Application of a multiple model integration framework for mapping evapotranspiration with high spatial–temporal resolution in the Haihe River Basin, China. (December 2022)

• Record Type: Journal Article
• Authors: Chen, Yang; Lei, Tianjie; Xia, Jiangzhou; Tu, Yan; Wang, Yidong; Wang, Zhong-Liang
• Is Part Of: Ecological indicators. Volume 145(2023)
• Publication Date: 2022-12
• Subjects: Daily evapotranspiration -- Remote sensing -- Satellite-based ET models -- Eddy covariance -- Water balance method -- Bayesian model averaging (BMA); Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2022.109661
• Languages: English
• ISSNs: 1470-160X

Abstract

Graphical abstract: Highlights: Developed a multiple evapotranspiration (ET) model integration framework to calculate ET. High accuracy meteorological driven datasets were developed to reduce the uncertainties. Eddy covariance (EC) observation and water balance method proved the quality of ET estimates. Regional and spatial–temporal variations of ET in Haihe River Basin (HRB) were analysed. The increasing ET in HRB was mainly attributed to the increase of the leaf area index. Abstract: Evapotranspiration (ET) is a key component of the water and carbon cycles. Because it cannot be observed directly on large regional scales at present, many satellite-based ET datasets have been widely used for different purposes. However, their use has been limited at regional and field scales because of their coarse spatial and temporal resolution. In this study, the Bayesian model averaging (BMA) method was used to simulate daily ET values with 500 m spatial resolution in the Haihe River Basin (HRB) from 2000 to 2019. Validation performed with the in-situ observations showed that the BMA ET values had higher accuracy (R 2 = 0.69, RMSE = 1.15 mm/day) than those found with individual models. The BMA ET values also had higher accuracy and more credibility based on a water balance equation validation in the HRB. We used interpolated meteorological datasets, reanalysis net radiation products, and remote-sensing datasets to drive the BMA ET model. The mean annual BMA ET in the HRB from 2000 to 2019 was about 601.8 mm/year. The monthly change characteristics of this BMA ET product reflected water consumption characteristics and irrigation regularity of the winter wheat and summer maize rotation system. The BMA ET in the HRB showed a significant increasing trend from 2000 to 2019 of 3.39 mm/y 2 . The BMA ET values showed a strong positive trend at 80 % of HRB areas. The increasing trend of the BMA ET values was mainly attributed to an increase in the leaf area index. The high spatiotemporal resolution product showed variations in ET trends more accurately than the coarse resolution products. This high spatiotemporal product has great potential for applications in studies of regional microclimate change, interactions between human activities and climate change, drought disaster monitoring, agricultural policy making, and water security.