基于蒸散发的干旱监测及时效性分析  

Drought monitoring and timeliness based on evapotranspiration model

作　　者：田国珍[1] 武永利[2] 梁亚春[3] 杨超[1] 

机构地区：[1]山西省气候中心,山西太原030006 [2]山西省气象台,山西太原030006 [3]山西省气象局,山西太原030006

出　　处：《干旱区地理》2016年第4期721-729,共9页Arid Land Geography

基　　金：基于风云三号卫星农业干旱遥感监测与预报技术研究(编号:20130311037-2)

摘　　要：在改进的SEBS模型的基础上,基于作物缺水指数方法(CWSI),利用研究区域2014年风云二号、风云三号气象卫星数据及同期全省107个气象台站、农业气象观测站及土壤水分站数据,进行山西省干旱监测及时效性分析。结果显示:(1)CWSI受地形和植被的影响,植被茂盛的地区出现旱情低估的现象,而在城镇密集区则出现旱情高估的现象。(2)CWSI的干旱监测结果的精度达到80%以上,可以满足业务工作的精度需求。(3)CWSI与土壤湿度和降水都显示了一致的时间和空间分布规律,说明了CWSI用于干旱监测具有较高的时效性,可见,气象站实测的点数据与遥感数据的完美结合,有效的提高了监测结果在时间和空间上的精度,弥补了常规模型的不足。Traditionally,drought monitoring models based on evapotranspiration do not consider the weather influence in the calculating of solar radiation. In fact,clouds have a significant impact on the solar radiation,so that the calculated evapotranspiration results have great errors in cloudy weather,which reduce the drought monitoring accuracy. Because of the lag of vegetation to precipitation,the traditional remote sensing drought model based on temperature and vegetation index has the hysteresis,and the remote sensing model without considering the differences between crop types and only relying on the vegetation index derived by sensor,and the response mechanism of different crops to drought varied widely,all of these are not reflected by the remote sensing data,so that the monitoring results of drought are always unsatisfactory. In this paper,SEBS model is applied to localization,and the time series expansion method and the pixel accuracy were improved,the land surface parameters with high spatial accuracy and real-time meteorological elements of high temporal precision are fully utilized,at the same time,the FY-2E data is used to calculate the objective ground solar radiation. This paper monitored drought based on improved SEBS model and Crop Water Stress Index（CWSI）in Shanxi Province with remote sensing date from FY-3A/3B and FY-2E satellite,and meteorological date from automatic weather stations,agricultural meteorological stations and soil moisture stations. The results showed as follows：（1）CWSI is influenced by topography and vegetation,the drought is underestimated in lush vegetation area,and overestimated in city area;（2）The accuracy of CWSI for drought monitoring reached more than 80%,can meet the precision requirements of the daily work;（3）CWSI and soil moisture and precipitation showed a consistent distribution,and CWSI was proved to be more timely for drought monitoring. The perfect combination of data from meteorological observation stations and from remote sensing data effectively impr

关 键 词：干旱监测 SEBS模型 作物缺水指数 

分 类 号：P426.2[天文地球—大气科学及气象学] P412