodology lies in its creation of a scientific decision-making tool for direct application in urban planning. This tool can significantly enhance a city’s climate resilience and facilitate the coordinated, optimal management of water resources amid environmental changes.

Rapid urbanization has intensified challenges in urban water management, highlighting the growing importance of sponge city development. However, at present, the unique role of groundwater aquifers in regulating the water cycle process has been ignored, and overly simplistic construction methods are relied on. To address these limitations, this study introduces an integrated spatial optimization framework for urban-scale sponge ecosystems by coupling hydrodynamic modeling, ArcGIS-based spatial analysis, and Monte Carlo simulation. The framework systematically incorporates surface water depth, formation lithology, and groundwater depth to construct a comprehensive evaluation system for sponge ecological suitability. Shenzhen serves as the empirical case to demonstrate the framework’s applicability. Surface water depth is quantified using the Finite-Volume Community Ocean Model (FVCOM), while groundwater conditions are assessed through a calibrated groundwater model, thereby improving the scientific precision of ecological suitability evaluation. Leveraging GIS and Monte Carlo simulation, the study develops a streamlined yet robust methodology for optimizing the spatial configuration of sponge ecological infrastructure. Building on ecological redlines and protected areas, a landscape ecology–oriented matrix–corridor–patch analysis is applied to delineate ecologically suitable zones. Tailored planning and management strategies are subsequently formulated for each zone based on its ecological attributes. The findings offer methodological advances for sponge ecosystem construction and contribute to enhancing urban climate resilience and adaptive capacity under accelerating environmental change.