Urban flooding has emerged as a critical challenge, driven by rapid urbanization, the expansion of impervious surfaces, and unplanned infrastructure development. Effective stormwater management through well-designed sewer systems is essential for mitigating flood risks and safeguarding public health. This study employs the U.S. EPA’s storm water management model (SWMM) to design a closed drainage network for the proposed NIT Patna campus at Bihta, Bihar, India. The campus area was delineated into 12 hydrologically significant sub-catchments, and stormwater runoff was simulated for various return periods. Intensity-duration-frequency (IDF) curves were developed using Gumbel’s extreme value distribution based on 31 years (1990–2021) of rainfall data sourced from India-WRIS. A 50-year return period was selected for design simulations to ensure system resilience against extreme rainfall events. The study integrates hydrologic and hydraulic design methodologies within SWMM, with model performance validated through calibration. The results highlight SWMM’s effectiveness in accurately designing drainage infrastructure that accounts for urban hydrologic variability, thereby supporting resilient and sustainable campus development.

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SWMM-Based Modeling and Assessment of Open Drainage System: A Case Study of the Proposed New NIT Campus at Bihta, Patna

  • Atul Kumar,
  • Joseph Tripura,
  • Suraj Kumar

摘要

Urban flooding has emerged as a critical challenge, driven by rapid urbanization, the expansion of impervious surfaces, and unplanned infrastructure development. Effective stormwater management through well-designed sewer systems is essential for mitigating flood risks and safeguarding public health. This study employs the U.S. EPA’s storm water management model (SWMM) to design a closed drainage network for the proposed NIT Patna campus at Bihta, Bihar, India. The campus area was delineated into 12 hydrologically significant sub-catchments, and stormwater runoff was simulated for various return periods. Intensity-duration-frequency (IDF) curves were developed using Gumbel’s extreme value distribution based on 31 years (1990–2021) of rainfall data sourced from India-WRIS. A 50-year return period was selected for design simulations to ensure system resilience against extreme rainfall events. The study integrates hydrologic and hydraulic design methodologies within SWMM, with model performance validated through calibration. The results highlight SWMM’s effectiveness in accurately designing drainage infrastructure that accounts for urban hydrologic variability, thereby supporting resilient and sustainable campus development.