摘要
在充分考虑2001−2019年TRMM 3B43降水量数据在长江流域适用性的基础上,基于地理加权回归模型(GWR),结合归一化植被指数(NDVI)、增强型植被指数(EVI)、高程、坡度、坡向数据,选取不同组合对19a内TRMM降水量数据进行降尺度,并对优选的降尺度数据分别进行GDA、GRA校正,最后在年、季、月尺度下进行精度评价与结果分析。结果表明:(1)降尺度数据与站点实测数据的R²、BIAS、RMSE满足精度要求的同时,空间分辨率由0.25°提高至1km,且TRMMNDVI数据精度优于TRMMEVI数据。(2)GDA校正结果优于GRA校正结果,且数据稳定性更好,更适于长江流域TRMM数据校正。(3)TRMM_(NDVI)^(GDA)数据与站点实测数据R²在年(0.91~0.986)、季(0.704~0.88)、月(0.625~0.89)尺度上均有较高精度,细节特征较TRMM数据表现更好。(4)降水量越大的月份降尺度及校正效果越好。降尺度及校正后的TRMM数据能更好地反映长江流域真实降水信息,为农业生产、水资源优化配置、防洪减灾等提供可靠的数据支持。
The Yangtze River Basin has abundant rainfall,and rainfall is unevenly distributed in space and time,which is prone to flood disasters.It is of great significance to obtain precipitation information accurately and quickly.At present,remote sensing precipitation data has been widely used,but its spatial resolution and data accuracy still cannot meet actual application requirements.Therefore,based on the full consideration of the applicability of TRMM 3B43 data for 2001-2019 in the Yangtze River Basin using a geographically weighted regression model,combining NDVI,EVI,elevation,slope,and aspect,different vegetation index combinations are selected to establish low and high resolution GWR models based on pixels to achieve the downscaling of TRMM data in the Yangtze River basin from 2001 to 2019.Geographical Differential Analysis(GDA)and Geographical Ratio Analysis(GRA)corrections are then applied to the preferred TRMMNDVI data.Finally,accuracy evaluation and result analysis are performed on annual,seasonal,and monthly scales based on the actual measurement data from the meteorological stations.The results of the study showed that,(1)the R²,BIAS and RMSE of the downscaled data and the measured data at the site meet the accuracy requirements,while the spatial resolution is improved from 0.25°to 1km,and the accuracy of TRMMNDVI data is higher than the TRMMEVI data.(2)The GDA calibration results are better than the GRA calibration results,and the GDA calibration results shows a higher stability and precise accuracy.Therefore,GDA calibration is more suitable for the calibration of TRMM data in the Yangtze River Basin.(3)The TRMM_(NDVI)^(GDA) data have high accuracy on annual(0.91−0.986),seasonal(0.704−0.88),and monthly(0.625−0.89)scales with the site measured data R²,and its detailed characteristics are better than TRMM data.(4)The downscaling and correction are better in the months with higher precipitation.The TRMM data of downscaling and correction can better reflect the real precipitation information of the Yangtze River Basin,and it provide reliable data support for agricultural production,optimal allocation of water resources,and flood prevention and disaster reduction.
作者
窦世卿
张寒博
徐勇
温颖
张楠
DOU Shi-qing;ZHANG Han-bo;XU Yong;WEN Ying;ZHANG Nan(Guangxi Key Laboratory of Spatial Information and Geomatics/College of Geomatics and Geoinformation,Guilin University of Technology,Guilin 541006,China)
出处
《中国农业气象》
CSCD
北大核心
2021年第5期377-389,共13页
Chinese Journal of Agrometeorology
基金
广西八桂学者专项项目
国家自然科学基金项目(42061059)
广西自然科学基金项目(2020GXNSFBA297160)
广西空间信息与测绘重点实验室资助课题(191851016)
桂林理工大学科研启动基金项目(GUTQDJJ2019046
GUTQDJJ2019172)。
