What Has Caused Desertification in China?

Feng, Qi; Ma, Hua; Jiang, Xuemei; Wang, Xin; Cao, Shixiong

doi:10.1038/srep15998

Cited by 159 publications

(96 citation statements)

References 27 publications

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“…Changes in pasture areas also occurred as result of transformation both from and into barren land (797.53 and 571.5 km 2 , respectively). These changes were caused by climate change, which in turn, led to the extension of pasture into high altitudes and desertification (Feng et al, ). In order to compare the net transformation according to different land‐use types, Table shows the predominating forms of changes.…”

Section: Resultsmentioning

confidence: 99%

Identifying separate impacts of climate and land use/cover change on hydrological processes in upper stream of Heihe River, Northwest China

Yang

Feng

Yin

et al. 2017

Hydrological Processes

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145

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Climate change and land use/cover change (LUCC) are two factors that produce major impacts on hydrological processes. Understanding and quantifying their respective influence is of great importance for water resources management and socioeconomic activities as well as policy and planning for sustainable development. In this study, the Soil and Water Assessment Tool (SWAT) was calibrated and validated in upper stream of the Heihe River in Northwest China. The reliability of the SWAT model was corroborated in terms of the Nash–Sutcliffe efficiency (NSE), the correlation coefficient (R), and the relative bias error (BIAS). The findings proposed a new method employing statistical separation procedures using a physically based modeling system for identifying the individual impacts of climate change and LUCC on hydrology processes, in particular on the aspects of runoff and evapotranspiration (ET). The results confirmed that SWAT was a powerful and accurate model for diagnosis of a key challenge facing the Heihe River Basin. The model assessment metrics, NSE, R, and BIAS, in the data were 0.91%, 0.95%, and 1.14%, respectively, for the calibration period and 0.90%, 0.96%, and −0.15%, respectively, for the validation period. An assessment of climate change possibility showed that precipitation, runoff, and air temperature exhibited upward trends with a rate of 15.7 mm, 6.1 mm, and 0.38 °C per decade for the 1980 to 2010 period, respectively. Evaluation of LUCC showed that the changes in growth of vegetation, including forestland, grassland, and the shrub area have increased gradually while the barren area has decreased. The integrated effects of LUCC and climate change increased runoff and ET values by 3.2% and 6.6% of the total runoff and ET, respectively. Climate change outweighed the impact of LUCC, thus showing respective increases in runoff and ET of about 107.3% and 81.2% of the total changes. The LUCC influence appeared to be modest by comparison and showed about −7.3% and 18.8% changes relative to the totals, respectively. The increase in runoff caused by climate change factors is more than the offsetting decreases resulting from LUCC. The outcomes of this study show that the climate factors accounted for the notable effects more significantly than LUCC on hydrological processes in the upper stream of the Heihe River.

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Section: Resultsmentioning

confidence: 99%

Identifying separate impacts of climate and land use/cover change on hydrological processes in upper stream of Heihe River, Northwest China

Yang

Feng

Yin

et al. 2017

Hydrological Processes

Self Cite

145

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“…Feng et al used a pooled regression model to consider the relative roles of climate change and human activities on desertified areas and vegetation coverage. The results showed that socioeconomic factors were the dominant factors affecting desertification [24]. Lü et al [25] quantified the changing trends in vegetation using the FVC estimated by remote sensing and analyzed the influential factors.…”

Section: Introductionmentioning

confidence: 99%

Human Activity Influences on Vegetation Cover Changes in Beijing, China, from 2000 to 2015

et al. 2017

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For centuries, the rapid development of human society has already made human activity the dominant factor in the terrestrial ecosystem. As the city of greatest importance in China, the capital Beijing has experienced eco-environmental changes with unprecedented economic and population growth during the past few decades. To better understand the ecological transition and its correlations in Beijing, Landsat Thematic Mapper (TM) and Operational Land Imager (OLI) images were used to investigate vegetation coverage changes using a dimidiate pixel model. Piecewise linear regression, bivariate-partial correlation analysis, and factor analysis were applied to the probing of the relationship between vegetation coverage changes and climatic/human-induced factors. The results showed that from 2000 to 2005, 2005 to 2010, and 2010 to 2015, Beijing experienced both restoration (6.33%, 10.08%, and 12.81%, respectively) and degradation (13.62%, 9.35%, and 9.49%, respectively). The correlation analysis results between climate and vegetation changes demonstrated that from 2000 to 2015, both the multi-year annual mean temperature (r = −0.819, p < 0.01) and the multi-year annual mean precipitation (r = 0.653, p < 0.05) had a significantly correlated relationship with vegetation change. The Beijing-Tianjin Sandstorm Source Control Project (BTSSCP) has shown beneficial spatial effects on vegetation restoration; the total effectiveness in conservation areas (84.94 in 2000-2010) was much better than non-BTSSCP areas (34.34 in 2000-2010). The most contributory socioeconomic factors were the population (contribution = 54.356%) and gross domestic product (GDP) (contribution = 30.677%). The population showed a significantly negative correlation with the overall vegetation coverage (r = −0.684, p < 0.05). The GDP was significantly negatively correlated with vegetation in Tongzhou, Daxing, Central city, Fangshan, Shunyi, and Changping (r = −0.601, p < 0.01), while positively related in Huairou, Miyun, Pinggu, Mentougou and Yanqing (r = 0.614, p < 0.01). These findings confirm that human activity is a very significant factor in impacting and explaining vegetation changes, and that some socioeconomic influences on vegetation coverage are highly spatially heterogeneous, based on the context of different areas.

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“…In the YLC region, the forest increased mainly due to the conversion from the pasture (63.65 km 2 ), which is primarily attributed to the afforestation programs and ecological environment restoration programs in Qilian mountain launched in early 2000s [43]. Pasture area increased results from the conversion from barren land (226.03 km 2 ), which is due to the global warming that led to pasture extending to higher altitude area [33]. The other two conversion types in YLC are pasture to farm land (13.3 km 2 ) and glacier to barren land (28.37 km 2 ), which occupies about 12% of total land use conversion area.…”

Section: Calibration and Validation Of Swat Modelmentioning

confidence: 99%

“…The total annual runoff is 16.05 × 10 8 m 3 with significant interannual variability [31]. Conditions within the Heihe River have attracted great attention in China due to increasing pressures in the nation, particularly in water resources and the degradation of natural environmental sectors [32,33]. [28].…”

Section: Introductionmentioning

confidence: 99%

Separation of the Climatic and Land Cover Impacts on the Flow Regime Changes in Two Watersheds of Northeastern Tibetan Plateau

Yang

Feng

Yin

et al. 2017

Advances in Meteorology

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Assessment of the effects of climate change and land use/cover change (LUCC) on the flow regimes in watershed regions is a fundamental research need in terms of the sustainable water resources management and ecosocial developments. In this study, a statistical and modeling integrated method utilizing the Soil and Water Assessment Tool (SWAT) has been adopted in two watersheds of northeastern Tibetan Plateau to separate the individual impacts of climate and LUCC on the flow regime metrics. The integrated effects of both LUCC and climate change have led to an increase in the annual streamflow in the Yingluoxia catchment (YLC) region and a decline in the Minxian catchment (MXC) region by 3.2% and 4.3% of their total streamflow, respectively. Climate change has shown an increase in streamflow in YLC and a decline in MXC region, occupying 107.3% and 93.75% of the total streamflow changes, respectively, a reflection of climatic latitude effect on streamflow. It is thus construed that the climatic factors contribute to more significant influence than LUCC on the magnitude, variability, duration, and component of the flow regimes, implying that the climate certainly dominates the flow regime changes in northeastern Tibetan Plateau.

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What Has Caused Desertification in China?

Cited by 159 publications

References 27 publications

Identifying separate impacts of climate and land use/cover change on hydrological processes in upper stream of Heihe River, Northwest China

Identifying separate impacts of climate and land use/cover change on hydrological processes in upper stream of Heihe River, Northwest China

Human Activity Influences on Vegetation Cover Changes in Beijing, China, from 2000 to 2015

Separation of the Climatic and Land Cover Impacts on the Flow Regime Changes in Two Watersheds of Northeastern Tibetan Plateau

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