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张庆竹, 李占华, 赵 琳, 孙静静.遥感蒸散发数据在黑河中游荒漠绿洲区的应用评估水资源与水工程学报[J].,2025,36(5):214-222
遥感蒸散发数据在黑河中游荒漠绿洲区的应用评估
Application evaluation of remote sensing evapotranspiration data in the desert-oasis region of the middle reaches of the Heihe River Basin
  
DOI:10.11705/j.issn.1672-643X.2025.05.25
中文关键词:  蒸散发  遥感数据  精度评估  STAEDM  SSEBop  MOD16  黑河中游
英文关键词:evapotranspiration  remote sensing data  accuracy assessment  STAEDM  SSEBop  MOD16  the middle reaches of the Heihe River Basin
基金项目:中央高校基本科研业务费专项资金项目(B250201007)
作者单位
张庆竹1, 李占华1, 赵 琳2, 孙静静3,4,5 (1.山东省海河淮河小清河流域水利管理服务中心 山东 济南 250100 2.山东省水利勘测设计院有限公司 山东 济南 250013 3.山东省水利科学研究院 山东 济南 250013 4.河海大学 江苏 南京 210098
5.山东省水网调度与水资源高效利用重点实验室
山东 济南 250013) 
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中文摘要:
      黑河中游气候干旱,地表蒸散发强烈,农田灌溉耗水量大。目前针对遥感蒸散发数据的评估方法大多是与实测通量数据进行对比,而较少从耗水量监测应用这一角度进行评估。从站点实测数据、已发布的遥感蒸散发产品(SSEBop和MOD16)以及灌溉耗水量统计数据这3个方面对黑河流域中游荒漠绿洲区时空连续的遥感数据STAEDM(时间分辨率为10 d,空间分辨率为30 m)进行了对比评估。结果表明:与站点实测数据对比,STAEDM在植被下垫面的精度优于干旱下垫面;STAEDM精度最高(大满农田站r2=0.88),SSEBop次之(r2=0.83),MOD16精度最差(r2=0.68),STAEDM在蒸散发的季节性变化规律和数值大小方面均有着更高的精度,且STAEDM较SSEBop和MOD16(空间分辨率为1 km)在蒸散发空间分布方面更为细致,能清晰地展示出复杂荒漠绿洲下垫面的蒸散发空间分布特征。基于STAEDM数据获取的灌溉耗水量与水资源公报中的数据对比结果显示,二者相关性较高(r2=0.91),相对误差为15.4%,虽然数值上略有高估,但年际变化规律呈现良好的一致性。STAEDM蒸散发数据具有高时空连续性,能够精细化监测田块尺度的灌溉耗水量,可为灌溉制度的优化提供数据支撑。
英文摘要:
      The arid climate in the middle reaches of the Heihe River Basin leads to intense surface evapotranspiration and considerable irrigation water use for farmland. Most current assessments of remote sensing evapotranspiration data focus on the comparison between the remote sensing data and the measured flux data, fewer efforts have been made from the perspective of monitoring irrigation water use. The STAEDM (with a temporal resolution of 10 days and a spatial resolution of 30 meters) data of the desert-oasis region in the middle reaches of the Heihe River Basin was compared with site observations, other evapotranspiration products (SSEBop and MOD16), and irrigation water use statistics. The results showed that compared with the observations, STAEDM had a better accuracy under the vegetated surface than under the arid surface. STAEDM was the most accurate (r2=0.88 at Daman Station), followed by SSEBop (r2=0.83), whereas MOD16 was the least accurate (r2=0.68). STAEDM had better simulation accuracy in terms of the seasonal variation pattern and magnitude of evapotranspiration. Furthermore, STAEDM had more detailed textures in the spatial distribution of evapotranspiration than SSEBop and MOD16 (with a spatial resolution of 1 km), which could clearly display the spatial characteristics of evapotranspiration on the complex desert oasis surface. A comparison of the irrigation water use data based on STAEDM and the Water Resources Bulletin showed a high correlation (r2=0.91), with a relative error of 15.4%. Although there was a slight overestimation in the numerical value, the inter-annual variation patterns showed good consistency. The assessment results indicate that STADEM data has high spatial and temporal continuity, which can be used to refine irrigation water use monitoring at field scale, and provide data support for the optimization of irrigation schemes.
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