scholarly journals Investigating a complex lake-catchment-river system using artificial neural networks: Poyang Lake (China)

2015 ◽  
Vol 46 (6) ◽  
pp. 912-928 ◽  
Author(s):  
Y. L. Li ◽  
Q. Zhang ◽  
A. D. Werner ◽  
J. Yao
Keyword(s):  
Water Level ◽  
Lake Water ◽  
Yangtze River ◽  
Poyang Lake ◽  
Multiple Stressors ◽  
Resource Planning ◽  
Water Levels ◽  
The Yangtze River ◽  
Large Lake ◽  
Lake Catchment

Lake hydrological simulations using physically based models are cumbersome due to extensive data and computational requirements. Despite an abundance of previous modeling investigations, real-time simulation tools for large lake systems subjected to multiple stressors are lacking. The back-propagation neural network (BPNN) is applied as a first attempt to simulate the water-level variations of a large lake, exemplified by the Poyang Lake (China) case study. The BPNN investigation extends previous modeling efforts by considering the Yangtze River effect and evaluating the influence of the Yangtze River on the lake water levels. Results indicate that the effects of both the lake catchment and the Yangtze River are required to produce reasonable BPNN calibration statistics. Modeling results suggest that the Yangtze River plays a significant role in modifying the lake water-level changes. Comparison of BPNN models to a 2D hydrodynamic model (MIKE 21) shows that comparable accuracies can be obtained from both modeling approaches. This implies that the BPNN approach is well suited to long-term predictions of the water-level responses of Poyang Lake. The findings of this work demonstrate that BPNN can be used as a valuable and computationally efficient tool for future water resource planning and management of the Poyang Lake.

scholarly journals Monitoring Temporal Change of River Islands in the Yangtze River by Remotely Sensed Data

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1484 ◽  
Author(s):  
Jinyan Sun ◽  
Lei Ding ◽  
Jiaze Li ◽  
Haiming Qian ◽  
Mengting Huang ◽  
...  
Keyword(s):  
Water Level ◽  
Yangtze River ◽  
Temporal Change ◽  
Flood Disaster ◽  
Water Levels ◽  
Sediment Supply ◽  
The Yangtze River ◽  
Flood Warning ◽  
River Islands ◽  
The Impact

The spatial extent and area of river islands are always changing due to the impact of hydrodynamic conditions, sediment supply and human activities. A catastrophic flood disaster was driven by sustained and heavy rainfall around the middle and lower Yangtze River in 18 June to 21 July 2016. The flood resulted in the most serious social-economic loss since 1954 and caused a larger-scale inundation for a short time. It is essential to continuously monitor the dynamics changes of river islands because this can avoid frequent field measurements in river islands before and after flood disasters, which are helpful for flood warning. This paper focuses on the temporal change of three river islands called Fenghuangzhou, Changshazhou, and one uninhabited island in the Yangtze River in 2016. In this study, GF-1 (GaoFen-1) WFV (wide field view) data was used for our study owing to its fine spatial and temporal resolution. A simple NDWI (Normalized Difference Water Index) method was used for the river island mapping. Human checking was then performed to ensure mapping accuracy. We estimated the relationship between the area of river islands and measured water levels using four models. Furthermore, we mapped the spatial pattern of inundation risk of river islands. The results indicate a good ability of the GF-1 WFV data with a 16-m spatial resolution to characterize the variation of river islands and to study the association between flood disaster and river islands. A significantly negative but nonlinear relationship between the water level and the area of the river island was observed. We also found that the cubic function fits best among three models (R2 > 0.8, P < 0.001). The maximum of the inundated area at the river island appeared in the rainy season on 8 July 2016 and the minimum occurred in the dry season on 28 December 2016, which is consistent with the water level measured by the hydrological station. Our results derived from GF-1 data can provide a useful reference for decision-making of flood warning, disaster assessment, and post-disaster reconstruction.

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.

Analysis of the Three Gorges Reservoir Operation on the Water Level of Yangtze River during the Non-Flood Season

2013 ◽  
Vol 864-867 ◽  
pp. 2207-2212 ◽  
Author(s):  
Jing Zheng
Keyword(s):  
Water Level ◽  
Yangtze River ◽  
Three Gorges Reservoir ◽  
Water Levels ◽  
Three Gorges ◽  
The Yangtze River ◽  
The Three Gorges Reservoir ◽  
Flood Season ◽  
The Three Gorges ◽  
Downstream Area

In the middle and downstream area of the Yangtze River, low water levels had occurred at post-flood season or before the flood season in recent years, since the trial impoundment of the Three Gorges Reservoir (TGR) in 2008. Based on the analysis of the low water levels, both rating curve of main stations in the middle and lower reaches of the Yangtze River and the operation of TGR in the dry season were analyzed in study to reveal the effects of the impoundment of TGR on water level of downstream areas. The research results show that the water supplement of the TGR could raise the downstream water level, which has positive effect on water supplement and navigation in this area.

scholarly journals Integrated model projections of climate change impacts on water-level dynamics in the large Poyang Lake (China)

2019 ◽  
Author(s):  
Yunliang Li ◽  
Qi Zhang ◽  
Hui Tao ◽  
Jing Yao
Keyword(s):  
Climate Change ◽  
Water Level ◽  
Lake Water ◽  
Hydrological Model ◽  
Poyang Lake ◽  
Baseline Period ◽  
Global Climate Models ◽  
Water Levels ◽  
Future Climate Change ◽  
Increased Risk

Abstract This study outlines a framework for examining potential impacts of future climate change in Poyang Lake water levels using linked models. The catchment hydrological model (WATLAC) was used to simulate river runoffs from a baseline period (1986–2005) and near-future (2020–2035) climate scenarios based on eight global climate models (GCMs). Outputs from the hydrological model combined with the Yangtze River's effects were fed into a lake water-level model, developing in the back-propagation neural network. Model projections indicate that spring–summer water levels of Poyang Lake are expected to increase by 5–25%, and autumn–winter water levels are likely to be lower and decrease by 5–30%, relative to the baseline period. This amounts to higher lake water levels by as much as 2 m in flood seasons and lower water levels in dry seasons in the range of 0.1–1.3 m, indicating that the lake may be wet-get-wetter and dry-get-drier. The probability of occurrence for both the extreme high and low water levels may exhibit obviously increasing trends by up to 5% more than at present, indicating an increased risk in the severity of lake floods and droughts. Projected changes also include possible shifts in the timing and magnitude of the lake water levels.

scholarly journals Quantitative Assessment of the Influences of Three Gorges Dam on the Water Level of Poyang Lake, China

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1519 ◽  
Author(s):  
Dan Wang ◽  
Shuanghu Zhang ◽  
Guoli Wang ◽  
Qiaoqian Han ◽  
Guoxian Huang ◽  
...  
Keyword(s):  
Water Level ◽  
Yangtze River ◽  
Poyang Lake ◽  
Model Simulation ◽  
Water Storage ◽  
Three Gorges Dam ◽  
Three Gorges ◽  
The Yangtze River ◽  
Middle Reach ◽  
Significant Downward Trend

Lakes are important for global ecological balance and provide rich biological and social resources. However, lake systems are sensitive to climate change and anthropogenic activities. Poyang Lake is an important wetland in the middle reach of the Yangtze River, China and has a complicated interaction with the Yangtze River. In recent years, the water level of Poyang Lake was altered dramatically, in particular showing a significant downward trend after the operation of the Three Gorges Dam (TGD) in 2003, thus seriously affecting the lake wetland ecosystem. The operation of the TGD changed both the hydrological regime and the deeper channel in the middle reach of the Yangtze River, and affected the river–lake system between the Yangtze River and Poyang Lake. This study analyzed the change in the water level of Poyang Lake and quantified the contributions of the TGD operation, from the perspectives of water storage and erosion of the deeper channel in the middle reach of the Yangtze River, through hydrodynamic model simulation. The erosion of the deeper channel indicated a significant decrease in annual water level. However, due to the water storage of the TGD in September and October, the discharge in the Yangtze River sharply decreased and the water level of Poyang Lake was largely affected. Especially in late September, early October, and mid-October, the contributions of water storage of the TGD to the decline in the water level of Poyang Lake respectively reached 68.85%, 59.04%, and 54.88%, indicating that the water storage of the TGD was the main factor in the decrease in water level. The erosion of the deeper channel accelerated the decline of the water level of Poyang Lake and led to about 10% to 20% of the decline of water level in September and October. Due to the combined operation of the TGD and more reservoirs under construction in the upper TGD, the long-term and irreversible influence of the TGD on Poyang Lake should be further explored in the future.

Impact of lake inflow and the Yangtze River flow alterations on water levels in Poyang Lake, China

2014 ◽  
Vol 30 (4) ◽  
pp. 321-330 ◽  
Author(s):  
Xijun Lai ◽  
Qun Huang ◽  
Yinghao Zhang ◽  
Jiahu Jiang
Keyword(s):  
Yangtze River ◽  
River Flow ◽  
Poyang Lake ◽  
Water Levels ◽  
The Yangtze River

scholarly journals Hydrological evidence and causes of seasonal low water levels in a large river-lake system: Poyang Lake, China

2016 ◽  
Vol 47 (S1) ◽  
pp. 24-39 ◽  
Author(s):  
Jing Yao ◽  
Qi Zhang ◽  
Yunliang Li ◽  
Mengfan Li
Keyword(s):  
Yangtze River ◽  
Water Resource Management ◽  
Poyang Lake ◽  
Large River ◽  
Water Levels ◽  
The Yangtze River ◽  
Lake System ◽  
Spatial Differences ◽  
Northern Portion ◽  
Lake Systems

Seasonal variations in local catchments and connected rivers lead to complex hydrological behaviours in river-lake systems. Poyang Lake is a seasonally dynamic lake with frequent low levels in spring and autumn, which may be triggered by the local catchment and Yangtze River. Based on two typical years, a hydrodynamic model combined with long term hydrological observations was applied to quantify the spatiotemporal impacts of the local catchment and Yangtze River on spring and autumn low water levels in Poyang Lake. As a first attempt, this study explored the spatial differences of the two influences. Simulation results showed that the contributions of the catchment and the Yangtze River were approximately 70% and 30% in spring 1963, and 5% and 95% in autumn 2006, respectively. The area of catchment influence was mainly distributed in channels and southern floodplains, with relatively uniform water levels. The area impacted by the Yangtze River mainly spanned from the northern portion of the waterway to the central lake, with strong spatial variability. This study focused on two typical years; however, the results can be extended to explain common hydrological phenomena and improve future strategies of water resource management in this river-lake system.

Paleohydrological changes over the last 4000 years in the middle and lower reaches of the Yangtze River: Evidence from particle size and n-alkanes from Longgan Lake

The Holocene ◽  
2017 ◽  
Vol 27 (9) ◽  
pp. 1318-1324 ◽  
Author(s):  
Jiantao Xue ◽  
Jingjing Li ◽  
Xinyue Dang ◽  
Philip A Meyers ◽  
Xianyu Huang
Keyword(s):  
Grain Size ◽  
Water Level ◽  
Lake Water ◽  
Yangtze River ◽  
Late Holocene ◽  
Average Chain Length ◽  
The Yangtze River ◽  
Lake Water Level ◽  
Longgan Lake ◽  
History Of

We have reconstructed the history of late-Holocene paleohydrological changes in the middle and lower reaches of the Yangtze River using grain size and n-alkane data from a sediment core retrieved from Longgan Lake. We employ changes in the grain size distribution to reflect the water level in the floodplain lake, with a higher percentage of the finer fraction indicating higher water level and vice versa. The n-alkane molecular distribution, average chain length (ACL), and Paq ratio (C23+C25)/(C23+C25+C29+C31) are used to reflect mainly vegetation composition that is also sensitive to water depth. Our results reveal that the lake water level was relatively low and gradually increased from 4 to 2.7 ka. The period from 2.7 to 1.2 ka exhibited the highest late-Holocene lake water level in this region. The water level then decreased toward the present. This paleohydrological reconstruction agrees with existing paleoclimate reconstructions of the middle and lower reaches of the Yangtze River, confirming that the intensity of Asian monsoon rains is an important factor in affecting paleohydrological changes in this region.

scholarly journals Evolution characteristics and drivers of the water level at an identical discharge in the Jingjiang reaches of the Yangtze River

2020 ◽  
Vol 30 (10) ◽  
pp. 1633-1648
Author(s):  
Yuanfang Chai ◽  
Yunping Yang ◽  
Jinyun Deng ◽  
Zhaohua Sun ◽  
Yitian Li ◽  
...  
Keyword(s):  
Water Level ◽  
Yangtze River ◽  
The Yangtze River ◽  
Evolution Characteristics
Sign in / Sign up

Export Citation Format

Share Document