Monitoring and Analysis of Water Level–Water Storage Capacity Changes in Ngoring Lake Based on Multisource Remote Sensing Data

Abstract

Mastering the fluctuation of water levels and the water storage capacity of plateau lakes is greatly important for monitoring the water balance of the Tibetan Plateau and predicting regional and global climate change. The water level of plateau lakes is difficult to measure, and the ground measured data of long-time series are difficult to obtain. Ngoring Lake is considered in this study, using spaceborne single-photon lidar ICESat-2/ATL13 inland lake standard data products, the water level values provided by Hydroweb laboratory, and the image data of an optical remote sensing satellite. A new method is proposed in the absence of measured data. The method uses multisource remote sensing data to estimate the long-term changes in the water levels, surface area, and water storage capacity of Ngoring Lake in the past three decades. The results show that the water level values of ICESat-2 and Hydroweb on overlapping observation days are highly correlated, with R2 = 0.9776, MAE = 0.420 m, RMSE = 0.077 m, and the average absolute height difference is 0.049 m. The fusion of multiple altimetry data can obtain more continuous long-time series water-level observation results. From 1992 to 2021, the water body information of Ngoring Lake basin fluctuated greatly and showed different variation characteristics in different time periods. The lowest water level in January 1997 was approximately 4268.49 m, and it rose to its highest in October 2009, approximately 4272.44 m. The change in the water level in the basin was mainly affected by natural factors, such as precipitation, air temperature, and human activities. The analysis shows that ICESat-2 can be combined with other remote sensing data to realize the long-time series dynamic monitoring of plateau lakes, showing great advantages in the comprehensive observation of plateau lakes in no man’s land.

Land–Water Transition Zone Monitoring in Support of Drinking Water Production

“…This is a low computational cost operationally used practice, which this study examined for its performance. A Spearman correlation was applied between the water extent derived from WaterMask (in km 2 ) and the water level (in altitude m) derived from the suggested practice since the relationship between the two variables is considered to be monotonic [13,16].…”

“…In [15], Binh Pham-Duc et al calculated monthly variations in the surface water volume of Thac Mo hydroelectric reservoir, located in Vietnam, by extracting the surface water extent from S1 observations and the water level from Jason-3 altimetry data. In a similar context, Weidong Zhu et al [16] proposed a new method based on multisource remote sensing data to calculate the changes in water level, surface area and storage capacity of Ngoring Lake, located in Tibetan Plateau in Qinghai Province. In [9], Schwatke et al also used satellite altimetry data to extract the water level, and along with in situ water level measurements, they evaluated the performance of the inundation maps generated with multispectral satellite data.…”