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Riverine flood mapping and impact assessment using remote sensing technique: a case study of Chenab flood-2014 in Multan district, Punjab, Pakistan

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Abstract

The Multan district is mainly prone to riverine floods but has remained understudied. Chenab flood-2014 was the worst flood that this district experienced in recorded history. This study applies remote sensing (RS) techniques to estimate the extent, calculate duration, assess the major causes and resulting impacts of the flood-2014, using Landsat-8 OLI images. These images were obtained for pre-flood, during-flood and post-flood instances. Secondary data of flood causing factors were obtained for comprehensive analysis. Spatially trained and validated datasets were obtained through Google Earth platform and Global positioning system. The supervised classification with maximum likelihood algorithm was used to classify land use and land cover of the study area. The Modified Normalized Difference Water Index was utilized to detect flood inundation extent and duration, and Normalized Difference Vegetation Index was utilized to monitor vegetation coverage and changes. The analysis allowed us to assess flood causes, and calculate the extent of the flooded areas with duration and recession, as well as damages to standing crops and built-up areas. The results revealed that the flood-2014 occurred due to heavy rains in early September in upper Chenab catchment. The flood inundation continued for around two months, which heavily affected agriculture and built-up areas. The present study introduces practical use of RS techniques to provide basis for effective flood inundation mapping and impact assessment, as an application for early flood response and recovery in the world.

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Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgment and Funding

This work was funded by the National Key Research and Development Program (2018YFC1506506), the Frontier Project of Applied Foundation of Wuhan (2019020701011502), Key Research and Development Program of Jiangxi Province (20201BBG71002), and the LIESMARS Special Research Funding.

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Authors and Affiliations

  1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, China

    Asif Sajjad, Jianzhong Lu & Xiaoling Chen

  2. Department of Earth Sciences, Ndata School of Climate and Earth Sciences, Malawi University of Science and Technology, Box 5196, Limbe, Malawi

    Chikondi Chisenga

  3. Department of Geography, Lahore College for Women University, Lahore, Pakistan

    Nausheen Mazhar

  4. Department of Geography, Bahauddin Zakariya University, Multan, Pakistan

    Basit Nadeem

Authors
  1. Asif Sajjad
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  2. Jianzhong Lu
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  3. Xiaoling Chen
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  4. Chikondi Chisenga
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  5. Nausheen Mazhar
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  6. Basit Nadeem
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Contributions

SA and JL conceptualized overall research design; image analysis, flood inundation maps, LULC maps and flood impact assessment were contributed by SA; validation was contributed by SA, JL and CC; investigation was contributed by CX; writing—original draft preparation was contributed by SA; writing—review and editing were contributed by SA, JL, NM and BN.

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Correspondence to Jianzhong Lu.

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Sajjad, A., Lu, J., Chen, X. et al. Riverine flood mapping and impact assessment using remote sensing technique: a case study of Chenab flood-2014 in Multan district, Punjab, Pakistan. Nat Hazards 110, 2207–2226 (2022). https://doi.org/10.1007/s11069-021-05033-9

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