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Enhancing Sustainable Flood Resilience and Energy Efficiency in Residential Structures: Integrating Hydrological Data, BIM, and GIS in Quetta, Pakistan

Author

Listed:
  • Muhammad Asfandyar

    (Key Laboratory of Mountain Hazards and Earth Surface Process, Institute of Mountain Hazard and Environment, Chinese Academy of Sciences, Chengdu 610041, China)

  • Nazir Ahmed Bazai

    (Key Laboratory of Mountain Hazards and Earth Surface Process, Institute of Mountain Hazard and Environment, Chinese Academy of Sciences, Chengdu 610041, China
    Department of Civil Engineering Technology, National Skills University, Islamabad 44000, Pakistan)

  • Huayong Chen

    (Key Laboratory of Mountain Hazards and Earth Surface Process, Institute of Mountain Hazard and Environment, Chinese Academy of Sciences, Chengdu 610041, China)

  • Muhammad Habib

    (Department of Civil Engineering Technology, National Skills University, Islamabad 44000, Pakistan)

  • Javed Iqbal

    (China-Pakistan Joint Research Centre on Earth Science (CPJRC), Chinese Academy of Sciences, Islamabad 44000, Pakistan
    Department of Earth Science, The Haripur University, Haripur 22620, Pakistan)

  • Muhammad Aslam Baig

    (Key Laboratory of Mountain Hazards and Earth Surface Process, Institute of Mountain Hazard and Environment, Chinese Academy of Sciences, Chengdu 610041, China)

  • Muhammad Hasan

    (China-Pakistan Joint Research Centre on Earth Science (CPJRC), Chinese Academy of Sciences, Islamabad 44000, Pakistan
    State Key Laboratory of Mountain Hazards and Engineering Resilience, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610299, China)

Abstract

This study explores the integration of Building Information Modeling (BIM) and Geographic Information Systems (GISs) to enhance sustainable energy efficiency and flood resilience in residential buildings, with a case study from Quetta, Pakistan. The research leverages BIM to optimize energy performance through scenario-based energy consumption assessments, thermal efficiency, material properties, and groundwater considerations, ensuring structural integrity against water infiltration. Enhanced insulation and double-glazed windows reduced energy use by 11.78% and 5.8%, respectively, with monthly energy cost savings of up to 48.2%. GIS tools were employed for high-resolution flood risk analysis, utilizing Digital Elevation Models (DEMs) and hydrological data to simulate flood scenarios with depths of up to 2 m, identifying vulnerabilities and estimating non-structural damage costs at PKR 250,000 (~10% of total building costs). Groundwater data were also incorporated to evaluate their impact on foundation stability, ensuring the building’s resilience to surface and subsurface water challenges. A novel BIM-GIS integration framework provided precise 2D and 3D visualizations of flood impacts, facilitating accurate damage assessments and cost-effective resilience planning. The findings demonstrated that incorporating flood-resistant materials and design modifications could reduce repair costs by 30–50%, highlighting the cost-efficiency of sustainable resilience strategies. This research advances sustainable and resilient construction practices by showcasing the dual potential of BIM-GIS integration to address energy efficiency and groundwater-related structural vulnerabilities alongside hazard mitigation challenges. Future applications include automating workflows, integrating renewable energy systems, and validating models across diverse climatic regions to promote the global adoption of innovative urban planning solutions.

Suggested Citation

  • Muhammad Asfandyar & Nazir Ahmed Bazai & Huayong Chen & Muhammad Habib & Javed Iqbal & Muhammad Aslam Baig & Muhammad Hasan, 2025. "Enhancing Sustainable Flood Resilience and Energy Efficiency in Residential Structures: Integrating Hydrological Data, BIM, and GIS in Quetta, Pakistan," Sustainability, MDPI, vol. 17(6), pages 1-16, March.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:6:p:2496-:d:1610724
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    References listed on IDEAS

    as
    1. Delgarm, N. & Sajadi, B. & Kowsary, F. & Delgarm, S., 2016. "Multi-objective optimization of the building energy performance: A simulation-based approach by means of particle swarm optimization (PSO)," Applied Energy, Elsevier, vol. 170(C), pages 293-303.
    2. Raaghul Kumar & Munshi Md. Shafwat Yazdan, 2022. "Evaluating Preventive Measures for Flooding from Groundwater: A Case Study," J, MDPI, vol. 6(1), pages 1-16, December.
    3. Si, Binghui & Tian, Zhichao & Jin, Xing & Zhou, Xin & Tang, Peng & Shi, Xing, 2016. "Performance indices and evaluation of algorithms in building energy efficient design optimization," Energy, Elsevier, vol. 114(C), pages 100-112.
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