@article{PAR00011495,
  title = {{I}nversion of soil hydraulic properties from the {DE}n{KF} analysis of {SMOS} soil moisture over {W}est {A}frica},
  author = {{L}ee, {J}. {H}. and {P}ellarin, {T}. and {K}err, {Y}ann},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he application of {S}oil-{V}egetation-{A}tmosphere-{T}ransfer ({SVAT}) scheme into the estimation of soil moisture profile in semi-arid regions is largely constrained by a scarcity of spatially distributed soil and hydraulic property information. {E}specially, on a large scale in very dry and sandy soils or other extreme conditions, it is difficult to accurately map soil and hydraulic properties with soil maps-based {P}edo-{T}ransfer {F}unctions ({PTF}s), because {PTF}s are usually semi-empirically defined for specific sites. {O}ne strategy to overcome this limitation is to employ satellite data for a purpose of calibration. {T}his paper provides an operational framework of inverting the {SVAT} soil hydraulic variables from the deterministic ensemble {K}alman filter ({DE}n{KF}) analysis of {S}oil {M}oisture and {O}cean {S}alinity ({SMOS}) surface soil moisture product. {T}his inverse calibration was first verified with the {A}nalyses {M}ultidisciplinaires de la {M}ousson {A}fricaine ({AMMA}) super site data representative of a single grid cell (0.25 degrees) of satellite data. {A}t this local scale, the results demonstrated that the mis-estimation problems of soil surface variable {C}-1 and equilibrium soil moisture theta(geq) were successfully solved after calibration, demonstrating a better agreement with the field measurement of soil moisture profile than the {SMOS} product and un-calibrated {SVAT} scheme using soil maps-based {PTF}s. {O}n the meso scale, the calibrated {SVAT} scheme using inverted surface variables appropriately captured a non-linear relationship between surface and root zone soil moisture by showing a typical soil moisture profile in dry climates, where dry surface soil moisture is spatially consistent with rainfall events, but wet root zone soil moisture shows low correlations with surface soil moisture distributions and rainfall events. {I}n contrast, the un-calibrated {SVAT} scheme using soil maps-based {PTF}s significantly overestimated surface soil moisture and rainfall effect. {T}his approach suggests several operational merits in that there is no need to heavily rely on empirically defined {PTF}s or recalibrate land surface parameters for different land surface conditions, and this can be applied even when parameter measurements are unavailable or highly uncertain. {C}rown {C}opyright ({C}) 2013 {P}ublished by {E}lsevier {B}.{V}. {A}ll rights reserved.},
  keywords = {{SMOS} surface soil moisture ; {ISBA} land surface parameterization ; {DE}n{KF} ; {SVAT} model ; {P}arameter inversion ; {S}oil and hydraulic property in semi-arid regions ; {AFRIQUE} {DE} {L}'{OUEST}},
  booktitle = {},
  journal = {{A}gricultural and {F}orest {M}eteorology},
  volume = {188},
  numero = {},
  pages = {76--88},
  ISSN = {0168-1923},
  year = {2014},
  DOI = {10.1016/j.agrformet.2013.12.009},
  URL = {https://www.documentation.ird.fr/hor/{PAR}00011495},
}