Historical Water Storage Changes Over China's Loess Plateau

Abstract

Estimating long-term average annual water balance at the catchment scale has been an important scientific problem in hydrology and a reliable method for long-term estimates of evapotranspiration (D. Wang, 2012). Water and vegetation in the catchments have reached equilibrium through long-term evolution, so that there is an inextricable relationship between water balance and vegetation change (Gerten et al., 2004). Changes in vegetation affect the elements of water balance, thus vegetation coverage plays an influential role in regulating regional water balance (Heimann & Reichstein, 2008; Seddon et al., 2016). Precipitation (P), evapotranspiration (ET), streamflow (Q), and water storage changes (ΔS) are important components of water balance estimates. Previous studies (e.g., Shao et al., 2019) have demonstrated that vegetation restoration could lead to increases in regional ET over the Loess Plateau, thus changing the water availability. This could potentially exacerbate tensions between water supply and demand in water-stressed regions. Thus, it can be further hypothesized that the vegetation changes may influence the catchment-scale water balance. In addition, the relationship between ΔS and vegetation may be scale dependent and remains unclear, thus studying the time scale of ΔS in vegetation recovery areas is particularly important. The Loess Plateau, a typical arid and semi-arid region, accounts for 6.6% of China's total land area and supports 8.5% of the population (Fu et al., 2011). It is one of the most water scarce regions with the most fragile ecosystems in the world (Y. Wang et al., 2011; B. Zhang et al., 2016). In the past, the Loess Plateau, with its sparse vegetation coverage, frequent summer rains and intensive agricultural practices, suffered unprecedented water scarcity, soil erosion and fragile ecosystems (C. Wang et al., 2016; Z. Yang et al., 2016). These ecological and environmental problems significantly affect ecological environment and socioeconomic

Changes in Dry-Season Water Availability and Attributions in the Yellow River Basin, China

“…During recent decade, the water storage over the YRB also showed a significant decreasing trend (Jiang et al, 2019), which was majorly induced by the vegetation greening . In the middle portion of the YRB, the E has significantly increased during the past 15 years and resulted in declines in total water resources (Shao et al, 2019;Shao et al, 2021). These findings together with our results have implications for ecosystem restoration and management in the YRB, because the decreased dry-season water availability may exert negative influences on vegetation growth and soil carbon sequestration.…”

Spatio-Temporal Variation and Driving Forces of Land-Use Change from 1980 to 2020 in Loess Plateau of Northern Shaanxi, China

“…Systematic analysis of land-use change provides decision-making references for the implementation of regional ecological policies, sustainable land use and the layout of regional agricultural industry. First, the implementation of the GFGP not only increases the area of woodland and improves the regional ecological environment, but also bring about the shortage of regional water resources and the water cycle at the basin scale [80][81][82]. In the future, the implementation of ecological projects should systematically consider the sustainable allocation of regional water and soil resources, especially in water-limited areas like the Loess Plateau.…”

Revegetation Does Not Decrease Water Yield in the Loess Plateau of China

“…Monthly evapotranspiration ( E ) is estimated based on multiple datasets, including the Global Land Evaporation—The Amsterdam Method E product (Martens et al., 2017) (GLEAM; 0.25° × 0.25°), the Priestley‐Taylor Jet Propulsion Laboratory model forced with remotely‐sensed vegetation dynamics and ground‐based auxiliary meteorological variables (0.1° spatial resolution; Fisher et al., 2008; Shao et al., 2019; Shao et al., 2021), and the modified WRF model with vegetation dynamics (WRF‐DYN) simulation (10 km spatial resolution). The ensemble mean of E datasets is used here given the large uncertainties of E from individual models (Han et al., 2020; Lian et al., 2018).…”