The dynamics of Paiku Co lake area in response to climate change

Abstract

With the drastic change in global climate, the wide distribution of natural lakes over the Qinghai-Tibet Plateau (TP) has attracted extensive attention due to their high climate sensitivity. In this paper, we investigated the dynamics of Paiku Co, the largest inland lake in the Qomolangma Natural Reserve, with the associated response to climate change in the past three decades. The methods used contain the water index method, the spatial and temporal fusion model, the statistical mono-window algorithm, and multi-variable linear regression. Lake area fluctuated greatly in 1990–2000, followed by a continuous shrinkage in 2000–2010, and stabled after that 2010–2020. We forecasted that Paiku Co would enter a slow expansion period. Conjoint analysis with climate factors showed that the area variation of Paiku Co was not significantly related to precipitation change, but negatively related to the change of air temperature and lake temperature. We found that the lake change was not dominated by a single factor but showed different climate sensitivity in each period. Especially, there was a common inflection point around 2013 that might herald the occurrence of a new trend of climate change. This article provides new ideas and solutions for the research of lakes in the Qinghai-Tibet Plateau and offers a reference for water resource management.

Evaluation and prediction of water conservation of the Yellow river basin in Sichuan Province, China, based on Google Earth Engine and CA-Markov

“…At present, there is still no unified standard for the evaluation of WC, and the methods for WC evaluation are very diverse (including SWAT and InVEST, etc.) [ [75] , [76] , [77] , [78] , [79] , [80] ]. Existing researches usually reflect WC function/capacity in terms of WC amount, and none have verified the evaluation results [ [10] , [48] , [70] , [81] , [82] , [83] ].…”

Google Earth Engine: A Global Analysis and Future Trends

“…use/cover [90], classification [91], forest fires [92], predictions [93], and climatic changes [94], among others.…”

“…As well as theoretical literature review studies [1,2]. In the last year (2022), a considerable number of publications focused on land use/cover [90], classification [91], forest fires [92], predictions [93], and climatic changes [94], among others.…”