Limnology under Climate-Driven Regime Shifts: Impacts on Water Balance, Dynamics, Physico-Chemical Properties and Ecology

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 2466

Special Issue Editors


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Guest Editor
Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
Interests: lake dynamics and climate change; lake hydrology
Special Issues, Collections and Topics in MDPI journals
Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
Interests: lake hydrology; lake-basin interaction; cryosphere hydrological modelling

Special Issue Information

Dear Colleagues,

We are pleased to announce the new Special Issue of Water entitled ‘Limnology under Climate-Driven Regime Shifts: Impacts on Water Balance, Dynamics and Physico-Chemical Properties’. Lakes not only play an important role in the global hydrological and biogeochemical cycle but also serve as important water resources including drinking water supply, agricultural production, recreation and fisheries. Based on in situ observation, satellite data and modeling, significant changes in lake physical conditions have been investigated during the past decades, including loss of ice cover, rising surface water temperature, changes in evaporation and water budgets, and alteration of mixing regimes, etc.

While our understanding of physical lake response to global climate change has improved in recent decades, only a small portion of lakes have been investigated in detail. More research about changes in lake conditions is still needed, especially for lakes in remote areas where there is a lack of in situ observations. Therefore, this Special Issue main focuses on the response of lake physical-chemical conditions to climate change in different regions of the world, mainly in terms of changes in the lake area, water level and water storage, lake ice phenology, water temperature, mixing regimes, evaporation, and water quality, etc.

We are looking forward to your participation and submission.

Dr. Yanbin Lei
Dr. Jing Zhou
Guest Editors

Manuscript Submission Information

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Keywords

  • lake level and extent
  • lake water storage
  • lake water budget
  • lake water temperature
  • lake mixing regimes
  • lake ice phenology
  • lake evaporation
  • lake water clarity
  • lake water quality

Published Papers (1 paper)

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Research

14 pages, 16479 KiB  
Article
Estimation of Lake Storage Based on the Surrounding Topography around the Lake from the SRTM DEM
by Yi Xiao, Guofeng Wang, Huihui Zhao, Jizheng Wang and Baojin Qiao
Water 2023, 15(6), 1015; https://doi.org/10.3390/w15061015 - 7 Mar 2023
Cited by 2 | Viewed by 2133
Abstract
The estimation of lake depth and water storage is crucial for water resource management in inland waters. In previous studies, lake water storage estimation required in situ bathymetry data; however, the high cost of fieldwork prevented the extension of this method to all [...] Read more.
The estimation of lake depth and water storage is crucial for water resource management in inland waters. In previous studies, lake water storage estimation required in situ bathymetry data; however, the high cost of fieldwork prevented the extension of this method to all lakes. This study aims to solve this problem by studying how to estimate lake water storage without using bathymetric data. According to the similarity between the topography surrounding the lake and the underwater topography, we present an approach to estimate the lake water storage. The principle of the method is to extend the surrounding terrain into the underwater area to establish an underwater model. In this study, six lakes of the Tibetan Plateau were selected, and the results showed that the average R2 between the estimated and measured water depths of the six lakes was about 0.76. Among them, the estimated water depth of Taiyang Lake (maximum depth of 61.57 m) had the largest deviation from the measured water depth, with an RMSE (root mean square error) of 19.77 m, while the estimated water depth of Bangda Co (maximum depth of 41.04 m) had the best result, with an RMSE of 7.83 m. The relative errors of all water storage estimations were less than 20%. The lake with the best accuracy was Zigetang Co (measured water storage of 39.6 Gt), and the estimated water storage was 42.2 Gt, with a relative error of 6.57%. The lake with the worst accuracy was Taiyang Lake (measured water storage of 31.94 Gt), and the estimated water storage was 36.47 Gt, with a relative error of 14.18%. This study provides an effective method for lake depth estimation and improves the ability to monitor changes in lake storage, especially for lakes with harsh environments or in remote areas. Full article
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