Tie Liu

Dr. Tie Liu

Xinjiang Institute of Ecology and Geography Chinese Academy of Sciences, Urumqi, China
orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 May 2018 in Science of The Total Environment
Verified
Journal Article
Closed access
Hao GuoHao Guo
Hao Guo
ABAnming Bao
Anming Bao
TLTie Liu
Tie Liu
GJGuli Jiapaer
Guli Jiapaer
FNFelix Ndayisaba
Felix Ndayisaba
Philippe De MaeyerPhilippe De Maeyer
Philippe De Maeyer

7 August 2018 in Water
Verified
Journal Article
Open access
PDF file
MLMin Luo
Min Luo
TLTie Liu
Tie Liu
FMFanhao Meng
Fanhao Meng
YDYongchao Duan
Yongchao Duan
AFAmaury Frankl
Amaury Frankl
Philippe De MaeyerPhilippe De Maeyer
Philippe De Maeyer
The systemic biases of Regional Climate Models (RCMs) impede their application in regional hydrological climate-change effects analysis and lead to errors. As a consequence, bias correction has become a necessary prerequisite for the study of climate change. This paper compares the performance of available bias correction methods that focus on the performance of precipitation and temperature projections. The hydrological effects of these correction methods are evaluated by the modelled discharges of the Kaidu River Basin. The results show that all used methods improve the performance of the original RCM precipitation and temperature simulations across a number of levels. The corrected results obtained by precipitation correction methods demonstrate larger diversities than those produced by the temperature correction methods. The performance of hydrological modelling is highly influenced by the choice of precipitation correction methods. Furthermore, no substantial differences can be identified from the results of the temperature-corrected methods. The biases from input data are often greater from the works of hydrological modelling. The suitability of these approaches depends upon the regional context and the RCM model, while their application procedure and a number of results can be adapted from region to region.

1 September 2018 in Journal of Hydrology
Verified
Journal Article
Closed access
Hao GuoHao Guo
Hao Guo
ABAnming Bao
Anming Bao
FNFelix Ndayisaba
Felix Ndayisaba
TLTie Liu
Tie Liu
GJGuli Jiapaer
Guli Jiapaer
PMPhilippe De Maeyer
Philippe De Maeyer

29 May 2017 in Sustainability
Verified
Journal Article
Open access
PDF file
Hao GuoHao Guo
Hao Guo
ABAnming Bao
Anming Bao
TLTie Liu
Tie Liu
FFFelix Ndayisaba Felix
Felix Ndayisaba Felix
DHDaming He
Daming He
Philippe De MaeyerPhilippe De Maeyer
Philippe De Maeyer
Lower Mekong Basin (LMB) experiences a recurrent drought phenomenon. However, few studies have focused on drought monitoring in this region due to lack of ground observations. The newly released Climate Hazards Group Infrared Precipitation with Station data (CHIRPS) with a long-term record and high resolution has a great potential for drought monitoring. Based on the assessment of CHIRPS for capturing precipitation and monitoring drought, this study aims to evaluate the drought condition in LMB by using satellite-based CHIRPS from January 1981 to July 2016. The Standardized Precipitation Index (SPI) at various time scales (1–12-month) is computed to identify and describe drought events. Results suggest that CHIRPS can properly capture the drought characteristics at various time scales with the best performance at three-month time scale. Based on high-resolution long-term CHIRPS, it is found that LMB experienced four severe droughts during the last three decades with the longest one in 1991–1994 for 38 months and the driest one in 2015–2016 with drought affected area up to 75.6%. Droughts tend to occur over the north and south part of LMB with higher frequency, and Mekong Delta seems to experience more long-term and extreme drought events. Severe droughts have significant impacts on vegetation condition.

1 August 2019 in Science of The Total Environment
Verified
Journal Article
Closed access
MLMin Luo
Min Luo
TLTie Liu
Tie Liu
FMFanhao Meng
Fanhao Meng
YDYongchao Duan
Yongchao Duan
ABAnming Bao
Anming Bao
AFAmaury Frankl
Amaury Frankl

1 October 2020 in Journal of Cleaner Production
Verified
Journal Article
Closed access
MLMin Luo
Min Luo
CSChula Sa
Chula Sa
FMFanhao Meng
Fanhao Meng
YDYongchao Duan
Yongchao Duan
TLTie Liu
Tie Liu
YBYuhai Bao
Yuhai Bao