干旱是一種復(fù)雜且不為人所知的潛在自然災(zāi)害。一直以來,中國頻繁遭受干旱事件,對(duì)可持續(xù)作物的生產(chǎn)帶來潛在危害。為了監(jiān)測(cè)干旱,需要大量的歷史氣象、土壤和農(nóng)業(yè)數(shù)據(jù)等。研究農(nóng)業(yè)干旱監(jiān)測(cè)的時(shí)空變化特征對(duì)抗旱和農(nóng)業(yè)種植規(guī)劃有著重要意義。因此,為了研究干旱,需要一種自動(dòng)化且高效的方法在龐大的數(shù)據(jù)集中提取出有價(jià)值的信息。本研究采用多個(gè)基于遙感產(chǎn)品的數(shù)據(jù)集和實(shí)測(cè)氣象站點(diǎn)數(shù)據(jù),包括中國氣象局1961-2017年552個(gè)氣象站的日降水量和溫度數(shù)據(jù)集,衛(wèi)星網(wǎng)格化月降水?dāng)?shù)據(jù)、土地覆蓋數(shù)據(jù)、歸一化差異植被指數(shù)(NDVI)數(shù)據(jù)和土壤濕度數(shù)據(jù)等,通過計(jì)算和分析標(biāo)準(zhǔn)化降水(SPI)、標(biāo)準(zhǔn)化降水蒸散發(fā)指數(shù)(SPEI)、降水距平、植被狀況指數(shù)(VCI)、NDVI距平、增強(qiáng)型植被指數(shù)(EVI)、標(biāo)準(zhǔn)化土壤水分指數(shù)(SSI)、多變量標(biāo)準(zhǔn)化干旱指數(shù)(MSDI)和植被健康指數(shù)(VHI),基于皮爾遜相關(guān)系數(shù)(R)、線性回歸、決定系數(shù)(R²)、均方根誤差(RMSE)和改進(jìn)的Mann-Kendall檢驗(yàn)(MMK檢驗(yàn))等方法評(píng)估了中國不同地區(qū)干旱事件的發(fā)生規(guī)律。本論文包括三個(gè)部分。第一部分首先用MMK趨勢(shì)檢驗(yàn)方法分析了...

【文章頁數(shù)】：169 頁

【學(xué)位級(jí)別】：博士

【文章目錄】：
ABSTRACT
摘要
Abbreviations
Chapter 1.Introduction
    1.1 Background of the Study
    1.2 Advances of drought analysis
        1.2.1 Description of drought
        1.2.2 Types of drought
        1.2.3 Meteorological and agricultural drought indices
            1.2.3.1 Standardized precipitation index(SPI)
            1.2.3.2 Standardized precipitation evapotranspiration index(SPEI)
            1.2.3.3 Standardized soil moisture index(SSI)and multivariate standardized drought index(MSDI)
        1.2.4 Satellite-based drought indices for drought characterization
            1.2.4.1 Normalized difference vegetation index(NDVI)
            1.2.4.2 Vegetation condition index(VCI)
            1.2.4.3 Enhanced vegetation index(EVI)
            1.2.4.4 Vegetation health index(VHI)
    1.3 Identified research gaps
    1.4 General Aims and specific Objectives
    1.5 Structure of the research
Chapter 2.Study area and data
    2.1 The study area
    2.2 Climate zones of China
    2.3 Data acquisition
        2.3.1 Satellite data
            2.3.1.1 AVHRR/MODIS surface reflectance
            2.3.1.2 AVHRR/MODIS land surface temperature/emissivity
            2.3.1.3 Soil Moisture data
        2.3.2 Meteorological data
    2.4 Software used
Chapter 3.Drought assessment over different land cover types
    3.1 Drought evolution indicated by meteorological and remote-sensing
    3.2 Methodology
        3.2.1 Estimation of Standardized precipitation anomaly
        3.2.2 Estimation of standardized precipitation index(SPI)
        3.2.3 To calculate the NDVI anomaly and VCI
        3.2.4 Correlation and regression analysis
        3.2.5 The modified Mann-Kendall test
    3.3 Results and discussion
        3.3.1 Temporal variations of different land cover types
        3.3.2 The relationship between meteorological and RS-based drought indices
        3.3.3 Trends and significance
            3.3.1.1 Monthly and annual precipitation
            3.3.1.2 Temporal variations of SPI,VCI,and the NDVI anomaly and their correlation
    3.4 Spatial distribution
        3.5.1 Spatial distribution of precipitation,NDVI,and VCI in dry and wet seasons
        3.5.2 Precipitation,NDVI,and VCI in the driest and wettest years
    3.5 Brief Summary
Chapter 4.The response of vegetation phenology and productivity to extreme climatic
    4.1 Background
    4.2 Data collection
    4.3 Methodology
        4.3.1 Computation of enhanced vegetation index(EVI)
        4.3.2 Standardized anomalies
        4.3.3 Computation of drought indices
            4.3.3.1 Standardized precipitation-evapotranspiration index(SPEI)
            4.3.3.2 Aridity index(AI)
        4.3.4 Extraction of phenological metrics
        4.3.5 Statistics analysis
    4.4 Results and discussion
        4.4.1 Variation characteristics of the climatic variables
        4.4.2 Impact of climatic variability on vegetation phenology and productivity
        4.4.3 Effects of extreme drought and wet years on vegetation phenology and productivity
        4.4.4 The sensitivity of climatic and ecosystem variations in China
    4.5 Brief conclusion
Chapter 5.Investigate the drought indices performances for prediction of agriculture drought
    5.1 Background
    5.2 Data
    5.3 Methodology
    5.4 Results and discussion
        5.4.1 Temporal variations of precipitation,relative soil moisture,and vegetation health index(VHI)
        5.4.2 Spatial distribution of precipitation,relative soil moisture,and VHI
        5.4.3.Drought identification
        5.4.4.The Correlation analysis among the drought indices
        5.4.5.The2011drought
        5.4.6 Trends and significance
    5.5 Brief conclusion
Chapter 6.Monitoring the agricultural drought dynamics effect on crop production
    6.1 Background
    6.2 Data
    6.3 Methodology
        6.3.1 Computation of agricultural standardized precipitation index(a SPI)
        6.3.2 Computation of Vegetation Supply Water Index(VSWI)
        6.3.3 Computation of crop yield anomaly
    6.4 Results and discussion
        6.4.1 Drought frequency
        6.4.2 Temporal variations and correlation between a SPI and VSWI over the different sub-regions
        6.4.3.Trends analysis of a SPI and VSWI
        6.4.4.Relationships and trends between the drought indices and crop yield anomaly(YAI)
    6.5.Conclusions
Chapter 7.Conclusions and Recommendations
    7.1 Conclusions
    7.2 Recommendations
References
ACKNOWLEDGEMENTS
RESUME OF THE AUTHOR



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