地球科学进展 ›› 2014, Vol. 29 ›› Issue (11): 1262 -1270. doi: 10.11867/j.issn.1001-8166.2014.11.1262

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TRMM遥感降水数据在伊洛瓦底江流域的精度检验和校正方法研究
曲伟 1, 2( ), 路京选 1, 2, 宋文龙 1, 2, 张婷婷 3, 谭亚男 1, 黄萍 1   
  1. 1.中国水利水电科学研究院, 北京 100038
    2.水利部防洪抗旱减灾工程技术研究中心, 北京100038
    3.沈阳农业大学, 辽宁 沈阳 110866
  • 出版日期:2014-11-27
  • 基金资助:
    中国水利水电科学研究院科研专项“突发性水灾害应急遥感监测评估及区域河流遥感监测平台与软件研制”(编号:遥集1453);国家高技术计划项目“典型应用领域全球定量遥感产品生产体系”(编号:2013AA12A302)资助

Research on Accuracy Validation and Calibration Methods of TRMM Remote Sensing Precipitation Data in Irrawaddy Basin

Wei Qu 1, 2( ), Jingxuan Lu 1, 2, Wenlong Song 1, 2, Tingting Zhang 3, Ya’nan Tan 1, Ping Huang 1   

  1. 1. China Institute of Water Resources and Hydropower Research, Beijing, 100038
    2.Research Center on Flood & Drought Disaster Reduction of the Ministry of Water Resources, Beijing, 100038
    3. Shenyang Agricultural University, Shenyang, 110866
  • Online:2014-11-27 Published:2014-11-20

在伊洛瓦底江流域利用13个雨量站数据对TRMM日降水数据进行了精度检验, 提出了一种基于水量平衡的TRMM数据校正方法。该方法首先以SWAT模型为基础, 以不同子流域内的水量平衡为目标, 计算各个子流域的TRMM数据校正系数;其次以子流域内的坡度值为自变量, 校正系数为因变量, 对二者进行回归分析, 在没有水文控制站的子流域根据坡度求得对应的校正系数, 对各个子流域的降水数据分别进行校正。结果显示, 校正前TRMM年降水量和月降水量与实测值有较高相关性, 但偏差较大;校正后年降水量与实测值基本一致;月降水量与实测曲线吻合较好;日降水量的预报等级从中等提高到了良好, 校正前2个站预报等级差, 7个良好, 4个中等, 校正后6个良好, 2个中等, 5个优秀。结果表明此方法在伊江流域能在不同时间尺度上显著提高TRMM数据的精度, 为流域水文水资源分析提供数据支持。

TRMM daily precipitation data were validated compared to thirteen precipitation observation station data in Irrawaddy basin, and a calibration method of TRMM 3B42 data based on water balance concept was developed. SWAT model was used to calculate water balance, and then the TRMM data calibration ratio was inferred based on it. Average slope of sub-basin was the independent variable, and calibration ration was the dependent variable for the regression analysis. The calibration ratio of sub-basins without hydrological observation stations were calculated according to the average slope, and then the TRMM precipitation were calibrated according to the ratio in the whole basin. Results showed that TRMM annual and monthly precipitation had a highly correlation with observed data, but had a bad bias. Annual precipitation of TRMM precipitation after calibration were nearly the same as observed; monthly precipitation curve were similar with observed. Daily precipitation forecast rank was improved from medium to well, and there were 2 station forecast bad, 7 forecast well and 4 forecast medium before calibration, but 6 forecast well, 2 forecast medium and 5 forecast excellent after calibration. The results proved that TRMM data precision were highly improved over different temporal scales in Irrawaddy basin through this method, data for hydrological and water resources analysis were also provided.

中图分类号: 

图1 伊洛瓦底江流域示意图
Fig.1 Photo of Irrawaddy Basin
图2 2009年和2010年实测和TRMM年降水量
Fig.2 Annual precipitation of Observation and TRMM data of 2009 and 2010
图3 实测和TRMM年、月降水量相关性分析
Fig.3 Correlation analysis of monthly and annual precipitation of observation and TRMM
图4 不同情景下TRMM数据校正系数η的变化
Fig.4 Change of η under different circumstances
图5 密支那以上流域月平均径流量与 η回归分析
Fig.5 Regression analysis of average monthly precipitation and η in Mizhina basin
图6 全流域月平均径流量与 η回归分析
Fig.6 Regression analysis of average monthly precipitation and η in Irrawaddy basin
图7 平均坡度与 η相关性分析
Fig. 7 Correlation of average slope and η
表1 实测与模拟径流量比较
Table 1 Comparison of runoff of observation and modelling
图 8 校正系数 η分布图
Fig. 8 Distribution map of η
表2 雨量站位置及校正系数表
Table 2 Table of station position and calibration ratio
图9 校正后2009年和2010年年降水量比较
Fig.9 Comparison of annual precipitation after calibration of 2009 and 2010
图10 校正后月降水量比较(2009年1月至2010年12月)
Fig.10 Comparison of monthly precipitation after calibration(Jan. 2009 to Dec. 2010)
表3 日降水量模糊评分表
Table 3 Table of fuzzy ratings of daily precipitation
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