Hansheng Wang

Monitoring the hydrological processes of lakes can provide reliable data for regional water resources assessment. This paper analyzed changes in the lake area and water level of Hala Lake from 2011 to 2023, subsequently estimating its lake water storage change (LWSC). We used image data from Landsat series satellites and multi-source satellite altimetry data, and then quantitatively assessed the influence of various driving factors on the LWSC in combination with hydrological and meteorological models. The results show three stages of parallel changes in the area, water level and LWSC of Hala Lake in the past 13 years. The first stage is from 2011 to 2014, when the lake expanded slightly, the second stage is from 2015 to 2019, when the lake expanded rapidly, and the last stage is from 2020 to 2023, with relatively stable conditions. Over the entire study period, the LWSC increased with a trend of 0.192 ± 0.009 km³/a. Lake surface precipitation, precipitation-caused runoff, and glacier meltwater contributed to the total recharge input by 51%, 40.96%, and 8.04%, respectively, while the lake surface evaporation accounted for 59.37% of the total recharge input as water loss. Thus, the left 40.63% of the input caused the LWSC increase. Although lake surface precipitation provided the primary contribution to the Hala Lake LWSC, precipitation-caused runoff was the key factor forming the three stages in the LWSC. The results of this study provide valuable information for the rational development and utilization of water resources by government departments and are also beneficial to the study of global change.

Annual mass balance (AMB) is a critical parameter to understand the rapid variation of glaciers that can serve water resource management, glacier disaster prevention, and global change studies. However, estimating AMB for widely distributed glaciers is hindered by existing satellite geodetic and albedo-based methods due to low spatio-temporal resolution or reliance on in-situ data for model calibration. In this study, we propose a novel method to estimate AMB by combining remote sensing albedo with differencing DEM data. We validated the estimated AMB with in-situ data for 88 tested glaciers in Alaska, Western Canada and USA, the European Alps, High Mountain Asia, and the Andes Mountains. The proposed method achieves an average RMSE of 495 mm w.e., its accuracy is 11.3% on average higher than that of other available AMB model data from previous studies (Snow line altitude-based method, degree day model, and DEM interpolation method), and the correlation with in-situ data for our method is 47.2% greater than that for other AMB model data. Because remote sensing albedo and differencing DEM can be available globally, the novel method proposed in this study is potentially suitable to estimate AMB for widely distributed glaciers, except for those with high debris cover ratios and surge-type glaciers.

The GRACE twin satellite gravity mission from 2002 to 2017 has considerably improved investigations on global and regional hydrological changes. However, there are different GRACE solutions and products available which may yield different results for certain regions despite applying the same postprocessing and time span. This is especially the case for the Tibetan Plateau (TP) with its special hydrological conditions represented by localized but strong signals that can overlap or merge with signals inside the plateau, which can falsify the determination of terrestrial water storage (TWS) changes in the TP area. To investigate the effect of GRACE solution selection on inverted TWS changes, we analyze quantitatively the secular and monthly changes for 14 glacier areas and 10 water basins in and around the TP area that have been calculated from 16 different available GRACE solutions. Our analysis provides expectable results. While trend results from different spherical harmonic (SH) GRACE solutions match well, there are significant differences to and between mascon GRACE solutions. This is related to the different processing concepts of mascon solutions and their forced handling in our comparisons. SH solution time series match each other when mass changes are strong with a large amplitude and regular periodicity. However, for regions where small TWS changes are associated with small amplitudes, trends, and/or unstable signal periods, SH solutions can also yield different results. Such behavior is known from a time series analysis. Interestingly though, we find that the COST-G and ITSG SH GRACE solutions are closest to the average of all solutions. Therefore, these solutions appear to be preferable for TWS investigations in regions with highly variable hydrological conditions, such as in the Tibetan Plateau and its surroundings. This also indicates that combined solutions such as COST-G provide a promising pathway for an improved TWS analysis, which should be further elaborated.

The Tibetan Plateau (TP) has the largest number of high-altitude glaciers on Earth. As a source of major rivers in Asia, this region provides fresh water to more than one billion people. Any terrestrial water storage (TWS) changes there have major societal effects in large parts of the continent. Due to the recent acceleration in global warming, part of the water environment in TP has become drastically unbalanced, with an increased risk of water disasters. We quantified secular and monthly glacier-mass-balance and TWS changes in water basins from April 2002 to December 2021 through the Gravity Recovery and Climate Experiment and its Follow-on satellite mission (GRACE/GRACE-FO). Adequate data postprocessing with destriping filters and gap filling and two regularization methods implemented in the spectral and space domain were applied. The largest glacier-mass losses were found in the Nyainqentanglha Mountains and Eastern Himalayas, with rates of −4.92 ± 1.38 Gt a⁻¹ and −4.34 ± 1.48 Gt a⁻¹, respectively. The Tien Shan region showed strong losses in its eastern and central parts. Furthermore, we found small glacier-mass increases in the Karakoram and West Kunlun. Most of the glacier mass change can be explained by snowfall changes and, in some areas, by summer rainfall created by the Indian monsoon. Major water basins in the north and south of the TP exhibited partly significant negative TWS changes. In turn, the endorheic region and the Qaidam basin in the TP, as well as the near Three Rivers source region, showed distinctly positive TWS signals related to net precipitation increase. However, the Salween River source region and the Yarlung Zangbo River basin showed decreasing trends. We suggest that our new and improved TWS-change results can be used for the maintenance of water resources and the prevention of water disasters not only in the TP, but also in surrounding Asian countries. They may also help in global change studies.

The high spatial-temporal variability of soil moisture necessitates monitoring at a high resolution in order to improve our understanding of Earth system processes. Current large-scale soil moistures inferred from the microwave satellites have limited spatial resolution, typically in the range of tens of kilometers. Recent studies have revealed that synthetic aperture radar (SAR) backscatter exhibits qualitative relationships with soil moisture, suggesting the potential for large-scale high-resolution mapping of soil moisture. Here, we proposed a method for directly estimating soil moisture content based on the Advanced Integral Equation Model (AIEM) and Mironov dielectric model. The approach involves establishing a series of semi-empirical models, independent of preceding surface roughness determination, using two Envisat ASAR alternating polarization (AP) model precision products. We generate a time series of high-resolution soil moisture using Envisat ASAR AP data acquired from 2004 to 2011, with an uncertainty of approximately 0.05 m ³ /m ³ . Our soil moisture retrievals demonstrate very good agreement with European Space Agency (ESA) Climate Change Initiative (CCI) soil moisture products and the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 re-analysis hourly products, even in the absence of synchronous ground measurements. Furthermore, our study reveals good temporal coherence between drought and heavy rainfall events, and SAR-derived soil moisture, which suggests a potential to capture heavy rainfall and drought events. We conclude that SAR-derived soil moisture is a more direct and efficient method in quantifying soil moisture at a high spatial resolution, making it more suitable for watershed scale hydrological studies.

The fidelity of Inter-Campaign Biases (ICBs) estimates for Ice, Cloud, and land Elevation Satellite (ICESat) ice elevation products is critical for ice sheet mass balance research. Prior studies have confirmed that ICBs are significantly dependent on data products, released versions, and surface types, leading to the hypothesis that ICBs for Level 2 Geosciences Laser Altimeter (GLA12) newly released products remain poorly determined. Here, we propose a new method to estimate ICBs using altimetry crossovers relative to a known stable ice surface, Dome A summit, East Antarctica, and a multi-time reference framework, which maximizes the number of crossovers. The ICBs of GLA12 release 634 product range from -8.1±1.1 cm (L3A) to 19.3±0.8 cm (L2C), and most of them range from -5 cm to 10 cm. However, the ICBs for a few campaigns show significant campaign-dependent variations (L2B and L3D). They exhibit insignificant trend (-0.9±0.8 cm/yr) during entire ICESat mission, but there is a clear trend at -3.0±0.3 cm/yr since February 2006 (L3E). We conclude that the time-variable ICBs should be carefully considered on ice sheet mass balance estimate, especially for specific campaigns.

Terrestrial laser scanning (TLS) is an important means to monitor landslides, and the layout is the key to guarantee captured point clouds with a high quality and low cost. Nevertheless, TLS layout in landslide monitoring is currently determined by user’s subjective experience, and shows a poor performance in reliability and point accuracy. Therefore, we propose multi-objective optimization based TLS layout planning for landslide monitoring. Three-dimensional (3D) scanning simulation of candidate scan positions is first carried out. A multi-objective optimization problem (MOP) is then constructed according to requirements of landslide TLS monitoring in the coverage, cost, and point accuracy. Finally, the combination of an improved non-dominated sorting genetic algorithm Ⅱ (NSGA-II) and the Pareto-Edgeworth-Grierson (PEG) algorithm is introduced to solve the MOP and obtain the optimal layout. To test the proposed method, experiments were performed in two landslide sites in Wuhan, China. Results showed that the planned TLS layouts reached a trade-off among coverage, point accuracy, and the number of TLS scan positions. Comparison experiments based on simulation demonstrated that the constraints fused into NSGA-II dramatically improved the reliability of the planned TLS layout, and the proposed method improved the coverage and point accuracy by 11.62% and 1.52 times compared to the user’s experience. Real scanning demonstrated the proposed method improved the coverage by 10.48%, and reduced the deformation error by 0.78 mm~7.66 mm compared to the user’s experience. In summary, the proposed method is an efficient approach for TLS layout planning, which can improve the ability of landslide TLS monitoring.

Retrieval of glacier surface heights from ICESat-2 photon-counting data is significant to monitor glacier surface morphologies (e.g., crevasses) and their changes. However, existing methods are susceptible to complex glacier surfaces and diverse signal-to-noise ratios (SNRs). Therefore, we propose a robust density estimation method for glacier-height retrieval from ICESat-2 photon-counting data. A multi-scale random sample consensus (RANSAC) strategy is firstly employed to obtain the best elliptical neighborhood for each photon, to improve the consistency of neighboring photons. Then, a hybrid weighted density estimation method is developed to robustly describe the differences in the spatial distribution patterns between signal and noise photons. High-quality extraction of signal photons is finally implemented using adaptive thresholds in the local along-track segments. To test its performance, four datasets with strong and weak beams from the Jakobshavn Isbræ Glacier, western Greenland, were selected. Results showed that the proposed method achieved excellent performances in glacier-height retrieval in various glacier surface morphologies and diverse SNRs, due to discriminative densities between noise and signal photons were obtained. The average percentages of along-track segments with signal densities larger than noise densities for weak and strong beams were 92.0% and 99.9%. The average F₁-scores reached 0.927 and 0.968 for the weak and strong beams, even the F₁-score reached 0.892 for the heavily crevassed complex surface with a low SNR. Moreover, comparison experiments with existing methods demonstrated that the proposed method showed superior performances in density estimation and glacier-height retrieval, and improved more than 17.33% and 16.10% in the most complex surface, respectively.