Long-Term Lake Area Change and Its Relationship with Climate in the Endorheic Basins of the Tibetan Plateau

Wang, Junxiao; Li, Mengyao; Wang, Liuming; She, Jinhua; Zhu, Liping; Li, Xingong

doi:10.3390/rs13245125

Cited by 11 publications

(9 citation statements)

References 64 publications

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“…Furthermore, Wang et al . 68 also indicated that the trends in the lake area (>1 km 2 ) in the endorheic basin of the QTP are consistent with the SLWB derived in this study. This further supports the validity of the data and conclusions presented in our study.…”

Section: Technical Validationsupporting

confidence: 89%

An intra-annual 30-m dataset of small lakes of the Qilian Mountains for the period 1987–2020

Li¹,

Zhang²,

Zhang³

et al. 2023

Sci Data

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Small lakes (areas between 0.01 km2 and 1 km2) on the Qinghai–Tibet Plateau (QTP) are prone to fluctuations in number and area, with serious implications for the surface water storage and water and carbon cycles of this fragile environment. However, there are no detailed long-term datasets of the small lakes of the QTP. Therefore, the intra-annual changes of small lakes in the Qilian Mountains region (QMR) in the northeastern part of the QTP were investigated. The small lake water bodies (SLWB) in the QMR were extracted by improving existing commonly used waterbody extraction algorithms. Using the Google Earth Engine platform and 13,297 Landsat TM/ETM + /OLI images, the SLWB of the QMR were extracted from 1987 to 2020 applying the improved algorithm, cross-validation and manual corrections. The reliability, uncertainty and limitations of the improved algorithm were discussed. An intra-annual small lake dataset for QMR (QMR-SLD) from 1987 to 2020 was released, containing eight attributes: code, perimeter (km), area (km2), latitude and longitude, elevation (m), area error, relative error (%), and subregion.

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Section: Technical Validationsupporting

confidence: 89%

An intra-annual 30-m dataset of small lakes of the Qilian Mountains for the period 1987–2020

Li¹,

Zhang²,

Zhang³

et al. 2023

Sci Data

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“…This study posits that factors such as snowfall, rainfall, surface runoff, and groundwater influx compensate for the water deficit caused by sublimation, thereby stabilizing annual lake surface elevations. However, the recent literature suggests a rise in the water level of Nam Co and an expansion of its surface area in recent years, which may influence its salinity and evaporation rate [18,68,69]. While our investigation was constrained to a bidimensional analysis and Owing to the distinctive climatic conditions of the Tibetan Plateau, numerical simulations of its lakes have revealed limitations, especially in modeling the deep lake ice-on phase.…”

Section: Discussionmentioning

confidence: 99%

Lake Ice Simulation and Evaluation for a Typical Lake on the Tibetan Plateau

Si,

Li,

Wang

et al. 2023

Water

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This study aims to simulate the lake ice conditions in the Nam Co lake using a lake ice model, which is a one-dimensional physics-based model that utilizes enthalpy as the predictor variable. We modified the air density schemes within the model to improve the accuracy of the lake ice simulation. Additionally, the process of lake ice sublimation was included, and the effect of lake water salinity on the freezing point was considered. Using the improved lake ice model, we simulated lake surface water temperature, lake ice thickness, and interannual variations in lake ice phenology, and we compared these results with observations at Nam Co. The results demonstrate that the improved model better reproduces the lake surface water temperature, lake ice thickness, and lake ice phenology at Nam Co. Additionally, the thin air density affects lake processes by weakening sensible heat and latent heat, which ultimately leads to a delayed ice-on date and a slightly earlier ice-free date in Nam Co. This study contributes to an enhanced understanding of the freeze–thaw processes in Nam Co and reduces the biases in lake ice simulation on the Tibetan Plateau through the lake model improvement.

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“…In the study, we calculated P W and E W amount based on annual lake area extracted from Landsat images (see Section 2.2.2). As the area tends to be the maximum water surface area in a year (J. Wang et al., 2021), the overestimation of P W and E W amount may also introduce some bias and uncertainty to inflow calculation. Followed the uncertainty propagation laws, we estimated the uncertainties of R L rate and amount based on the uncertainty estimates of other water balance terms (Equations , and Figure S18 in Supporting Information ).…”

Section: Discussionmentioning

confidence: 99%

“…With little human disturbance, theses lakes are effective sentinels of climate change and sensitive to hydrological change (Adrian et al., 2009; G. Zhang & Duan, 2021). Under recent regional climate warming and wetting, most lakes in the TP has been undergoing dramatic expansion, manifested as the increase in water surface area, water level and lake water volume (Qiao et al., 2019; J. Wang et al., 2021; G. Zhang et al., 2019; G. Zhang et al., 2020). To illustrate the mechanism of such rapid lake expansion, accurate estimation of lake water balance components, such as lake inflow from catchment ( R L ), lake surface precipitation ( P W ) and evaporation ( E W ), are crucial (Ding et al., 2018; Tong et al., 2016; Zhou et al., 2015).…”

Section: Introductionmentioning

confidence: 99%

Lake Evaporation and Its Effects on Basin Evapotranspiration and Lake Water Storage on the Inner Tibetan Plateau

Wang,

Wang

et al. 2023

Water Resources Research

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Effects of lake evaporation (EW) on basin evapotranspiration (ETB) and lake water storage change (LWSC) at lake‐basin scale have never been reported for most basins on the inner Tibetan Plateau (IB). In this study, EW of 118 large lakes in 95 closed lake‐basins were estimated, and its effects on ETB and LWSC over 2001–2018 were examined using a derivative‐guided framework from the aspects of EW amount, rate, trend slope and inter‐annual variability. We found that EW amount has a high effect (17%) on regional ETB amount compared to the average lake area ratio (α) (∼5%), and the effect has increased significantly (2%/10 a). The spatial pattern of the effect is mainly controlled by α, and the increasing trend of α (0.6%/10 a) also dominated the increasing trend in regional ETB rate (0.30 mm/a) though with large spatial heterogeneity. Variance in α and EW rate have a minor effect (∼3%) on ETB variance, especially for the basins with lower α. The combination of quasi lake inflow (RL, 41%) and lake surface precipitation (PW, 16%) offset the depletion of EW (−43%), resulting in the surplus of regional lake water (LWSC > 0). The increase in EW mount, which is mainly from lake area expansion (90%), caused a decreasing trend in LWSC (i.e., slower growth rate) with a contribution of −59%. This suggests a negative feedback between lake area expansion and EW amount in the IB, and the feedback may continue with the predicted area increases.

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Long-Term Lake Area Change and Its Relationship with Climate in the Endorheic Basins of the Tibetan Plateau

Cited by 11 publications

References 64 publications

An intra-annual 30-m dataset of small lakes of the Qilian Mountains for the period 1987–2020

An intra-annual 30-m dataset of small lakes of the Qilian Mountains for the period 1987–2020

Lake Ice Simulation and Evaluation for a Typical Lake on the Tibetan Plateau

Lake Evaporation and Its Effects on Basin Evapotranspiration and Lake Water Storage on the Inner Tibetan Plateau

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