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.

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.

scholarly journals Statistical analysis of rainfall and streamflow time series in the Lake Tana Basin, Ethiopia

2018 ◽  
Vol 11 (1) ◽  
pp. 258-273 ◽  
Author(s):  
Tibebe B. Tigabu ◽  
Georg Hörmann ◽  
Paul D. Wagner ◽  
Nicola Fohrer
Keyword(s):  
Time Series ◽  
Water Level ◽  
Lake Water ◽  
Land Use Changes ◽  
Annual Rainfall ◽  
Lake Tana ◽  
Agricultural Water Management ◽  
Lake Water Level ◽  
Rainfall Variation ◽  
Sample Data

Abstract This research focuses on the statistical analyses of hydrometeorological time series in the basin of Lake Tana, the largest freshwater lake in Ethiopia. We used autocorrelation, cross-correlation, Mann–Kendall, and Tukey multiple mean comparison tests to understand the spatiotemporal variation of the hydrometeorological data in the period from 1960 to 2015. Our results show that mean annual streamflow and the lake water level are varying significantly from decade to decade, whereas the mean annual rainfall variation is not significant. The decadal mean of the lake outflow and the lake water level decreased between the 1990s and 2000s by 11.34 m3/s and 0.35 m, respectively. The autocorrelation for both rainfall and streamflow were significantly different from zero, indicating that the sample data are non-random. Changes in streamflow and lake water level are linked to land use changes. Improvements in agricultural water management could contribute to mitigate the decreasing trends.

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 The Exchange of Water and Salt across the Drogden Sill in Øresund September 1993-November 1994

1996 ◽  
Vol 27 (5) ◽  
pp. 351-368 ◽  
Author(s):  
FI. Jakobsen ◽  
M.J. Lintrup
Keyword(s):  
Time Series ◽  
Water Discharge ◽  
Water Levels ◽  
Salt Transport ◽  
Salt Flux ◽  
Layer System ◽  
Data Analyses ◽  
Baltic Proper ◽  
One Year ◽  
The Baltic

In this paper accurate hourly time series of water and salt transport across the Drogden Sill in Øresund are presented for a period of more than one year. The investigation is based on measured current, salinity and water levels from two fixed stations in the Drogden Channel and the Flinten Channel. The water transport is calculated by the method outlined in Jakobsen and Castejon (1995), which is extended in the present paper to include salt transport. The resulting water and salt transport distributions are given as functions of time or salinity. The data analyses show a net water discharge out of the Baltic Proper across the Drogden Sill of 2.5×103 m3/s and a net salt flux into the Baltic Proper of 58 tonnes/s. The outflow is water with a salinity less than 12 g/kg, while the inflow takes place in the interval from 12 g/kg to 32 g/kg. The Knudsen relations are extended by two equations regarding gross transport, whereby the barotropically pulsating flow of changing salinity may be equated with a corresponding two-layer system of opposing residual fluxes.

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.

scholarly journals Using multi-source satellite data for lake level modelling in ungauged basins: a case study for Lake Turkana, East Africa

2011 ◽  
Vol 8 (3) ◽  
pp. 4851-4890 ◽  
Author(s):  
N. M. Velpuri ◽  
G. B. Senay ◽  
K. O. Asante
Keyword(s):  
Lake Water ◽  
Satellite Altimetry ◽  
Lake Level ◽  
Water Levels ◽  
Ungauged Basins ◽  
Altimetry Data ◽  
Lake Turkana ◽  
Lake Water Level ◽  
Surface Water Resources ◽  
Satellite Altimetry Data

Abstract. Managing limited surface water resources is a great challenge in areas where ground-based data are either limited or unavailable. Direct or indirect measurements of surface water resources through remote sensing offer several advantages of monitoring in ungauged basins. A physical based hydrologic technique to monitor lake water levels in ungauged basins using multi-source satellite data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, a digital elevation model, and other data is presented. This approach is applied to model Lake Turkana water levels from 1998 to 2009. Modelling results showed that the model can reasonably capture all the patterns and seasonal variations of the lake water level fluctuations. A composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data is used for model calibration (1998–2000) and model validation (2001–2009). Validation results showed that model-based lake levels are in good agreement with observed satellite altimetry data. Compared to satellite altimetry data, the Pearson's correlation coefficient was found to be 0.81 during the validation period. The model efficiency estimated using NSCE is found to be 0.93, 0.55 and 0.66 for calibration, validation and combined periods, respectively. Further, the model-based estimates showed a root mean square error of 0.62 m and mean absolute error of 0.46 m with a positive mean bias error of 0.36 m for the validation period (2001–2009). These error estimates were found to be less than 15 % of the natural variability of the lake, thus giving high confidence on the modelled lake level estimates. The approach presented in this paper can be used to (a) simulate patterns of lake water level variations in data scarce regions, (b) operationally monitor lake water levels in ungauged basins, (c) derive historical lake level information using satellite rainfall and evapotranspiration data, and (d) augment the information provided by the satellite altimetry systems on changes in lake water levels.

scholarly journals Stochastic modeling of Lake Van water level time series with jumps and multiple trends

2013 ◽  
Vol 17 (6) ◽  
pp. 2297-2303 ◽  
Author(s):  
H. Aksoy ◽  
N. E. Unal ◽  
E. Eris ◽  
M. I. Yuce
Keyword(s):  
Time Series ◽  
Water Level ◽  
Lake Water ◽  
Linear Trend ◽  
Lake Van ◽  
Lake Water Level ◽  
Trend Model ◽  
Level Data ◽  
Water Level Data ◽  
Surrounding Areas

Abstract. In the 1990s, water level in the closed-basin Lake Van located in the Eastern Anatolia, Turkey, has risen up about 2 m. Analysis of the hydrometeorological data shows that change in the water level is related to the water budget of the lake. In this study, stochastic models are proposed for simulating monthly water level data. Two models considering mono- and multiple-trend time series are developed. The models are derived after removal of trend and periodicity in the dataset. Trend observed in the lake water level time series is fitted by mono- and multiple-trend lines. In the so-called mono-trend model, the time series is treated as a whole under the hypothesis that the lake water level has an increasing trend. In the second model (so-called multiple-trend), the time series is divided into a number of segments to each a linear trend can be fitted separately. Application on the lake water level data shows that four segments, each fitted with a trend line, are meaningful. Both the mono- and multiple-trend models are used for simulation of synthetic lake water level time series under the hypothesis that the observed mono- and multiple-trend structure of the lake water level persist during the simulation period. The multiple-trend model is found better for planning the future infrastructural projects in surrounding areas of the lake as it generates higher maxima for the simulated lake water level.

scholarly journals Investigating the effect of hydroclimatological variables on Urmia Lake water level using wavelet coherence measure

2018 ◽  
Vol 10 (1) ◽  
pp. 13-29 ◽  
Author(s):  
Vahid Nourani ◽  
Mahsa Ghasemzade ◽  
Ali Danande Mehr ◽  
Elnaz Sharghi
Keyword(s):  
Time Series ◽  
Water Level ◽  
Lake Water ◽  
Geographical Location ◽  
Urmia Lake ◽  
Wavelet Coherence ◽  
Water Level Fluctuations ◽  
Lake Water Level ◽  
North West ◽  
North East

Abstract In this paper, wavelet transform coherence is implemented to examine the impacts of hydroclimatological variables on water level fluctuations in two large saline lakes in the Middle East with a similar geographical location, namely, Urmia Lake in north-west Iran, which has an extremely simple ecological pyramid where water level decrease produces a very sensitive ecosystem, and Van Lake in north-east Turkey. The present study investigates trends in higher order moments of hydrological time series. The aim of this paper is to investigate the complexity of Urmia Lake water level time series which could lead to decrease fluctuations of time series. To this end, the strength and relationships between five hydroclimatological variables, including rainfall, runoff, temperature, relative humidity, as well as evaporation and water level fluctuations in the lakes were determined and discussed in terms of high common power region, phase relationships, and local multi-scale correlations. The results showed that among the hydroclimatological variables, runoff has the most coherencies (0.9–1) with water level fluctuations in the lakes. Although both lakes are located in a similar climatic region, for the recent 15 years, adverse trend in water level fluctuations of Urmia Lake indicates a critical condition for this lake.

Sign in / Sign up

Export Citation Format

Share Document