Modelling glacier variation and its impact on water resource in the Urumqi Glacier No. 1 in Central Asia
(2018) In Science of the Total Environment 644. p.1160-1170- Abstract
Climate warming is expected to accelerate glacier retreat and shift hydrological regime, which poses great threat to regional water resources in terms of amount, variability, and quality. This is especially true in arid regions with glaciers such as the Central Asia. However, few models manage to mimic both glacier runoff and surface changes with adequate performance. To narrow this gap, we integrated a spatially distributed hydrological model (FLEX G ) and a glacier retreat model (∆h-parameterization), and tested the new model in the Urumqi Glacier No. 1 catchment, which is best monitored in China. The model inputs include climate forcing,... (More)
Climate warming is expected to accelerate glacier retreat and shift hydrological regime, which poses great threat to regional water resources in terms of amount, variability, and quality. This is especially true in arid regions with glaciers such as the Central Asia. However, few models manage to mimic both glacier runoff and surface changes with adequate performance. To narrow this gap, we integrated a spatially distributed hydrological model (FLEX G ) and a glacier retreat model (∆h-parameterization), and tested the new model in the Urumqi Glacier No. 1 catchment, which is best monitored in China. The model inputs include climate forcing, topographic map and initial ice thickness. Here we validated the model with runoff observation at downstream and glacier measurements, i.e. three historical glacier area maps (1980, 1994 and 2002), annual glacier mass balance (GMB) and equilibrium line altitude (ELA). Results show that the FLEX G -∆h model performed well in estimating runoff (with Kling-Gupta efficiency 0.75 for hydrograph) and reproducing historical glacier area variation. Additionally the model generated reasonably spatial distribution of glacier thickness, which is important to examine glacier evolution at the Urumqi Glacier No. 1. Subsequently we ran the model forced by 12 combinations of two climate scenarios and six bias correction methods to assess the impact of climate change on glacier thinning, retreat, and its influence on water resource. The impact assessment shows that glacier area will lose up to a half (54%) of their 1980 extent in 2050, and up to 80% in 2100; while ice volume will decrease up to 79% in 2050, and 92% in 2100. The tipping point (peak water) of glacier melt supply was projected to occur around 2020 and then runoff would decrease significantly. These results alert us that there is a need for immediate mitigation measures to adapt to fast glacier change to assure long-term water security in this region.
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- author
- Gao, Hongkai ; Li, Hong ; Duan, Zheng LU ; Ren, Ze ; Meng, Xiaoyu and Pan, Xicai
- publishing date
- 2018-12-10
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- China, Climate change, FLEX hydrological model, Glacier retreat model, The Urumqi Glacier No. 1 catchment, Water resources
- in
- Science of the Total Environment
- volume
- 644
- pages
- 11 pages
- publisher
- Elsevier
- external identifiers
-
- scopus:85049732755
- pmid:30743829
- ISSN
- 0048-9697
- DOI
- 10.1016/j.scitotenv.2018.07.004
- language
- English
- LU publication?
- no
- id
- 83ccf7d7-8e85-48ed-88d8-da3455fea4ce
- date added to LUP
- 2019-12-22 20:17:52
- date last changed
- 2024-06-13 09:37:54
@article{83ccf7d7-8e85-48ed-88d8-da3455fea4ce,
abstract = {{<p> Climate warming is expected to accelerate glacier retreat and shift hydrological regime, which poses great threat to regional water resources in terms of amount, variability, and quality. This is especially true in arid regions with glaciers such as the Central Asia. However, few models manage to mimic both glacier runoff and surface changes with adequate performance. To narrow this gap, we integrated a spatially distributed hydrological model (FLEX <sup>G</sup> ) and a glacier retreat model (∆h-parameterization), and tested the new model in the Urumqi Glacier No. 1 catchment, which is best monitored in China. The model inputs include climate forcing, topographic map and initial ice thickness. Here we validated the model with runoff observation at downstream and glacier measurements, i.e. three historical glacier area maps (1980, 1994 and 2002), annual glacier mass balance (GMB) and equilibrium line altitude (ELA). Results show that the FLEX <sup>G</sup> -∆h model performed well in estimating runoff (with Kling-Gupta efficiency 0.75 for hydrograph) and reproducing historical glacier area variation. Additionally the model generated reasonably spatial distribution of glacier thickness, which is important to examine glacier evolution at the Urumqi Glacier No. 1. Subsequently we ran the model forced by 12 combinations of two climate scenarios and six bias correction methods to assess the impact of climate change on glacier thinning, retreat, and its influence on water resource. The impact assessment shows that glacier area will lose up to a half (54%) of their 1980 extent in 2050, and up to 80% in 2100; while ice volume will decrease up to 79% in 2050, and 92% in 2100. The tipping point (peak water) of glacier melt supply was projected to occur around 2020 and then runoff would decrease significantly. These results alert us that there is a need for immediate mitigation measures to adapt to fast glacier change to assure long-term water security in this region. </p>}},
author = {{Gao, Hongkai and Li, Hong and Duan, Zheng and Ren, Ze and Meng, Xiaoyu and Pan, Xicai}},
issn = {{0048-9697}},
keywords = {{China; Climate change; FLEX hydrological model; Glacier retreat model; The Urumqi Glacier No. 1 catchment; Water resources}},
language = {{eng}},
month = {{12}},
pages = {{1160--1170}},
publisher = {{Elsevier}},
series = {{Science of the Total Environment}},
title = {{Modelling glacier variation and its impact on water resource in the Urumqi Glacier No. 1 in Central Asia}},
url = {{http://dx.doi.org/10.1016/j.scitotenv.2018.07.004}},
doi = {{10.1016/j.scitotenv.2018.07.004}},
volume = {{644}},
year = {{2018}},
}