Large-scale afforestation significantly increases permanent surface water in China's vegetation restoration regions
Graphical abstract
Introduction
Surface water represents only part of the total water resources, but it is the most easily used by humans (Postel et al., 1996) and supplies a wide range of ecosystem services. Changes in surface water resources are an increasingly important indicator of climate change (Holgerson and Raymond, 2016), biological diversity (Gardner et al., 2015) and human wellbeing (Jin et al., 2019). In particular, surface water resources have been valued as a critical factor affecting urban development and regional competition (Veldkamp et al., 2017). Surface water resources are highly sensitive, whose location and persistence are both influenced by climate and anthropogenic activities (Vörösmarty et al., 2000). Surface water variations, despite different influencing factors, are widespread worldwide (Pekel et al., 2016). For example, Australia's millennium drought severely affected surface hydrological processes, resulting in a continuous decline in water resources in Australia from 1999 to 2009 (Tulbure and Broich, 2019). In the Mongolian Plateau, lakes have significantly shrunk as an important component of surface water reduction (Zhang et al., 2017). The number of lakes has decreased from 785 in the 1980s to 577 in 2010, mainly due to precipitation changes, coal mining and irrigation (Tao et al., 2015). The spatiotemporal patterns of surface water change are crucial due to the increasing demands for water and the various ecosystem services provided by water resources, which are caused by population increases (Piao et al., 2010). Studies on the dynamic changes and influencing factors of surface water will help us better regulate water resources and provide benefits for human beings (Oki and Kanae, 2006).
Current studies on large-scale surface waters mainly focus on influencing factors that correspond to surface water variations, such as climate change (Gebrechorkos et al., 2019; Heimhuber et al., 2017; Sridhar and Anderson, 2017) and anthropogenic impacts; the latter mainly include fast agricultural activities, uncomfortably fast industrial development and overgrazing (Donchyts et al., 2016; Wang et al., 2019). However, informative reports about the effects of vegetation cover changes, especially forest dynamics, on the variation in surface water at the regional scale remain unavailable. Most previous studies are small-scale case studies (Yao et al., 2012), investigating an individual type of surface water (i.e., streamflow, lake or reservoir) (Buttle and Metcalfe, 2000; Ma et al., 2010). Small-scale research cannot clarify the dynamics of surface water in a complex system with multi-factor interactions, which must be influenced by neighbouring systems in terms of climate and human activity, and studies on a single surface water type also ignore the integrity of surface water (Xu, 1988). At different scales, geographical locations and analytical methods could derive conflicting conclusions regarding the role of forests in surface water regulation (Evaristo and McDonnell, 2019). Global forests have undergone dramatic changes in recent decades (Hansen et al., 2013); these changes will accordingly act synergistically with climate change and other human activities to change the spatiotemporal distribution of surface water.
Since the 1970s, the Chinese government has implemented six key forestry projects to restore forests and grasslands to produce ecosystem service benefits (Lu et al., 2018; Ouyang et al., 2016; Zhang et al., 2015). Under the implementation of such projects, significant afforestation has occurred. The official forestry report indicated that the forest area in China increased by 19.0% from 2000 to 2015, with a net increase of 3.3 × 105 km2 (http://www.forestry.gov.cn/). Recent research has also revealed that China's greening pattern is extremely prominent. Human activities such as afforestation in China dominate the greening of the planet (Chen et al., 2019). Most of these projects are located in regions with fragile and sensitive ecological environments, and urban development is relatively slow (Cao et al., 2011). The spatiotemporal dynamics of surface water caused by afforestation are critical to the development of these regions as they provide a new range of ecosystem services (Grizzetti et al., 2016). However, in the context of large-scale ecological projects, the response of surface water resources to vegetation restoration and other human activities in China's vegetation restoration region is still controversial. Recently, it has been reported that large-scale tree planting in arid areas of northwest China may lead to the depletion of surface water resources (Zastrow, 2019). Feng et al. (2016) indicated that the current vegetation productivity on the Loess Plateau is close to the threshold, and further afforestation may lead to regional surface water shortages. Cao (2008) pointed out that afforestation in arid and semi-arid regions of China will aggravate environmental degradation and significantly affect regional surface water resources and ecosystems. In contrast, some studies pointed out that forests change the runoff distribution process by reducing flood runoff and increasing underground runoff, increase the stability of surface water, and have important water conservation functions (Biao et al., 2010; Chen et al., 2005). Li et al. (2018) used a couple land-atmosphere global climate model to clarify that vegetation feedbacks may lead to increased precipitation and pointed out that the increase in desertification in arid and semi-arid regions in China should not be attributed to reforestation. Therefore, the uncertain influence of large-scale vegetation cover changes on water resources in vegetation restoration regions in China needs to be further explored.
How to quantify the spatiotemporal dynamics of surface water and clarify its driving mechanisms to provide effective information to policy makers has always been a major challenge (Wang et al., 2019). Traditional methods mainly obtain in situ hydrological data from ground stations, which requires long-term ground monitoring and consumes extensive manpower and material resources (Liu et al., 2017). In contrast, remote sensing technology can provide long-term surface water data over a large spatial scale, which is a valuable alternative to monitoring surface water changes. Here, we use multi-source remote sensing data to comprehensively clarify the spatiotemporal patterns of surface water changes in vegetation restoration regions in China and further explore the influencing factors such as climate change and human activities. The objectives of this study were to (1) clarify and quantify the patterns of seasonality and transition of surface water in China's vegetation restoration regions regarding the implementation of large-scale ecological projects and (2) analyse the roles of climate and human activities, especially afforestation, on surface water changes using dynamic spatiotemporal data.
Section snippets
Study area description
To clarify the impact of vegetation restoration on surface water resources while reducing the interference of other factors, we selected our study area based on two principles: significant increases in vegetation cover, and similar regional geographic and climatic conditions. We calculated the per-pixel annual NDVI linear trends in China from 2000 to 2015 using the China NDVI spatial distribution dataset (http://www.resdc.cn/DOI) (Fig. 1c) and found that the region with the largest increasing
Surface water characteristics
The statistics for water seasonality for NE and LP are shown in Table 1. The total surface water areas of NE and LP in 2015 were 6715.7 km2 and 1043.6 km2, respectively. There was a high proportion of permanent water (12 months of water) in NE, which accounted for 55%. In contrast, the permanent water in LP accounted for only 40%. These seasonal waters were mainly concentrated in areas that were under water for 1 to 3 months of the year (Table 1), which is consistent with the rainfall events
Spatiotemporal patterns of surface water transition
The transitions of permanent water and seasonal water show different trends, which may be related to the different responses of permanent water and seasonal water to different influencing factors (Pekel et al., 2016). Studies have shown that a significant increase or decrease in vegetation cover may change the patterns of surface water (Egginton et al., 2014). In our study regions, permanent water seems to be mostly affected by changes in vegetation cover, especially by the implementation of
Conclusion
Here, we used multi-source remote sensing data to describe the characteristics of seasonality and transition of surface water. From 1984 to 2015, surface water in China's vegetation restoration regions underwent a significant transition. There were significant net increases in permanent water in the regions where large-scale ecological projects were implemented, such as NE in Stage-1 (increased by 13.0%) and Stage-2 (increased by 26.2%) and LP in Stage-2 (increased by 36.1%). Conversely,
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (41525003 and 41671282); the Strategic Priority Research Program of Chinese Academy of Sciences(grant no. XDB40020302).
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