@inproceedings{fdi:010095099,
  title = {{A}ssessing long-term changes in annual monsoon inundations in the {M}ekong {D}elta ({C}ambodia) : testing an innovative approach linking remote sensing and in-situ measurements to overcome data scarcity [r{\'e}sum{\'e}]},
  author = {{O}rieschnig, {C}hristina and {B}elaud, {G}. and {V}enot, {J}ean-{P}hilippe and {M}assuel, {S}ylvain},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he annual monsoon inundations are vital in maintaining the fertility and productivity of the delta of the {M}ekong, {S}outheast {A}sia's largest river. {D}uring the inundations, which traditionally last from {J}uly until {N}ovember, nutrient-rich sediments are deposited on the floodplains, groundwater is recharged, and fish populations regenerate in the shallow waters. {C}onsequently, local agriculture and fisheries are keyed to the timing of flood arrival and recession and reliant on overall flood duration. {H}owever, in recent years, the hydrological dynamics of the region have shifted. {T}he {M}ekong's hydrological regime has been impacted by shifts in land cover, the construction of hydropower infrastructure, and climate change.  {Y}et the effects of these changes on the spatio-temporal patterns of inundations in the {M}ekong {D}elta remain largely unstudied, especially at local scales. {P}art of the reason for this is data sparsity: there is a lack of consistent long-term data on spatial inundation dynamics. {N}o concerted in-situ monitoring efforts of flood extents existed until recently, while optical earth observation satellite missions such as {L}andsat often fail to provide data during the wet season due to cloud cover. {H}ydrological modelling approaches struggle with insufficiently precise elevation data - due to the flat topography of the {M}ekong {D}elta, even high-resolution {D}igital {E}levation {M}odels ({DEM}s) fail to capture small-scale dykes that determine whether large swaths of land become flooded.  {T}o cope with this data-scarce environment, we propose an innovative methodology harnessing recent satellite missions and long-term in-situ river water level measurements. {T}his approach uses remote sensing data from the {S}entinel-1 and 2 missions operated by the {E}uropean {S}pace {A}gency. {S}ince 2017, these satellites provide optical and synthetic aperture radar ({SAR}) data at a spatial resolution of 10 m and a return frequency of 5-6 days. {F}urthermore, {SAR} provides data independent of cloud cover, which makes it particularly well-suited for operational flood monitoring purposes. {A}fter deriving inundation maps from available {S}entinel images, we link these maps to water levels measured at a local hydrological station through a correlative approach to create a water-level flood link ({WAFL}). {U}sing this link, we can describe the evolution of inundation patterns in the {M}ekong {D}elta since the 1990s. {T}o quantify uncertainties, comparisons with historical inundation maps derived from available {L}andsat images,  and with a high- resolution {DEM} were carried out.   {T}he approach was tested in two study areas in the {C}ambodian {M}ekong {D}elta.  {T}he results indicate that the accuracy of the {WAFL} for quantifying inundations on a per-pixel basis lies at 87%, reaching up to 93%. {T}he spatio-temporal analysis shows that inundation incidence in the early wet season has declined by 21% since 1991 and that the average duration of inundations has decreased by 19 days. {T}his illustrates that annual monsoon inundations have become an increasingly volatile resource, with significant impacts on agriculture, fisheries, and ecosystems.},
  keywords = {{CAMBODGE} ; {MEKONG} {DELTA}},
  numero = {},
  pages = {{EGU}22--9619 [1 ]},
  booktitle = {},
  year = {2022},
  DOI = {10.5194/egusphere-egu22-9619},
  URL = {https://www.documentation.ird.fr/hor/fdi:010095099},
}