| 基于多源数据与多模型集成的流域人为蒸散发变异评估 |
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| 引用本文： | 韦林,段凯,刘效东,林玉茹,陈晓宏,王小辣.基于多源数据与多模型集成的流域人为蒸散发变异评估[J].水利学报,2022,53(4):433-444. |
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| 作者姓名： | 韦林 段凯 刘效东 林玉茹 陈晓宏 王小辣 |
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| 作者单位： | 中山大学 土木工程学院, 广东 广州 510275;中山大学 土木工程学院, 广东 广州 510275;南方海洋科学与工程广东省实验室(珠海), 广东 珠海 519082;华南农业大学 林学与风景园林学院, 广东 广州 510642;长江水利委员会 长江科学院, 湖北 武汉 430010 |
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| 基金项目： | 国家重点研发计划项目（2021YFC3001000，2021YFC3200205）；国家自然科学基金项目（51909285）；广东省“珠江人才计划”引进创新创业团队（2019ZT08G090）；广州市基础研究计划基础与应用基础研究项目（202102020377） |
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| 摘 要： | 人类活动对流域蒸散发的干扰日益显著,然而实测蒸散发数据稀少,且尺度差异与空间异质性等问题限制了大尺度陆面模型与遥感产品在人为蒸散发评估中的适用性与可靠性.本文提出了一种基于多源数据与贝叶斯模型平均的人为蒸散发变异评估框架,并应用于珠江流域.结果表明,通过综合利用地面观测(降水、径流、潜热通量)、社会统计(水资源开发利用...
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| 关 键 词： | 流域蒸散发 人类活动 多源数据 贝叶斯模型平均 珠江流域 |
| 收稿时间： | 2021/9/14 0:00:00 |
Assessing human-induced evapotranspiration change based on multi-source data and Bayesian model averaging at the basin scale |
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| WEI Lin,DUAN Kai,LIU Xiaodong,LIN Yuru,CHEN Xiaohong,WANG Xiaola.Assessing human-induced evapotranspiration change based on multi-source data and Bayesian model averaging at the basin scale[J].Journal of Hydraulic Engineering,2022,53(4):433-444. |
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| Authors: | WEI Lin DUAN Kai LIU Xiaodong LIN Yuru CHEN Xiaohong WANG Xiaola |
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| Affiliation: | College of Civil Engineering, Sun Yat-Sen University, Guangzhou 510275, China;College of Civil Engineering, Sun Yat-Sen University, Guangzhou 510275, China;Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai), Zhuhai 519082, China;College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China;Changjiang River Scientific Research Institute, CWRC, Wuhan 430010, China |
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| Abstract: | Anthropogenic disturbance on terrestrial evapotranspiration intensifies with socioeconomic developments. However,on-site evapotranspiration measurement is not readily available in many areas,and the applicability of data from large-scale land surface models and remote-sensing products is restrained by challenges in resolution gaps and spatial heterogeneity. In this paper, an evaluation framework of human-induced evapotranspiration change based on multi-source data and the Bayesian model averaging method is proposed. The case study in the Pearl River basin of China indicates that the reliability of assessment can be significantly improved by assimilating datasets derived from ground observations (precipitation, streamflow), water census, remote-sensing (GRACE satellite), and land surface models (Noah, CLSM, VIC, ERA-Interim), and synthesizing outputs from individual models in a probabilistic way. The results show that mean annual evapotranspiration was enhanced by 21% (137 mm/a) by human activities during 2003-2016,with the maximum and minimum impact found in May (+38 mm/month) and July (-27 mm/month),respectively. Irrigation water consumption and reservoir regulation were likely to be the major factors that dominated monthly variations in human-induced evapotranspiration change. |
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| Keywords: | evapotranspiration human activity multi-source data Bayesian model averaging the Pearl River Basin |
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