@article{fdi:010094301,
  title = {{C}ontrasting short-term dynamics of supraglacial ponds along the {H}indu {K}ush-{H}imalaya revealed by {P}lanet{S}cope imagery and deep learning},
  author = {{X}u, {X}. {Y}. and {L}iu, {L}. and {H}uang, {L}. {C}. and {H}u, {Y}. and {Z}hang, {G}. {Q}. and {R}acoviteanu, {A}dina and {L}iu, {E}. {V}. and {C}han, {Y}. {A}.},
  editor = {},
  language = {{ENG}},
  abstract = {{A}n increasing number of supraglacial ponds have formed and expanded on the surface of debris-covered glaciers across the {H}indu {K}ush-{H}imalaya ({HKH}) mountain range in the last decades. {D}espite the pronounced spatiotemporal variability observed in supraglacial ponds at annual and decadal scales, investigations of their seasonal changes are limited over large spatial scales. {T}hese investigations are critical for evaluating their impacts on glacier ablation and dynamics and predicting water resource availability. {H}ere, we produced detailed seasonal maps of supraglacial ponds at five sites of the {HKH} for the years 2017 to 2022 using a deep-learning-based mapping method applied to {P}lanet{S}cope imagery. {U}sing these maps, we investigate pond seasonality and interannual variability. {W}e found that (1) the average pond number and percentage ponded area over the debriscover area were higher in the {C}entral {H}imalaya (417, 1.55%) and {E}astern {H}imalaya (481, 1.93%) compared to those in the {H}indu {K}ush (142, 0.20%) and {W}estern {H}imalaya (153, 0.19%); (2) pond percentage area over debris-cover area showed an increase in the {K}arakoram (+0.2% in an absolute sense), {C}entral {H}imalaya (+0.6%) between 2017 and 2020, and {E}astern {H}imalaya (+0.9%) between 2018 to 2021; (3) supraglacial ponds reached their peak at the onset of the ablation season ({M}ay-{J}une) in the {K}arakoram and the {H}indu {K}ush, during the premonsoon season in the {W}estern and {C}entral {H}imalaya, and during the monsoon or post-monsoon period in the {E}astern {H}imalaya; (4) the {C}entral {H}imalaya displayed a highest occurrence of persistent ponds (17.2%), while only 4.3% of supraglacial ponds in the {K}arakoram were persistent. {O}ur results provide a spatially diverse and temporally detailed dataset that serves to advance the understanding of supraglacial pond dynamics across the {H}indu {K}ush-{H}imalaya.},
  keywords = {{S}upraglacial ponds ; {D}eep learning ; {P}lanet{S}cope imagery ; {G}laciers ; {H}indu ; {K}ush-{H}imalaya ; {HIMALAYA} ; {HINDOU} {KOUCH} ; {KARAKORAM}},
  booktitle = {},
  journal = {{G}lobal and {P}lanetary {C}hange},
  volume = {253},
  numero = {},
  pages = {104949 [17 p.]},
  ISSN = {0921-8181},
  year = {2025},
  DOI = {10.1016/j.gloplacha.2025.104949},
  URL = {https://www.documentation.ird.fr/hor/fdi:010094301},
}