Climate and land use change impacts on water yield ecosystem service in the Yellow River Basin, China

2021 ◽  
Vol 80 (3) ◽  
Author(s):  
Jie Yang ◽  
Baopeng Xie ◽  
Degang Zhang ◽  
Wenqian Tao
2010 ◽  
Vol 136 (1) ◽  
pp. 106-115 ◽  
Author(s):  
Yaqin Qiu ◽  
Yangwen Jia ◽  
Jincheng Zhao ◽  
Xuehong Wang ◽  
Jeff Bennett ◽  
...  

2021 ◽  
Vol 69 (1) ◽  
pp. 29-40
Author(s):  
CaiHong Hu ◽  
Guang Ran ◽  
Gang Li ◽  
Yun Yu ◽  
Qiang Wu ◽  
...  

AbstractThe changes of runoff in the middle reaches of the Yellow River basin of China have received considerable attention owing to their sharply decline during recent decades. In this paper, the impacts of rainfall characteristics and land use and cover change on water yields in the Jingle sub-basin of the middle reaches of the Yellow River basin were investigated using a combination of statistical analysis and hydrological simulations. The Levenberg Marquardt and Analysis of Variance methods were used to construct multivariate, nonlinear, model equations between runoff coefficient and rainfall intensity and vegetation coverage. The land use changes from 1971 to 2017 were ascertained using transition matrix analysis. The impact of land use on water yields was estimated using the M-EIES hydrological model. The results show that the runoff during flood season (July to September) decreased significantly after 2000, whereas slightly decreasing trend was detected for precipitation. Furthermore, there were increase in short, intense, rainfall events after 2000 and this rainfall events were more conducive to flood generation. The “Grain for Green” project was carried out in 1999, and the land use in the middle reaches of the Yellow River improved significantly, which make the vegetation coverage (Vc) of the Jingle sub-basin increased by 13%. When Vc approaches 48%, the runoff coefficient decreased to the lowest, and the vegetation conditions have the greatest effect on reducing runoff. Both land use and climate can change the water yield in the basin, but for areas where land use has significantly improved, the impact of land use change on water yield plays a dominant role. The results acquired in this study provide a useful reference for water resources planning and soil and water conservation in the erodible areas of the middle reaches of the Yellow River basin.


2020 ◽  
Author(s):  
Jingjing Liu ◽  
Jing Wang ◽  
Ying Fang ◽  
Zehui Li

<p>The Yellow River basin, from west to east through different gradient terrains and climates, has huge spatial differences of land use and problematic eco‐environment. The understanding of relationship between land use change and agricultural production is crucial for coordinating the conflict between land development and environment protection in the Yellow River basin. In this study, the relationship between changes in arable land and urban land and changes in vegetation cover and agricultural production potential were quantitatively analyzed. Whether reclaimed land in the Yellow River basin can be converted to arable land and whether the occupation of urban land will cause ecosystem degradation were also discussed. The results indicated that: (1) Land use change in the Yellow River basin was greatly influenced by precipitation, which also affected the agricultural production potential and the Normalized Difference Vegetation Index (NDVI) in the Yellow River basin. The implementation of the Grain for Green program (GGP) had an effective restoration for vegetation cover and the resistance of soil erosion. Although the net area of arable land decreased by 71.6 ten thousand ha, the net production potential of arable land still increased by 1.7 ten thousand tons due to the inferior quality of the arable land for ecological restoration. (2) The concentrated distributed grassland and forest shrunk and the supply of ecosystem services and NDVI reduced, leading to ecological degraded in urban agglomeration regions where human activity was concentrated and construction land was increasing rapidly during the period of 2000–2015. The arable land was reduced by 43.3 ten thousand ha due to urban expansion, accounting for 59% of the total area of urban expansion, and consequently the agricultural production potential in the lower reaches was decreased. (3) Although it has not contributed significantly to agricultural production, the reclaimed land can be converted to arable land to a certain extent, due to its reasonable use for improving the ecological status of the Yellow River basin. 34.1 ten thousand ha of unused land and grassland were reclaimed for arable land under the Requisition‐Compensation Equilibrium of Farmland, which accounts for 1.27% of the total arable land. The increase of potential productivity brought by the reclamation of land for agricultural use only accounts for 0.56% of the total arable land potential productivity. However, compared with the whole Yellow River basin and the GGP region, the region with arable land reclaimed by low-coverage grassland and unused land leads to the highest increasing rate of the supply of ecosystem services and NDVI. The results could provide theoretical support and decision-making basis for further eco‐environment reconstruction, and promoting the reasonable land use and high-quality development in the Yellow River basin.</p>


Author(s):  
Yanbo Qu ◽  
Haining Zong ◽  
Desheng Su ◽  
Zongli Ping ◽  
Mei Guan

The basic premise of regional ecological construction would be to scientifically and effectively grasp the characteristics of land use change and its impact on landscape ecological risk. The research objects of this paper are the typical areas of the Yellow River Basin in China and “process-change-drive” as the logical main line. Moreover, this paper is based on multi-period land use remote sensing data from 2000 to 2020, the regional land use change process and influencing factors are identified, the temporal and spatial evolution and response process of landscape ecological risk are discussed, and the land use zoning control strategy to reduce ecological risk is put forward. The results indicated: (1) The scale and structure of land use show the characteristics of “many-to-one” and “one-to-many”; (2) the process of land use change is affected by the alternation of multiple factors. The natural environment and socio-economic factors dominate in the early stage and the location and policy factors have a significant impact in the later stage; (3) the overall landscape ecological risk level and conversion rate show a trend of “high in the southeast, low in the northwest”, shift from low to high and landscape ecological risks gradually increase; and (4) in order to improve the regional ecological safety and according to the characteristics of landscape ecological risk and spatial heterogeneity, we should adopt the management and control zoning method and set different levels of control intensity (from key intensity to strict intensity to general intensity), and develop differentiated land use control strategies.


Author(s):  
Lichang Yin ◽  
Xiaoming Feng ◽  
Bojie Fu ◽  
Shuai Wang ◽  
Xiaofeng Wang ◽  
...  

Author(s):  
Aijun Guo ◽  
Yongnian Zhang ◽  
Fanglei Zhong ◽  
Daiwei Jiang

By integrating multiple remote sensing data sources this study accurately assesses the spatiotemporal characteristics of changes in ecosystem service values (ESVs) in the Yellow River Basin from 2000 to 2015 through Theil-Sen median trend analysis and the Mann-Kendall test. The stability and continuity of the ESVs were comprehensively characterized using coefficients of variation and the Hurst exponent. The degree of coherence between ESVs and economic growth (represented by gross domestic product GDP) on the same temporal and spatial scales was analyzed using ecological-economic coordination (EEC) models. The results show that (1) from 2001 to 2015 the total ESV and the ESV per unit area in the Yellow River Basin generally showed a U-shaped pattern (decreasing slightly then increasing rapidly). (2) The areas with increasing ESVs made up approximately 55.6% of the total area of the river basin. The areas with a decreasing pattern were mainly in the west and north of the Yellow River Basin. (3) The stability and continuity of the ESVs showed a clustered, compact distribution. (4) The most common level of EEC was slightly uncoordinated followed by slightly coordinated and highly coordinated. The proportion of coordinated areas was relatively higher in cultivated land and the lowest in built-up land.


Land ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 475 ◽  
Author(s):  
Xiao Lu ◽  
Yi Qu ◽  
Piling Sun ◽  
Wei Yu ◽  
Wenlong Peng

Exploring the green transition of cultivated land use from the perspective of green utilization efficiency evaluation has become an important content of deepening the study of cultivated land use transition, which is of great significance to promote food security and ecological civilization construction. At present, there are few studies on the green utilization efficiency of cultivated land (GUECL), which covers the comprehensive benefits of economy, ecology and society, combined with the requirements of ecological civilization and green development. Taking 65 cities (regions and autonomous prefectures) of the Yellow River Basin as the basic evaluation unit, the GUECL of the Yellow River Basin is evaluated with a Super-SBM model. In general, the GUECL of the Yellow River Basin was not high at four time points of 2000, 2006, 2012 and 2018, which presents a trend of “rising first and then falling”. Analyzing its temporal and spatial evolution pattern, the GUECL in the upper, middle and lower reaches presented an order of the upper reaches area > the lower reaches area > the middle reaches area; and the spatial variation trend showed a decrease from west to east, and a U-shaped change in the south-north direction. Using spatial correlation analysis, except for the year 2000, the GUECL in the Yellow River Basin presents a general distribution characteristic of spatial agglomeration, which is positively correlated in 2006, 2012 and 2018. The change of spatio-temporal pattern is the result of internal and external factors. The former mainly displays in the main characteristics of farmers, family characteristics and farmers’ cognition, while the latter is reflected in natural, social and policy factors.


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