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  <titleInfo>
    <title>Characterization of floods and assessment of flood susceptibility in Bangladesh</title>
  </titleInfo>
  <name type="personal">
    <namePart>Akhtar, Mst. Mariam</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
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  <name type="personal">
    <namePart>Natthachet Tangdamrongsub</namePart>
    <role>
      <roleTerm type="text">Chairperson</roleTerm>
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  </name>
  <name type="personal">
    <namePart>Ho, Huu Loc</namePart>
    <role>
      <roleTerm type="text">Co-Chairperson</roleTerm>
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  <name type="personal">
    <namePart>Babel, Mukand S.</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
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  <name type="personal">
    <namePart>Shanmugam, Mohana Sundaram</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
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  <name type="corporate">
    <namePart>LGED, Bangladesh</namePart>
    <role>
      <roleTerm type="text">Scholarship Donor</roleTerm>
    </role>
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  <genre authority="marc">series</genre>
  <genre authority="marc">technical report</genre>
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    <place>
      <placeTerm type="text">Pathum Thani, Thailand</placeTerm>
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    <publisher>Asian Institute of Technology</publisher>
    <dateIssued>2024</dateIssued>
    <issuance>continuing</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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    <extent>95 leaves : ill. + 1 online resource</extent>
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  <abstract>In recent times, floods have garnered global attention because of its destructive power as  well as propensity to cause enormous financial and human losses. Bangladesh, in  particular, faces recurring challenges amplified by its geographical setting and the  influence of climate change on its populous deltaic landscape. However, the absence of  an extensive database that correlates flood features with geographical and  geomorphologic data has hampered research on flood characterization of Bangladesh.  This study addresses this gap by employing a large-event dataset that relies on BWDB  classifications of floods, introducing a protocol for flood characterization using the Flood  Intensity Index (FII). This classification will open doors for better risk management and  hydrologic predictions. Examining flooding characteristics reveals variations in spatial and temporal scales across  different climatic regimes and geomorphological features. The Meghna Basin emerges as  a focal point, dominating in maximum flood years and hosting the highest number of  flood-vulnerable stations. It records the highest number of flooding events and annual  precipitation, falling under the Tropical monsoon climate (Am), indicating the highest  rainfall zone. Analysis of envelop curve indicates distinctive trends in unit peak discharge  values with catchment area among basins, reflecting their geomorphological attributes. To validate findings, a flood-susceptible map is prepared using a multi-criteria decision  technique integrating GIS and AHP. Seven parameters that can cause flooding are taken  into account are elevation, drainage density, rainfall, topographic moisture index, slope,  flood depth, and discharge. Analysis spanning from 1987 to 2021 highlights a significant  decreasing trend in floods across Bangladesh, as evidenced by the Mann-Kendall Trend  Test (MK). While pinpointing exact drivers remains challenging, potential explanations  include variations in precipitation due to climate change, global warming effects, and  water management strategies both within and beyond Bangladesh's borders. </abstract>
  <note>A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Water Engineering and Management, School of Engineering and Technology </note>
  <note>Thesis (M. Sc.) - Asian Institute of Technology, 2024</note>
  <subject authority="lcsh">
    <topic>Floods</topic>
    <geographic>Bangladesh</geographic>
  </subject>
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    <titleInfo>
      <title>Thesis;  no. WM-24-03</title>
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      <namePart>Asian Institute of Technology.</namePart>
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  <identifier type="uri">http://203.159.5.9/ait-thesis/detail.php?q=B20817</identifier>
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