Remote sensing to capture the dynamics of mountain cryosphere

Abstract/Description

Glaciers are a significant indicator of climate change and one of the sources of fresh water. Glacier status monitoring is an important task for scientific research, especially in the arid regions of Central Asia. An archive of multispectral Landsat and ALOS/AVNIR-2 data as well as KH-9 and Catalogues data from 1957 and 1980s were used to identify glaciers in the mountain area of Uzbekistan for different periods and to analyze trends in glacier area until 2024. To extend the investigations to glacier surface elevation changes in the Pskem River basin, InSAR techniques were used with bistatic TanDEM-X datasets until 2014, DInSAR with TerraSAR-X /PAZ constellation for 2022-2023, SBAS with Sentinel -1 data and ASF DAAC HyP3 interferometric processing products until 2024. The test areas were the glaciers where glaciological expeditionary observations have been held: Barkrak Middle, Pakhtakor and Tekeshsay Glaciers. Different software and approaches were used to process SAR data. The satellite data – based results show that the mean surface lowering rate for 10 glaciers in the basin of the Pskem River tributary is -0,68 m/y from 2012 to 2014 and the corresponding annual mass balance is -1,08 m w.e. The Tekeshsay Glacier’s annual mass balance is -0,136 m w.e. in 2012-2014. The Pakhtakor Glacier mean surface lowering rate is −1,3 ± 0,5 m/y for 2000-2012. The daily lowering rate of the Barkrak Glacier surface is 2 mm/d from August to October of 2023 and will be compared to field data acquired during summer. Twelve-day alternations of glacier subsidence and uplift in summer were considered with meteorological information of the Oygaing Station which is located at the elevation of 2100 m. The observed glacier uplift can also be related to an avalanche release from surrounding slopes and glacier movement. RAMMS software was used to estimate avalanche depositions on the surface of the Barkrak and Pakhtakor Glaciers. Avalanche feeding could contribute with 4 to 40% to the Barkrak Glacier mass balance since 2017. The daily glacier movement velocity (up to 10 cm per day) was estimated using offset tracking with Sentinel-1 data and amplitude tracking with TerraSAR-X /PAZ data.

Abstract/Description

Glacier mass balance is a key parameter for assessing glacier health and understanding its response to climate change. Previous studies have utilized various satellite-based techniques, such as stereo imaging, InSAR, and altimetry, to estimate geodetic glacier mass balance. However, these methods are often limited by either temporal constraints or sensor resolution. In this study, we combined time-series elevation data from CARTOSAT-1 and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) to provide an up-to-date geodetic glacier mass balance estimate for the period of 2002-2024. While ASTER, operational since 2000, offers spatial (30 m) and radiometric (8 bit) resolutions, CARTOSAT-1, which operated from 2005 to 2018, had superior spatial (2.5 m) and radiometric (10 bit) resolutions. To improve the accuracy of ASTER-based elevation change (dh/dt) data, we corrected the ASTER trend using the CARTOSAT-1 data from 2006-2018. We then applied this correction function to update ASTER observations from 2002-2024. When compared with in-situ glaciological mass balance measurements, our approach showed improved accuracy for ASTER-based geodetic mass balance estimates. Our study emphasizes the value of combining dh/dt time-series from different datasets to enhance the accuracy of glacier mass balance estimates with high temporal resolution, applicable across entire regions.

Abstract/Description

Paloma Palma Riveros1, Valentina Premier2, Carlo Marin2 and James McPhee1

Mountainous areas, such as the Andes Cordillera, are essential for the supply of fresh water due to their capacity to accumulate snow and release water during the warmer seasons. This process directly influences the provision of water for human consumption, irrigation, hydroelectric power generation, and ecosystem preservation. In the context of climate change, a reduction in the duration and extent of snow cover is projected, making it crucial to improve the models for predicting snowmelt and Snow Water Equivalent (SWE). High-resolution, distributed estimates of past SWE are valuable for evaluating predictive models, streamflow forecasting, and other applications. This study seeks to develop readily updated historical SWE based on remotely sensed data and melt models of varying complexity. We demonstrate this methodology on the mountainous sector of the Maipo River basin, where the main sub-basins exhibit hydrological regimes ranging from snow-dominated to mixed snow-rain. Three snowmelt estimation models are evaluated: one based on energy balance (Cornwell et al., 2016) and two based on a temperature index (Pellicciotti et al. 2005, Premier et al., 2023). These models are fed with meteorological data collected from snow monitoring stations within the basin, as well as Sentinel-2 satellite imagery, integrating variables such as temperature, solar radiation, and albedo. It is observed that all three approaches adequately or acceptably reproduce the SWE dynamics in the basin. However, each model exhibited specific strengths and limitations: the energy balance-based models demonstrated higher precision in short periods, while the degree-day factor model performed better in representing overall trends. The results highlight the importance of combining approaches based on meteorological and satellite data to model snowmelt, optimize water resource management, and respond to the challenges of climate change.

Abstract/Description

The two TanDEM-X satellites have been acquiring X-band radar data for the generation of digital elevation models (DEMs) starting in late 2010. For Fedchenko Glacier, one of the longest glaciers outside the polar regions and the largest glacier of the Pamir Mountains, an abundant sequence of elevation data is available with several acquisitions per year distributed over all seasons. Making use of the data of the Shuttle Radar Topography Mission the observations can be extended back to the year 2000.
This wealth of data can be used two-fold: firstly, annual elevation change rates can be derived using data with comparable properties regarding geometry and season in order to minimise systematic effects, which can be, secondly, analysed making use of the complete data base. In the first decade of the 21st century, Fedchenko Glacier experienced a typical elevation decrease in the lower parts and an elevation increase in the upper accumulation zone. In contrast, the glacier has thinned over its whole extent since the first TanDEM-X acquisitions. One of the main error sources for the determination of surface elevation changes is the effect of radar penetration into ice and snow. In order to assess its magnitude, especially the repeated acquisitions in late summer/early fall reveal valuable insights into short term changes in penetration properties due to the transition from melting to freezing conditions.