@article{fdi:010053672,
  title = {{T}hermal remote sensing of water under flooded vegetation: {N}ew observations of inundation patterns for the '{S}mall' {L}ake {C}had},
  author = {{L}eblanc, {M}. and {L}emoalle, {J}acques and {B}ader, {J}ean-{C}laude and {T}weed, {S}. and {M}ofor, {L}.},
  editor = {},
  language = {{ENG}},
  abstract = {{L}ake {C}had at the border of the {S}ahara desert in central {A}frica, is well known for its high sensitivity to hydroclimatic events. {G}aps in in situ data have so far prevented a full assessment of the response of {L}ake {C}had to the ongoing prolonged drought that started in the second half of the 20th century. {L}ike many other wetlands and shallow lakes, the '{S}mall' {L}ake {C}had includes large areas of water under aquatic vegetation which needs to be accounted for to obtain the total inundated area. {I}n this paper, a methodology is proposed that uses {M}eteosat thermal maximum composite data ({T}max) to account for water covered by aquatic vegetation and provide a consistent monthly time series of total inundated area estimates for {L}ake {C}had. {T}otal inundation patterns in {L}ake {C}had were reconstructed for a 15-yr period (1986-2001) which includes the peak of the drought (86-91) and therefore provides new observations on the hydrological functioning of the '{S}mall' {L}ake {C}had. {D}uring the study period, {L}ake {C}had remained below 16,400 km(2) (third quartile similar to 8800 km(2)). {T}he variability of the inundated area observed in the northern pool (standard deviation sigma(northern pool) = 1980 km(2)) is about 60% greater than that of the southern pool (sigma(southern pool) 1250 km(2)). {T}he same methodology could be applied to other large wetlands and shallow lakes in semi-arid or arid regions elsewehere using {M}eteosat (e.g. {N}iger {I}nland {D}elta, {S}udd in {S}udan, {O}kavango {D}elta) and other weather satellites (e.g., floodplains of the {L}ake {E}yre {B}asin in {A}ustralia and {A}ndean {A}ltiplano {L}akes in {S}outh {A}merica).},
  keywords = {{D}rought ; {R}emote sensing ; {G}lobal change ; {W}ater resources ; {A}frica},
  booktitle = {},
  journal = {{J}ournal of {H}ydrology},
  volume = {404},
  numero = {1-2},
  pages = {87--98},
  ISSN = {0022-1694},
  year = {2011},
  DOI = {10.1016/j.jhydrol.2011.04.023},
  URL = {https://www.documentation.ird.fr/hor/fdi:010053672},
}