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<p>Urban flooding has emerged as a critical challenge for rapidly expanding cities, necessitating proactive flood risk assessment and mitigation strategies. Gurugram, located in the National Capital Region (NCR) of India, was selected as the study area due to its rapid, unplanned urbanization and increasing incidence of waterlogging. This study applied the Integrated Valuation of Ecosystem Services and Tradeoffs–Urban Flood Risk Mitigation (InVEST-UFRM) model to simulate urban flood behavior across a 48.42&#xa0;km² urban catchment, analyzing the impact of 1-hour rainfall events with varying depths corresponding to 2-, 5-, and 10-year return periods. The results indicate that approximately 44.6% of the area is covered by impervious surfaces, with high runoff generation observed in central and northern sectors. Under the highest rainfall scenario (43.6&#xa0;mm rainfall in 1&#xa0;h), more than 80% of stormwater became runoff, and the runoff retention index falls below 0.2 in densely built-up zones. A sharp 47% increase in flood volume was recorded with a 46% rise in rainfall depth, indicating the nonlinear nature of urban flood risks. Green and open spaces demonstrated the highest stormwater retention, storing up to 4.36&#xa0;m³ per pixel, while impervious surfaces retained less than 2.0&#xa0;m³. These findings highlight the increasing flood risk in Gurugram and the diminishing capacity of the landscape to manage extreme rainfall. Mitigation recommendations focus on managing precipitation intensity, reducing surface runoff through green infrastructure, and enhancing runoff retention using nature-based solutions. The InVEST-UFRM model, due to its spatial clarity and ease of application, proves effective for evaluating flood risk and guiding urban flood resilience planning in semi-arid environments like Gurugram.</p>

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Evaluating urban flood risk and retention potential using InVEST-UFRM: a case study from Gurugram, India

  • 期刊论文

  • 发表日期：

    2026年3月7日

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  • Simran Sehrawat,
  • Sulochana Shekhar

摘要

Urban flooding has emerged as a critical challenge for rapidly expanding cities, necessitating proactive flood risk assessment and mitigation strategies. Gurugram, located in the National Capital Region (NCR) of India, was selected as the study area due to its rapid, unplanned urbanization and increasing incidence of waterlogging. This study applied the Integrated Valuation of Ecosystem Services and Tradeoffs–Urban Flood Risk Mitigation (InVEST-UFRM) model to simulate urban flood behavior across a 48.42 km² urban catchment, analyzing the impact of 1-hour rainfall events with varying depths corresponding to 2-, 5-, and 10-year return periods. The results indicate that approximately 44.6% of the area is covered by impervious surfaces, with high runoff generation observed in central and northern sectors. Under the highest rainfall scenario (43.6 mm rainfall in 1 h), more than 80% of stormwater became runoff, and the runoff retention index falls below 0.2 in densely built-up zones. A sharp 47% increase in flood volume was recorded with a 46% rise in rainfall depth, indicating the nonlinear nature of urban flood risks. Green and open spaces demonstrated the highest stormwater retention, storing up to 4.36 m³ per pixel, while impervious surfaces retained less than 2.0 m³. These findings highlight the increasing flood risk in Gurugram and the diminishing capacity of the landscape to manage extreme rainfall. Mitigation recommendations focus on managing precipitation intensity, reducing surface runoff through green infrastructure, and enhancing runoff retention using nature-based solutions. The InVEST-UFRM model, due to its spatial clarity and ease of application, proves effective for evaluating flood risk and guiding urban flood resilience planning in semi-arid environments like Gurugram.