Ning Yao

Dr. Ning Yao


Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

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

Representative Publications

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22 November 2019 in Science of The Total Environment
Verified
Journal Article
Closed access
NYNing Yao
Ning Yao
LLLinchao Li
Linchao Li
PFPuyu Feng
Puyu Feng
HFHao Feng
Hao Feng
De Li LiuDe Li Liu
De Li Liu
Yi LiYi Li
Yi Li

1 October 2018 in Science of The Total Environment
Verified
Journal Article
Closed access
NYNing Yao
Ning Yao
Yi LiYi Li
Yi Li
NLNa Li
Na Li
DYDaqing Yang
Daqing Yang
OAOlusola Olaitan Ayantobo
Olusola Olaitan Ayantobo

16 October 2020 in Remote Sensing
Verified
Journal Article
Open access
PDF file
NYNing Yao
Ning Yao
HZHuichao Zhao
Huichao Zhao
Yi LiYi Li
Yi Li
Asim BiswasAsim Biswas
Asim Biswas
HFHao Feng
Hao Feng
BPBakhtiyor Pulatov
Bakhtiyor Pulatov
The regional and national scales variation and propagation characteristics of different types of droughts are critical for improving drought resilience, while information is limited in China. The objective of this research was to investigate the evolution and propagation characteristics of three types of droughts using standardized indices at multi-timescales in different sub-regions of China. The indices included Standardized Precipitation/Soil Moisture/Runoff Index (SPI/SSI/SRI) using the optimal probability density function, representing meteorological, agricultural, and hydrological droughts based on precipitation, soil water storage, and baseflow-groundwater runoff, respectively. Wavelet analysis was used to reveal their periodical characteristics. Modified Mann-Kendall trend test was used to compare the trend among drought indices. Correlation coefficients between SPI and SSI/SRI were calculated to identify the time-lags of SPI with SSI and SRI. In general, droughts indicated by SPI agreed well with the historical drought events at different sub-regions. The main periods of SSI were closer to SPI than SRI, indicating stronger connections of agricultural drought with meteorological drought. A weaker connection between meteorological and agricultural/hydrological droughts at shorter timescales was observed in northwestern arid and semi-arid regions. The propagation from meteorological to agricultural or hydrological droughts were well denoted by the lagged time (months) from SPI to SSI or SRI at a timescale ranged from 0 (mostly located in south China) to 5 months (mostly located in northeastern China) for 1-, 3-, 6-, 12-, or 24-month timescale; this was a new finding for China. The methods of wavelet combining trend test and Pearson coefficient showed meaningful power for revealing the drought propagation characteristics and the obtained results can be a good reference for other regions of the world since this study compared different climate zones from arid to humid conditions. The study provides crucial information and guidance to develop drought management strategies at regional to national scale and their critical time of action.

1 April 2020 in European Journal of Agronomy
Verified
Journal Article
Closed access
HMHaijiao Ma
Haijiao Ma
RMRobert W. Malone
Robert W. Malone
TJTengcong Jiang
Tengcong Jiang
NYNing Yao
Ning Yao
Shang ChenShang Chen
Shang Chen
JHJianqiang He
Jianqiang He

8 September 2019 in Land Degradation & Development
Verified
Journal Article
Closed access
PDF file
NYNing Yao
Ning Yao
Yi LiYi Li
Yi Li
QDQin'ge Dong
Qin'ge Dong
LLLinchao Li
Linchao Li
LPLingling Peng
Lingling Peng
HFHao Feng
Hao Feng

21 July 2021 in Agronomy
Verified
Journal Article
Open access
PDF file
FXFang Xu
Fang Xu
Bin WangBin Wang
Bin Wang
CHChuan He
Chuan He
De Li LiuDe Li Liu
De Li Liu
PFPuyu Feng
Puyu Feng
JHJianqiang He
Jianqiang He
We used the APSIM-Maize model to simulate maize potential yield (Yp) and rain-fed yield (Yw) when adaptation options of sowing date and planting density were adopted under Representative Concentration Pathway (RCP) 4.5 and 8.5 in the Guanzhong Plain of China. The results showed that Yp would decrease by 10.6–14.9% and 15.0–31.4% under RCP4.5 and RCP8.5 for summer maize, and 13.9–19.7% and 18.5–36.3% for spring maize, respectively. The Yw would decrease by 17.1–19.0% and 23.6–41.1% under RCP4.5 and RCP8.5 for summer maize, and 20.9–24.5% and 27.8–45.5% for spring maize, respectively. The loss of Yp and Yw could be reduced by 2.6–9.7% and 0–9.9%, respectively, under future climate for summer maize through countermeasures. For spring maize, the loss of Yp was mitigated by 14.0–25.0% and 2.0–21.8% for Yw. The contribution of changing sowing date and plant density on spring maize yield was more than summer maize, and the optimal adaptation options were more effective for spring maize. Additionally, the influences of changing sowing date and planting density on yields become weak as climate changes become more severe. Therefore, it is important to investigate the potential of other adaptation measures to cope with climate change in the Guanzhong Plain of China.