scholarly journals Spatiotemporal variation and climatic response of water level of major lakes in China, Mongolia, and Russia

2020 ◽  
Vol 12 (1) ◽  
pp. 1200-1211
Author(s):  
Qinghua Tan ◽  
Yujie Liu
Keyword(s):  
Water Level ◽  
Lake Water ◽  
Climatic Factors ◽  
Water Levels ◽  
Key Factors ◽  
Large Lakes ◽  
Factors Affecting ◽  
Lake Water Level ◽  
Ecological Protection ◽  
Belt And Road

AbstractLakes are important indicators of climate change. The change in lake water level objectively reflects the availability of regional water resources. Analyzing the changes in water level and climate response of major lakes in countries along the “Belt and Road” is essential for sustainable water use and ecological protection. Based on the water level datasets of 39 large lakes (>400 km2) in China, Mongolia, and Russia (CMR) from 2002 to 2016, this study analyzed the spatiotemporal characteristics of water levels in major lakes of CMR, and their responses to climatic factors containing temperature, precipitation, and evapotranspiration. The results showed that (1) the water level of main lakes in CMR slightly increased with change rates ranged from −0.36 to 0.48 m/a, and the trends varied in lakes, (2) the water level of most lakes was sensitive to temperature with sensitivity value ranged from −2.14 m/°C to 5.59 m/°C, (3) changes of annual cumulative precipitation and evapotranspiration contributed most to the change of lake water level, but key factors affecting water level varied in lakes. Human activity is an important driving factor for the change in water levels and its impacts need further study.

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 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.

scholarly journals Densified multi-mission observations by developed optical water levels show marked increases in lake water storage and overflow floods on the Tibetan Plateau

2019 ◽  
Author(s):  
Xingdong Li ◽  
Di Long ◽  
Qi Huang ◽  
Pengfei Han ◽  
Fanyu Zhao ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Water Level ◽  
Lake Water ◽  
Water Storage ◽  
Water Levels ◽  
The Tibetan Plateau ◽  
Altimetry Data ◽  
Data Set ◽  
Lake Water Level ◽  
And Storage

Abstract. The Tibetan Plateau (TP) known as Asia's water towers is quite sensitive to climate change, reflected by changes in hydrological state variables such as lake water storage. Given the extremely limited ground observations on the TP due to the harsh environment and complex terrain, we exploited multisource remote sensing, i.e., multiple altimetric missions and Landsat archives to create dense time series (monthly and even higher such as 10 days on average) of lake water level and storage changes across 52 large lakes (> 100 km2) on the TP during 2000–2017 (the data set is available online with a DOI: https://doi.org/10.1594/PANGAEA.898411). Field experiments were carried out in two typical lakes to validate the remotely sensed results. With Landsat archives and partial altimetry data, we developed optical water levels that cover most of TP lakes and serve as an ideal reference for merging multisource lake water levels. The optical water levels show an uncertainty of ~ 0.1 m that is comparable with most altimetry data and largely reduce the lack of dense altimetric observations with systematic errors well removed for most of lakes. The densified lake water levels provided critical and accurate information on the long-term and short-term monitoring of lake water level and storage changes on the TP. We found that the total storage of the 52 lakes increased by 97.3 km3 at two stages, i.e., 6.68 km3/yr during 2000–2012 and 2.85 km3/yr during 2012–2017. The total overflow from Lake Kusai to Lake Haidingnuoer and Lake Salt during Nov 9–Dec 31 in 2011 was estimated to be 0.22 km3, providing critical information on lake overflow flood monitoring and prediction as the expansion of some TP lakes becomes a serious threat to surrounding residents and infrastructure.

Lake water level modeling using newly developed hybrid data intelligence model

2020 ◽  
Vol 141 (3-4) ◽  
pp. 1285-1300 ◽  
Author(s):  
Zaher Mundher Yaseen ◽  
Shabnam Naghshara ◽  
Sinan Q. Salih ◽  
Sungwon Kim ◽  
Anurag Malik ◽  
...  
Keyword(s):  
Water Level ◽  
Lake Water ◽  
Lake Water Level ◽  
Hybrid Data

Groundwater level assessment and prediction in the Nebraska Sand Hills using LIDAR-derived lake water level

2021 ◽  
pp. 126582
Author(s):  
Nawaraj Shrestha ◽  
Aaron Mittelstet ◽  
Aaron R. Young ◽  
Troy E. Gilmore ◽  
David C. Gosselin ◽  
...  
Keyword(s):  
Water Level ◽  
Lake Water ◽  
Groundwater Level ◽  
Lake Water Level ◽  
Nebraska Sand Hills ◽  
Sand Hills

scholarly journals Evaluation of historic and operational satellite radar altimetry missions for constructing consistent long-term lake water level records

2021 ◽  
Vol 25 (3) ◽  
pp. 1643-1670
Author(s):  
Song Shu ◽  
Hongxing Liu ◽  
Richard A. Beck ◽  
Frédéric Frappart ◽  
Johanna Korhonen ◽  
...  
Keyword(s):  
Water Level ◽  
Lake Water ◽  
Small Lakes ◽  
Radar Altimetry ◽  
Lake Water Level ◽  
Systematic Biases ◽  
Data Missing ◽  
Satellite Radar ◽  
Satellite Radar Altimetry

Abstract. A total of 13 satellite missions have been launched since 1985, with different types of radar altimeters on board. This study intends to make a comprehensive evaluation of historic and currently operational satellite radar altimetry missions for lake water level retrieval over the same set of lakes and to develop a strategy for constructing consistent long-term water level records for inland lakes at global scale. The lake water level estimates produced by different retracking algorithms (retrackers) of the satellite missions were compared with the gauge measurements over 12 lakes in four countries. The performance of each retracker was assessed in terms of the data missing rate, the correlation coefficient r, the bias, and the root mean square error (RMSE) between the altimetry-derived lake water level estimates and the concurrent gauge measurements. The results show that the model-free retrackers (e.g., OCOG/Ice-1/Ice) outperform the model-based retrackers for most of the missions, particularly over small lakes. Among the satellite altimetry missions, Sentinel-3 gave the best results, followed by SARAL. ENVISAT has slightly better lake water level estimates than Jason-1 and Jason-2, but its data missing rate is higher. For small lakes, ERS-1 and ERS-2 missions provided more accurate lake water level estimates than the TOPEX/Poseidon mission. In contrast, for large lakes, TOPEX/Poseidon is a better option due to its lower data missing rate and shorter repeat cycle. GeoSat and GeoSat Follow-On (GFO) both have an extremely high data missing rate of lake water level estimates. Although several contemporary radar altimetry missions provide more accurate lake level estimates than GFO, GeoSat was the sole radar altimetry mission, between 1985 and 1990, that provided the lake water level estimates. With a full consideration of the performance and the operational duration, the best strategy for constructing long-term lake water level records should be a two-step bias correction and normalization procedure. In the first step, use Jason-2 as the initial reference to estimate the systematic biases with TOPEX/Poseidon, Jason-1, and Jason-3 and then normalize them to form a consistent TOPEX/Poseidon–Jason series. Then, use the TOPEX/Poseidon–Jason series as the reference to estimate and remove systematic biases with other radar altimetry missions to construct consistent long-term lake water level series for ungauged lakes.

Flow-Based Structural Modelling and Dynamic Simulation of Lake Water Levels

2011 ◽  
pp. 798-814
Author(s):  
Nashon Juma Adero ◽  
John Bosco Kyalo Kiema
Keyword(s):  
Water Balance ◽  
Water Level ◽  
Dynamic Simulation ◽  
Lake Water ◽  
Complex Dynamics ◽  
Water Levels ◽  
Major Question ◽  
Modern Computer ◽  
Hydrological System ◽  
Dynamic Simulation Model

The continuing decline in lake water levels is both a concern and daunting challenge to scientists and policymakers in this era, demanding a rethinking of technological and policy interventions in the context of broader political and socio-economic realities. It is self-evident that diverse factors interact in space and time in complex dynamics to cause these water-level changes. However, the major question demanding sound answers is how these factors interact and by what magnitude they affect lake water balance with time. This chapter uses Lake Victoria’s hydrological system to shed light on the extensive and flexible modelling and simulation capabilities availed by modern computer models to understand the bigger picture of water balance dynamics. The study used the 1950-2000 hydrological data and riparian population growth to develop a dynamic simulation model for the lake’s water level. The intuitive structure of the model provided clear insights into the combined influence of the main drivers of the lake’s water balance. The falling lake water levels appeared to be mainly due to dam outflows at the outlet and reduced rainfall over the lake. The ensuing conclusions stressed the need for checks against over-release of lake water for hydropower production and measures for sustainable land and water management in the entire basin.

scholarly journals Bathymetry Development and Flow Analyses Using Two-Dimensional Numerical Modeling Approach for Lake Victoria

Fluids ◽  
2019 ◽  
Vol 4 (4) ◽  
pp. 182 ◽  
Author(s):  
Seema Paul ◽  
Jesper Oppelstrup ◽  
Roger Thunvik ◽  
John Mango Magero ◽  
David Ddumba Walakira ◽  
...  
Keyword(s):  
Water Level ◽  
Lake Water ◽  
Lake Victoria ◽  
State Level ◽  
Linear Measurement ◽  
Two Dimensional ◽  
Mean Flow ◽  
Lake Water Level ◽  
Outflow Boundary Condition ◽  
Outflow Boundary

This study explored two-dimensional (2D) numerical hydrodynamic model simulations of Lake Victoria. Several methods were developed in Matlab to build the lake topography. Old depth soundings taken in smaller parts of the lake were combined with more recent extensive data to produce a smooth topographical model. The lake free surface numerical model in the COMSOL Multiphysics (CM) software was implemented using bathymetry and vertically integrated 2D shallow water equations. Validated by measurements of mean lake water level, the model predicted very low mean flow speeds and was thus close to being linear and time invariant, allowing long-time simulations with low-pass filtered inflow data. An outflow boundary condition allowed an accurate simulation to achieve the lake’s steady state level. The numerical accuracy of the linear measurement of lake water level was excellent.

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