The Impact of Human Activities on the Water-Level Changes of Bosten Lake

Climate change and human activities cause lake water level (WL) fluctuations to exceed natural thresholds, with implications for the available water resources. Studies that explore WL change trends and the main driving forces that affect water level changes are essential for future lake water resource planning. This study uses the Mann–Kendall trend test method to explore the WL fluctuations trend and WL mutation in Erhai Lake (EL) during 1990–2019 and explore the main driving factors affecting water level changes, such as characteristic WL adjustments. We also use the principal component analysis to quantify the contribution of compound influencing factors to the water level change in different periods. The results showed that the WL rose at a rate of 47 mm/a during 1990–2019 but was influenced by the characteristic WL adjustment of EL in 2004 and the WL mutation in 2005. In 1990–2004, the WL showed a downtrend caused by the increase in water resource development and utilization intensity, and in 2005–2019, the WL showed an uptrend caused by the combined decrease in evaporation, outflow, and the increase in water supply for water conservancy projects. Additionally, the largest contributions of outflow to WL change were 19.34% and 21.61% in 1990–2019 and 1990–2004, respectively, while the largest contribution of cultivated area to WL change was 20.48% in 2005–2019, and it is worth noting that the largest contribution of climate change to WL change was 40.35% in 2013–2019. In the future, under the increase in outflow and evaporation and the interception of inflow, the WL will decline (Hurst exponent = 0.048). Therefore, planning for the protection and management of lakes should consider the impact of human activities, while also paying attention to the influence of climate change.

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Unraveling the Role of Human Activities and Climate Variability in Water Level Changes in the Taihu Plain Using Artificial Neural Network

Water ◽

10.3390/w11040720 ◽

2019 ◽

Vol 11 (4) ◽

pp. 720 ◽

Cited By ~ 2

Author(s):

Yuefeng Wang ◽

Hossein Tabari ◽

Youpeng Xu ◽

Yu Xu ◽

Qiang Wang

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Climate Variability ◽

Water Level ◽

Human Activities ◽

Nonlinear Dependence ◽

Rapid Urbanization ◽

Evaluation Period ◽

Water Level Changes ◽

Artificial Neural

Water level, as a key indicator for the floodplain area, has been largely affected by the interplay of climate variability and human activities during the past few decades. Due to a nonlinear dependence of water level changes on these factors, a nonlinear model is needed to more realistically estimate their relative contribution. In this study, the attribution analysis of long-term water level changes was performed by incorporating multilayer perceptron (MLP) artificial neural network. We took the Taihu Plain in China as a case study where water level series (1954–2014) were divided into baseline (1954–1987) and evaluation (1988–2014) periods based on abrupt change detection. The results indicate that climate variables are the dominant driver for annual and seasonal water level changes during the evaluation period, with the best performance of the MLP model having precipitation, evaporation, and tide level as inputs. In the evaluation period, the contribution of human activities to water level changes in the 2000s is higher than that in the 1990s, which indicates that human activities, including the rapid urbanization, are playing an important role in recent years. The influence of human activities, especially engineering operations, on water level changes in the 2000s is more evident during the dry season (March-April-May (MAM) and December-January-February (DJF)).

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Changing Water Levels in Lake Superior, MI (USA) Impact Periphytic Diatom Assemblages in the Keweenaw Peninsula

Water ◽

10.3390/w13030253 ◽

2021 ◽

Vol 13 (3) ◽

pp. 253

Author(s):

M. Megan Woller-Skar ◽

Alexandra Locher ◽

Ellen Audia ◽

Evan W. Thomas

Keyword(s):

Water Level ◽

Surface Area ◽

Lake Superior ◽

Water Levels ◽

Ecological Processes ◽

Periphyton Community ◽

Water Level Changes ◽

Community Assemblages ◽

Keweenaw Peninsula ◽

The Impact

Predicted climate-induced changes in the Great Lakes include increased variability in water levels, which may shift periphyton habitat. Our goal was to determine the impacts of water level changes in Lake Superior on the periphyton community assemblages in the Keweenaw Peninsula with different surface geology. At three sites, we identified periphyton assemblages as a function of depth, determined surface area of periphyton habitat using high resolution bathymetry, and estimated the impact of water level changes in Lake Superior on periphyton habitat. Our results suggest that substrate geology influences periphyton community assemblages in the Keweenaw Peninsula. Using predicted changes in water levels, we found that a decrease in levels of 0.63 m resulted in a loss of available surface area for periphyton habitat by 600 to 3000 m2 per 100 m of shoreline with slopes ranging 2 to 9°. If water levels rise, the surface area of substrate will increase by 150 to 370 m2 per 100 m of shoreline, as the slopes above the lake levels are steeper (8–20°). Since periphyton communities vary per site, changes in the surface area of the substrate will likely result in a shift in species composition, which could alter the structure of aquatic food webs and ecological processes.

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Lake Mead and Hoover Dam monitoring in Nevada and Arizona states, USA using InSAR

10.5194/egusphere-egu2020-21582 ◽

2020 ◽

Author(s):

Mehdi Darvishi ◽

Georgia Destouni ◽

Fernando Jaramillo

Keyword(s):

Los Angeles ◽

Water Level ◽

Land Surface ◽

Ground Deformation ◽

The United States ◽

Water Levels ◽

Lake Mead ◽

Water Level Changes ◽

Hoover Dam ◽

The Impact

<p>Man-made reservoirs and lakes are key elements in the terrestrial water system. The increased concern about the impact of anthropogenic interventions on and the dynamics of these water resources has given rise to various approaches for representing human-water interactions in land surface models. Synthetic aperture radar interferometry (InSAR) has become a powerful geodetic tool for this purpose, by evidencing changes of ground and water surfaces across time and space. In this research, the Lake Mead and associated Hoover Dam are studied using Small Baseline Subset (SBAS) technique. Lake Mead is the largest reservoir in the United States, in terms of water capacity, supplies water and hydropower for millions of people in Las Vegas, Los Angeles and southwestern part of the USA. In recent years, rising temperature, increasing evaporation and decreasing precipitation have decreased water levels substantially, and probably modified its surrounding groundwater and surface as well.</p><p>This study aims to identify a hydrology-induced ground deformation around the lake Mead and a probable Hoover dam movement displacement. For the reservoir, we used the SBAS technique using 138 SAR data, including ERS1/2, Envisat, ALOS PALSAR and Sentinel-1, covering a time-spam between 1995 and 2019. For the analysis on the dam, we used the SBAS technique from 2014 to 2019 with descending and ascending modes of Sentinel-1A/B imageries. We found two main deformation patterns around the lake associated with the water level changes. Firstly, ERS and Sentinel-1 data evidenced a ground deformation that manifested itself as as a subsidence pattern in 1995 that has gradually changed into an uplift up to 2019. Secondly, the correlation trend between the deformation and water level changes has changed from negative to positive, with a transition point around March 2008. A possible interpretation for this is that the ground has initially reacted to the water fluctuations in the reservoir before March 2008 but after no longer plays a dominant role in the deformation occurring around the lake. The findings will help us to have a better understanding over the changes happened around the lake due to the water level changes and provide the valuable information for more effective management and maintenance of hydraulic structures and facilities near by the lake and water control in the future.</p>

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Analysis of impacts of polders on flood processes in Qinhuai River Basin, China, using the HEC-RAS model

Water Science & Technology Water Supply ◽

10.2166/ws.2018.008 ◽

2018 ◽

Vol 18 (5) ◽

pp. 1852-1860 ◽

Cited By ~ 4

Author(s):

Yuqin Gao ◽

Yu Yuan ◽

Huaizhi Wang ◽

Zhenxing Zhang ◽

Liu Ye

Keyword(s):

Water Level ◽

River Basin ◽

Flood Control ◽

Water Level Changes ◽

Maximum Water Level ◽

Increasing Trend ◽

Maximum Water ◽

Analysis System ◽

The Impact ◽

Qinhuai River

Abstract Flood control with polders is prevalent in East China. Their impact on flood processes is critically important for flood control, but has not been well documented. The Qinhuai River Basin was selected as the study area. A Hydrologic Engineering Center – River Analysis System (HEC-RAS) hydraulic model was developed to simulate and predict storm flood processes and the associated impact of polders. The study shows that the HEC-RAS model is capable of simulating the impact of polders on flood processes in the Qinhuai River Basin. The polders increased the water level outside of the polders. The polders in upstream watersheds have a greater impact on the water level than polders close to basin outlets when individually distributed. The maximum water level at Dongshan section shows an increasing trend for different sized flood with the increasing number of polders in the basin, and a linear increasing trend associated with urbanization. The smaller the flood scale is, the greater the maximum water level changes.

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An evaluation of the impact of persistent water level changes on the areal extent of Georgian Bay/North Channel marshlands

Environmental Management ◽

10.1007/bf01867525 ◽

1988 ◽

Vol 12 (3) ◽

pp. 359-368 ◽

Cited By ~ 6

Author(s):

Robert P. Bukata ◽

J. Edward Bruton ◽

John H. Jerome ◽

William S. Haras

Keyword(s):

Water Level ◽

Areal Extent ◽

Georgian Bay ◽

Water Level Changes ◽

The Impact

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A Settlement Landscape Reconstruction Approach Using GIS Analysis with Integrated Terrain Data of Land and Water: A Case Study of the Panlongcheng Site in the Shang Dynasty (Wuhan, China)

Remote Sensing ◽

10.3390/rs13245087 ◽

2021 ◽

Vol 13 (24) ◽

pp. 5087

Author(s):

Jianfeng Liu ◽

Qiushi Zou ◽

Qingwu Hu ◽

Changping Zhang

Keyword(s):

Water Level ◽

Human Activities ◽

Spatial Information ◽

Yangtze River Basin ◽

Water Area ◽

Shang Dynasty ◽

Landscape Reconstruction ◽

Water Level Changes ◽

History Of ◽

Spatial Information Technology

The landscape of ancient sites has changed greatly with the passage of time. Among all of the factors, human activities and the change in natural environment are the main factors leading to the change in site landscape. The Panlongcheng site, which is located in Hubei Province, China, has a history of 3500 years with the most abundant relics in the Yangtze River Basin during the Shang Dynasty. As a near-water site, the landscape of the Panlongcheng site is greatly affected by water level changes and water conservancy activities. In this paper, by using spatial information technology, the data obtained from land and underwater archaeological exploration were integrated to restore landscapes of Panlongcheng sites in different periods. After removing modern artificial features and topsoil, the landscapes of the sites before the Shang Dynasty, in the Shang Dynasty and modern time were reconstructed. Combining historical records of water level changes, the landscape and water–land distribution of the Panlongcheng site were compared. The analysis results reflect the interaction between water level changes and human activities in this region for thousands of years, and support the archaeological findings in the near-water area of the Panlongcheng site, which provides a new idea for the landscape reconstruction and analysis of near-water sites.

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Hydrogeological Earthquake Precursors: A Case Study From the Kamchatka Peninsula

Frontiers in Earth Science ◽

10.3389/feart.2020.576017 ◽

2020 ◽

Vol 8 ◽

Author(s):

Galina Kopylova ◽

Svetlana Boldina

Keyword(s):

Water Level ◽

Far East ◽

Kamchatka Peninsula ◽

Earthquake Parameters ◽

Strong Earthquakes ◽

Earthquake Sources ◽

Water Level Changes ◽

Spatio Temporal ◽

Predictive Assessments ◽

The Impact

The relevance of hydrogeological precursors (HGPs) study is justified by the need to obtain reliable information about the spatio-temporal manifestations and the relationships of HGPs with the parameters of subsequent earthquakes for seismic forecasting. In the review the data on repeated manifestations of HGPs before strong earthquakes obtained from long-term observations in five deep wells on the Kamchatka Peninsula (Far East of Russia) are presented. The analysis of the correlation of HGPs occurring in several wells is carried out in comparison with earthquake parameters characterizing both earthquake sources (magnitude, linear size of the source) and the impact of earthquakes in the area of wells (specific energy density in wave, intensity of shaking). It is shown that the manifestation of HGPs in several wells is observed before earthquakes with Mw = 6.6–7.8 at epicentral distances up to the first hundreds of km to observation wells in the near and intermediate zones of the sources with the ratio of the epicentral distances and the source sizes no more than 1–5. A feature of our study was the use of certain types of HGPs in water-level changes for predictive assessments of the strong earthquakes in the Kamchatka Peninsula. The review presents precursors in water-level changes detected in real time and the corresponding earthquake forecasts, which were recognized as successful according to the conclusions of the expert council on earthquake prediction.

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