Qiudong Zhao

Dr. Qiudong Zhao


Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

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

Representative Publications

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24 May 2012 in Environmental Earth Sciences
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Journal Article
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QZQiudong Zhao
Qiudong Zhao
BYBaisheng Ye
Baisheng Ye
YDYongjian Ding
Yongjian Ding
SZShiqiang Zhang
Shiqiang Zhang
SYShuhua Yi
Shuhua Yi
HHHaidong Han
Haidong Han

15 October 2009 in Hydrology and Earth System Sciences
Verified
Journal Article
Open access
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QZQiudong Zhao
Qiudong Zhao
ZLZ. Liu
Z. Liu
BYB. Ye
B. Ye
YQY. Qin
Y. Qin
ZWZ. Wei
Z. Wei
SFS. Fang
S. Fang
This study linked the Weather Research and Forecasting (WRF) modelling system and the Distributed Hydrology Soil Vegetation Model (DHSVM) to forecast snowmelt runoff. The study area was the 800 km2 Juntanghu watershed of the northern slopes of Tianshan Mountain Range. This paper investigated snowmelt runoff forecasting models suitable for meso-microscale application. In this study, a limited-region 24-h Numeric Weather Forecasting System was formulated using the new generation atmospheric model system WRF with the initial fields and lateral boundaries forced by Chinese T213L31 model. Using the WRF forecasts, the DHSVM hydrological model was used to predict 24 h snowmelt runoff at the outlet of the Juntanghu watershed. Forecasted results showed a good similarity to the observed data, and the average relative error of maximum runoff simulation was less than 15%. The results demonstrate the potential of using a meso-microscale snowmelt runoff forecasting model for forecasting floods. The model provides a longer forecast period compared with traditional models such as those based on rain gauges or statistical forecasting.

24 September 2021 in Hydrological Processes
Verified
Journal Article
Closed access
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ZJZizhen Jin
Zizhen Jin
QZQiudong Zhao
Qiudong Zhao
XQXiang Qin
Xiang Qin
JZJingtian Zhang
Jingtian Zhang
HZHui Zhang
Hui Zhang
LWLihui Wang
Lihui Wang

24 March 2022 in Remote Sensing
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RWRongjun Wang
Rongjun Wang
Yongjian DingYongjian Ding
Yongjian Ding
DSDonghui Shangguan
Donghui Shangguan
Wanqin GuoWanqin Guo
Wanqin Guo
QZQiudong Zhao
Qiudong Zhao
MSMiao Song
Miao Song
Most studies attribute the glacier mass balance within High Mountain Asia (HMA) to climate change, ignoring the influence of its complex terrain. Knowledge of the influence of this complex terrain is crucial for understanding the spatial variability in its mass balance. However, there is a lack of any systematic assessment of this influence across HMA. Therefore, in this study, we used the glacier outlines and raster data (SRTM DEM, slope and aspect) to calculate the topographic shading of all 97,965 glaciers within HMA during the ablation period, which is regarded as a major index of the influence of complex terrain on the mass balance. The results showed that 27.19% of HMA glacier area was subjected to topographic shading, and regional differences were significant with respect to both their altitudinal and spatial distributions. The topographic shading contributed to the protection of the smallest glaciers from solar illumination. Furthermore, we found a significant correlation between the topographic shading and mass balance in these small north-facing glaciers. However, these small glaciers were most prevalent in the north-facing orientation, especially in West Kunlun, East Kunlun, Inner Tibet Plateau and Qilian Shan, where shading was found to increase with decreases in the glacier area. This indicates that complex terrain can affect the spatial distribution of the mass balance by altering the solar illumination pattern.

27 December 2019 in Remote Sensing
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Journal Article
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YCYaping Chang
Yaping Chang
Yongjian DingYongjian Ding
Yongjian Ding
QZQiudong Zhao
Qiudong Zhao
Shiqiang ZhangShiqiang Zhang
Shiqiang Zhang
Diurnal variation of land surface temperature (LST) is essential for land surface energy and water balance at regional or global scale. Diurnal temperature cycle (DTC) model with least parameters and high accuracy is the key issue in estimating the spatial–temporal variation of DTC. The alpine meadow is the main land cover in the Tibetan Plateau (TP). However, few studies have been reported on the performance of different DTC models over alpine meadows in the TP. Four semi-empirical types of DTC models were used to generate nine 4-parameter (4-para) models by fixing some of free parameters. The performance of the nine 4-para DTC models were evaluated with four in situ and MODIS observations. All models except GOT09-dT-ts (dT means the temperature residual between T0 and T (t→∞); ts means the time when free attenuation begins) had higher correlation with in situ data (R2 > 0.9), while the INA08-ts model performed best with NSE of 0.99 and RMSE of 2.04 K at all sites. The GOT09-ts-τ (τ is the total optical thickness), VAN06-ts-ω1 (ω1 means the half-width of the cosine term in the morning), and GOT01-ts models had better performance, followed by GOT09-dT-τ, GOT01-dT, and VAN06-ts-ω2 (ω2 means the half-width of the cosine term in the afternoon) models. All models had higher accuracy in summer than in other seasons, while poorer performance was produced in winter. The INA08-ts model showed best performance among all seasons. Models with fixing ts could produce higher accuracy results than that with fixing dT. The comparison of INA08-ts model driven by in situ and Moderate Resolution Imaging Spectroradiometer (MODIS) data indicated that the simulation accuracy mainly depended on the accuracy of MODIS LST. The daily maximum temperature generated by the nine models had high accuracy when compared with in situ data. The sensitivity analysis indicated that the INA08-dT and GOT09-dT-ts models were more sensitive to parameter dT, while all models were insensitive to parameter ts, and all models had weak relationship with parameters ω and τ. This study provides a reference for exploring suitable DTC model in the TP.

24 March 2015 in Journal of Mountain Science
Verified
Journal Article
Closed access
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JYJunqiang Yao
Junqiang Yao
QZQiudong Zhao
Qiudong Zhao
ZLZhihui Liu
Zhihui Liu