多光谱干旱严重度指数的评价与修正

Evaluation and Modifying of Multispectral Drought Severity Index

干旱是一种破坏力极强的自然灾害,近年来,受气候变化的影响,干旱在全球的发生频率不断升高,造成了严重的经济损失,准确监测干旱信息是防灾减灾的基础。干旱严重度指数(DSI)监测全球干旱的能力已经得到证实,但在局部区域的应用具有明显的差异性。为了检验DSI在省级尺度的适用性、修正其等级划分差异,以山西省为研究区,基于MODISET/PET,以及MODIS和AVHRR的NDVI数据集分别得到2001年-2014年的DSI(MODIS)和DSI(AVHRR),同时结合SPEI,对三者进行了干旱时空分布的对比分析;为了证实SPEI的可靠性,将长时序的SPEI与历史干旱记录进行了比对;为了考察DSI在区域范围内的误差,将DSI(MODIS), DSI(AVHRR)和SPEI进行了时间频率与空间分布的比较;最后,以SPEI为参照,基于DSI的原始划分标准,以0.1为步长调整DSI(MODIS)的干旱等级阈值,得到了新的干旱等级划分标准DSI(MM);并利用DSI(MM)监测了全省2001年-2014年季节尺度的旱情,捕捉了研究区2001年和2002年的典型干旱事件,验证了DSI(MM)在山西省干旱监测中的适用性和稳健性。研究表明,DSI(MODIS)与DSI(AVHRR)之间存在较高的相关性,相关系数为0.75,二者对干旱的空间分布和时间频率具有一致的表现,说明在数据缺失的情况下, DSI可拓展应用于AVHRR数据集,以弥补MODIS数据在长时序监测中的不足;DSI(MODIS)低估了山西省D1等级干旱信息,而高估了D2~D4等级干旱;对于轻度干旱D1,中度干旱D2,重度干旱D3,极度干旱D4四个等级, DSI(MM)与SPEI在干旱时间频率和空间分布占比方面表现出高度的一致性,其中D3等级的时间频率完全一致, D4等级的空间分布一致性为0.98;在干旱类型丰富的地区可精确地修正DSI的干旱等级划分。研究结果对利用DSI进行区域尺度干旱监测具有借鉴作用,为山西省干旱信息监测获取了一种计算简易、精确度高的方法。

Drought is a very destructive natural disaster.In recent years,affected by climate change,the frequency of drought is increasing all over the world,causing serious economic losses.Accurate monitoring of drought information is the basis of disaster prevention and reduction.Drought Severity Index(DSI)is a kind of index that can effectively capture regional drought information.It has been proved that it has great potential in global drought monitoring,but its classification of drought grade is obviously regional.In order to test the applicability of DSI on the provincial scale and correct the classification differences,DSI MODIS and DSI AVHRR from 2001 to 2014 were obtained based on the data sets of MODIS ET/PET,NDVI and AVHRR NDVI in Shanxi Province.Meanwhile,combined with SPEI,the spatial and temporal distribution of drought in these three indexes was compared and analyzed.To verify the reliability of SPEI,long time series SPEIs were compared with historical drought records.In order to investigate the errors of DSI in the region,DSI MODIS,DSI AVHRR and SPEI were compared in time frequency and spatial distribution.Finally,as SPEI a reference and based on the original DSI classification standard,the new drought classification standard was obtained by adjusting the threshold of drought grade of DSI MODIS with 0.1 as the step size.In addition,DSI MM was used to monitor the provincial seasonal scale from 2001 to 2014,to capture the typical drought events in 2001 and 2002,and to verify the applicability and robustness of DSI MM in drought monitoring in Shanxi.Studies show that there is a high correlation between DSI MODIS and DSI AVHRR,with a correlation coefficient of 0.75.Both of them have consistent performance in spatial distribution and time frequency of drought,indicating that DSI can be extended to AVHRR data set in the absence of data to make up for the deficiency of MODIS data in long time series monitoring.D1 was underestimated by DSI MODIS,while D2,D3 and D4 were overestimated in Shanxi province.In the four grades of mild drought D1,moderate drought D2,severe drought D3 and extreme drought D4,DSI MM and SPEI showed a high degree of consistency in the occurrence frequency and spatial ratio of drought.The time frequency of D3 was completely consistent,and the spatial distribution consistency of D4 was 0.98.The drought classification standard of DSI MM can monitor the drought information at different temporal and spatial scale accurately,which can be applied to the whole governor time series drought monitoring.The results can be used for reference in regional scale drought monitoring using DSI,and a simple calculation method with high accuracy is obtained for Shanxi Province drought information monitoring.