Abstract

The lake ice phenology variations are vital for the land–surface–water cycle. Qinghai Lake is experiencing amplified warming under climate change. Based on the MODIS imagery, the spatio-temporal dynamics of the ice phenology of Qinghai Lake were analyzed using machine learning during the 2000/2001 to 2019/2020 ice season, and cloud gap-filling procedures were applied to reconstruct the result. The results showed that the overall accuracy of the water–ice classification by random forest and cloud gap-filling procedures was 98.36% and 92.56%, respectively. The annual spatial distribution of the freeze-up and break-up dates ranged primarily from DOY 330 to 397 and from DOY 70 to 116. Meanwhile, the decrease rates of freeze-up duration (DFU), full ice cover duration (DFI), and ice cover duration (DI) were 0.37, 0.34, and 0.13 days/yr., respectively, and the duration was shortened by 7.4, 6.8, and 2.6 days over the past 20 years. The increased rate of break-up duration (DBU) was 0.58 days/yr. and the duration was lengthened by 11.6 days. Furthermore, the increase in temperature resulted in an increase in precipitation after two years; the increase in precipitation resulted in the increase in DBU and decrease in DFU in corresponding years, and decreased DI and DFI after one year.

Highlights

  • Explicit knowledge of lake ice is crucial for understanding a wide variety of earth system processes and interactions with the environment, including hydrological budgets, sediment trapping; heat fluxes and coupled weather and climate effects; lake productivity; species richness; food chain dynamics; and inland fishery yields [1,2]

  • The lake surface water–ice state is controlled by the local geolocation and climate conditions, especially the freeze-up dates and the break-up dates

  • The Qinghai Lake locates in the Yellow River sub-basin, which is an area of approximately 2.5 × 105 km2 ; the distinctive climatic conditions and geophysical environment make it a highly attractive research region [5]

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Summary

Introduction

Explicit knowledge of lake ice is crucial for understanding a wide variety of earth system processes and interactions with the environment, including hydrological budgets, sediment trapping; heat fluxes and coupled weather and climate effects; lake productivity; species richness; food chain dynamics; and inland fishery yields [1,2]. The lake surface water–ice state is controlled by the local geolocation and climate conditions, especially the freeze-up dates and the break-up dates. The lake surface water’s physical properties changed due to the transition of the lake surface water–ice state processes [3]. With an overall surface water area of 47,000 km , which makes up beyond 50% of the overall surface water area of Chinese lakes, including the largest lake: Qinghai Lake (4254.90 km2 ) [4]. The Qinghai Lake locates in the Yellow River sub-basin, which is an area of approximately 2.5 × 105 km ; the distinctive climatic conditions and geophysical environment make it a highly attractive research region [5]

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