---
_id: '12584'
abstract:
- lang: eng
  text: This project explored the integrated use of satellite, ground observations
    and hydrological distributed models to support water resources assessment and
    monitoring in High Mountain Asia (HMA). Hydrological data products were generated
    taking advantage of the synergies of European and Chinese data assets and space-borne
    observation systems. Energy-budget-based glacier mass balance and hydrological
    models driven by satellite observations were developed. These models can be applied
    to describe glacier-melt contribution to river flow. Satellite hydrological data
    products were used for forcing, calibration, validation and data assimilation
    in distributed river basin models. A pilot study was carried out on the Red River
    basin. Multiple hydrological data products were generated using the data collected
    by Chinese satellites. A new Evapo-Transpiration (ET) dataset from 2000 to 2018
    was generated, including plant transpiration, soil evaporation, rainfall interception
    loss, snow/ice sublimation and open water evaporation. Higher resolution data
    were used to characterize glaciers and their response to environmental forcing.
    These studies focused on the Parlung Zangbo Basin, where glacier facies were mapped
    with GaoFeng (GF), Sentinal-2/Multi-Spectral Imager (S2/MSI) and Landsat8/Operational
    Land Imager (L8/OLI) data. The geodetic mass balance was estimated between 2000
    and 2017 with Zi-Yuan (ZY)-3 Stereo Images and the SRTM DEM. Surface velocity
    was studied with Landsat5/Thematic Mapper (L5/TM), L8/OLI and S2/MSI data over
    the period 2013–2019. An updated method was developed to improve the retrieval
    of glacier albedo by correcting glacier reflectance for anisotropy, and a new
    dataset on glacier albedo was generated for the period 2001–2020. A detailed glacier
    energy and mass balance model was developed with the support of field experiments
    at the Parlung No. 4 Glacier and the 24 K Glacier, both in the Tibetan Plateau.
    Besides meteorological measurements, the field experiments included glaciological
    and hydrological measurements. The energy balance model was formulated in terms
    of enthalpy for easier treatment of water phase transitions. The model was applied
    to assess the spatial variability in glacier melt. In the Parlung No. 4 Glacier,
    the accumulated glacier melt was between 1.5 and 2.5 m w.e. in the accumulation
    zone and between 4.5 and 6.0 m w.e. in the ablation zone, reaching 6.5 m w.e.
    at the terminus. The seasonality in the glacier mass balance was observed by combining
    intensive field campaigns with continuous automatic observations. The linkage
    of the glacier and snowpack mass balance with water resources in a river basin
    was analyzed in the Chiese (Italy) and Heihe (China) basins by developing and
    applying integrated hydrological models using satellite retrievals in multiple
    ways. The model FEST-WEB was calibrated using retrievals of Land Surface Temperature
    (LST) to map soil hydrological properties. A watershed model was developed by
    coupling ecohydrological and socioeconomic systems. Integrated modeling is supported
    by an updated and parallelized data assimilation system. The latter exploits retrievals
    of brightness temperature (Advanced Microwave Scanning Radiometer, AMSR), LST
    (Moderate Resolution Imaging Spectroradiometer, MODIS), precipitation (Tropical
    Rainfall Measuring Mission (TRMM) and FengYun (FY)-2D) and in-situ measurements.
    In the case study on the Red River Basin, a new algorithm has been applied to
    disaggregate the SMOS (Soil Moisture and Ocean Salinity) soil moisture retrievals
    by making use of the correlation between evaporative fraction and soil moisture.
article_number: '5122'
article_processing_charge: No
article_type: letter_note
author:
- first_name: Massimo
  full_name: Menenti, Massimo
  last_name: Menenti
- first_name: Xin
  full_name: Li, Xin
  last_name: Li
- first_name: Li
  full_name: Jia, Li
  last_name: Jia
- first_name: Kun
  full_name: Yang, Kun
  last_name: Yang
- first_name: Francesca
  full_name: Pellicciotti, Francesca
  id: b28f055a-81ea-11ed-b70c-a9fe7f7b0e70
  last_name: Pellicciotti
- first_name: Marco
  full_name: Mancini, Marco
  last_name: Mancini
- first_name: Jiancheng
  full_name: Shi, Jiancheng
  last_name: Shi
- first_name: Maria José
  full_name: Escorihuela, Maria José
  last_name: Escorihuela
- first_name: Chaolei
  full_name: Zheng, Chaolei
  last_name: Zheng
- first_name: Qiting
  full_name: Chen, Qiting
  last_name: Chen
- first_name: Jing
  full_name: Lu, Jing
  last_name: Lu
- first_name: Jie
  full_name: Zhou, Jie
  last_name: Zhou
- first_name: Guangcheng
  full_name: Hu, Guangcheng
  last_name: Hu
- first_name: Shaoting
  full_name: Ren, Shaoting
  last_name: Ren
- first_name: Jing
  full_name: Zhang, Jing
  last_name: Zhang
- first_name: Qinhuo
  full_name: Liu, Qinhuo
  last_name: Liu
- first_name: Yubao
  full_name: Qiu, Yubao
  last_name: Qiu
- first_name: Chunlin
  full_name: Huang, Chunlin
  last_name: Huang
- first_name: Ji
  full_name: Zhou, Ji
  last_name: Zhou
- first_name: Xujun
  full_name: Han, Xujun
  last_name: Han
- first_name: Xiaoduo
  full_name: Pan, Xiaoduo
  last_name: Pan
- first_name: Hongyi
  full_name: Li, Hongyi
  last_name: Li
- first_name: Yerong
  full_name: Wu, Yerong
  last_name: Wu
- first_name: Baohong
  full_name: Ding, Baohong
  last_name: Ding
- first_name: Wei
  full_name: Yang, Wei
  last_name: Yang
- first_name: Pascal
  full_name: Buri, Pascal
  last_name: Buri
- first_name: Michael J.
  full_name: McCarthy, Michael J.
  last_name: McCarthy
- first_name: Evan S.
  full_name: Miles, Evan S.
  last_name: Miles
- first_name: Thomas E.
  full_name: Shaw, Thomas E.
  last_name: Shaw
- first_name: Chunfeng
  full_name: Ma, Chunfeng
  last_name: Ma
- first_name: Yanzhao
  full_name: Zhou, Yanzhao
  last_name: Zhou
- first_name: Chiara
  full_name: Corbari, Chiara
  last_name: Corbari
- first_name: Rui
  full_name: Li, Rui
  last_name: Li
- first_name: Tianjie
  full_name: Zhao, Tianjie
  last_name: Zhao
- first_name: Vivien
  full_name: Stefan, Vivien
  last_name: Stefan
- first_name: Qi
  full_name: Gao, Qi
  last_name: Gao
- first_name: Jingxiao
  full_name: Zhang, Jingxiao
  last_name: Zhang
- first_name: Qiuxia
  full_name: Xie, Qiuxia
  last_name: Xie
- first_name: Ning
  full_name: Wang, Ning
  last_name: Wang
- first_name: Yibo
  full_name: Sun, Yibo
  last_name: Sun
- first_name: Xinyu
  full_name: Mo, Xinyu
  last_name: Mo
- first_name: Junru
  full_name: Jia, Junru
  last_name: Jia
- first_name: Achille Pierre
  full_name: Jouberton, Achille Pierre
  last_name: Jouberton
- first_name: Marin
  full_name: Kneib, Marin
  last_name: Kneib
- first_name: Stefan
  full_name: Fugger, Stefan
  last_name: Fugger
- first_name: Nicola
  full_name: Paciolla, Nicola
  last_name: Paciolla
- first_name: Giovanni
  full_name: Paolini, Giovanni
  last_name: Paolini
citation:
  ama: Menenti M, Li X, Jia L, et al. Multi-source hydrological data products to monitor
    High Asian river basins and regional water security. <i>Remote Sensing</i>. 2021;13(24).
    doi:<a href="https://doi.org/10.3390/rs13245122">10.3390/rs13245122</a>
  apa: Menenti, M., Li, X., Jia, L., Yang, K., Pellicciotti, F., Mancini, M., … Paolini,
    G. (2021). Multi-source hydrological data products to monitor High Asian river
    basins and regional water security. <i>Remote Sensing</i>. MDPI. <a href="https://doi.org/10.3390/rs13245122">https://doi.org/10.3390/rs13245122</a>
  chicago: Menenti, Massimo, Xin Li, Li Jia, Kun Yang, Francesca Pellicciotti, Marco
    Mancini, Jiancheng Shi, et al. “Multi-Source Hydrological Data Products to Monitor
    High Asian River Basins and Regional Water Security.” <i>Remote Sensing</i>. MDPI,
    2021. <a href="https://doi.org/10.3390/rs13245122">https://doi.org/10.3390/rs13245122</a>.
  ieee: M. Menenti <i>et al.</i>, “Multi-source hydrological data products to monitor
    High Asian river basins and regional water security,” <i>Remote Sensing</i>, vol.
    13, no. 24. MDPI, 2021.
  ista: Menenti M, Li X, Jia L, Yang K, Pellicciotti F, Mancini M, Shi J, Escorihuela
    MJ, Zheng C, Chen Q, Lu J, Zhou J, Hu G, Ren S, Zhang J, Liu Q, Qiu Y, Huang C,
    Zhou J, Han X, Pan X, Li H, Wu Y, Ding B, Yang W, Buri P, McCarthy MJ, Miles ES,
    Shaw TE, Ma C, Zhou Y, Corbari C, Li R, Zhao T, Stefan V, Gao Q, Zhang J, Xie
    Q, Wang N, Sun Y, Mo X, Jia J, Jouberton AP, Kneib M, Fugger S, Paciolla N, Paolini
    G. 2021. Multi-source hydrological data products to monitor High Asian river basins
    and regional water security. Remote Sensing. 13(24), 5122.
  mla: Menenti, Massimo, et al. “Multi-Source Hydrological Data Products to Monitor
    High Asian River Basins and Regional Water Security.” <i>Remote Sensing</i>, vol.
    13, no. 24, 5122, MDPI, 2021, doi:<a href="https://doi.org/10.3390/rs13245122">10.3390/rs13245122</a>.
  short: M. Menenti, X. Li, L. Jia, K. Yang, F. Pellicciotti, M. Mancini, J. Shi,
    M.J. Escorihuela, C. Zheng, Q. Chen, J. Lu, J. Zhou, G. Hu, S. Ren, J. Zhang,
    Q. Liu, Y. Qiu, C. Huang, J. Zhou, X. Han, X. Pan, H. Li, Y. Wu, B. Ding, W. Yang,
    P. Buri, M.J. McCarthy, E.S. Miles, T.E. Shaw, C. Ma, Y. Zhou, C. Corbari, R.
    Li, T. Zhao, V. Stefan, Q. Gao, J. Zhang, Q. Xie, N. Wang, Y. Sun, X. Mo, J. Jia,
    A.P. Jouberton, M. Kneib, S. Fugger, N. Paciolla, G. Paolini, Remote Sensing 13
    (2021).
date_created: 2023-02-20T08:10:49Z
date_published: 2021-12-16T00:00:00Z
date_updated: 2023-02-28T13:26:53Z
day: '16'
doi: 10.3390/rs13245122
extern: '1'
intvolume: '        13'
issue: '24'
keyword:
- General Earth and Planetary Sciences
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.3390/rs13245122
month: '12'
oa: 1
oa_version: Published Version
publication: Remote Sensing
publication_identifier:
  issn:
  - 2072-4292
publication_status: published
publisher: MDPI
quality_controlled: '1'
scopus_import: '1'
status: public
title: Multi-source hydrological data products to monitor High Asian river basins
  and regional water security
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2021'
...
---
_id: '12591'
abstract:
- lang: eng
  text: 'Glacier albedo determines the net shortwave radiation absorbed at the glacier
    surface and plays a crucial role in glacier energy and mass balance. Remote sensing
    techniques are efficient means to retrieve glacier surface albedo over large and
    inaccessible areas and to study its variability. However, corrections of anisotropic
    reflectance of glacier surface have been established for specific shortwave bands
    only, such as Landsat 5 Thematic Mapper (L5/TM) band 2 and band 4, which is a
    major limitation of current retrievals of glacier broadband albedo. In this study,
    we calibrated and evaluated four anisotropy correction models for glacier snow
    and ice, applicable to visible, near-infrared and shortwave-infrared wavelengths
    using airborne datasets of Bidirectional Reflectance Distribution Function (BRDF).
    We then tested the ability of the best-performing anisotropy correction model,
    referred to from here on as the ‘updated model’, to retrieve albedo from L5/TM,
    Landsat 8 Operational Land Imager (L8/OLI) and Moderate Resolution Imaging Spectroradiometer
    (MODIS) imagery, and evaluated these results with field measurements collected
    on eight glaciers around the world. Our results show that the updated model: (1)
    can accurately estimate anisotropic factors of reflectance for snow and ice surfaces;
    (2) generally performs better than prior approaches for L8/OLI albedo retrieval
    but is not appropriate for L5/TM; (3) generally retrieves MODIS albedo better
    than the MODIS standard albedo product (MCD43A3) in both absolute values and glacier
    albedo temporal evolution, i.e., exhibiting both fewer gaps and better agreement
    with field observations. As the updated model enables anisotropy correction of
    a maximum of 10 multispectral bands and is implemented in Google Earth Engine
    (GEE), it is promising for observing and analyzing glacier albedo at large spatial
    scales.'
article_number: '1714'
article_processing_charge: No
article_type: original
author:
- first_name: Shaoting
  full_name: Ren, Shaoting
  last_name: Ren
- first_name: Evan S.
  full_name: Miles, Evan S.
  last_name: Miles
- first_name: Li
  full_name: Jia, Li
  last_name: Jia
- first_name: Massimo
  full_name: Menenti, Massimo
  last_name: Menenti
- first_name: Marin
  full_name: Kneib, Marin
  last_name: Kneib
- first_name: Pascal
  full_name: Buri, Pascal
  last_name: Buri
- first_name: Michael J.
  full_name: McCarthy, Michael J.
  last_name: McCarthy
- first_name: Thomas E.
  full_name: Shaw, Thomas E.
  last_name: Shaw
- first_name: Wei
  full_name: Yang, Wei
  last_name: Yang
- first_name: Francesca
  full_name: Pellicciotti, Francesca
  id: b28f055a-81ea-11ed-b70c-a9fe7f7b0e70
  last_name: Pellicciotti
citation:
  ama: Ren S, Miles ES, Jia L, et al. Anisotropy parameterization development and
    evaluation for glacier surface albedo retrieval from satellite observations. <i>Remote
    Sensing</i>. 2021;13(9). doi:<a href="https://doi.org/10.3390/rs13091714">10.3390/rs13091714</a>
  apa: Ren, S., Miles, E. S., Jia, L., Menenti, M., Kneib, M., Buri, P., … Pellicciotti,
    F. (2021). Anisotropy parameterization development and evaluation for glacier
    surface albedo retrieval from satellite observations. <i>Remote Sensing</i>. MDPI.
    <a href="https://doi.org/10.3390/rs13091714">https://doi.org/10.3390/rs13091714</a>
  chicago: Ren, Shaoting, Evan S. Miles, Li Jia, Massimo Menenti, Marin Kneib, Pascal
    Buri, Michael J. McCarthy, Thomas E. Shaw, Wei Yang, and Francesca Pellicciotti.
    “Anisotropy Parameterization Development and Evaluation for Glacier Surface Albedo
    Retrieval from Satellite Observations.” <i>Remote Sensing</i>. MDPI, 2021. <a
    href="https://doi.org/10.3390/rs13091714">https://doi.org/10.3390/rs13091714</a>.
  ieee: S. Ren <i>et al.</i>, “Anisotropy parameterization development and evaluation
    for glacier surface albedo retrieval from satellite observations,” <i>Remote Sensing</i>,
    vol. 13, no. 9. MDPI, 2021.
  ista: Ren S, Miles ES, Jia L, Menenti M, Kneib M, Buri P, McCarthy MJ, Shaw TE,
    Yang W, Pellicciotti F. 2021. Anisotropy parameterization development and evaluation
    for glacier surface albedo retrieval from satellite observations. Remote Sensing.
    13(9), 1714.
  mla: Ren, Shaoting, et al. “Anisotropy Parameterization Development and Evaluation
    for Glacier Surface Albedo Retrieval from Satellite Observations.” <i>Remote Sensing</i>,
    vol. 13, no. 9, 1714, MDPI, 2021, doi:<a href="https://doi.org/10.3390/rs13091714">10.3390/rs13091714</a>.
  short: S. Ren, E.S. Miles, L. Jia, M. Menenti, M. Kneib, P. Buri, M.J. McCarthy,
    T.E. Shaw, W. Yang, F. Pellicciotti, Remote Sensing 13 (2021).
date_created: 2023-02-20T08:12:06Z
date_published: 2021-04-28T00:00:00Z
date_updated: 2023-02-28T12:51:10Z
day: '28'
doi: 10.3390/rs13091714
extern: '1'
intvolume: '        13'
issue: '9'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.3390/rs13091714
month: '04'
oa: 1
oa_version: Published Version
publication: Remote Sensing
publication_identifier:
  issn:
  - 2072-4292
publication_status: published
publisher: MDPI
quality_controlled: '1'
scopus_import: '1'
status: public
title: Anisotropy parameterization development and evaluation for glacier surface
  albedo retrieval from satellite observations
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2021'
...
---
_id: '12595'
abstract:
- lang: eng
  text: The seasonal dynamic changes of Tibetan glaciers have seen little prior investigation,
    despite the increase in geodetic studies of multi-year changes. This study compares
    seasonal glacier dynamics (“cold” and “warm” seasons) in the ablation zone of
    Parlung No. 4 Glacier, a temperate glacier in the monsoon-influenced southeastern
    Tibetan Plateau, by using repeat unpiloted aerial vehicle (UAV) surveys combined
    with Structure-from-Motion (SfM) photogrammetry and ground stake measurements.
    Our results showed that the surveyed ablation zone had a mean change of −2.7 m
    of ice surface elevation during the period of September 2018 to October 2019 but
    is characterized by significant seasonal cyclic variations with ice surface elevation
    lifting (+2.0 m) in the cold season (September 2018 to June 2019) but lowering
    (−4.7 m) in the warm season (June 2019 to October 2019). Over an annual timescale,
    surface lowering was greatly suppressed by the resupply of ice from the glacier’s
    accumulation area—the annual emergence velocity compensates for about 55% of surface
    ablation in our study area. Cold season emergence velocities (3.0 ± 1.2 m) were
    ~5-times larger than those observed in the warm season (0.6 ± 1.0 m). Distinct
    spring precipitation patterns may contribute to these distinct seasonal signals.
    Such seasonal dynamic conditions are possibly critical for different glacier responses
    to climate change in this region of the Tibetan Plateau, and perhaps further afield.
article_number: '2389'
article_processing_charge: No
article_type: original
author:
- first_name: Wei
  full_name: Yang, Wei
  last_name: Yang
- first_name: Chuanxi
  full_name: Zhao, Chuanxi
  last_name: Zhao
- first_name: Matthew
  full_name: Westoby, Matthew
  last_name: Westoby
- first_name: Tandong
  full_name: Yao, Tandong
  last_name: Yao
- first_name: Yongjie
  full_name: Wang, Yongjie
  last_name: Wang
- first_name: Francesca
  full_name: Pellicciotti, Francesca
  id: b28f055a-81ea-11ed-b70c-a9fe7f7b0e70
  last_name: Pellicciotti
- first_name: Jianmin
  full_name: Zhou, Jianmin
  last_name: Zhou
- first_name: Zhen
  full_name: He, Zhen
  last_name: He
- first_name: Evan
  full_name: Miles, Evan
  last_name: Miles
citation:
  ama: Yang W, Zhao C, Westoby M, et al. Seasonal dynamics of a temperate Tibetan
    glacier revealed by high-resolution UAV photogrammetry and in situ measurements.
    <i>Remote Sensing</i>. 2020;12(15). doi:<a href="https://doi.org/10.3390/rs12152389">10.3390/rs12152389</a>
  apa: Yang, W., Zhao, C., Westoby, M., Yao, T., Wang, Y., Pellicciotti, F., … Miles,
    E. (2020). Seasonal dynamics of a temperate Tibetan glacier revealed by high-resolution
    UAV photogrammetry and in situ measurements. <i>Remote Sensing</i>. MDPI. <a href="https://doi.org/10.3390/rs12152389">https://doi.org/10.3390/rs12152389</a>
  chicago: Yang, Wei, Chuanxi Zhao, Matthew Westoby, Tandong Yao, Yongjie Wang, Francesca
    Pellicciotti, Jianmin Zhou, Zhen He, and Evan Miles. “Seasonal Dynamics of a Temperate
    Tibetan Glacier Revealed by High-Resolution UAV Photogrammetry and in Situ Measurements.”
    <i>Remote Sensing</i>. MDPI, 2020. <a href="https://doi.org/10.3390/rs12152389">https://doi.org/10.3390/rs12152389</a>.
  ieee: W. Yang <i>et al.</i>, “Seasonal dynamics of a temperate Tibetan glacier revealed
    by high-resolution UAV photogrammetry and in situ measurements,” <i>Remote Sensing</i>,
    vol. 12, no. 15. MDPI, 2020.
  ista: Yang W, Zhao C, Westoby M, Yao T, Wang Y, Pellicciotti F, Zhou J, He Z, Miles
    E. 2020. Seasonal dynamics of a temperate Tibetan glacier revealed by high-resolution
    UAV photogrammetry and in situ measurements. Remote Sensing. 12(15), 2389.
  mla: Yang, Wei, et al. “Seasonal Dynamics of a Temperate Tibetan Glacier Revealed
    by High-Resolution UAV Photogrammetry and in Situ Measurements.” <i>Remote Sensing</i>,
    vol. 12, no. 15, 2389, MDPI, 2020, doi:<a href="https://doi.org/10.3390/rs12152389">10.3390/rs12152389</a>.
  short: W. Yang, C. Zhao, M. Westoby, T. Yao, Y. Wang, F. Pellicciotti, J. Zhou,
    Z. He, E. Miles, Remote Sensing 12 (2020).
date_created: 2023-02-20T08:12:29Z
date_published: 2020-07-24T00:00:00Z
date_updated: 2023-02-28T12:36:22Z
day: '24'
doi: 10.3390/rs12152389
extern: '1'
intvolume: '        12'
issue: '15'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.3390/rs12152389
month: '07'
oa: 1
oa_version: Published Version
publication: Remote Sensing
publication_identifier:
  issn:
  - 2072-4292
publication_status: published
publisher: MDPI
quality_controlled: '1'
scopus_import: '1'
status: public
title: Seasonal dynamics of a temperate Tibetan glacier revealed by high-resolution
  UAV photogrammetry and in situ measurements
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 12
year: '2020'
...