基于贝叶斯模型平均的2003–2015年青海三江源地区地表蒸散发数据集  

A dataset of surface evapotranspiration in the Three-River Headwaters Region of Qinghai Province based on Bayesian model averaging from 2003 to 2015

作　　者：杨妍希 王军邦[1] 叶辉 张秀娟[2] YANG Yanxi;WANG Junbang;YE Hui;ZHANG Xiujuan(Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,P.R.China;College of Horticulture and Landscape Architecture,Yangtze University,Jingzhou 434000,P.R.China;School of Tourism and Geography,Jiujiang University,Jiujiang 332005,P.R.China)

机构地区：[1]中国科学院地理科学与资源研究所,生态系统网络观测与模拟重点实验室,生态系统大数据与模拟中心,北京100101 [2]长江大学园艺园林学院,湖北荆州434000 [3]九江学院旅游与地理学院,江西九江332005

出　　处：《中国科学数据（中英文网络版）》2024年第2期261-271,共11页China Scientific Data

基　　金：自然科学基金项目(31971507);中国科学院-青海省人民政府三江源国家公园联合研究专项(LHZX-2020-07);青海省科技项目(2017-SF-A6)。

摘　　要：蒸散发(Evapotranspiration,ET)是陆地水、碳和能量交换的重要组成部分。基于不同模型和不同遥感数据估算的ET,存在不同程度的不确定性。贝叶斯模型平均(Bayesian model averaging,BMA)提供了降低不确定性的一种途径。本研究采用中国三江源地区水热通量观测数据,以ARTS、PT-JPL、MOD16和SSEBop遥感蒸散发产品为基础,进行了BMA集成研究,生成了三江源地区2003–2015年250 m空间分辨率的年均地表蒸散发数据集。通过验证各输入模型和BMA集成模型结果,发现基于BMA的ET与通量观测数据相关性达0.94,能够解释观测数据季节变化的89%,优于单个模型的性能。说明BMA模型集成能够整合不同模型内在优势,降低结果估算的不确定性,从而获得更可靠的估算结果。本数据集可为三江源区域水热变化研究和生态系统调节功能评估提供更精确的数据支持。Evapotranspiration(ET)plays an important in the exchange of water,carbon and energy on land.The ET estimates based on different models and remote sensing data have different degrees of uncertainty.Bayesian model averaging(BMA)provides a way to reduce the uncertainty.Based on water and heat flux observation data in the Three-River Headwaters Region of China,evapotranspiration simulated by ARTS and PT-JPL models,and internationally shared MOD16 and SSEBop remote sensing evapotranspiration products,we conducted a BMA integration study,resulting in a dataset of surface evapotranspiration in the Three-River Headwaters Region of Qinghai Province based on Bayesian model averaging from 2003 to 2015.By verifying the results of each input model and BMA integrated model,it is found that the correlation between ET based on BMA and flux observation data is 0.94,which can explain 89%of the seasonal variation data,outperforming the performance of a single model.The results show that BMA model integration can integrate the inherent advantages of different models and reduce the uncertainty of result estimation for more reliable estimation results.This dataset can provide more accurate data for studying hydrothermal changes and evaluating ecosystem regulation functions in the Three-River Headwaters Region.

关 键 词：蒸散发 中国三江源 贝叶斯模型平均BMA 通量数据 遥感产品 

分 类 号：P426.2[天文地球—大气科学及气象学] P407