Optimizing Urban Stormwater Systems with SAP Business Technology Platform and AI

Abstract

Urban stormwater management has emerged as one of the most pressing challenges in contemporary civil engineering and environmental governance. Rapid urbanization, the progressive expansion of impervious surfaces, and the intensification of extreme precipitation events attributed to climate change have collectively strained conventional drainage infrastructure beyond its design thresholds. This review article examines how the SAP Business Technology Platform (BTP), augmented by artificial intelligence (AI) and machine learning (ML) capabilities, offers a transformative paradigm for optimizing the planning, operation, and governance of urban stormwater systems. Drawing on peer-reviewed literature, SAP technical documentation, and municipal case studies published up to 2023, the article synthesizes evidence across four thematic pillars: real-time sensor integration and data orchestration, predictive analytics for flood forecasting, AI-driven asset lifecycle management, and cross-departmental decision support. The review finds that SAP BTP's unified data architecture, combined with embedded AI services and IoT Edge capabilities, enables municipalities to transition from reactive, siloed stormwater operations toward proactive, integrated urban water intelligence.