Impact of lake water level decline on river evolution in Ebinur Lake Basin (an ungauged terminal lake basin)

Managing lake water levels from an ecological perspective has become an urgent issue in recent years in efforts to protect, conserve, and restore lake eco-environments. In this study, we considered the actual situation of Ebinur Lake basin to develop a lake water balance model using a System Dynamics (SD) method. The objective of this study is based on the lake water balance model to sufficiently understand the variation and relationship between the lake depth–area–volume. We combined field investigations and hydrological data analysis to expose the major factors affecting lake water level fluctuations (WLFs), as well as the impact of WLFs on lake eco-environments. All with the aim of providing a theoretical basis to manage Ebinur Lake ecosystems for conservation and restoration. The main findings of this study include: (I) The model’s calculation results agree with the observation value, as the monthly lake surface area was used to validate the model. (II) The factors influencing the dynamic changes in the water level of the lake are ranked in ascending order (from the lowest to the highest) as follows: Precipitation, groundwater recharge, evaporation, river inflow. (III) Fluctuations in water level play a significant role in lake shoreline displacement variation, and when the lake’s water level drops below 1 m, the surface area of the water body decreases to approximately 106 km2. (IV) The magnitude and frequency of WLFs drive major differences in the ecology of lake littoral zones, influencing not only the structure and functioning of benthic assemblages but also littoral habitat structure. These results established a quantitative linkage between hydrological variables and ecosystem health for the Ebinur Lake wetlands. These findings could be widely used in managing the Ebinur Lake basin as well as other similar water bodies, and could provide a useful tool for managing lake ecosystems for conservation and restoration.

Download Full-text

Examining the Driving Factors of the Direct Carbon Emissions of Households in the Ebinur Lake Basin Using the Extended STIRPAT Model

Sustainability ◽

10.3390/su13031339 ◽

2021 ◽

Vol 13 (3) ◽

pp. 1339

Author(s):

Ziyuan Chai ◽

Zibibula Simayi ◽

Zhihan Yang ◽

Shengtian Yang

Keyword(s):

Energy Consumption ◽

Carbon Emissions ◽

Carbon Emission ◽

Driving Factors ◽

Series Data ◽

Lake Basin ◽

Stirpat Model ◽

Consumption Structure ◽

Ebinur Lake ◽

Ebinur Lake Basin

In order to achieve the carbon emission reduction targets in Xinjiang, it has become a necessary condition to study the carbon emission of households in small and medium-sized cities in Xinjiang. This paper studies the direct carbon emissions of households (DCEH) in the Ebinur Lake Basin, and based on the extended STIRPAT model, using the 1987–2017 annual time series data of the Ebinur Lake Basin in Xinjiang to analyze the driving factors. The results indicate that DCEH in the Ebinur Lake Basin during the 31 years from 1987 to 2017 has generally increased and the energy structure of DCEH has undergone tremendous changes. The proportion of coal continues to decline, while the proportion of natural gas, gasoline and diesel is growing rapidly. The main positive driving factors affecting its carbon emissions are urbanization, vehicle ownership and GDP per capita, while the secondary driving factor is residents’ year-end savings. Population, carbon intensity and energy consumption structure have negative effects on carbon emissions, of which energy consumption structure is the main factor. In addition, there is an environmental Kuznets curve between DCEH and economic development, but it has not yet reached the inflection point.

Download Full-text

Digital Mapping of Soil Organic Carbon Using Sentinel Series Data: A Case Study of the Ebinur Lake Watershed in Xinjiang

Remote Sensing ◽

10.3390/rs13040769 ◽

2021 ◽

Vol 13 (4) ◽

pp. 769

Author(s):

Xiaohang Li ◽

Jianli Ding ◽

Jie Liu ◽

Xiangyu Ge ◽

Junyong Zhang

Keyword(s):

Remote Sensing ◽

Organic Carbon ◽

Soil Organic Carbon ◽

Prediction Accuracy ◽

Lake Basin ◽

Arid Areas ◽

Annual Average ◽

Machine Learning Methods ◽

Ebinur Lake ◽

Ebinur Lake Basin

As an important evaluation index of soil quality, soil organic carbon (SOC) plays an important role in soil health, ecological security, soil material cycle and global climate cycle. The use of multi-source remote sensing on soil organic carbon distribution has a certain auxiliary effect on the study of soil organic carbon storage and the regional ecological cycle. However, the study on SOC distribution in Ebinur Lake Basin in arid and semi-arid regions is limited to the mapping of measured data, and the soil mapping of SOC using remote sensing data needs to be studied. Whether different machine learning methods can improve prediction accuracy in mapping process is less studied in arid areas. Based on that, combined with the proposed problems, this study selected the typical area of the Ebinur Lake Basin in the arid region as the study area, took the sentinel data as the main data source, and used the Sentinel-1A (radar data), the Sentinel-2A and the Sentinel-3A (multispectral data), combined with 16 kinds of DEM derivatives and climate data (annual average temperature MAT, annual average precipitation MAP) as analysis. The five different types of data are reconstructed by spatial data and divided into four spatial resolutions (10, 100, 300, and 500 m). Seven models are constructed and predicted by machine learning methods RF and Cubist. The results show that the prediction accuracy of RF model is better than that of Cubist model, indicating that RF model is more suitable for small areas in arid areas. Among the three data sources, Sentinel-1A has the highest SOC prediction accuracy of 0.391 at 10 m resolution under the RF model. The results of the importance of environmental variables show that the importance of Flow Accumulation is higher in the RF model and the importance of SLOP in the DEM derivative is higher in the Cubist model. In the prediction results, SOC is mainly distributed in oasis and regions with more human activities, while SOC is less distributed in other regions. This study provides a certain reference value for the prediction of small-scale soil organic carbon spatial distribution by means of remote sensing and environmental factors.

Download Full-text

Lake water level modeling using newly developed hybrid data intelligence model

Theoretical and Applied Climatology ◽

10.1007/s00704-020-03263-8 ◽

2020 ◽

Vol 141 (3-4) ◽

pp. 1285-1300 ◽

Cited By ~ 3

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

Download Full-text

Fuzzy logic model of lake water level fluctuations in Lake Van, Turkey

Theoretical and Applied Climatology ◽

10.1007/s00704-006-0267-z ◽

2007 ◽

Vol 90 (3-4) ◽

pp. 227-233 ◽

Cited By ~ 30

Author(s):

A. Altunkaynak ◽

Z. Şen

Keyword(s):

Fuzzy Logic ◽

Water Level ◽

Lake Water ◽

Logic Model ◽

Water Level Fluctuations ◽

Lake Van ◽

Lake Water Level ◽

Fuzzy Logic Model

Download Full-text

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

Journal of Hydrology ◽

10.1016/j.jhydrol.2021.126582 ◽

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

Download Full-text

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

Hydrology and Earth System Sciences ◽

10.5194/hess-25-1643-2021 ◽

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.

Download Full-text

Lake water level response to drought in a lake-rich region explained by lake and landscape characteristics

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/cjfas-2019-0270 ◽

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.

Download Full-text

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

Fluids ◽

10.3390/fluids4040182 ◽

2019 ◽

Vol 4 (4) ◽

pp. 182 ◽

Cited By ~ 1

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.

Download Full-text