@article{fdi:010093575,
  title = {{S}ensitivity of lumped and semi-distributed hydrological models to 20 gridded precipitation products in a transboundary basin},
  author = {{P}acheco, {M}. {P}. {L}. and {S}atg{\'e}, {F}r{\'e}d{\'e}ric and {B}onnet, {M}arie-{P}aule and {M}olina-{C}arpio, {J}. and {Z}olá, {R}. {P}. and {R}amírez, {E}. and {E}spinoza-{R}omero, {D}. and {H}ostache, {R}enaud},
  editor = {},
  language = {{ENG}},
  abstract = {{T}his study proposes a dual approach to assess 20 {G}ridded {P}recipitation {P}roducts ({GPP}s) within a transboundary region with complex topography. {GPP}s were first compared with observed precipitation to assess their spatiotemporal accuracy. {T}hey were then integrated into a lumped ({GR}4{J}) and a semi-distributed ({MGB}-{IPH}) hydrological model to evaluate their impact on streamflow simulations for three basins. {E}ven if most {GPP}s effectively captured the dominant north-south precipitation gradient shaped by the {A}ndean topography, the results show significant variations in {GPP} effectiveness across the considered basins. {T}he most reliable {GPP}s for streamflow simulation across {K}atari, {I}lave, and {R}amis basins are {MSWEP}, {CHIRPS}, and {MSWEP} when considering the lumped {GR}4{J} model and {SM}2{R}ain_{CCI}, {IMERG}_{FR}, and {SM}2{R}ain_{CCI} when considering the semi-distributed {MGB} model. {T}his discrepancy among the models shows that {GPP}s' reliability assessment is sensitive to the model structure and that different conclusions could be made according to the selected model. {O}ur findings show that the {GR}4j lumped model is barely influenced by precipitation bias due to its buffering capacity. {I}n contrast, the semi-distributed {MGB}-{IPH} model is sensitive to precipitation bias in space and time and therefore is more suitable to reveal {GPP} inconsistencies. {O}verall, this study not only provides {GPP} reliability feedback but also new insights on the respective limits and advantages of different assessment methods (i.e., gauges, lumped and semidistributed models). {T}hese findings support the development of a practical framework for {GPP} selection according to the forecast use.},
  keywords = {{T}ransboundary basin ; {G}ridded precipitation ; {L}umped hydrological model ; {S}emi-distributed hydrological model ; {T}iticaca basin ; {PEROU} ; {BOLIVIE} ; {CHILI} ; {TITICACA} {BASSIN}},
  booktitle = {},
  journal = {{J}ournal of {H}ydrology},
  volume = {660},
  numero = {{B}},
  pages = {133462 [16 p.]},
  ISSN = {0022-1694},
  year = {2025},
  DOI = {10.1016/j.jhydrol.2025.133462},
  URL = {https://www.documentation.ird.fr/hor/fdi:010093575},
}