Knowledge Network Node

Analysis of the Characteristics and Driving Forces of the Spatial and Temporal Evolution of Drought in China Based on the BasinCN

陈晨

西安理工大学

Abstract:It is of great scientific significance to investigate the spatiotemporal evolution and driving force analysis of drought in river basin.Based on the monthly precipitation,monthly mean air temperature,and potential evapotranspiration data in the CRU TS 4.03 dataset from 1982 to 2018,this paper calculated the self-corrected Palmer drought index as the meteorological and agricultural integrated drought index,to measure the drought degree in China.Based on the national watershed scale,the spatial and temporal evolution of drought events in the past 37 years was analyzed,Such as drought trend,drought covered area ratio,drought center migration,drought frequency,etc.Secondly,the Yellow River Basin and the Pearl River Basin were selected as representative basins,and the climatic factors and underlying surface factors of drought in the two basins were qualitatively analyzed.Finally,geodetector model was used to quantitatively study the influencing factors of drought in the two basins.The main research contents and results are as follows:(1)Based on the CRU dataset,the modified Palmer drought index(sc-PDSI),which represents the meteorological and agricultural drought,was calculated,and the temporal characteristics of drought at the national and river basin scales were analyzed by drought trend and drought area ratio.The results show that from 1982 to 2018,the whole region of China showed a weak trend of aridity,while the sc-PDSI in the northwest rivers showed a significant upward trend,and the drought decreased,while the sc-PDSI in the Songhua River,Liaohe River showed a significant downward trend.Liaohe River,Haihe River and Yellow River had a relatively high proportion of interannual drought area,and the drought was the most serious in 2000-2003.The proportion of drought-affected areas was higher from August to December,but lower from May to June,and there was no obvious change in the proportion of drought-affected areas in the Yangtze River and the northwestern rivers.(2)Sen+Mann-Kendall non-parametric trend test,gravity center transfer model,run theory,drought frequency and other methods were used to further analyze the spatial evolution characteristics of drought in each basin,and construct drought-causing factors to evaluate the drought risk level of each basin.The results showed that the drought gravity center under different drought levels was mainly distributed in the Yellow River Basin,Southwest River Basin and Northwest River Basin during 1982-2018,and the migration trend was generally east-west more than north-south,and the migration distance of the gravity center increased with the higher the drought level.On the trend of drought,the northwestern part of the Yangtze River and the eastern part of the Northwest Rivers became significantly wetter,while most of the Songhua River,the northwestern part of the Liaohe River,the northern part of the Yangtze River and some parts of the Northwest Rivers became significantly drier.Before 2000,the easy-dry area was mainly in the northwest rivers and the Yellow River basin,and after 2000,the extremely dry area was mainly in the Songliao Sea basin.The average duration of drought was higher in the northern part of Liaohe River,the western middle part of Yellow River and the southern part of Northwest Zhuhe River.The local drought intensity was stronger and its peak value was larger in the northwestern part of Liaohe River,the northern part of Haihe River and the southern part of Northwest Zhuhe River.The spatial distribution of drought-induced disaster risk in most regions of China showed low or medium risk grade,while the proportion of medium or above risk grade was higher in Liaohe River and Haihe River.(3)The Yellow River and the Pearl River were selected as two representative basins,The spatiotemporal correlation between different driving factors and sc-PDSI in the two river basins was qualitatively explored by Pearson correlation analysis.The results showed that The precipitation,soil moisture and sc-PDSI in the Yellow River were significantly positively correlated at the basin scale and pixel scale,while the precipitation,average water vapor pressure and sc-PDSI in the Pearl River were significantly positively correlated at the basin scale and pixel scale,and the sc-PDSI in the two basins were significantly negatively correlated with potential evapotranspiration and dryness.There was no significant negative correlation with air temperature,and the correlation showed obvious spatial difference.(4)The geographic detector model is used to detect factors,ecology,risk and interaction,The effects of different driving factors on drought in the Yellow River Basin and the Pearl River Basin were further quantitatively studied.The results show that precipitation in the Yellow River Basin has the highest explanatory power for sc-PDSI,and is the primary factor affecting drought in the Yellow River Basin,followed by mean temperature,altitude and potential evapotranspiration.The potential evapotranspiration in the Pearl River Basin has the highest explanatory power for sc-PDSI,and is the primary factor affecting drought in the Pearl River Basin,followed by precipitation,mean pressure and altitude.In addition,compared with the interaction between other factors,the interaction between precipitation and potential evapotranspiration is the most significant for drought in the Yellow River Basin.The nonlinear enhanced interaction between potential evapotranspiration and dryness has the most obvious effect on drought in the Pearl River Basin.
  • Series:

    (A) Mathematics/ Physics/ Mechanics/ Astronomy; (D) Agriculture

  • Subject:

    Meteorology; Fundamental Science of Agriculture; Plant Protection

  • DOI:

    10.27398/d.cnki.gxalu.2021.000547

  • Classification Code:

    S423

Download the mobile appuse the app to scan this coderead the article.

Download:328 Page:79 Size:12413K

Related Literature
  • Similar Article
  • Reader Recommendationr
  • Related Funding Articles
  • Citation Network
  • Study Results