Variations in water level, area and volume of Hongze Lake, China from 2003 to 2018

2020 ◽  
Vol 46 (6) ◽  
pp. 1511-1520
Author(s):  
Yu Cai ◽  
Chang-Qing Ke ◽  
Xiaoyi Shen
Keyword(s):  
Water Level ◽  
Hongze Lake ◽  
Area And Volume

scholarly journals Optimal Operation of Floodwater Resources Utilization of Lakes in South-to-North Water Transfer Eastern Route Project

2021 ◽  
Vol 13 (9) ◽  
pp. 4857
Author(s):  
Zitong Yang ◽  
Xianfeng Huang ◽  
Jiao Liu ◽  
Guohua Fang
Keyword(s):  
Water Level ◽  
Resource Utilization ◽  
Flood Control ◽  
Optimal Operation ◽  
Water Transfer ◽  
Water Levels ◽  
Reservoir Storage ◽  
Flood Season ◽  
Hongze Lake ◽  
North Water

In order to meet the demand of emergency water supply in the northern region without affecting normal water transfer, considering the use of the existing South-to-North Water Transfer eastern route project to explore the potential of floodwater resource utilization in the flood season of Hongze Lake and Luoma Lake in Jiangsu Province, this paper carried out relevant optimal operating research. First, the hydraulic linkages between the lakes were generalized, then the water resources allocation mode and the scale of existing projects were clarified. After that, the actual available amount of flood resources in the lakes was evaluated. The average annual available floodwater resources in 2003–2017 was 1.49 billion m3, and the maximum available capacity was 30.84 billion m3. Then, using the floodwater resource utilization method of multi period flood limited water levels, the research period was divided into the main flood season (15 July to 15 August) and the later flood season (16 August to 10 September, 11 September to 30 September) by the Systematic Clustering Analysis method. After the flood control calculation, the limited water level of Hongze Lake in the later flood season can be raised from 12.5 m to 13.0 m, and the capacity of reservoir storage can increase to 696 million m3. The limited water level of Luoma Lake can be raised from 22.5 m to 23.0 m (16 August to 10 September), 23.5 m (11 September to 30 September), and the capacity of reservoir storage can increase from 150 to 300 million m3. Finally, establishing the floodwater resource optimization model of the lake group with the goals of maximizing the floodwater transfer amount and minimizing the flood control risk rate, the optimal water allocation scheme is obtained through the optimization algorithm.

scholarly journals Influence of Hydrological Conditions on the Ecological State of Shallow Lake Vörtsjärv

Geografie ◽  
2004 ◽  
Vol 109 (2) ◽  
pp. 129-144
Author(s):  
Arvo Järvet
Keyword(s):  
Water Level ◽  
Shallow Lake ◽  
Water Body ◽  
Water Regime ◽  
Water Level Fluctuations ◽  
Ecological State ◽  
Fish Kills ◽  
Lake Võrtsjärv ◽  
Phosphorous Compounds ◽  
Area And Volume

Lake Vörtsjärv as a very shallow (mean depth 2.8 m) water-body and considerable water level fluctuations cause changes in both the surface area and volume of the lake. Due to the shallowness of the lake, low level periods are accompanied by several phenomena detrimental to its ecosystem, like cyanophyte blooms, overgrowing with macrophytes, resuspension of phosphorous compounds, restricted spawning places for pike and winter fish kills. In the years of low water level the perspectives to catch in established fishing sites using particular gear as well as access to harbours are hindered. Causal relations between the water regime and ecological state of the lake Vörtsjärv have been discussed in this paper.

scholarly journals Estimation of the Bay Proval Volumein Lake Baikal Using the QGIS and the SAGA GIS Geographic Information Systems

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Polina Sorokina
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Water Level ◽  
Population Size ◽  
Lake Baikal ◽  
Water Surface ◽  
Water Area ◽  
Geographic Information ◽  
Water Surface Area ◽  
Area And Volume

The research estimated the water surface area and volume of the fishing bay Proval in Lake Baikal by using the QGIS and SAGA geographic information systems. Such characteristics are used by ichthyologists to assess the reception capacity of the water area. Additionally, we considered the cases when the water level drops by 0.6 and 1.2 meters. The results may be used to predict population size of Baikal omul in low-water periods.

Multi-station joint forecast model of water level in Hongze lake based on PSO-LightGBM

2021 ◽  
Author(s):  
Tao Sun ◽  
Yibin Wang ◽  
Xin Jin ◽  
Zhicheng Zha
Keyword(s):  
Water Level ◽  
Forecast Model ◽  
Hongze Lake

Maximum water level of Hongze Lake and its relationship with natural changes and human activities from 1736 to 2005

2013 ◽  
Vol 304 ◽  
pp. 85-94 ◽  
Author(s):  
Yixing Yin ◽  
Ying Chen ◽  
Shutong Yu ◽  
Wucheng Xu ◽  
Wen Wang ◽  
...  
Keyword(s):  
Water Level ◽  
Human Activities ◽  
Hongze Lake ◽  
Maximum Water Level ◽  
Maximum Water

scholarly journals Škilietų ir Tabaliukų ežerų morfometrija / Morphometry of Škilietai and Tabaliukai Lakes

2020 ◽  
pp. 69-84
Author(s):  
Marijus Pileckas ◽  
Tauras Alekna
Keyword(s):  
Water Level ◽  
Surface Area ◽  
Water Level Fluctuations ◽  
Small Surface ◽  
Depth Measurement ◽  
Catchment Areas ◽  
Lake Bottom ◽  
Closed Groups ◽  
The Baltic ◽  
Area And Volume

Depth measurements of Škilietai and Tabaliukai Lakes (located in the Baltic Uplands, Aukštadvaris regional park, Lithuania) were taken in January and February of 2019. At the same time, the shorelines of the lakes were revised. Measurements were made from ice; measurement density varies from 34 to 46 spots per hectare. Depth measurement accuracy up to 0,05 m in Tabaliukai Lakes and Lake Škilietai I, up to 0,1 m in Lake Škilietai II. Accuracy of spot coordinates and water surface elevation measurement using GNSS receiver Topcon Hiper SR up to 1–2 cm. Later, detailed (0.50 x 5 m) digital lake bottom models (DEM) were developed, bathymetric plans of the lakes were created, the main morphometric features were calculated, the boundaries and area of the lake catchments were defined, and the physical-geographical characteristics of the lakes were described based on field observations and various data. Škilietai and Tabaliukai are small and closed groups of lakes (each group consists of 2 lakes) of glaciokarst origin. Despite small surface area (1.7–5.3 ha) the lakes are quite deep (9.8–18.5 m). Differences in the surface area and volume (77.8–436.3 thousand m3) of lakes are due to large differences in catchment areas. The shape of the lakes is remarkably regular, close to the circle. Tabaliukai Lakes usually are connected through bog lag and share the same water level, meanwhile, the water level in Škilietai Lakes differs on average by ~0.20 m. During the observation period (from spring of 2018 to May of 2020), the amplitude of water level fluctuations in Škilietai Lakes reached 0,41–0,48 m, and in Tabaliukai Lakes 0,67 m. The differences in the area and volume of the studied lakes are mainly due to the very different area of the lake catchments. Keywords: Škilietai, Tabaliukai, glaciokarst, lakes, bathymetric chart, morphometry, Lithuania, Aukštadvaris Regional Park.

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