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.

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 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 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

scholarly journals Seasonal behaviour of tidal damping and residual water level slope in the Yangtze River estuary: identifying the critical position and river discharge for maximum tidal damping

2019 ◽  
Vol 23 (6) ◽  
pp. 2779-2794 ◽  
Author(s):  
Huayang Cai ◽  
Hubert H. G. Savenije ◽  
Erwan Garel ◽  
Xianyi Zhang ◽  
Leicheng Guo ◽  
...  
Keyword(s):  
Water Level ◽  
River Discharge ◽  
Yangtze River ◽  
River Estuary ◽  
Yangtze River Estuary ◽  
Residual Water ◽  
The Yangtze River ◽  
The Yangtze River Estuary ◽  
Seasonal Behaviour ◽  
Residual Water Level

Abstract. As a tide propagates into the estuary, river discharge affects tidal damping, primarily via a friction term, attenuating tidal motion by increasing the quadratic velocity in the numerator, while reducing the effective friction by increasing the water depth in the denominator. For the first time, we demonstrate a third effect of river discharge that may lead to the weakening of the channel convergence (i.e. landward reduction of channel width and/or depth). In this study, monthly averaged tidal water levels (2003–2014) at six gauging stations along the Yangtze River estuary are used to understand the seasonal behaviour of tidal damping and residual water level slope. Observations show that there is a critical value of river discharge, beyond which the tidal damping is reduced with increasing river discharge. This phenomenon is clearly observed in the upstream part of the Yangtze River estuary (between the Maanshan and Wuhu reaches), which suggests an important cumulative effect of residual water level on tide–river dynamics. To understand the underlying mechanism, an analytical model has been used to quantify the seasonal behaviour of tide–river dynamics and the corresponding residual water level slope under various external forcing conditions. It is shown that a critical position along the estuary is where there is maximum tidal damping (approximately corresponding to a maximum residual water level slope), upstream of which tidal damping is reduced in the landward direction. Moreover, contrary to the common assumption that larger river discharge leads to heavier damping, we demonstrate that beyond a critical value tidal damping is slightly reduced with increasing river discharge, owing to the cumulative effect of the residual water level on the effective friction and channel convergence. Our contribution describes the seasonal patterns of tide–river dynamics in detail, which will, hopefully, enhance our understanding of the nonlinear tide–river interplay and guide effective and sustainable water management in the Yangtze River estuary and other estuaries with substantial freshwater discharge.

scholarly journals Determining Extreme Still Water Levels for Design and Planning Purposes Incorporating Sea Level Rise: Sydney, Australia

Atmosphere ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 95
Author(s):  
Phil J. Watson
Keyword(s):  
Sea Level Rise ◽  
Water Level ◽  
Sea Level ◽  
Tide Gauge ◽  
Water Levels ◽  
Extreme Value Analysis ◽  
Tide Gauge Record ◽  
Value Analysis ◽  
Mean Sea Level ◽  
The Impact

This paper provides an Extreme Value Analysis (EVA) of the hourly water level record at Fort Denison dating back to 1915 to understand the statistical likelihood of the combination of high predicted tides and the more dynamic influences that can drive ocean water levels higher at the coast. The analysis is based on the Peaks-Over-Threshold (POT) method using a fitted Generalised Pareto Distribution (GPD) function to estimate extreme hourly heights above mean sea level. The analysis highlights the impact of the 1974 East Coast Low event and rarity of the associated measured water level above mean sea level at Sydney, with an estimated return period exceeding 1000 years. Extreme hourly predictions are integrated with future projections of sea level rise to provide estimates of relevant still water levels at 2050, 2070 and 2100 for a range of return periods (1 to 1000 years) for use in coastal zone management, design, and sea level rise adaptation planning along the NSW coastline. The analytical procedures described provide a step-by-step guide for practitioners on how to develop similar baseline information from any long tide gauge record and the associated limitations and key sensitivities that must be understood and appreciated in applying EVA.

Street Level Flood Monitoring and Warning System, a conceptual model using IoT: A Case of Surat City

2021 ◽  
Vol 14 (12) ◽  
pp. 55-65
Author(s):  
Anant Patel ◽  
Sanjay Yadav
Keyword(s):  
Developing Countries ◽  
Water Level ◽  
Warning System ◽  
Water Levels ◽  
Mitigation Measures ◽  
Developed Country ◽  
River Bank ◽  
Street Level ◽  
Flood Warning ◽  
Flood Monitoring

Most of the natural disasters are unpredictable, but the most frequent occurring catastrophic event over the globe is flood. Developing countries are severely affected by the floods because of the high frequencies of floods. The developing countries do not have good forecasting system compared to the developed country. The metro cities are also settled near the coast or river bank which are the most vulnerable places to floods. This study proposes plan for street level flood monitoring and warning system for the Surat city, India. Waterlogging happens in the low lying area of the Surat city due to heavy storm and heavy releases from the Ukai dam. The high releases from upstream Ukai dam and heavy rainfall resulted into flooding in the low lying area of the Surat city. This research proposed a wireless water level sensor network system for the street water level flood monitoring. The system is proposed to monitor the water levels of different areas of city through the wireless water level sensors as well as to capture live photos using CCTV camera. This will help authority not only to issue flood warning but also to plan flood mitigation measures and evacuation of people.

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