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.

Lake water level response to drought in a lake-rich region explained by lake and landscape characteristics

2020 ◽  
Vol 77 (11) ◽  
pp. 1836-1845
Author(s):  
K. Martin Perales ◽  
Catherine L. Hein ◽  
Noah R. Lottig ◽  
M. Jake Vander Zanden
Keyword(s):  
Climate Change ◽  
Water Level ◽  
Lake Water ◽  
Water Levels ◽  
Water Level Fluctuations ◽  
Lake Area ◽  
Lake Water Level ◽  
Landscape Characteristics ◽  
Lake Ecology ◽  
Coarse Woody Habitat

Climate change is altering hydrologic regimes, with implications for lake water levels. While lakes within lake districts experience the same climate, lakes may exhibit differential climate vulnerability regarding water level response to drought. We took advantage of a recent drought (∼2005–2010) and estimated changes in lake area, water level, and shoreline position on 47 lakes in northern Wisconsin using high-resolution orthoimagery and hypsographic curves. We developed a model predicting water level response to drought to identify characteristics of the most vulnerable lakes in the region, which indicated that low-conductivity seepage lakes found high in the landscape, with little surrounding wetland and highly permeable soils, showed the greatest water level declines. To explore potential changes in the littoral zone, we estimated coarse woody habitat (CWH) loss during the drought and found that drainage lakes lost 0.8% CWH while seepage lakes were disproportionately impacted, with a mean loss of 40% CWH. Characterizing how lakes and lake districts respond to drought will further our understanding of how climate change may alter lake ecology via water level fluctuations.

Zooplankton species richness and abiotic conditions in Thirlmere Lakes, New South Wales, Australia, with reference to water-level fluctuations

2020 ◽  
Vol 41 (1) ◽  
pp. 107-123
Author(s):  
Tsuyoshi Kobayashi ◽  
Martin Krogh ◽  
Hiroyuki ◽  
Russell J. Shiel ◽  
Hendrik Segers ◽  
...  
Keyword(s):  
Species Richness ◽  
Water Level ◽  
Lake Water ◽  
New South ◽  
Water Levels ◽  
Water Level Fluctuations ◽  
Zooplankton Species ◽  
Abiotic Conditions ◽  
Lake Water Level ◽  
South Wales

Water-level fluctuations can have significant effects on lake biological communities. Thirlmere Lakes are a group of five interconnected lakes located near Sydney. Water levels in Thirlmere Lakes have fluctuated over time, but there has been a recent decline that is of significant concern. In this study, we examined over one year the species composition and richness of zooplankton (Rotifera, Cladocera and Copepoda) and abiotic conditions in Lakes Nerrigorang and Werri Berri, two of the five Thirlmere lakes, with reference to lake water level. We recorded a total of 66 taxa of zooplankton, with the first report of the rotifer Notommata saccigera from Australia, and the first report of the rotifers Keratella javana, Lecane rhytida and Rousseletia corniculata from New South Wales. There was a marked difference in abiotic conditions between the two lakes, with more variable conditions in Lake Nerrigorang. There was a significant positive correlation between zooplankton species richness and lake water level but only for Lake Nerrigorang. Although the two lakes are closely situated and thought to be potentially connected at high water levels, they show distinct ecological characters and the effect of water-level fluctuations on zooplankton species richness seems to differ between the lakes.

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 Lake water level variations in Belarus

2013 ◽  
Vol 13 (2) ◽  
pp. 115-126 ◽  
Author(s):  
Aleksandr A. Volchak ◽  
Ivan Kirvel
Keyword(s):  
Time Series ◽  
Lake Water ◽  
Prediction Models ◽  
Hydrological Regime ◽  
Water Levels ◽  
Work Time ◽  
Lake Ecosystems ◽  
Lake Water Level ◽  
Water Level Variations ◽  
One Year

Abstract Lake level is one of the most important lake characteristics which allows the results of different effects to be identified and detected. In this work time series of the water levels of Belorussian lakes were analysed in order to detect pattern variations, to evaluate quantitatively the transformation of the hydrological regime of lake ecosystems and to develop prediction models. The possibility of plotting predicting models of lake water levels one year in advance was shown. The complication in plotting predicting models is in its individuality, the huge volume of initial data and the impossibility of immediate assessment of the results. Additional complications are caused by the inhomogeneity of time series of water levels in lakes.

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