Reconsideration of wind stress, wind waves, and turbulence in simulating wind-driven currents of shallow lakes in the Wave and Current Coupled Model (WCCM) version 1.0

Wu, Tingfeng; Qin, Boqiang; Huang, Anning; Sheng, Yongwei; Feng, Shunxin; Casenave, Céline

doi:10.5194/gmd-15-745-2022

Cited by 10 publications

(6 citation statements)

References 60 publications

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“…Theoretical studies have indicated that the response of a depth-variable lake to a strong uniform wind often leads to the formation of two counter-rotating gyres, also known as a double-gyre or dipole (Csanady, 1973;Bennett, 1974;Shilo et al, 2007), as was confirmed by early numerical simulations (Simons, 1980). With increased computational power, threedimensional (3D) hydrodynamic models with higher accuracy, stability and resolution have since been developed and have significantly contributed to the understanding of lake circulation, especially that driven by wind (e.g., Beletsky et al, 1999;Laval et al, 2005;Beletsky and Schwab, 2008;Bai et al, 2013;Mao and Xia, 2020;Lin et al 2022;Wu et al 2022). Recent numerical simulations have also highlighted the role of baroclinicity induced by gradients of surface buoyancy (mainly surface heating and cooling), which can enhance the large-scale circulation in the Great Lakes (Schwab and Beletsky, 2003;Bennington et al, 2010;Verburg et al, 2011;McKinney et al, 2012).…”

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confidence: 99%

Basin-scale gyres and mesoscale eddies in large lakes: A novel procedure for their detection and characterization, assessed in Lake Geneva

Hamze‐Ziabari

Lemmin

Soulignac

et al. 2022

Preprint

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Abstract. Gyres and eddies, i.e., large-scale rotating coherent water masses, are prominent features of large lakes and oceans, are formed due to the interplay between Coriolis force and wind stress. Understanding their dynamics is important as they are known to play a crucial role in spreading bio-chemical materials and energy throughout lakes and oceans. Since field observations in large lakes are sparse in time and location, often limited to a few moorings, they cannot provide a comprehensive validation dataset for such large-scale current systems. Previous numerical studies suggested the presence of different and complex gyre systems in many large lakes, however none were confirmed with detailed field measurements. In order to assess the spatial and temporal extent of gyres and eddies, their dynamics and vertical structure, as well as validate their prediction in numerical simulation results, transect field observations should be carried out. However, at present it is difficult to forecast when and where such transect field observations should be taken. To overcome this problem, a novel procedure combining 3D numerical simulations, statistical analyses, and remote sensing data was developed that permits determination of the spatial and temporal patterns of basin-scale gyres during different seasons. The efficiency and robustness of the proposed procedure was validated in Lake Geneva. For the first time in a lake, detailed field evidence of the existence of basin-scale gyres and (sub)mesoscale eddies was provided by data collected along transects whose locations were predetermined by the proposed procedure. The close correspondence between field observations and detailed numerical results further confirms the validity of the model for capturing large-scale current circulations as well as submesoscale eddies. The procedure can be applied to other large lakes and can be extended to the interaction of biological-chemical-physical processes.

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confidence: 99%

Basin-scale gyres and mesoscale eddies in large lakes: A novel procedure for their detection and characterization, assessed in Lake Geneva

Hamze‐Ziabari

Lemmin

Soulignac

et al. 2022

Preprint

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“…The correlation coefficient between the wind speed and turbidity was the largest (r = 0.57, p < 0.05). Global studies have shown [33][34][35] that wind is the main driving force of sediment resuspension in shallow lakes. Therefore, we developed the LSTM-based turbidity model using synchronous wind speed.…”

Section: Turbidity Wind and Chl-a During In Situ Observationsmentioning

confidence: 99%

Comparison between Machine-Learning-Based Turbidity Models Developed for Different Lake Zones in a Large Shallow Lake

Xu²,

Yan

et al. 2023

Water

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Machine learning has been used to mine the massive data collected by automatic environmental monitoring systems and predict the changes in the environmental factors in lakes. However, further study is needed to assess the feasibility of the development of a universal machine-learning-based turbidity model for a large shallow lake with considerable spatial heterogeneity in environmental factors. In this study, we collected and examined sediment and water quality data from Lake Taihu, China. Three monitoring stations were established in three lake zones to obtain continuous time series data of the water quality and meteorological variables. We used these data to develop three turbidity models based on long short-term memory (LSTM). The three zones differed in terms of environmental factors related to turbidity: in West Taihu, the Lake Center, and the mouth of Gonghu Bay, the critical shear stress of bed sediments was 0.029, 0.055, and 0.032 N m−2, and the chlorophyll-a concentration was 23.27, 14.62, 30.80 μg L−1, respectively. The LSTM-based turbidity model developed for any zone could predict the turbidity in the other two zones. For the model developed for West Taihu, its performance to predict the turbidity in the local zone (i.e., West Taihu) was inferior to that for the other zones; the reverse applied to the models developed for the Lake Center and Gonghu Bay. This can be attributed to the complex hydrodynamics in West Taihu, which weakens the learning of LSTM from the time series data. This study explores the feasibility of the development of a universal LSTM-based turbidity model for Lake Taihu and promotes the application of machine learning algorithms to large shallow lakes.

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“…The water-air interface is an important component in tracking and modeling changes in the water and energy cycles through wind-driven surface water dynamics [1,2]. Wind induces waves and seiches and increases evaporation rates over lakes, for example [3,4].…”

Section: Introductionmentioning

confidence: 99%

How Does Wind Influence Near-Nadir and Low-Incidence Ka-Band Radar Backscatter and Coherence from Small Inland Water Bodies?

Fayne

Smith

2023

Remote Sensing

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While many studies have been conducted regarding wind-driven Ka-band scattering on the ocean and sea surfaces, few have identified the impacts of Ka-band scattering on small inland water bodies, and fewer have identified the influence of wind on coherence over water. These previous studies have been limited in spatial scale, covering only large water bodies >25 km2. The recently launched Surface Water and Ocean Topography (SWOT) mission is the first Ka-band InSAR satellite designed for mapping water surface elevations and open water areas for rivers as narrow as 100 m and lakes as small as 0.0625 km2. Because measurements of these types are novel, there remains some uncertainty about expected backscatter amplitudes given wind-driven water surface roughness variability. A previous study using the airborne complement to SWOT, AirSWOT, found that low backscatter and low coherence values were indicative of higher errors in the water surface elevation products, recommending minimum thresholds for backscatter and coherence for filtering the data to increase the accuracy of averaged data for lakes and rivers. We determined that the global average wind speed over lakes is 4 m/s, and after comparing AirSWOT backscatter and coherence data with ERA-5 wind speeds, we found that the minimum required speed to retrieve high backscatter and coherence is 3 m/s. We examined 11,072 lakes across Canada and Alaska, with sizes ranging from 350 m2 to 156 km2, significantly smaller than what could be measured with previous Ka-band instruments in orbit. We found that small lakes (0.0625–0.25 km2) have significantly lower backscatter (3–5 dB) and 0.20–0.25 lower coherence than larger lakes (>1 km2). These results suggest that approximately 75% of SWOT observable lake areas around the globe will have consistently high-accuracy water surface elevations, though seasonal wind variability should remain an important consideration. Despite very small lakes presenting lower average backscatter and coherence, this study asserts that SWOT will be able to accurately resolve the water surface elevations and water surface extents for significantly smaller water bodies than have been previously recorded from satellite altimeters. This study additionally lays the foundation for future high-resolution inland water wind speed studies using SWOT data, when the data become available, as the relationships between wind speed and Ka-band backscatter reflect those of traditional scatterometers designed for oceanic studies.

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Reconsideration of wind stress, wind waves, and turbulence in simulating wind-driven currents of shallow lakes in the Wave and Current Coupled Model (WCCM) version 1.0

Cited by 10 publications

References 60 publications

Basin-scale gyres and mesoscale eddies in large lakes: A novel procedure for their detection and characterization, assessed in Lake Geneva

Basin-scale gyres and mesoscale eddies in large lakes: A novel procedure for their detection and characterization, assessed in Lake Geneva

Comparison between Machine-Learning-Based Turbidity Models Developed for Different Lake Zones in a Large Shallow Lake

How Does Wind Influence Near-Nadir and Low-Incidence Ka-Band Radar Backscatter and Coherence from Small Inland Water Bodies?

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