Spatiotemporal Patterns of Terrestrial Evapotranspiration in Response to Climate and Vegetation Coverage Changes across the Chinese Loess Plateau

Abstract

Spatiotemporal patterns of evapotranspiration (ET) and its controlling factors are important for ecosystem services and water resources management in the Chinese Loess Plateau (CLP). In this study, we assessed the spatial patterns of ET and then investigated the interannual variability of ET and its relationships with climate variability and vegetation coverage changes at the timescales of annual, active growing season, as well as different seasons across the entire CLP from 2000 to 2014. A MODIS-derived ET dataset, ground-based datasets of precipitation and atmospheric evaporative demand (AED), and a remote-sensing dataset of Normalized Difference Vegetation Index (NDVI) were comprehensively analyzed. Results showed that mean annual ET varied distinctly among different vegetation zones, generally higher in the more humid southeastern parts of the CLP. Summer ET and ET over active growing season significantly increased for more than 40% of the entire CLP area, and winter ET significantly decreased over ~70% of the entire CLP region, while annual ET, spring ET, and autumn ET remained quite stable during 2000–2014. Per-pixel interannual variability of ET was mainly positively correlated with that of precipitation and NDVI except for winter, but negatively correlated with AED trends. Our study also demonstrated that ET variation trends were exactly consistent for the entire CLP region, the areas mainly implemented with the Grain for Green (GFG) project, and other CLP areas not implemented with the GFG project during 2000–2014. Our findings suggest that the spatiotemporal patterns of CLP ET were mainly water-limited, and climate variability played an essential role in shaping the interannual variability of ET in the CLP. This study will improve our understanding on the ET variations over water-limited areas under climate and vegetation coverage changes.

Trends and attribution analysis of modelled evapotranspiration on the Tibetan Plateau

“…While being an important part of the water cycle, ET remains the least understood component of surface processes, and it has always received considerable attention (Katul et al, 2012; Paço et al, 2009; Pascolini‐Campbell et al, 2021; Piao et al, 2010; Zhang et al, 2001). To accurately assess ET variation, various ET estimation methods have been proposed, such as plant physiology (Marasco et al, 2014), micrometeorology (Maruyama et al, 2019; Xu et al, 2015; Zhou et al, 2016), water balance (Pascolini‐Campbell et al, 2021; Soni & Syed, 2021), isotope analysis (Wei et al, 2018), and remote sensing (Zhang, Kong, et al, 2019; Zhang, Wang, et al, 2019; Zheng et al, 2019). The methods based on plant physiology, micrometeorology, and water balance are often difficult to separate T from E. In addition, observation‐based methods are simultaneously limited by the heterogeneity of underlying surfaces, and are not easily applied to large‐scale ecosystems.…”

“…In recent years, with the development of satellite remote sensing, the quantitative estimation of large‐scale ET has made considerable progress. Satellite remote sensing can estimate large‐scale ET more easily and accurately with advances in technology (Zhang & Chen, 2017; Zheng et al, 2019). Zhang, Kong, et al (2019) and Zhang, Wang, et al (2019) used a complete carbon‐constrained, global ET diagnostic model at a high resolution, known as the Coupled Diagnostic Biophysical Model (called PML‐V2).…”