气候变化领域集成服务门户(CCPortal): Improving evapotranspiration estimation models through quantitative watershed parameter analysis and remote sensing applications

CCPortal

DOI	10.1002/hyp.15153
	Improving evapotranspiration estimation models through quantitative watershed parameter analysis and remote sensing applications
	Xue, Meimei; Pan, Yixuan; Zhang, Yundi; Wu, Jianping; Yan, Wenting; Liu, Xiaodong; Chen, Yuchan; Zhou, Guoyi; Chen, Xiuzhi
发表日期	2024
ISSN	0885-6087
EISSN	1099-1085
起始页码	38
结束页码	5
卷号	38 期号:5
英文摘要	Numerous models had been developed to predict the annual evapotranspiration (ET) in vegetated lands across various spatial scales. Fu's (Scientia Atmospherica Sinica, 5, 23-31) and Zhang's (Water Resources Research, 37, 701-708) ET simulation models have emerged as highly effective and have been widely used. However, both formulas have the non-quantitative parameters (m in Fu's model and w in Zhang's model). Based on the collected 1789 samples from global long-term hydrological studies, this study discovered significant relations between m (or w) and vegetation coverage or greenness in collected catchments. Then, we used these relations to qualify the parameters in both Zhang's and Fu's models. Results show that the ET estimation accuracies of Fu's (or Zhang's) model are significantly improved by about 13.49 mm (or 6.74 mm) for grassland and cropland, 38.52 mm (or 29.84 mm) for forest and shrub land (coverage<40%), 19.74 mm (or 16.17 mm) for mixed land (coverage<40%), respectively. However, Zhang's model shows higher errors compared with Fu's model, especially in regions with high m (or w) values, such as those with dense vegetations or P/E-0 (annual precipitation to annual potential ET) smaller than 1.0. Additionally, this study also reveals that for regions with vegetation cover less than 40%, the annual ET is not only determined by vegetation types, but also relates to the sizes of vegetation-covered areas. Conversely, for regions with vegetation cover more than 40%, the annual ET is mainly determined by the vegetation density rather than vegetation types or vegetation coverage. Thus, linking m (or w) parameters with vegetation greenness allows leveraging remote sensing for forest management in data-scarce areas, safeguarding regional water resources. This study pioneers integrating vegetation-related indices with basin parameters, advocating for their crucial role in more effective hydrological modelling.
英文关键词	ecohydrology; evapotranspiration estimation model; forest hydrology; vegetation cover; vegetation greenness
语种	英语
WOS研究方向	Water Resources
WOS类目	Water Resources
WOS记录号	WOS:001214077700001
来源期刊	HYDROLOGICAL PROCESSES
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/303704
作者单位	Sun Yat Sen University; Guangdong Academy of Sciences; South China Agricultural University; Nanjing University of Information Science & Technology; Nanjing University of Information Science & Technology
推荐引用方式 GB/T 7714	Xue, Meimei,Pan, Yixuan,Zhang, Yundi,et al. Improving evapotranspiration estimation models through quantitative watershed parameter analysis and remote sensing applications[J],2024,38(5).
APA	Xue, Meimei.,Pan, Yixuan.,Zhang, Yundi.,Wu, Jianping.,Yan, Wenting.,...&Chen, Xiuzhi.(2024).Improving evapotranspiration estimation models through quantitative watershed parameter analysis and remote sensing applications.HYDROLOGICAL PROCESSES,38(5).
MLA	Xue, Meimei,et al."Improving evapotranspiration estimation models through quantitative watershed parameter analysis and remote sensing applications".HYDROLOGICAL PROCESSES 38.5(2024).