This study proposes the Sponge City+ parametric design toolkit, which integrates low-impact development (LID) measures into urban design to support compliance checking, runoff risk analysis, and optimization of design alternatives. Compliance is evaluated using the annual runoff volume capture ratio (AVCR) calculated via the Volume Method, which is the core criterion in sponge city standards. The toolkit combines a measures database, runoff volume control functions, and runoff simulation functions to evaluate and compare design alternatives. Its applicability was tested through case studies of three university campuses in China. These cases were used to: (1) conduct a sensitivity analysis of the toolkit’s response to different LID strategies, ranking three typical LID measures (sunken green spaces > permeable pavements > green roofs) in terms of their contribution to runoff control; (2) perform multi-objective optimization considering cost, runoff control, and peak reduction, which, under ordinary PC computational capacity, efficiently identified 27 qualified solutions out of more than 5000 samples, thereby providing a broader set of design choices while ensuring compliance with runoff control requirements; and (3) demonstrate a design optimization process based on runoff visualization, where human–computer interaction helped avoid potential flood risks during the early design stage. This study demonstrates the potential of a parametric workflow to bridge disciplinary boundaries and support the achievement of global sustainability goals.

Sponge city theory utilizes policy-driven design to mitigate urban flooding and shape urban development. However, existing approaches primarily focus on micro-scale landscape facilities and performance assessments, overlooking the integration of macro-scale urban design strategies. This study develops a parametric design framework linking the quantitative control requirements of sponge city policies to urban morphological elements, establishing a "form-performance" correlation model. Key design indicators (green space, roof, water body, pavement, and their sub-indicators) were identified, and sensitivity analysis evaluated their responses to varying plot ratios and site scales. Results indicate that policy-guided stormwater runoff reduction strategies differ significantly by development density: high-density projects favor increased green roof ratios, while low-density projects are better suited for permeable pavements. Larger sites necessitate greater emphasis on peak runoff control and rational catchment zoning. The analysis empirically validated the framework and model, revealing that current policies risk over-incentivizing specific high-performance technologies, potentially compromising strategic diversity and resilience to extreme weather events. Consequently, optimizing policy evaluation metrics and refining design guidelines is recommended to achieve more balanced, efficient, and resilient stormwater management during preliminary urban design phases.