@article{fdi:010057339,
  title = {{O}n the sources of hydrological prediction uncertainty in the {A}mazon},
  author = {{P}aiva, {R}. {C}. {D}. and {C}ollischonn, {W}. and {B}onnet, {M}arie-{P}aule and de {G}oncalves, {L}. {G}. {G}.},
  editor = {},
  language = {{ENG}},
  abstract = {{R}ecent extreme events in the {A}mazon {R}iver basin and the vulnerability of local population motivate the development of hydrological forecast systems using process based models for this region. {I}n this direction, the knowledge of the source of errors in hydrological forecast systems may guide the choice on improving model structure, model forcings or developing data assimilation systems for estimation of initial model states. {W}e evaluate the relative importance of hydrologic initial conditions and model meteorological forcings errors (precipitation) as sources of stream flow forecast uncertainty in the {A}mazon {R}iver basin. {W}e used a hindcast approach that compares {E}nsemble {S}treamflow {P}rediction ({ESP}) and a reverse {E}nsemble {S}treamflow {P}rediction (reverse-{ESP}). {S}imulations were performed using the physically-based and distributed hydrological model {MGB}-{IPH}, comprising surface energy and water balance, soil water, river and floodplain hydrodynamics processes. {T}he model was forced using {TRMM} 3{B}42 precipitation estimates. {R}esults show that uncertainty on initial conditions plays an important role for discharge predictability, even for large lead times (similar to 1 to 3 months) on main {A}mazonian {R}ivers. {I}nitial conditions of surface waters state variables are the major source of hydrological forecast uncertainty, mainly in rivers with low slope and large floodplains. {I}nitial conditions of groundwater state variables are important, mostly during low flow period and in the southeast part of the {A}mazon where lithology and the strong rainfall seasonality with a marked dry season may be the explaining factors. {A}nalyses indicate that hydrological forecasts based on a hydrological model forced with historical meteorological data and optimal initial conditions may be feasible. {A}lso, development of data assimilation methods is encouraged for this region.},
  keywords = {{AMAZONIE} ; {AMAZONE} {COURS} {D}'{EAU}},
  booktitle = {},
  journal = {{H}ydrology and {E}arth {S}ystem {S}ciences},
  volume = {16},
  numero = {9},
  pages = {3127--3137},
  ISSN = {1027-5606},
  year = {2012},
  DOI = {10.5194/hess-16-3127-2012},
  URL = {https://www.documentation.ird.fr/hor/fdi:010057339},
}