Impact of vegetation coverage on regional water balance in the nonhumid regions of China

Abstract

[1] The growth of vegetation is affected by water availability, while vegetation growth also feeds back to influence regional water balance. A better understanding of the relationship between vegetation state and water balance would help explain the complicated interactions between climate change, vegetation dynamics, and the water cycle. In the present study, the impact of vegetation coverage on regional water balance was analyzed under the framework of the Budyko hypothesis by using data from 99 catchments in the nonhumid regions of China, including the Inland River basin, the Hai River basin, and the Yellow River basin. The distribution of vegetation coverage on the Budyko curve was analyzed, and it was found that a wetter environment (higher P/E 0 ) had a higher vegetation coverage (M) and was associated with a higher evapotranspiration efficiency (E/E 0 ). Moreover, vegetation coverage was related not only to climate conditions (measured by the dryness index DI = E 0 /P) but also to landscape conditions (measured by the parameter n in the coupled water-energy balance equation). This suggests that the regional long-term water balance should not vary along a single Budyko curve; instead, it should form a group of Budyko curves owing to the interactions between vegetation, climate, and water cycle. A positive correlation was found between water balance component (E/P) and vegetation coverage (M) for most of the Yellow River basin and for the Inland River basin, while a negative correlation of M $ E/P was found in the Hai River basin. Vegetation coverage was successfully incorporated into an empirical equation for estimating the catchment landscape parameter n in the coupled water-energy balance equation. It was found that interannual variability in vegetation coverage could improve the estimation of the interannual variability in regional water balance.

Comparison of future runoff projections using Budyko framework and global hydrologic model: conceptual simplicity vs process complexity

“…(Roderick and Farquhar, 2011;Yang D. et al, 2007;Yang H. et al, 2008;Zhang X. et al, 2001). Although geology, topography and soils are not likely to experience any large scale changes in the time considered in this study, the catchment characteristic of n itself may change in the future due to land cover change (Li et al, 2013), vegetation change (Porporato et al, 2004;Yang D. et al, 2009) and increased CO 2 (Gedney et al, 2006). Those changes in the catchment characteristics were out of the scope of this study since the compared global hydrologic models also assumed constant land and vegetation covers.…”

“…Most of these studies have been applied at single basins (Donohue et al, 2011;Jiang et al, 2015;Liang and Liu, 2014;Liu and McVicar, 2012;Roderick and Farquhar, 2011;Xu et al, 2014;Zhang X. et al, 2014) or multiple basins within a single region: USA (Chen et al, 2013;Wang and Hejazi, 2011;Carmona et al, 2014;Istanbulluoglu et al, 2012), Australia (Donohue et al, 2010(Donohue et al, , 2012Teng et al, 2012), China (Yang D. et al, 2007(Yang D. et al, , 2009Yang and Yang, 2011;Yang H. et al, 2014;Cong et al, 2015;Xiong and Guo, 2012;Yu et al, 2013) and Europe (Velde et al, 2014;Oudin et al, 2008). The global scale studies have also been conducted but mainly focusing on the development of the Budyko functional forms (Koster and Suarez, 1999;Zhang L. et al, 2001;Arora, 2002) and their parameters (Li et al, 2013;Williams et al, 2012).…”

Analysis of catchment evapotranspiration at different scales using bottom-up and top-down approaches

“…This theoretical equation has also been extended to a variety of time scales. In order to consider the effect of the vegetation, Yang et al (2009) …”

Spatial cross‐correlation patterns of European low, mean and high flows

“…(1.1)) are negligible such that dS/dt ≈ 0. The aridity index and the evaporation ratio can be put into relation such that Koster and Suarez , 1999;Arora, 2002;Sankarasubramanian and Vogel , 2003;Donohue et al, 2007;Yang et al, 2007;Oudin et al, 2008;Yang et al, 2008;Szilagyi and Jozsa, 2009;Yang et al, 2009], but only relatively few assessed its variability across large spatial scales and along hydroclimatic gradients. For the eastern part of the continental United States (US) Milly [1994] was one of the first to use a physically based parametrisation of F to estimate mean annual runoff.…”