基于贝叶斯模型平均的蒸散遥感产品集成——以三江源国家公园为例

Integration of evapotranspiration remote sensing products based on Bayesian model averaging:An example from Three-River-Source National Park

蒸散发(ET)是陆表水热过程的一个基础通量,不同模型基于的概念、假设、应用尺度等诸多差异给ET的准确模拟带来了多种不确定性。本研究以三江源国家公园为例,应用贝叶斯模型平均(BMA)方法,通过通量塔观测值对模型进行训练,并综合PT-JPL、ARTS-GIMMS3g、ARTS-MODIS、MOD16和SSEBo 5个模型结果,以提高ET的估测精度。结果表明:5个模型结果可以捕捉海北高寒草地通量塔观测ET的季节变化,可解释观测ET季节变异的64%~86%,均方根误差(RMSD)的范围为0.47~0.76 mm·(8 d)^(-1);基于BMA得到的ET的解释能力提高至89%,RMSD降低至0.43 mm·(8 d)^(-1)。2003—2015年,三江源国家公园地表ET总体呈不显著增加的趋势,在全区尺度上,温度和降水对蒸散的影响不显著;但在长江源园区,降水和气温对其影响达到显著水平。气温和降水对蒸散发有积极的影响,但不同园区之间的地理差异导致蒸散发也出现不同的变化趋势。本研究为其他多源数据的集成分析提供了方法参考,所集成的蒸散数据可以有效降低原各自模型的不确定性,为区域水热变化研究提供了更为精确的数据基础。这对于更好地认识气候变化背景下的水循环过程具有重要意义。

Evapotranspiration(ET)is a fundamental flux in land surface hydrothermal process.Because of the differences in basic concepts,assumptions,application scales,different models have induced varying uncertainties to the estimation and simulation of evapotranspiration.With the Three-River-Source National Park as an example,we used the Bayesian model averaging(BMA)method to integrate the ET estimations from five models of PT-JPL,ARTS-GIMMS3,ARTS-MODIS,MODIS global evapotranspiration product(MOD16),and SSEBop,and tried to improve the estimating accuracy of evapotranspiration.The results showed that the five models could well capture the seasonal variations in evapotranspiration at Haibei Flux Station,with an explanation range of 64%-86%variability in the observed ET,and a root means square deviation(RMSD)ranged from 0.47 mm·(8 d)^(-1)to 0.76 mm·(8 d)^(-1).BMA-based ET greatly improved its explanation to 89%and decreased the RMSD to 0.43 mm·(8 d)^(-1).The Three-River-Source National Park experienced an overall insignificant increasing trend in its inter-annual ET from 2003 to 2015.At the regional scale,the effects of temperature and precipitation on evapotranspiration were not significant,but were significant in the Yangtze River Source Park.Temperature and precipitation had positive impacts on evapotranspiration.The evapotranspiration showed different trends due to the geographi-cal differences between parks.This study provided a method reference for other multi-source data integration analysis.The integrated evapotranspiration data could effectively reduce the uncertainty of the original models and provide a more accurate data basis for the study of regional water heat change,which is of great significance to better understand water cycle under climate changes.