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Shenyang Agricultural University (2021)

Drought Characteristics and Prediction Models in Northeast China


Titre : Drought Characteristics and Prediction Models in Northeast China

Auteur : 李增

Grade : Doctoral Dissertation 2021

Université : Shenyang Agricultural University

Résumé partiel
Drought is one of the most serious natural disasters in the world.The frequent occurrence of droughts has had an extreme adverse impact on the sustainable development of agriculture in our country.The impact of droughts on Northeast area that is the main grain-producing areas of China is particularly serious.Study on drought characteristics and prediction models is one of the important methods for disaster reduction and prevention.Based on the theory of run,this research utilized the China Z Index(CZI),Standardized Precipitation Index(SPI),Standardized Precipitation Evapotranspiration Index(SPEI)and Reconnaissance drought index(RDI)to identify the drought frequency,duration,severity and drought types in Northeast China respectively,and then comparatively analyzed their applicability.Afterwards this research investigated the variation tendency of drought frequency,duration and severity in Northeast China by the Mann-Kendall trend analysis method,the drought return period by Copula function,the periodic change rule of drought characteristics by wavelet analysis ;sensitivity of drought to meteorological factors by the extended Fourier Amplitude Sensitivity Test method,respectively ;In addition,a variety of drought prediction models based on penalty linear regression and ensemble methods were established and compared,and the optimal drought prediction model based on machine learning methods was selected.Finally,a new Long Short-Term Memory(LSTM)drought prediction model based on deep learning technology was established,and its performance advantages compared with the traditional multi-layer perceptron(MLP)model with similar structure were compared and analyzed,as well as the methods to improve its prediction performance.The main research results are as follows :(1)Study on the applicability of drought index in Northeast China.The frequency,duration and severity of drought based on SPI,SPEI and RDI in Northeast China were relatively consistent in the spatial and temporal distribution characteristics,while SPEI and the corresponding NDVI showed the most significant positive correlation.Furthermore,the SPEI-based drought types were also accord with the drought records over the years in Northeast China that were more spring and autumn droughts,hence SPEI is the most suitable index for evaluating drought conditions in Northeast China.In addition,the drought frequency,duration and severity identified by SPI,SPEI and RDI were influenced significantly by timescales,but their variation characteristics at different timescales were almost agreement.(2)Analysis of the characteristics of the spatial and temporal evolution of drought in Northeast China.The drought frequency and duration in Northeast China showed a downward trend,while the drought severity showed an upward trend,but they were not significant basically.The drought risk was more higher in the western of Northeast China,Heilongjiang Province and northwestern Liaoning,while was lower risk in eastern Liaoning and southern Jilin.The drought frequency,duration and severity showed the periodic characteristics of multi-period superimposed oscillations.

Mots clés : drought characteristics ;theory of run ;Standardized Precipitation Evapotranspiration Index ;drought return period ;machine learning ;deep learning ;

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Page publiée le 21 octobre 2021