scholarly journals A Conceptual Model for Remote Data Acquisition Using SMSLib Software. Case study: Kivu Lake Water Level

2012 ◽  
Vol 27 (1) ◽  
Author(s):  
C Niyomugabo ◽  
C Twizere
Keyword(s):  
Data Acquisition ◽  
Water Level ◽  
Conceptual Model ◽  
Lake Water ◽  
Lake Water Level ◽  
Remote Data

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 Reconstruction of Bog Lake Water Level Fluctuations Using Method of Simple Modelling: A Case Study on Lake Rėkyva

2011 ◽  
Vol 1 (4) ◽  
pp. 15-20
Author(s):  
Julius Taminskas ◽  
Adomas Mažeikis ◽  
Rita Linkevičienė
Keyword(s):  
Water Level ◽  
Lake Water ◽  
Meteorological Data ◽  
Precipitation Amount ◽  
Water Level Fluctuations ◽  
Data Series ◽  
Large Area ◽  
Lake Water Level ◽  
Bog Lakes

Considering lack of observations and meteorological data, the article analyses the reconstruction of bog lake water level fluctuations. The main issue of using advanced methods for determining water level fluctuations and balance can be lack of verified data. The proposed method uses only a variable length period of precipitation amount data series. Bog lake Rėkyva can be distinguished from other bog lakes due to its large area, and therefore has been chosen for this case study. The main conclusion is that the proposed method is suitable for determining trends towards water level fluctuation over long time periods.

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.

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 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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