High-temporal-resolution water level and storage change data sets for lakes on the Tibetan Plateau during 2000–2017 using multiple altimetric missions and Landsat-derived lake shoreline positions

Abstract

Abstract. The Tibetan Plateau (TP), known as Asia's water tower, is quite sensitive to climate change, which is reflected by changes in hydrologic state variables such as lake water storage. Given the extremely limited ground observations on the TP due to the harsh environment and complex terrain, we exploited multiple altimetric missions and Landsat satellite data to create high-temporal-resolution lake water level and storage change time series at weekly to monthly timescales for 52 large lakes (50 lakes larger than 150 km2 and 2 lakes larger than 100 km2) on the TP during 2000–2017. The data sets are available online at https://doi.org/10.1594/PANGAEA.898411 (Li et al., 2019). With Landsat archives and altimetry data, we developed water levels from lake shoreline positions (i.e., Landsat-derived water levels) that cover the study period and serve as an ideal reference for merging multisource lake water levels with systematic biases being removed. To validate the Landsat-derived water levels, field experiments were carried out in two typical lakes, and theoretical uncertainty analysis was performed based on high-resolution optical images (0.8 m) as well. The RMSE of the Landsat-derived water levels is 0.11 m compared with the in situ measurements, consistent with the magnitude from theoretical analysis (0.1–0.2 m). The accuracy of the Landsat-derived water levels that can be derived in relatively small lakes is comparable with most altimetry data. The resulting merged Landsat-derived and altimetric lake water levels can provide accurate information on multiyear and short-term monitoring of lake water levels and storage changes on the TP, and critical information on lake overflow flood monitoring and prediction as the expansion of some TP lakes becomes a serious threat to surrounding residents and infrastructure.

Map and Quantify the Ground Deformation Around Salt Lake in Hoh Xil, Qinghai-Tibet Plateau Using Time-Series InSAR From 2006 to 2018

“…The area increased 10.1 km 2 from December 2014 to January 2017 while the area increased approximate 30.7 km 2 from January 2017 to January 2019 with about three times expansion rate. The water level of the Salt Lake from 2006 to 2019 have been obtained from the Li and Long et al, [9]. From the observed measurement data, we can see that the water level of Salt Lake changes through four stages in recent 15 years (Fig.…”

“…According to the research [6] the Salt Lake is likely to burst in 1-2 years based on the measured water level and area, which would threaten the safety of the Qinghai-Tibet Railway (QTR) in the east. Several studies using optical remote sensing [7] and radar altimetry data [8][9] have been conducted to monitor the water area and level change of Salt Lake and. The expansion of the lake would accelerate the melting of permafrost, leading to more severe surface deformation around the lake, which contributed the further lake expansion [7].…”

“…Relative water level change of the Salt Lake during the whole observation period calculated from the Cryosat-2 radar altimeter data. Raw data were from Li et al, 2019[9].…”

An integration of gauge, satellite and reanalysis precipitation datasets for the largest river basin of the Tibetan Plateau

“…Generally, the intra-annual distribution of precipitation is extremely uneven, with more precipitation distributed in the warm seasons (Wang et al, 2019a). Since the Indian and East Asian monsoons bring more water vapor in summer and the westerlies dominate in winter (Yi et al, 2013;Wang et al, 2018;Li et al, 2019aLi et al, , 2019b, there is a declining trend of precipitation from the humid southeast to the arid northwest, on average. In recent decades, the TP has been experiencing a significant warming trend exceeding that in the Northern Hemisphere (Liu and Chen, 2000;Yang et al, 2014), which will affect the generation and distribution of precipitation and influence hydrological processes throughout the Upper Brahmaputra.…”

An integration of gauge, satellite, and reanalysis precipitation datasets for the largest river basin of the Tibetan Plateau

“…Most studies have focused on evapotranspi- ration, soil moisture, and groundwater products derived from GLDAS or MERRA2 (Bibi et al, 2019;Deng et al, 2019;; meanwhile, to the best of our knowledge, there has been less focus on the evaluation of methods of precipitation estimation and little work on the corresponding river discharge simulations within the upper Brahmaputra River basin. These precipitation products generally have the advantage of wide and consistent coverage and have shown great potential in many applications (Li et al, 2015;Zhang et al, 2017;Fang et al, 2019) but also suffer from large uncertainties over the upper Brahmaputra River basin due to indirect observations, insufficient gauge calibration, and complex topography (Tong et al, 2014;Yong et al, 2015;Xu et al, 2017). In this study, we focus on integrating gauge, satellite, and reanalysis precipitation datasets to generate a new dataset over the upper Brahmaputra, suitable for use in hydrological simulations and other scientific research related to climate change.…”