Journal of Geographical Sciences >
Growing impacts of lowflow events on vegetation dynamics in hydrologically connected wetlands downstream Yangtze River Basin after the operation of the Three Gorges Dam
Wang Dandan (1978), PhD, specialized in environmental science, hydrology and watershed management. Email: 17052133@qq.com 
Received date: 20220311
Accepted date: 20221130
Online published: 20230511
Supported by
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(YBNLTS2021028)
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 Northernbranch Delta (GND) and the Ganjiang Southernbranch Delta (GSD), using the Objectoriented 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 lowflow periods in Poyang Lake. Vegetation coverage in the GND and GSD increased at the rates of 0.39 and 0.22 km^{2}/year, respectively. The reservoir storage at the end of September accelerated the runoff recession in the GND and the GSD, making lowflow 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.
WANG Dandan , LIU Ying , ZHENG Lilin , LI Dahui . Growing impacts of lowflow events on vegetation dynamics in hydrologically connected wetlands downstream Yangtze River Basin after the operation of the Three Gorges Dam[J]. Journal of Geographical Sciences, 2023 , 33(4) : 885 904 . DOI: 10.1007/s1144202321110
Figure 1 Location of the Poyang Lake: (a) location of Poyang Lake in the Yangtze River Basin; (b) location of Ganjiang Northernbranch Delta (GND) and Ganjiang Southernbranch Delta (GSD) in Poyang Lake; (c) water body coverage of Poyang Lake when the lake levels reach 10, 14, and 19 m, respectively; (d) annual regulation of Three Gorges Dam 
Figure 2 Flowchart showing the research methodology and the structure of this study 
Table 1 Hydrological variables selected for this study. 
Aspect  Time scale  Hydrological variable 

Magnitude  Annual/spring/summer/autumn/winter, antecedent 5/10/15/20/25/30 days  AWL (annual/spr/sum/aut/win), AWI day 5/10/15/20/25/30 
Extremes  Annual/spring/summer/autumn/winter  HWL (annual/spr/sum/aut/win), LWL (annual/spr/sum/aut/win) 
Range of water level  Annual/spring/summer/autumn/winter  ROV (annual/spr/sum/aut/win) 
Duration  Flood/dry season  DDS (9 m), DDS(11 m), DFS (15 m), DFS (17 m), DFS (19 m) 
Timing  Flood/dry season  BDS (11 m), BFS (15 m) 
^{*} AWI day 10 indicates the average water level for the antecedent 10 days. DDS (11 m) indicates the duration of lake level lower than 11 m. DFS (17 m) means the duration of lake level higher than 17 m. BDS (11 m) means the date with lake level firstly lower than 11 m after flood recede. BFS (15 m) means the date with lake level firstly higher than 15 m. 
Table 2 Change trends of 33 hydrological variables from 1987 to 2020 
Aspect  Hydrological variable  Change point  Z  p 

Magnitude  AWL (annual)  2003  2.09  0.04 
AWL (spr)  2003  1.41  0.16  
AWL (sum)  1999  0.47  0.64  
AWL (aut)  2002  2.68  0.01  
AWL (win)  2003  1.35  0.18  
AWI day 5  2005  1.64  0.1  
AWI day 10  2005  1.64  0.1  
AWI day 15  2005  1.27  0.21  
AWI day 20  2005  1.35  0.18  
AWI day 25  2005  1.31  0.19  
AWI day 30  2005  1.44  0.15  
Extremes  HWL (annual)  1999  0.57  0.57 
HWL (spr)  2005  0.34  0.73  
HWL (sum)  1999  0  1  
HWL (aut)  2005  2.09  0.04  
HWL (win)  2003  1.33  0.18  
LWL (annual)  2002  2.32  0.02  
LWL (spr)  2003  2.17  0.03  
LWL (sum)  2005  0.88  0.38  
LWL (aut)  2005  2.45  0.01  
LWL (win)  2002  3.11  0  
Range of water level  ROV (annual)  1999  0.05  0.96 
ROV (spr)  1998  0.65  0.52  
ROV (sum)  2000  0.36  0.72  
ROV (aut)  2010  0.05  0.96  
ROV (win)  2003  0.49  0.63  
Duration  DDS (9 m)  2003  1.51  0.13 
DDS (11 m)  2003  2.89  0  
DFS (15 m)  2000  1.56  0.12  
DFS (17 m)  1999  0.88  0.38  
DFS (19 m)  1999  0.87  0.39  
Timing  BFS (15 m)  2003  1.04  0.3 
BDS (11 m）  2005  3.47  0 
Figure 3 Interannual variations in 9 significantly changed hydrological variables 
Figure 4 Classification maps of the GND and the GSD between 1987 and 2020 
Figure 5 Change trends in vegetation coverages in the GND and the GSD between 1987 and 2020 
Figure 6 Ordination plot by principal component analysis (PCA) based on 33 hydrological variables and vegetation area (VA = vegetation area): (a) GND; (b) GSD 
Figure 7 Correlation coefficients between vegetation coverage and 33 hydrological variables pre/postTGD operation: (a) GND; (b) GSD 
Figure 8 Variable importance plot for the hydrological variables in the random forest regression model. Higher value means the variable is more important in determining the accuracy of the prediction (a and b: GND; c and d: GSD) 
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