Quantitative Assessment of Ecological Flow in the Yellow River Under Changing Environments

被引:0
作者
Guo, Wenxian [1 ]
Jiao, Xuyang [1 ]
Wang, Baoliang [1 ]
Huang, Lintong [1 ]
Wang, Hongxiang [1 ]
机构
[1] North China Univ Water Resources & Elect Power, Zhengzhou, Peoples R China
关键词
degree of assurance; ecological flow; hydrological variability; Yellow River mainstem; CLIMATE-CHANGE; IMPACTS; BASIN; STREAMFLOW; DISCHARGE;
D O I
10.1002/rra.4396
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Studying the streamflow characteristics of the Yellow River mainstem under changing environmental conditions is crucial for the management and sustainable development of water resources within its basin. This research employs a long short-term memory (LSTM) model to restore the flow characteristics of the Yellow River's mainstream under natural conditions. Additionally, the range of variation approach (RVA) and nonparametric kernel density estimation (KDE) method are integrated to quantitatively assess the impact of environmental changes on streamflow. The findings indicate that: (1) Hydrological variability in the Yellow River was observed in 1985, with a degree of variability ranging from 26% to 58%, classified as moderate. (2) The annual ecological flow value of the Yellow River is 560-1001 m3/s, and the average annual ecological flow assurance is 43%. (3) Based on LSTM simulation results (NSE > 0.7, R-2 > 0.8), it is concluded that the ecological flow assurance under natural conditions in the Yellow River exceeds the measured values, primarily due to human activities, which contribute over 52% to this discrepancy. These results suggest that the river ecosystem of the Yellow River's mainstem is relatively unstable and requires further management.
引用
收藏
页码:679 / 694
页数:16
相关论文
共 53 条
[1]   Assessing impacts of climate change and river regulation on flow regimes in cold climate: A study of a pristine and a regulated river in the sub-arctic setting of Northern Europe [J].
Bin Ashraf, Faisal ;
Haghighi, Ali Torabi ;
Marttila, Hannu ;
Klove, Bjorn .
JOURNAL OF HYDROLOGY, 2016, 542 :410-422
[2]  
BONER MC, 1982, J WATER POLLUT CON F, V54, P1408
[3]   Sustainable development in the Yellow River Basin: Issues and strategies [J].
Chen, Yi-ping ;
Fu, Bo-jie ;
Zhao, Yan ;
Wang, Kai-bo ;
Zhao, Meng M. ;
Ma, Ji-fu ;
Wu, Jun-Hua ;
Xu, Chen ;
Liu, Wan-gang ;
Wang, Hong .
JOURNAL OF CLEANER PRODUCTION, 2020, 263
[4]   Improving streamflow prediction in the WRF-Hydro model with LSTM networks [J].
Cho, Kyeungwoo ;
Kim, Yeonjoo .
JOURNAL OF HYDROLOGY, 2022, 605
[5]   Development of a comprehensive framework for assessing the impacts of climate change and dam construction on flow regimes [J].
Cui, Tong ;
Tian, Fuqiang ;
Yang, Tao ;
Wen, Jie ;
Khan, Mohd Yawar Ali .
JOURNAL OF HYDROLOGY, 2020, 590
[6]   Water resources management in a reservoir-regulated basin: Implications of reservoir network layout on streamflow and hydrologic alteration [J].
Dong, Ningpeng ;
Yang, Mingxiang ;
Yu, Zhongbo ;
Wei, Jianhui ;
Yang, Chuanguo ;
Yang, Qianya ;
Liu, Xuan ;
Lei, Xiaohui ;
Wang, Hao ;
Kunstmann, Harald .
JOURNAL OF HYDROLOGY, 2020, 586
[7]   Comparative study on the calculation methods of ecological base flow in a mountainous river [J].
Gao, Cheng ;
Hao, Manqiu ;
Song, Lianghong ;
Rong, Wang ;
Shao, Shuaibing ;
Huang, Ying ;
Guo, Yufa ;
Liu, Xueyao .
FRONTIERS IN ENVIRONMENTAL SCIENCE, 2022, 10
[8]   Short-term runoff prediction with GRU and LSTM networks without requiring time step optimization during sample generation [J].
Gao, Shuai ;
Huang, Yuefei ;
Zhang, Shuo ;
Han, Jingcheng ;
Wang, Guangqian ;
Zhang, Meixin ;
Lin, Qingsheng .
JOURNAL OF HYDROLOGY, 2020, 589
[9]   Forecasting river water temperature time series using a wavelet-neural network hybrid modelling approach [J].
Graf, Renata ;
Zhu, Senlin ;
Sivakumar, Bellie .
JOURNAL OF HYDROLOGY, 2019, 578
[10]   Driving forces of hydrological health and multifractal response of fish habitat in regulated rivers [J].
Guo, Wenxian ;
Yang, Huan ;
Hu, Jianwen ;
Hong, Fengtian ;
Ma, Yinchu ;
Wang, Hongxiang .
JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2023, 345