Lidia Maria Giannini

Dr. Lidia Maria Giannini


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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12 April 2026 in Applied Sciences
Verified
Journal Article
Open access
PDF file
LGLidia Maria Giannini
Lidia Maria Giannini
Giada RomanoGiada Romano
Giada Romano
FTFabrizio Tucci
Fabrizio Tucci
Urban areas are increasingly exposed to water-related challenges, including flood risk and water scarcity, amplified by climate change, population growth, and extensive soil sealing. Addressing these pressures requires integrated stormwater management (SWM) strategies that balance hydraulic, environmental, and social objectives. This study introduces a novel, replicable Key Performance Indicator (KPI)-based assessment framework for 36 green–blue and grey sustainable stormwater management systems (SWMSs), designed to enable cross-typology, multiscale comparison. Six KPIs, encompassing flood regulation, water consumption, water quality, air quality, environmental amenity, and biodiversity potential, are derived through a critical synthesis and harmonisation of the literature and complemented with new parameters and sub-parameters to address existing methodological gaps. The framework structures evaluations into six analytical tables and one summary table, ensuring transparent, systematic, and comparative assessment of heterogeneous solutions. Application to a pilot project in Rome demonstrates how integrating KPI evaluation with parametric hydraulic modelling provides actionable insights for solution selection. It also facilitates identification of potential synergies between performance dimensions, enhancing its value as a decision-support tool in preliminary design. Overall, the study demonstrates the research value of multi-scalar, performance-based approaches for urban water planning, highlights the transferability of resilient stormwater strategies in climate-sensitive contexts, and identifies promising avenues for future research, including multi-sectoral integration, trade-off analysis, and cross-platform application.