@inproceedings{fdi:010096226,
  title = {{F}lood mapping using high-resolution topography and crowdsourced data with the geomorphic {HAND} approach in rural plains [r{\'e}sum{\'e}]},
  author = {{S}abeh, {H}. and {T}ournoud, {M}.{G}. and {C}hahinian, {N}an{\'e}e and {A}bdallah, {C}. and {M}oussa, {R}. and {H}deib, {R}.},
  editor = {},
  language = {{ENG}},
  abstract = {{F}lood mapping is essential for risk management and emergency response. {T}he most common approach is hydraulic modelling, a method that is still challenging and demanding in terms of data and computation. {L}ow complexity models are an increasingly adopted alternative that are capable of achieving good results while using minimal data input and low calculation time. {Y}et, the reliability and effectiveness of such approaches remain unclear in flat and engineered plains. {I}n this study we aim to optimize flood hazard mapping based on the {H}eight {A}bove {N}earest {D}rainage ({HAND}) geomorphic approach by utilizing a high-resolution digital elevation model (15 cm) with crowdsourced data. {T}he approach is tested on the {O}stouane river basin (144 km2) in {L}ebanon, and validated using crowdsourced data of the {J}anuary 2019 flood, which was the most intense flood within the past decade. {T}he workflow begins by developing a database of spatial and topographic information, including the digital elevation model,




bathymetry, land use and crowdsourced flood depths. {F}ive scenarios representing different terrain configurations with varying levels of hydro-conditioning and feature inclusion (e.g. bathymetry, canals and levees) are simulated. {T}he model's thresholding is then optimized by integrating rating curves produced by 1{D} {HEC}-{RAS} hydraulic model to assess and correct {HAND} based synthetic rating curves ({SRC}). {R}esults shows that extensive hydro-conditioning is necessary to improve the inundation extents within the floodplains. {C}orrecting synthetic rating curves is essential to overcome errors produced by terrain conditioning. {O}verall, the model is able to yield high accuracy of flood extent when ensuring hydrologic connectivity between the river and floodplain and within the floodplain itself. {O}ur findings indicate that leveraging high-resolution topography and crowdsourced inputs can enhance the accuracy of flood mapping results. {H}owever, achieving this precision necessitates a meticulous optimization procedure.},
  keywords = {},
  numero = {},
  pages = {{EGU}24--957 [1 ]},
  booktitle = {},
  year = {2024},
  DOI = {10.5194/egusphere-egu24-957},
  URL = {https://www.documentation.ird.fr/hor/fdi:010096226},
}