---
_id: '15298'
abstract:
- lang: eng
text: Mountains are important suppliers of freshwater to downstream areas, affecting
large populations in particular in High Mountain Asia (HMA). Yet, the propagation
of water from HMA headwaters to downstream areas is not fully understood, as interactions
in the mountain water cycle between the cryo-, hydro- and biosphere remain elusive.
We review the definition of blue and green water fluxes as liquid water that contributes
to runoff at the outlet of the selected domain (blue) and water lost to the atmosphere
through vapor fluxes, that is evaporation from water, ground, and interception
plus transpiration (green) and propose to add the term white water to account
for the (often neglected) evaporation and sublimation from snow and ice. We provide
an assessment of models that can simulate the cryo-hydro-biosphere continuum and
the interactions between spheres in high mountain catchments, going beyond disciplinary
separations. Land surface models are uniquely able to account for such complexity,
since they solve the coupled fluxes of water, energy, and carbon between the land
surface and atmosphere. Due to the mechanistic nature of such models, specific
variables can be compared systematically to independent remote sensing observations
– providing vital insights into model accuracy and enabling the understanding
of the complex watersheds of HMA. We discuss recent developments in spaceborne
earth observation products that have the potential to support catchment modeling
in high mountain regions. We then present a pilot study application of the mechanistic
land surface model Tethys & Chloris to a glacierized watershed in the Nepalese
Himalayas and discuss the use of high-resolution earth observation data to constrain
the meteorological forcing uncertainty and validate model results. We use these
insights to highlight the remaining challenges and future opportunities that remote
sensing data presents for land surface modeling in HMA.
acknowledgement: 'This work was supported by the ESA and NRSCC Dragon 5 cooperation
project “Cryosphere-hydrosphere interactions of the Asian water towers: using remote
sensing to drive hyper-resolution ecohydrological modelling” [Grant no. 59199].
PB and FP acknowledge funding from the SNSF (High-elevation precipitation in High
Mountain Asia, HOPE)) [Grant no. 183633]. ESM, MK, SFu and FP acknowledge funding
from the ERC under the European Union’s Horizon 2020 research and innovation program
(Rapid mass losses of debris-covered glaciers in High Mountain Asia, RAVEN) [Grant
no. 772751]. LJ, CZ and MMe acknowledge the Second Tibetan Plateau Scientific Expedition
and Research Program (STEP) [grant no. 2019QZKK010308, no. 2019QZKK0206], the National
Natural Science Foundation of China projects (Grant no. 42171039, no. 91737205),
the Chinese Academy of Sciences President’s International Fellowship Initiative
[Grant no. 2020VTA0001], and the MOST High-Level Foreign Expert Program [Grant no.
G2022055010L].'
article_processing_charge: Yes
article_type: original
author:
- first_name: Pascal
full_name: Buri, Pascal
last_name: Buri
- first_name: Simone
full_name: Fatichi, Simone
last_name: Fatichi
- first_name: Thomas
full_name: Shaw, Thomas
id: 3caa3f91-1f03-11ee-96ce-e0e553054d6e
last_name: Shaw
orcid: 0000-0001-7640-6152
- first_name: Catriona Louise
full_name: Fyffe, Catriona Louise
id: 001b0422-8d15-11ed-bc51-cab6c037a228
last_name: Fyffe
- first_name: Evan S.
full_name: Miles, Evan S.
last_name: Miles
- first_name: Michael
full_name: Mccarthy, Michael
id: 22a2674a-61ce-11ee-94b5-d18813baf16f
last_name: Mccarthy
- first_name: Marin
full_name: Kneib, Marin
last_name: Kneib
- first_name: Shaoting
full_name: Ren, Shaoting
last_name: Ren
- first_name: Achille
full_name: Jouberton, Achille
last_name: Jouberton
- first_name: Stefan
full_name: Fugger, Stefan
last_name: Fugger
- first_name: Li
full_name: Jia, Li
last_name: Jia
- first_name: Jing
full_name: Zhang, Jing
last_name: Zhang
- first_name: Cong
full_name: Shen, Cong
last_name: Shen
- first_name: Chaolei
full_name: Zheng, Chaolei
last_name: Zheng
- first_name: Massimo
full_name: Menenti, Massimo
last_name: Menenti
- first_name: Francesca
full_name: Pellicciotti, Francesca
id: b28f055a-81ea-11ed-b70c-a9fe7f7b0e70
last_name: Pellicciotti
orcid: 0000-0002-5554-8087
citation:
ama: 'Buri P, Fatichi S, Shaw T, et al. Land surface modeling informed by earth
observation data: Toward understanding blue–green–white water fluxes in High Mountain
Asia. Geo-Spatial Information Science. 2024;27(3):703-727. doi:10.1080/10095020.2024.2330546'
apa: 'Buri, P., Fatichi, S., Shaw, T., Fyffe, C. L., Miles, E. S., McCarthy, M.,
… Pellicciotti, F. (2024). Land surface modeling informed by earth observation
data: Toward understanding blue–green–white water fluxes in High Mountain Asia.
Geo-Spatial Information Science. Taylor & Francis. https://doi.org/10.1080/10095020.2024.2330546'
chicago: 'Buri, Pascal, Simone Fatichi, Thomas Shaw, Catriona Louise Fyffe, Evan
S. Miles, Michael McCarthy, Marin Kneib, et al. “Land Surface Modeling Informed
by Earth Observation Data: Toward Understanding Blue–Green–White Water Fluxes
in High Mountain Asia.” Geo-Spatial Information Science. Taylor & Francis,
2024. https://doi.org/10.1080/10095020.2024.2330546.'
ieee: 'P. Buri et al., “Land surface modeling informed by earth observation
data: Toward understanding blue–green–white water fluxes in High Mountain Asia,”
Geo-Spatial Information Science, vol. 27, no. 3. Taylor & Francis,
pp. 703–727, 2024.'
ista: 'Buri P, Fatichi S, Shaw T, Fyffe CL, Miles ES, McCarthy M, Kneib M, Ren S,
Jouberton A, Fugger S, Jia L, Zhang J, Shen C, Zheng C, Menenti M, Pellicciotti
F. 2024. Land surface modeling informed by earth observation data: Toward understanding
blue–green–white water fluxes in High Mountain Asia. Geo-Spatial Information Science.
27(3), 703–727.'
mla: 'Buri, Pascal, et al. “Land Surface Modeling Informed by Earth Observation
Data: Toward Understanding Blue–Green–White Water Fluxes in High Mountain Asia.”
Geo-Spatial Information Science, vol. 27, no. 3, Taylor & Francis,
2024, pp. 703–27, doi:10.1080/10095020.2024.2330546.'
short: P. Buri, S. Fatichi, T. Shaw, C.L. Fyffe, E.S. Miles, M. McCarthy, M. Kneib,
S. Ren, A. Jouberton, S. Fugger, L. Jia, J. Zhang, C. Shen, C. Zheng, M. Menenti,
F. Pellicciotti, Geo-Spatial Information Science 27 (2024) 703–727.
date_created: 2024-04-07T22:00:56Z
date_published: 2024-03-22T00:00:00Z
date_updated: 2025-09-04T13:28:38Z
day: '22'
ddc:
- '550'
department:
- _id: FrPe
doi: 10.1080/10095020.2024.2330546
external_id:
isi:
- '001189470100001'
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creator: dernst
date_created: 2024-07-29T11:34:54Z
date_updated: 2024-07-29T11:34:54Z
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language:
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license: https://creativecommons.org/licenses/by/4.0/
month: '03'
oa: 1
oa_version: Published Version
page: 703-727
publication: Geo-Spatial Information Science
publication_identifier:
issn:
- 1009-5020
publication_status: published
publisher: Taylor & Francis
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Land surface modeling informed by earth observation data: Toward understanding
blue–green–white water fluxes in High Mountain Asia'
tmp:
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legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 27
year: '2024'
...