Divergent hydrological response to large-scale afforestation and vegetation greening in China

Li, Yue; Piao, Shilong; Li, Laurent; Chen, Anping; Wang, Xuhui; Ciais, Philippe; Huang, Ling; Lian, Xu; Peng, Shushi; Zeng, Zhenzhong; Wang, Kai; Zhou, Liming

doi:10.1126/sciadv.aar4182

Cited by 351 publications

(219 citation statements)

References 64 publications

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“…Obtaining observed run‐off data in the absence of human activities except vegetation restoration in the basins is difficult, thus hindering the construction of a more accurate regression model between vegetation restoration and run‐off. In addition, large‐scale afforestation and vegetation greening increases evapotranspiration and may change precipitation (Li et al, ). In turn, change of precipitation affects vegetation growth, and it is hard to completely distinguish the impact of climate change and vegetation restoration on run‐off (Zhai & Tao, ).…”

Section: Discussionmentioning

confidence: 99%

Run‐off affected by climate and anthropogenic changes in a large semi‐arid river basin

Yang

Sun

et al. 2020

Hydrological Processes

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A rapid reduction in run-off has been observed in the middle reaches of the Yellow River basin in recent decades. Understanding the contributions of climate change and human activities, such as vegetation restoration and water consumption, to surface water resource reduction has become urgent and very important for future regional planning. Here, we use attribution approaches to explore the effects of climate change and human activities on run-off over the past six decades. The results showed that the observed annual run-off at Tongguan station, which is located within the mainstream of the Yellow River, exhibited a significant decreasing trend of −0.69 mm year −1 (p < .01) and varied from −0.28 to −1.46 mm year −1 (p < .01) in the eight selected tributaries from 1960 to 2015. Two relatively abrupt changes in the double mass curves occurred around 1979 and 1999; compared with Period 1 (P1; 1960-1979), the average catchment run-off decreased 32% during Period 2 (P2 ; 1980-1999) and up to 49% during Period 3 (P3;. We calculated that approximately 29% of the reduction in the run-off during P2 and 18% during P3 were attributed to climate change. Increased surface water consumption resulted in effective run-off reduction, with relative contributions of approximately 27% and 28% during P2 and P3, respectively. With the implementation of the "Grain-for-Green" project, the vegetation coverage rapidly increased from 36% in P1 to 52% in P3 and reduced run-off by 35% during P3. These findings explain the run-off reduction and benefit water resource management in the middle reaches of the Yellow River basin.

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Section: Discussionmentioning

confidence: 99%

Run‐off affected by climate and anthropogenic changes in a large semi‐arid river basin

Yang

Sun

et al. 2020

Hydrological Processes

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“…Before carrying out the Pettitt test, autocorrelations in the MDMC slope were removed following the methodology found in Yue et al [46]. To validate the statistical significance of the break point, the nonparametric Mann-Whitney U test Z statistic was adopted [8,30,56]. The linear relationship in the reference period was used to predict the cumulative annual streamflow for the disturbance period, with the difference between this and the observed line regarded as the cumulative impact of forest change on streamflow (∆Q f ).…”

Section: Modified Double Mass Curvementioning

confidence: 99%

The Cumulative Effects of Forest Disturbance and Climate Variability on Streamflow in the Deadman River Watershed

Giles-Hansen

Wei

2019

Forests

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Climatic variability and cumulative forest cover change are the two dominant factors affecting hydrological variability in forested watersheds. Separating the relative effects of each factor on streamflow is gaining increasing attention. This study adds to the body of literature by quantifying the relative contributions of those two drivers to the changes in annual mean flow, low flow, and high flow in a large forested snow dominated watershed, the Deadman River watershed (878 km2) in the Southern Interior of British Columbia, Canada. Over the study period of 1962 to 2012, the cumulative effects of forest disturbance significantly affected the annual mean streamflow. The effects became statistically significant in 1989 at the cumulative forest disturbance level of 12.4% of the watershed area. The modified double mass curve and sensitivity-based methods consistently revealed that forest disturbance and climate variability both increased annual mean streamflow during the disturbance period (1989–2012), with an average increment of 14 mm and 6 mm, respectively. The paired-year approach was used to further investigate the relative contributions to low and high flows. Our analysis showed that low and high flow increased significantly by 19% and 58%, respectively over the disturbance period (p < 0.05). We conclude that forest disturbance and climate variability have significantly increased annual mean flow, low flow and high flow over the last 50 years in a cumulative and additive manner in the Deadman River watershed.

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“…Dynamics of environmental factors including meteorological data, soil property, aerosol optical thickness (AOT) data, and land cover are all related to GPP. AOT affects the GPP by reducing solar radiation, while the influence of land cover on GPP is mainly related to the changes of vegetation photosynthesis due to disturbances (such as afforestation and forest harvesting), which can be reflected by leaf area index (LAI) in large part (Li et al 2018b). Therefore, factors concerning climate, soil property, and LAI were used to test the environment influence on GPP.…”

Section: Introductionmentioning

confidence: 99%

Trends and controls of terrestrial gross primary productivity of China during 2000–2016

Xiao

Miao

et al. 2019

Environ. Res. Lett.

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Terrestrial gross primary productivity (GPP) is an important flux that drives the global carbon cycle. However, quantifying the trend and the control factor of GPP from the pixel level to the regional level is still a challenge. We generated monthly GPP dataset using the vegetation photosynthesis model and calculated the interannual linear trend for China during 2000-2016. The Breaks For Additive Seasonal and Trend method was applied to detect the timing of breakpoint and trends shift of monthly GPP, while boosted regression tree analysis was used to identify the most important factor and its relative influence on GPP based on gridded leaf area index (LAI), aerosol optical thickness, and NCEP-DOE Reanalysis II meteorological data. The results show that annual mean GPP was significantly (P<0.001, R 2 =0.78) increased, especially in the Loess Plateau and South China, from 2000 to 2016. The change rate of annual mean GPP declined from 18.82 g C m −2 yr −1 in 2000-2008 to 3.48 g C m −2 yr −1 in 2008-2016. About 55.4% of the breakpoints occur between 2009 and 2011 and was mainly distributed in Qinghai-Tibet Plateau, Central China, Southwestern China, and South China, and negative oriented GPP trends variation type still accounts for about 28.76%. LAI and temperature related factors generally had the highest relative influence on GPP in the north part and south part of China, respectively. Our study indicates that the ecological restoration projects and rapid urbanization have respectively induced the most obvious increase and decrease trends of GPP in China. Land cover change and climate change are the main reasons for GPP dynamics in the north and south part of China, respectively.

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Divergent hydrological response to large-scale afforestation and vegetation greening in China

Abstract: We found high spatial heterogeneity in the hydrological response to 30-year afforestation and vegetation greening in China.

Cited by 351 publications

References 64 publications

Run‐off affected by climate and anthropogenic changes in a large semi‐arid river basin

Run‐off affected by climate and anthropogenic changes in a large semi‐arid river basin

The Cumulative Effects of Forest Disturbance and Climate Variability on Streamflow in the Deadman River Watershed

Trends and controls of terrestrial gross primary productivity of China during 2000–2016

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