Analyzing Joshimath's sinking: causes, consequences, and future prospects with remote sensing techniques.

The Himalayas are highly susceptible to various natural disasters, such as the tectonically induced land deformation, earthquakes, landslides, and extreme climatic events. Recently, the Joshimath town witnessed a significantly large land subsidence activity. The phenomenon resulted in the development of large cracks in roads and in over 868 civil structures, posing a significant risk to inhabitants and infrastructure of the area. This study uses a time-series synthetic aperture radar (SAR) interferometry-based PSInSAR approach to monitor land deformation utilizing multi-temporal Sentinel-1 datasets. The line of sight (LOS) land deformation velocity for the Joshimath region, calculated for the year 2022-2023 using a PSInSAR-based approach, varies from - 89.326 to + 94.46 mm/year. The + ve sign indicates the LOS velocity/displacement away from the SAR sensor, whereas - ve sign signifies the earth's movement towards the SAR sensor in the direction of LOS. In addition, the study investigates feature tracking land displacement analysis using multi-temporal high-resolution Planet datasets. The result of this analysis is consistent with the PSInSAR results. The study also estimated the land deformation for the periods 2016-2017, 2018-2019, and 2020-2021 separately. Our results show that the Joshimath region experienced the highest land deformation during the year 2022-2023. During this period, the maximum land subsidence was observed in the north-western part of the town. The maximum LOS land deformation velocity + 60.45 mm/year to + 94.46 mm/year (2022-2023), occurred around Singhdwar, whereas the north and central region of the Joshimath town experienced moderate to high subsidence of the order of + 10.45 mm/year to + 60.45 mm/year (2022-2023), whereas the south-west part experienced an expansion of the order of 84.65 mm/year to - 13.13 mm/year (2022-2023). Towards the south-east, the town experienced rapid land subsidence, - 13.13 mm/year to - 5 mm/year (2022-2023). The study analyzes the causative factors of the observed land deformation in the region. Furthermore, this work assesses the ground conditions of the Joshimath region using UAV datasets acquired in the most critically affected areas such as Singhdhaar, Hotel Mountain View, Malhari Hotel, and Manoharbagh. Finally, the study provides recommendations and future prospects for the development policies that need to be adopted in the critical Himalayan regions susceptible to land deformation. The study suggests that land deformation in the region is primarily attributed to uncontrolled anthropogenic activities, infrastructural development, along with inadequate drainage systems.

Ice thickness distribution of Himalayan glaciers inferred from DInSAR-based glacier surface velocity.

Retrieval of glacier ice thickness is extremely important for monitoring water resources and predicting glacier dynamics and changes. The inter-annual glacier ice thickness observations (more than 5 years) exploit the glacier mass changes. Ice thickness is one of the important parameters to predict the future sea-level rise. Without adequate knowledge and precise information of glacier ice thickness distribution, future sea-level changes cannot be accurately assessed. In this study, we use an existing flow model to estimate the ice thickness of the High Mountain Asia (HMA) glaciers, using remote sensing techniques. The glacier ice velocity is one of the significant parameters in the Laminar flow model to retrieve the ice thickness. The glacier ice velocity is derived by utilizing the Differential SAR Interferometry (DInSAR) technique. The most optimum DInSAR data (ALOS-2/PALSAR-2) is used for estimating the ice velocity of the HMA glaciers. The ice thickness is mainly estimated for five different states in the HMA region, namely Himachal Pradesh, Uttarakhand, Sikkim, Bhutan, and Arunachal Pradesh. Most of the states are observed with a mean ice thickness of 100 m. Five benchmark glaciers (Samudra Tapu, Bara Shigri, Chhota Shigri, Sakchum, and Gangotri glaciers) are also selected for validating our results with the existing thickness information. The issues related to velocity-based ice thickness inversion are also emphasized in this study. The high-velocity rate due to the influx of melting water from adjacent glaciers causes an increment in the flow rate. This abnormal velocity derives erroneous ice thickness measurements. This is one of the major problems to be considered in the velocity-based thickness-derived procedures. Finally, the investigation suggests the inclusion of the velocity influencing parameters in the physical-based models for an accurate ice thickness inversion.

Glacier mass balance estimation in Garhwal Himalaya using improved accumulation area ratio method.

Water requirements of the mountain communities living in the Himalaya are supported by snow and glacier melt. The availability of water from the source depends on numerous climatic and glacier parameters. One key parameter is mass balance, which helps to assess the glacier health and future water availability. We have used the improved accumulation area ratio (IAAR) method to estimate mass balance in Alaknanda and Bhagirathi basins, constituting 1055 glaciers covering ~1609 km2. The mean Equilibrium Line Altitude (ELA) of the Alaknanda and Bhagirathi basins are estimated as 6147 ± 130 and 5985 ± 130 m.a.s.l, respectively. The mass balance is estimated using the accumulation area ratio (AAR)-mass balance relationship. The mean specific mass balance of the Alaknanda and Bhagirathi for 2001-2013 is estimated as -1.1 ± 0.03 m.w.e.a-1 and -1.01 ± 0.07 m.w.e.a-1, respectively. Total mass loss from the study area is calculated as ~21.4 ± 1.1Gt during this period. The loss of glaciers in the mountain area will increase the vulnerability of communities living in the region. It suggests a need for better adaptation strategies to improve the resilience of high mountain communities.

Application of "OTSU"-an image segmentation method for differentiation of snow and ice regions of glaciers and assessment of mass budget in Chandra basin, Western Himalaya using Remote Sensing and GIS techniques.

In this study, an image segmentation algorithm ("OTSU") is applied for differentiation of snow/ice regions followed by interpretation of snowlines and estimation of mass budget of glaciers in Chandra basin, Western Himalaya, India between 2014 and 2020. The observations strongly suggest that the OTSU method can be used to differentiate the snow and ice regions on a glacier accurately from any satellite image, irrespective of the sensor characteristics. Also, this method suits well to delineate the snowlines for large sample of glaciers, other than the manual interpretation and semi-automated methods. The estimates of mass budget of the glaciers are observed varying from - 1.20 ± 0.51 m w.e to almost 0.64 ± 0.51 m w.e, with a total loss of - 61.91 ± 6.70 m w.e of ice mass at basin scale during the observation period. Based on this study, it is highly recommended the application of OTSU method for the differentiation of snow/ice zones of glaciers and snowline demarcation at a large spatial scale in the harsh weather rugged terrain of the Western Himalaya.

Assessment of runoff in Chandra river basin of Western Himalaya using Remote Sensing and GIS Techniques.

The runoff of Chandra river basin in the Himalayan India was assessed using a hydrological model combined with satellite remote sensing observations. During a test period between 2000 and 2015, in situ measurements of runoff and meteorological parameters were conducted in the glacial catchment areas of Sutridhaka and Chhotashigri. A good agreement was found between the observed and predicted runoff (correlation R2 > 0.8). The hydrological model was then used to simulate the runoff of Chandra River for a period of 2000 to 2015. Almost 68% of the predicted runoff occurred during the ablation period (May to September). A sensitivity study of the Chandra basin hydrology to a predicted warming climate of 1 to 4 K, toward the end of the century suggests that increased production of glacial melt water would have more impact on runoff than potential increase in precipitation. During the monsoon months (of June to August), increased runoff is predicted due to enhanced glacial melting but the runoff in other months to be lower than present mean runoff, except for the summer months (March to July).

Streamflow modeling and contribution of snow and glacier melt runoff in glacierized Upper Indus Basin.

The Upper Indus Basin has a large concentration of glaciers and mainly fed by snow and glacier melt. These melt runoffs are the primary driver of discharge and significantly contribute to Indus flows. Therefore, the present study was undertaken in the Upper Indus Basin (UIB) up to the Besham Quila site. This study focuses on quantifying runoff's contribution from different sources, including snow and glacier melt, and evaluates model performance in the glacierized Himalayan basin. The model was calibrated (1981-2000) and validated (2001-2007) daily and monthly using 27 years of measured discharge data at the Besham Quila station. A statistical indicator shows a "good" relationship between simulated and observed discharge on a daily and "very good" on a monthly timestamp. In this study, the annual contribution from snow/ice melt in the basin was quantified and found to be 51% of the total runoff. Apart from this, around 30% of water comes from direct runoff generated through liquid precipitation and 3.8% from groundwater. The remaining (~15%) is contributed by interflows sourced from the rainfall and snow/ice melt. The basin receives 61% contribution from snow and glacier melt during monsoon (July-Sept) and 38% during summer (April-June) seasons, while negligible in other seasons. A decreasing trend is observed in modelled total runoff and melt runoff of about 1.11 × 109 m3 a-1 and 0.73 × 109 m3 a-1, respectively.

Glacial changes over the Himalayan Beas basin under global warming.

We simulated and analyzed the glacier dynamics over the Beas basin (situated in the north-western Himalayas) for the present (1980-2015) and future climates (2006-2100) under RCP4.5 and RCP8.5 global warming scenarios. We first calibrated the Open Global Glacier Model over the study region and then conducted simulations for the present (forced by ERA-Interim) and future (forced by CMIP5 models) climates. For the present climate, the model simulations show that 50% of the total glacier volume (compared to 1980) is lost by 2011, with glacier area and volume showing a significantly decreasing trend, with higher fluctuations in the glacial area during recent decades. Future projections suggest 75% loss by 2040 ± 2.5 years and ~90% loss by 2094 ± 3.5 years under RCP4.5. Under RCP8.5, 75% loss is expected to occur by 2040 ± 3 years and ~90% loss by 2084 ± 8 years. Ensemble mean of the near-surface air temperature (both monthly mean and annual mean) shows a significantly increasing trend under both RCP4.5 and RCP8.5 for the entire 21st century. Ensemble mean of the total monthly precipitation shows no trend under RCP4.5, however, it shows a decreasing trend for months ODJFMA and an increasing trend for months JJ under RCP8.5. An increase in JJ precipitation does not increase glacier mass since this region does not receive snowfall during these months. Under RCP4.5, snowfall does not show any significant trend during NDJF, however, it shows a decreasing trend during October and March. Under RCP8.5, snowfall shows a significant decreasing trend for October through March. Overall, we find similar melting rates under RCP4.5 and RCP8.5 until ~2050, but the latter shows a higher rate afterward.

Glaciohydrology of the Himalaya-Karakoram.

Understanding the response of Himalayan-Karakoram (HK) rivers to climate change is crucial for ~1 billion people who partly depend on these water resources. Policy-makers tasked with sustainable water resources management require an assessment of the rivers' current status and potential future changes. We show that glacier and snow melt are important components of HK rivers, with greater hydrological importance for the Indus basin than for the Ganges and Brahmaputra basins. Total river runoff, glacier melt, and seasonality of flow are projected to increase until the 2050s, with some exceptions and large uncertainties. Critical knowledge gaps severely affect modeled contributions of different runoff components, future runoff volumes, and seasonality. Therefore, comprehensive field observation-based and remote sensing-based methods and models are needed.

Author Correction: Spatial distribution of decadal ice-thickness change and glacier stored water loss in the Upper Ganga basin, India during 2000-2014.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Spatial distribution of decadal ice-thickness change and glacier stored water loss in the Upper Ganga basin, India during 2000-2014.

Himalayan glaciers have long been the focus of glaciologists across the world while trying to understand the contrasting patterns of elevation and mass changes. However, with limited number of ground observations, a comprehensive assessment of mass balance on a regional scale still remains elusive. Using the synoptic coverage of remote sensing data, we estimate a detailed spatial variation of glacier ice thickness change in the Central Himalaya of Uttarakhand using geodetic method, on a catchment scale. High resolution TerraSAR-X/TanDEM-X (12 m) and SRTM (30 m) digital elevation models (DEMs) have been utilized. The mean elevation change in the catchments is found to be -9.56 ± 0.2 m (mean annual elevation change rate is -0.68 ± 0.01 m a-1). To highlight the water potential of this region, the total ice mass loss has been estimated to be 16.0 ± 1.2 Gigatonne (Gt) from 2000-2014 from eight identified catchments namely Yamunotri, Bhagirathi, Mandakini, Alaknanda, Dhauliganga, Pindar, Goriganga and Kali/Sarda. The estimated mass balance has been validated using reported observations on five selective glaciers and the coefficient of determination is 0.93. This spatial variation of ice thickness estimated in the eight catchments is critical, as the melt-water from these glaciers contribute to the upper Ganga basin.

Hydrodynamic moraine-breach modeling and outburst flood routing - A hazard assessment of the South Lhonak lake, Sikkim.

The presence of glacial lakes in the Himalaya makes it a potential mountain hazard, as catastrophic failure of such waterbodies may lead to high-magnitude glacial lake outburst flood (GLOF) events that can cause significant damage to the low-lying areas. The present study evaluates the hazard potential of the South Lhonak lake located in the state of Sikkim, using both one and two-dimensional hydrodynamic modeling approaches. Different breach parameters were calculated based on the lake bathymetry and moraine dimensions. The worst-case GLOF scenario is revealed during an overtopping failure of the moraine, producing a peak flood of 6064.6 m3 s-1 and releasing a total water volume of 25.7 × 106 m3. The GLOF hydrograph is routed to calculate peak flood (m3 s-1), inundation depth (m) and flow velocity (ms-1) along the main flow channel. The interaction of the flood wave with a major topographic obstruction located 15.6 km downstream of the lake, shows a significant reduction of the flow energy leading to a minimization of the South Lhonak GLOF impact. The flood wave reaches the nearest town Lachen, located at a distance of 46 km downstream from the lake, at 3 h 38 min after the initiation of the breach, with a peak flood of 3928.16 m3 s-1 and a maximum flow velocity of 13.6 ms-1. At Chungthang town, located at a distance of 62.35 km from South Lhonak lake, the flood wave potentially inundates settlements along the bank of the flow channel, where a peak flood of 3828.08 m3 s-1 is reached after 4 h of the initial dam breach event. The study also incorporates modeling of a framework to propose a potential flood remediation measure of the South Lhonak lake GLOF by demonstrating the effect of a lateral inline structure along the flow channel, to check the flow of the potential flood wave.

Assessing controls on mass budget and surface velocity variations of glaciers in Western Himalaya.

This study analyses spatially resolved estimates of mass budget and surface velocity of glaciers in the Zanskar Basin of Western Himalaya in the context of varying debris cover, glacier hypsometry and orientation. The regional glacier mass budget for the period of 1999-2014 is -0.38 ± 0.09 m w.e./a. Individual mass budgets of 10 major glaciers in the study area varied between -0.13 ± 0.07 and -0.66 ± 0.09 m w.e./a. Elevation changes on debris-covered ice are considerably less negative than over clean ice. At the same time, glaciers having >20% of their area covered by debris have more negative glacier-wide mass budgets than those with <20% debris cover. This paradox is likely explained by the comparatively larger ablation area of extensively debris-covered glaciers compared to clean-ice glaciers, as indicated by hypsometric analysis. Additionally, surface velocities computed for the 2013-14 period reveal near stagnant debris-covered snouts but dynamically active main trunks, with maximum recorded velocity of individual glaciers ranging between ~50 ± 5.58 and ~90 ± 5.58 m/a. The stagnant debris-covered extent, which varies from glacier-to-glacier, are also characterized by ice cliffs and melt ponds that appreciably increase the overall surface melting of debris-covered areas.

Assessment of snow-glacier melt and rainfall contribution to stream runoff in Baspa Basin, Indian Himalaya.

Hydrological regimes of most of the Himalayan river catchments are poorly studied due to sparse hydro-meteorological data. Hence, stream runoff assessment becomes difficult for various socio-industrial activities in the Himalaya. Therefore, an attempt is made in this study to assess the stream runoff of Baspa River in Himachal Pradesh, India, by evaluating the contribution from snow-ice melt and rainfall runoff. The total volume of flow was computed for a period of 15 years, from 2000 to 2014, and validated with the long-term field discharge measurements, obtained from Jaipee Hydropower station (31° 32' 35.53″ N, 78° 00' 54.80″ E), at Kuppa barrage in the basin. The observations suggest (1) a good correlation (r2 > 0.80) between the modeled runoff and field discharge measurements, and (2) out of the total runoff, 81.2% are produced by snowmelt, 11.4% by rainfall, and 7.4% from ice melt. The catchment receives ~75% of its total runoff in the ablation period (i.e., from May to September). In addition, an early snowmelt is observed in accumulation season during study period, indicating the significant influence of natural and anthropogenic factors on high-altitude areas.

Missing (in-situ) snow cover data hampers climate change and runoff studies in the Greater Himalayas.

The Himalayas are presently holding the largest ice masses outside the polar regions and thus (temporarily) store important freshwater resources. In contrast to the contemplation of glaciers, the role of runoff from snow cover has received comparably little attention in the past, although (i) its contribution is thought to be at least equally or even more important than that of ice melt in many Himalayan catchments and (ii) climate change is expected to have widespread and significant consequences on snowmelt runoff. Here, we show that change assessment of snowmelt runoff and its timing is not as straightforward as often postulated, mainly as larger partial pressure of H2O, CO2, CH4, and other greenhouse gases might increase net long-wave input for snowmelt quite significantly in a future atmosphere. In addition, changes in the short-wave energy balance - such as the pollution of the snow cover through black carbon - or the sensible or latent heat contribution to snowmelt are likely to alter future snowmelt and runoff characteristics as well. For the assessment of snow cover extent and depletion, but also for its monitoring over the extremely large areas of the Himalayas, remote sensing has been used in the past and is likely to become even more important in the future. However, for the calibration and validation of remotely-sensed data, and even more so in light of possible changes in snow-cover energy balance, we strongly call for more in-situ measurements across the Himalayas, in particular for daily data on new snow and snow cover water equivalent, or the respective energy balance components. Moreover, data should be made accessible to the scientific community, so that the latter can more accurately estimate climate change impacts on Himalayan snow cover and possible consequences thereof on runoff.