This paper analyzes the monitored data of the 4 times of stream water conveyances to the river section where the stream flow was cut-off, of 9 groundwater-monitoring sections and 18 vegetation plots in the lower reach...This paper analyzes the monitored data of the 4 times of stream water conveyances to the river section where the stream flow was cut-off, of 9 groundwater-monitoring sections and 18 vegetation plots in the lower reaches of Tarim River. The results show that the groundwater depth in the lower reaches of Tarim River rose from 9.87 m before the conveyances to 7.74 m and 3.79 m after the first and second conveyances, 3.61 and 3.16 m after the 2 phases of the third conveyance, and 2.66 m after the fourth conveyance. The transverse response scope of groundwater level was gradually enlarged along both sides of the channel of conveyances, i.e., from 450 m in width after the first conveyance to 1050 m after the fourth conveyance, but the response degree of groundwater level was reduced with the increase of the distance away from the channel of conveyances. The composition, distribution and growth status of the natural vegetation are directly related to the groundwater depth. The indexes of Simpson’s biodiversity, McIntosh’s evenness and Margalef’s richness, which reflect the change of the quantity of species and the degree of biodiversity, are reduced from 0.70, 0.48 and 0.90 to 0.26, 0.17 and 0.37 re- spectively along with the drawdown of groundwater level from the upper reaches to the lower reaches. After the stream water conveyances, the natural vegetation in the lower reaches is saved and restored along with the rise of groundwater level, the response scope of vegetation is gradually enlarged, i.e., from 200— 250 m in width after the first conveyance to 800 m after the fourth conveyance. However, there is still a great disparity to the objective of protecting the “Green Corridor”in the lower reaches of Tarim River. Thus, it is suggested to convey the stream water in double-channel way, combine the conveyance with water supply in surface scope, or construct the modern pipe-conveyance network systems so as to save the natural vegetation in an intensive way, achieve the efficient water consumption and speed u展开更多
Wetland vegetation is intimately related to floodplain inundations,which can be seriously affected by dam operation.Poyang Lake is the largest floodplain wetland in China and naturally connected with the Yangtze River...Wetland vegetation is intimately related to floodplain inundations,which can be seriously affected by dam operation.Poyang Lake is the largest floodplain wetland in China and naturally connected with the Yangtze River and the Three Gorges Dam(TGD)upstream.To understand the potential impacts of TGD on Poyang Lake wetlands,we collected remote sensing imagery acquired during dry season from 1987 to 2020 and extracted vegetation coverage data in the Ganjiang Northern-branch Delta(GND)and the Ganjiang Southern-branch Delta(GSD),using the Object-oriented Artificial Neural Network Regression.Principal components analysis,correlation analysis,and the random forest model were used to explore the interactions between vegetation extent in the two deltas and 33 hydrological variables regarding magnitude,duration,timing,and variation.The implementation of the TGD advanced and extended the low-flow periods in Poyang Lake.Vegetation coverage in the GND and GSD increased at the rates of 0.39 and 0.22 km2/year,respectively.The reservoir storage at the end of September accelerated the runoff recession in the GND and the GSD,making low-flow events more influential for vegetation dynamics and shortening the response time of vegetation to the water regime.This study provides an important reference for evaluating the impacts of dam engineering on downstream wetlands.展开更多
Changes in land productivity have been endorsed by the Inter Agency Expert Group on Sustainable Development Goals(IAEGSDGs)as key indicators for monitoring SDG 15.3.1.Multiple vegeta-tion parameters from optical remot...Changes in land productivity have been endorsed by the Inter Agency Expert Group on Sustainable Development Goals(IAEGSDGs)as key indicators for monitoring SDG 15.3.1.Multiple vegeta-tion parameters from optical remote sensing techniques have been widely utilized across different land productivity decline processes and scales.However,there is no consensus on indicator selection and their effectiveness at representing land productivity declining at different scales.This study proposes a fusion framework that incorporates the trends and consistencies within the four com-monly used remote sensing-based vegetation indicators.We ana-lyzed the differences among the four vegetation parameters in different land cover and climate zones,finally producing a new global land productivity dynamics(LPD)product with confidence level degrees.The LPD classes indicated by the four vegetation indicators(VIs)showed that all three levels(low,medium,and high confidence)of increasing area account for 23.99%of the global vegetated area and declining area account for 7.00%.The Increase high-confidence(HC)area accounted for 2.77%of the total area,and the Decline-HC accounted for 0.35%of the total area.This study demonstrates the accuracy of the high-confidence(HC)area for the evaluation of land productivity decline and increase.The“forest”landcover type and“humid”climate zone had the largest increasing and declining area but had the lowest high-confidence proportion.The data product provides an important and optional reference for the assessment of SDG 15.3.1 at global and regional scales according to the specific application target.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.90102007)the Knowledge Innovation Project of the Chinese Academy of Sciences(Grant No.KZCX1-08-03).
文摘This paper analyzes the monitored data of the 4 times of stream water conveyances to the river section where the stream flow was cut-off, of 9 groundwater-monitoring sections and 18 vegetation plots in the lower reaches of Tarim River. The results show that the groundwater depth in the lower reaches of Tarim River rose from 9.87 m before the conveyances to 7.74 m and 3.79 m after the first and second conveyances, 3.61 and 3.16 m after the 2 phases of the third conveyance, and 2.66 m after the fourth conveyance. The transverse response scope of groundwater level was gradually enlarged along both sides of the channel of conveyances, i.e., from 450 m in width after the first conveyance to 1050 m after the fourth conveyance, but the response degree of groundwater level was reduced with the increase of the distance away from the channel of conveyances. The composition, distribution and growth status of the natural vegetation are directly related to the groundwater depth. The indexes of Simpson’s biodiversity, McIntosh’s evenness and Margalef’s richness, which reflect the change of the quantity of species and the degree of biodiversity, are reduced from 0.70, 0.48 and 0.90 to 0.26, 0.17 and 0.37 re- spectively along with the drawdown of groundwater level from the upper reaches to the lower reaches. After the stream water conveyances, the natural vegetation in the lower reaches is saved and restored along with the rise of groundwater level, the response scope of vegetation is gradually enlarged, i.e., from 200— 250 m in width after the first conveyance to 800 m after the fourth conveyance. However, there is still a great disparity to the objective of protecting the “Green Corridor”in the lower reaches of Tarim River. Thus, it is suggested to convey the stream water in double-channel way, combine the conveyance with water supply in surface scope, or construct the modern pipe-conveyance network systems so as to save the natural vegetation in an intensive way, achieve the efficient water consumption and speed u
基金Open Research Fund of State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University(20R01)East China Normal University Excellent Doctoral Students’Academic Innovation Ability Improvement Plan Project,No.YBNLTS2021-028。
文摘Wetland vegetation is intimately related to floodplain inundations,which can be seriously affected by dam operation.Poyang Lake is the largest floodplain wetland in China and naturally connected with the Yangtze River and the Three Gorges Dam(TGD)upstream.To understand the potential impacts of TGD on Poyang Lake wetlands,we collected remote sensing imagery acquired during dry season from 1987 to 2020 and extracted vegetation coverage data in the Ganjiang Northern-branch Delta(GND)and the Ganjiang Southern-branch Delta(GSD),using the Object-oriented Artificial Neural Network Regression.Principal components analysis,correlation analysis,and the random forest model were used to explore the interactions between vegetation extent in the two deltas and 33 hydrological variables regarding magnitude,duration,timing,and variation.The implementation of the TGD advanced and extended the low-flow periods in Poyang Lake.Vegetation coverage in the GND and GSD increased at the rates of 0.39 and 0.22 km2/year,respectively.The reservoir storage at the end of September accelerated the runoff recession in the GND and the GSD,making low-flow events more influential for vegetation dynamics and shortening the response time of vegetation to the water regime.This study provides an important reference for evaluating the impacts of dam engineering on downstream wetlands.
基金was funded by the National Key Research and Development Program of China(No.2016YFC0500806)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant Number XDA19090124).
文摘Changes in land productivity have been endorsed by the Inter Agency Expert Group on Sustainable Development Goals(IAEGSDGs)as key indicators for monitoring SDG 15.3.1.Multiple vegeta-tion parameters from optical remote sensing techniques have been widely utilized across different land productivity decline processes and scales.However,there is no consensus on indicator selection and their effectiveness at representing land productivity declining at different scales.This study proposes a fusion framework that incorporates the trends and consistencies within the four com-monly used remote sensing-based vegetation indicators.We ana-lyzed the differences among the four vegetation parameters in different land cover and climate zones,finally producing a new global land productivity dynamics(LPD)product with confidence level degrees.The LPD classes indicated by the four vegetation indicators(VIs)showed that all three levels(low,medium,and high confidence)of increasing area account for 23.99%of the global vegetated area and declining area account for 7.00%.The Increase high-confidence(HC)area accounted for 2.77%of the total area,and the Decline-HC accounted for 0.35%of the total area.This study demonstrates the accuracy of the high-confidence(HC)area for the evaluation of land productivity decline and increase.The“forest”landcover type and“humid”climate zone had the largest increasing and declining area but had the lowest high-confidence proportion.The data product provides an important and optional reference for the assessment of SDG 15.3.1 at global and regional scales according to the specific application target.
