基于FY-3C和TRMM数据的西北干旱区干旱监测与评估

Monitoring and assessment of drought in arid area in northwest China based on FY-3C and TRMM Data

基于2015—2017年生长季(4—10月)FY-3C/MWRI(微波成像仪)的土壤水分(VSM)、陆表温度(LST)数据及TRMM3B43的降水数据,通过降尺度和归一化得到降雨量指数(PCI)、陆表温度指数(TCI)和土壤水分指数(SMCI)三指数,并将三指数融合,建立了微波综合干旱指数(MIDI),以此对西北干旱区的干旱状况进行了监测。结果表明:1)从时间变化看,2015—2017年西北干旱区每年均有干旱发生,其中特旱和重旱所占面积最大;从空间格局上看,干旱事件具有明显的地域分异规律,从东到西干旱程度逐渐加重,且变化趋势为先轻微加重后有所缓解。2)从时空演变来看,西北干旱区2015—2017年10.57%区域变湿,12.87%区域变旱,且旱情年内变化表现4—8月持续减轻,8—10月持续加重。3)MIDI指数对研究区短期干旱的检测效果较好,优于单一的干旱指数,与湿润指数存在的相关性最优且在空间上存在较高的实际一致率,为未来利用其他微波遥感数据进行干旱监测和相关研究奠定了基础。

Based on soil moisture(VSM),land surface temperature(LST)data of FY-3 C/MWRI(microwave imager)and precipitation data of TRMM3 B43 in the growing season(AprilOctober)during 2015-2017,three indices of Precipitation Condition Index(PCI),Temperature Condition Index(TCI)and Soil Moisture Condition Index(SMCI)were obtained through downscaling and normalization.The three indices were merged to establish a Microwave Integrated Drought Index(MIDI),which was used to assess drought status in the arid regions of northwest China.The results showed that:(1)Temporally,drought occurred in the arid regions of Northwest China every year from 2015 to 2017,with the dominance of extreme drought and heavy drought.Spatially,drought events had obvious regional differentiation.The degree of drought increased from east to west,and the trend of change was slightly aggravated and then alleviated.(2)From the perspective of spatiotemporal evolution,10.57%of area in the arid northwest China became wetter during 2015-2017,and 12.87%of the area became drier.Drought within a single year was continuously reduced from April to August,and continued to increase from August to October.(3)The MIDI index had a better detection effect than the single drought index on short-term drought in the study area.The correlation of MIDI index with Humidity Index was optimal,with a high actual agreement rate in space.Our results provide a basis for drought monitoring and related research using other microwave remote sensing data.