scholarly journals Urmia Lake water-level change detection and modeling

2016 ◽  
Vol 2 (4) ◽  
pp. 1-16 ◽  
Author(s):  
Farshad Fathian ◽  
Reza Modarres ◽  
Zohreh Dehghan
Keyword(s):  
Change Detection ◽  
Water Level ◽  
Lake Water ◽  
Urmia Lake ◽  
Water Level Change ◽  
Lake Water Level ◽  
Level Change

scholarly journals Evidences of hydraulic relationships between groundwater and lake water across the large floodplain wetland of Poyang Lake, China

2017 ◽  
Vol 18 (2) ◽  
pp. 698-712 ◽  
Author(s):  
Yunliang Li ◽  
Jing Yao ◽  
Guizhang Zhao ◽  
Qi Zhang
Keyword(s):  
Water Level ◽  
Lake Water ◽  
Poyang Lake ◽  
Spatial And Temporal Variability ◽  
Floodplain Wetland ◽  
Lake Water Level ◽  
Groundwater Dynamics ◽  
Isotope Evidence ◽  
To Receive ◽  
Poyang Lake Wetland

Abstract Hydraulic relationship between wetlands and lakes has become an important topic for the scientific and decision-making communities. Poyang Lake, an open freshwater lake in China, and the extensive floodplain wetland surrounding the lake, plays an important role in protecting the biodiversity of this internationally recognized wetland system. This paper is the first field-based study into an investigation of the groundwater dynamics in the floodplain wetland and the associated hydraulic relationship with the lake using hydrological, hydrochemical and stable isotope evidence, as exemplified by Poyang Lake wetland. Results show that groundwater stores within the floodplain wetland exhibit spatial and temporal variability in terms of the magnitudes of groundwater level variations. Floodplain groundwater fluctuations largely reflect patterns of the precipitation and the lake water level; however, the groundwater dynamics are highly affected by the variations in the lake water level, rather than local precipitation. Floodplain wetland is most likely to receive the lake water during spring and summer and may recharge the lake during periods of low lake water level. Additionally, floodplain groundwater displays similar hydrochemical and environmental isotope signatures to that of the lake at different sampling periods, indicating a close hydraulic relationship between groundwater and the lake throughout the year.

Effect of Three Gorges Dam on Poyang Lake water level at daily scale based on machine learning

2021 ◽  
Vol 31 (11) ◽  
pp. 1598-1614
Author(s):  
Sheng Huang ◽  
Jun Xia ◽  
Sidong Zeng ◽  
Yueling Wang ◽  
Dunxian She
Keyword(s):  
Machine Learning ◽  
Water Level ◽  
Lake Water ◽  
Poyang Lake ◽  
Three Gorges Dam ◽  
Three Gorges ◽  
Lake Water Level ◽  
Daily Scale

scholarly journals Comparison of random forests and other statistical methods for the prediction of lake water level: a case study of the Poyang Lake in China

2016 ◽  
Vol 47 (S1) ◽  
pp. 69-83 ◽  
Author(s):  
Bing Li ◽  
Guishan Yang ◽  
Rongrong Wan ◽  
Xue Dai ◽  
Yanhui Zhang
Keyword(s):  
Water Level ◽  
Random Forests ◽  
Lake Water ◽  
Poyang Lake ◽  
Time Lag ◽  
Water Levels ◽  
Support Vector ◽  
Lake Water Level ◽  
Water Level Variations

Modeling of hydrological time series is essential for sustainable development and management of lake water resources. This study aims to develop an efficient model for forecasting lake water level variations, exemplified by the Poyang Lake (China) case study. A random forests (RF) model was first applied and compared with artificial neural networks, support vector regression, and a linear model. Three scenarios were adopted to investigate the effect of time lag and previous water levels as model inputs for real-time forecasting. Variable importance was then analyzed to evaluate the influence of each predictor for water level variations. Results indicated that the RF model exhibits the best performance for daily forecasting in terms of root mean square error (RMSE) and coefficient of determination (R2). Moreover, the highest accuracy was achieved using discharge series at 4-day-ahead and the average water level over the previous week as model inputs, with an average RMSE of 0.25 m for five stations within the lake. In addition, the previous water level was the most efficient predictor for water level forecasting, followed by discharge from the Yangtze River. Based on the performance of the soft computing methods, RF can be calibrated to provide information or simulation scenarios for water management and decision-making.

CART and PSO+KNN algorithms to estimate the impact of water level change on water quality in Poyang Lake, China

2019 ◽  
Vol 12 (9) ◽  
Author(s):  
Yilu Li ◽  
Mohd Yawar Ali Khan ◽  
Yunzhong Jiang ◽  
Fuqiang Tian ◽  
Weihong Liao ◽  
...  
Keyword(s):  
Water Quality ◽  
Water Level ◽  
Poyang Lake ◽  
Water Level Change ◽  
Level Change ◽  
The Impact

scholarly journals Do the regular annual extreme water level changes affect the seasonal appearance of Anabaena in Poyang Lake?

2018 ◽  
Author(s):  
Kuimei Qian ◽  
Martin Dokulil ◽  
Yuwei Chen
Keyword(s):  
Water Temperature ◽  
Water Level ◽  
Poyang Lake ◽  
Environmental Parameters ◽  
High Water ◽  
Water Level Change ◽  
Extreme Water Level ◽  
Level Change ◽  
Heterocyst Frequency ◽  
Water Level Changes

Background. Poyang Lake is an exceptional system exhibiting a water level change of up to 14 m every year. In the years 2013 and 2014 water level changes were 8.03 m and 11.22m respectively. The biomass of Anabaena and heterocyst frequency increased in the summers of recent years. Methods. A weekly or bi-weekly monitoring period from June to November 2013 and 2014 was set up to explain the reason for this phenomenon. Results. Anabaena was observed throughout the year. The average relative biomass of Anabaena in the study period was over 40%, being most abundant in summer. The average heterocyst frequency was 0.226% in 2013 and 0.760% in 2014. The SPSS analysis indicated a positive correlation of Anabaena biomass with water temperature and water level and negative one with TN, which is the reason for the increase of heterocyst frequency from 2013 to 2014. It also indicated that heterocyst frequency of Anabaena was positively correlated with water temperature, water level and PO4-P, and negatively with DIN/DIP, NO3-N and TN. At the same time, water temperature and DIN/DIP were significantly correlated with water level, which means that water level changes have a direct effect on Anabaena and its heterocyst formation in Poyang Lake. Conclusions. The results of the study support the hypothesis that increasing biomass and heterocyst formation of Anabaena were primarily caused by changes in the environmental parameters, such as high water temperature and suitable nutrients in summer and autumn, driven by the regular annual extreme water level change of Poyang Lake. The results can provide a theoretical basis for the management and utilization of Lake Poyang.

scholarly journals Do the regular annual extreme water level changes affect the seasonal appearance of Anabaena in Poyang Lake?

2018 ◽  
Author(s):  
Kuimei Qian ◽  
Martin Dokulil ◽  
Yuwei Chen
Keyword(s):  
Water Temperature ◽  
Water Level ◽  
Poyang Lake ◽  
Environmental Parameters ◽  
High Water ◽  
Water Level Change ◽  
Extreme Water Level ◽  
Level Change ◽  
Heterocyst Frequency ◽  
Water Level Changes

Background. Poyang Lake is an exceptional system exhibiting a water level change of up to 14 m every year. In the years 2013 and 2014 water level changes were 8.03 m and 11.22m respectively. The biomass of Anabaena and heterocyst frequency increased in the summers of recent years. Methods. A weekly or bi-weekly monitoring period from June to November 2013 and 2014 was set up to explain the reason for this phenomenon. Results. Anabaena was observed throughout the year. The average relative biomass of Anabaena in the study period was over 40%, being most abundant in summer. The average heterocyst frequency was 0.226% in 2013 and 0.760% in 2014. The SPSS analysis indicated a positive correlation of Anabaena biomass with water temperature and water level and negative one with TN, which is the reason for the increase of heterocyst frequency from 2013 to 2014. It also indicated that heterocyst frequency of Anabaena was positively correlated with water temperature, water level and PO4-P, and negatively with DIN/DIP, NO3-N and TN. At the same time, water temperature and DIN/DIP were significantly correlated with water level, which means that water level changes have a direct effect on Anabaena and its heterocyst formation in Poyang Lake. Conclusions. The results of the study support the hypothesis that increasing biomass and heterocyst formation of Anabaena were primarily caused by changes in the environmental parameters, such as high water temperature and suitable nutrients in summer and autumn, driven by the regular annual extreme water level change of Poyang Lake. The results can provide a theoretical basis for the management and utilization of Lake Poyang.

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