Karakoram Region Research Articles

Assessing glacier mass balance variations and climate drivers of Shisper and Muchuhar glaciers in the Karakoram region, Pakistan: a remote sensing and GIS approach

ABSTRACT Glaciers in the Karakoram region of Pakistan are crucial water sources for downstream communities, supporting irrigation and power generation. Global warming has led to significant glacier mass loss and size reduction, posing risks to ecology, climate, and water resources. Understanding Glacier Mass Balance (GMB) is essential for climate change insights and predicting future trends, mainly due to limited long-term GMB and Equilibrium Line Altitude (ELA) data from the Karakoram region. We employed hypsometrically controlled methods, Accumulation Area Ratio (AAR) and Accumulation Area Balance Ratio (AABR) to fill this gap. AAR values ranged from 0.4 to 0.8 at 0.5 intervals, and AABR from 0.9 to 2.2 at 0.01 intervals. Findings indicate that Shisper Glacier had a negative mass balance of –1.0 m/y w.e., with the area below ELAs expanding by 1.72 km². Muchuhar Glacier showed a negative mass balance of -0.05 m/y w.e., with the area below ELAs decreasing to 0.96 km². Surface temperature trends indicate 6.44°C in 2023, highlighting a warming trend. Rising average air temperature (Tavg) is the significant factor influencing ELAs (26% and 72%, respectively), followed by average precipitation (Pavg) at 20% and 26%. These findings highlight the critical role of temperature and precipitation in glacier mass balance.

Distributed modelling of snow and ice melt in the Naltar Catchment, Upper Indus basin

Energy balance distributed modelling in High Mountain Asia (HMA) is important to examine glaciological and hydrological processes and assess changes in streamflow in the current and future climate. In this study, the Physically based Distributed Snow Land and Ice Model (PDSLIM) using detailed observed meteorological data at hourly scale is employed to simulate the hydrological response of the Naltar catchment, 242.62 km2 in size, (in the Karakoram region in Pakistan to simulate its glaciers’ mass balance as well as daily runoff. The results exhibited overall satisfactory performance in terms of coefficient of determination (R2 = 0.96) and Nash-Sutcliffe Efficiency (NSE=0.95) modelled against satellite-based snow cover areas, for internal model verification, in eight years. The results of runoff simulations compared for external model verification, with observed daily discharge resulted in NSE 0.90 and 0.89 for calibration and validation period respectively. Flow composition analysis revealed that the streamflow regime of Naltar catchment is composed to 40 % by glacier runoff, 42 % by sub-surface runoff and 18 % by surface runoff. The eight year mean value of net mass balance exhibited a slightly negative mass balance (−0.810 ± 0.31 m w.e. a-1) less pronounced than that observed globally in several continental glaciers distinct from the Greenland and Antarctic ice sheets in the current climate. It seems that the ‘Karakoram anomaly’, i.e. the balanced to slightly positive glacier budgets observed in the region in the recent decades, a unique dynamics worldwide, has a moderate impact in the central Karakoram. Overall, the distributed energy-balance model PDSLIM, so far tested in the Alps, results to be a suitable tool to estimate energy and mass balance in the glacierized catchments of Karakoram and Himalaya and to better understand snow and ice melt runoff dynamics and floods in highly complex and glacierized mountain basins in the current and, in our research perspective, in the future climate.

Snow Avalanche Hazard Mapping Using a GIS-Based AHP Approach: A Case of Glaciers in Northern Pakistan from 2012 to 2022

Snow avalanches are a type of serious natural disaster that commonly occur in snow-covered mountains with steep terrain characteristics. Susceptibility analysis of avalanches is a pressing issue today and helps decision makers to implement appropriate avalanche risk reduction strategies. Avalanche susceptibility maps provide a preliminary method for evaluating places that are likely to be vulnerable to avalanches to stop or reduce the risks of such disasters. The current study aims to identify areas that are vulnerable to avalanches (ranging from extremely high and low danger) by considering geo-morphological and geological variables and employing an Analytical Hierarchy Approach (AHP) in the GIS platform to identify potential snow avalanche zones in the Karakoram region in Northern Pakistan. The Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) was used to extract the elevation, slope, aspect, terrain roughness, and curvature of the study area. This study includes the risk identification variable of land cover (LC), which was obtained from the Landsat 8 Operational Land Imager (OLI) satellite. The obtained result showed that the approach established in this study provided a quick and reliable tool to map avalanches in the study area, and it might also work with other glacier sites in other parts of the world for snow avalanche susceptibility and risk assessments.

Evolution of Supraglacial Lakes from 1990 to 2020 in the Himalaya–Karakoram Region Using Cloud-Based Google Earth Engine Platform

Evolution of Supraglacial Lakes from 1990 to 2020 in the Himalaya–Karakoram Region Using Cloud-Based Google Earth Engine Platform

Assessment of Hydrological Response to Climatic Variables over the Hindu Kush Mountains, South Asia

The impact of climate extremes, such as heat waves and extreme rainfall, can cause harvest failures, flooding, and droughts that ultimately threaten global food security, harming the region’s economy. Fluctuations in streamflow indicate the sensitivity of streamflow responding to extreme precipitation events and other climatic variables (temperature extremes) that play a significant role in its generation. Pakistan is also considered one of the climate change hotspot regions in the world. The devastating impacts have often occurred in recent decades due to an excess or shortage of streamflow, majorly generated from the Upper Indus Basin (UIB). To better understand climate extremes’ impact on streamflow, this study examined climate extremes and streamflow (Q) changes for three decades: 1990–1999, 2000–2009, and 2010–2019. Observed streamflow and meteorological data from nine sub-catchments across all climatic zones of the UIB were analyzed using RGui (R language coding program) and partial least squares regression (PLSR). Climatic variables were estimated, including precipitation extremes, temperature extremes, and potential evapotranspiration. The Mann–Kendal test was applied to the climatic indices, revealing that precipitation increased during the last 30 years, while maximum and minimum temperatures during the summer months decreased in the Karakoram region from 1990 to 2019. The spatiotemporal trend of consecutive dry days (CDD) indicated a more increasing tendency from 1990 to 2019, compared to the consecutive wet days (CWD), which showed a decreasing trend. PLSR was applied to assess the relation between climatic variables (extreme P, T indices, and evapotranspiration). It was found that the dominant climatic variables controlling annual streamflow include the r95p (very wet days) and R25mm (heavy precipitation days), maximum precipitation event amount, CWD, PRCPTOT (annual total precipitation), and RX5 (maximum five-day precipitation). The TXn (Min Tmax) and Tmax mean (average maximum temperature) dominate streamflow variables. Moreover, the impact of evapotranspiration (ET) on variations in streamflow is more pronounced in arid catchments. Precipitation is the predominant factor influencing streamflow generation in the UIB, followed by temperature. From streamflow quantification, it was found that climate-driven annual streamflow decreased during 1999–2019 in comparison to 1990–1999, with an increase in a few catchments like Kalam, which increased by about 3.94% from 2000 to 2010 and 10.30% from 2010 to 2019, and Shigar, which increased by 0.48% from 2000 to 2009 and 37.37% from 2010 to 2019 concerning 1990–1999. These variations were due to changes in these climatic parameters. The PLSR approach enables the identification of linkages between climatic variables and streamflow variability and the prediction of climate-driven floods. This study contributes to an enhanced identification and hydroclimatological trends and projections.

A Review of Karakoram Glacier Anomalies in High Mountains Asia

Influenced by global warming, glaciers in High Mountains Asia (HMA) generally show a trend of retreat and thinning, but in Karakoram, Pamir, and West Kunlun there is a trend of glacier stabilization or even a weak advance. In this study, using a bibliometric analysis, we systematically sorted the area, mass balance, and elevation changes of the glaciers in Karakoram and summarized the glacier surges in HMA. The study shows that, since the 1970s, the glaciers in the Karakoram region have experienced a weak positive mass balance, with weakly reducing area and the increasing surface elevation. The north slope of Chogori Peak and the Keltsing River Basin presented a glacier retreat rate with a fast to slow trend. The anomaly is mainly due to low summer temperatures and heavy precipitation in winter and spring in the Karakoram region. There are a large number of surging glaciers in the Karakoram Mountains, the Pamir Plateau, and the West Kunlun region in the western part of HMA, especially in the Karakoram Mountains and the Pamir Plateau, which account for more than 70% of the number of surging glaciers in the entire HMA. The glaciers in the Karakoram and Kunlun Mountains are mainly affected by the synergistic influence of various factors, such as hydrothermal conditions, atmospheric circulation, and topography. However, the glaciers in the Pamir region are mainly influenced by the thermal mechanism of the glacier surge. The glaciers in and around Karakoram are critical to the hydrological response to climate change, and glacial meltwater is an important freshwater resource in arid and semi-arid regions of South and Central Asia, as well as in western China. Therefore, changes in the Karakoram anomaly will remain a hot research topic in the future.

Landslide Susceptibility Mapping: Analysis of Different Feature Selection Techniques with Artificial Neural Network Tuned by Bayesian and Metaheuristic Algorithms

The most frequent and noticeable natural calamity in the Karakoram region is landslides. Extreme landslides have occurred frequently along Karakoram Highway, particularly during monsoons, causing a major loss of life and property. Therefore, it is necessary to look for a solution to increase growth and vigilance in order to lessen losses related to landslides caused by natural disasters. By utilizing contemporary technologies, an early warning system might be developed. Artificial neural networks (ANNs) are widely used nowadays across many industries. This paper’s major goal is to provide new integrative models for assessing landslide susceptibility in a prone area in the north of Pakistan. To achieve this, the training of an artificial neural network (ANN) was supervised using metaheuristic and Bayesian techniques: Particle Swarm Optimization (PSO) algorithm, Genetic algorithm (GA), Bayesian Optimization Gaussian Process (BO_GP), and Bayesian Optimization Tree-structured Parzen Estimator (BO_TPE). In total, 304 previous landslides and the eight most prevalent conditioning elements were combined to form a geospatial database. The models were hyperparameter optimized, and the best ones were employed to generate susceptibility maps. The obtained area under the curve (AUC) accuracy index demonstrated that the maps produced by both Bayesian and metaheuristic algorithms are highly accurate. The effectiveness and efficiency of applying ANNs for landslide mapping, susceptibility analysis, and forecasting were studied in this research, and it was observed from experimentation that the performance differences for GA, BO_GP, and PSO compared to BO_TPE were relatively small, ranging from 0.32% to 1.84%. This suggests that these techniques achieved comparable performance to BO_TPE in terms of AUC. However, it is important to note that the significance of these differences can vary depending on the specific context and requirements of the ML task. Additionally, in this study, we explore eight feature selection algorithms to determine the geospatial variable importance for landslide susceptibility mapping along the Karakoram Highway (KKH). The algorithms considered include Information Gain, Variance Inflation Factor, OneR Classifier, Subset Evaluators, principal components, Relief Attribute Evaluator, correlation, and Symmetrical Uncertainty. These algorithms enable us to evaluate the relevance and significance of different geospatial variables in predicting landslide susceptibility. By applying these feature selection algorithms, we aim to identify the most influential geospatial variables that contribute to landslide occurrences along the KKH. The algorithms encompass a diverse range of techniques, such as measuring entropy reduction, accounting for attribute bias, generating single rules, evaluating feature subsets, reducing dimensionality, and assessing correlation and information sharing. The findings of this study will provide valuable insights into the critical geospatial variables associated with landslide susceptibility along the KKH. These insights can aid in the development of effective landslide mitigation strategies, infrastructure planning, and targeted hazard management efforts. Additionally, the study contributes to the field of geospatial analysis by showcasing the applicability and effectiveness of various feature selection algorithms in the context of landslide susceptibility mapping.

Metamorphic and intrusive history of the Hindu Raj region, northern Pakistan

AbstractThe Hindu Raj region of northern Pakistan is situated between the Karakoram to the east and the Hindu Kush to the west. Both the Karakoram and the Hindu Kush are better studied and have well-documented, distinct geological histories. Investigation of the Hindu Raj region has been mainly limited to reconnaissance exploration and as such little is known about its tectonometamorphic history and whether that history is similar to its neighbouring areas. Analysis of new specimens collected along the Yasin Valley within the Hindu Raj region outline mid-to-Late Cretaceous pluton emplacement (ca. 105 and 95 Ma). Some of those plutonic rocks were metamorphosed to ∼750 ± 30 °C and 0.65 ± 0.05 GPa during the ca. 80–75 Ma docking of the Kohistan arc. A record of this collisional event is well-preserved to the west in the Hindu Kush and variably so to the east in the Hunza Karakoram. A subsequent, ca. 61 Ma, thermal event is partially preserved in Rb–Sr geochronology from the Hindu Raj, which overlaps with sillimanite-grade metamorphism in the Hunza portion of the Karakoram region to the east. Finally, apatite U–Pb and in situ Rb–Sr both record a late Eocene thermal/fluid event likely related to the India-Asia collision. These new data outline a complex geological history within the Hindu Raj, one that shares similarities with both adjacent regions. The information about the tectonometamorphic development of the Hindu Raj is important to gaining a detailed view of the geological characteristics of the southern Asian margin prior to the India-Asia collision.

Characterization of Three Surges of the Kyagar Glacier, Karakoram

Glaciers experience periodic variations in flow velocity called surges, each of which influences the glacier’s characteristics and the occurrence of downstream disasters (e.g., ice-dammed lake outburst floods). The Karakoram region contains many surging glaciers, yet there are few comprehensive studies of multiple surge cycles. In this work, Landsat, topographic map, Shuttle Radar Topography Mission (SRTM), TerraSAR-X/TanDEM-X, ITS_LIVE, and Sentinel-1 glacier velocity data were used to systematically analyze the characteristics of Kyagar Glacier since the 1970s. Three surging events were identified, with active phases in 1975–1978, 1995–1997, and 2014–2016. The timing of these surges was similar, with a cycle of 19–20 years, an active phase of 3–4 years, and a quiescent phase of 16–17 years. During the quiescent phase, a large amount of ice accumulates in the lower part of the accumulation zone, and the terminal of the tongue thins significantly. According to the most recent surge event (2014–2016), glacier flow accelerated suddenly in the active phase and reached a maximum velocity of 2 ± 0.08 m d−1. Then, the glacier terminal thickened sharply, the reservoir zone thinned by 12 ± 0.2 m, and the terminal receiving zone thickened by 28 ± 0.2 m. The glacier may have entered a quiescent phase after July 2016. The glacier surge causes a large amount of material to transfer from upstream to downstream, forming an ice dam and creating conditions for a glacial lake outburst flood (GLOF). At the termination of the active phase, the subglacial drainage channel became effective, triggering the GLOF. For a period of the quiescent phase, the glacier ablation intensifies and the GLOF repeats constantly. One surge caused 7–8 GLOFs, and then a continuous reduction in the ice dam elevation. Eventually, the ice dam disappeared, and the GLOF no longer continued before the next glacier-surging event.

Study of dynamics in surface ice flow rate of glaciers in Hunza basin, Karakoram.

Glaciers in the Karakoram region are widely recognized for their historical surging phenomenon. Accurate field-based glacier monitoring is challenging in the Karakoram due to the presence of mixed-nature glaciers that are advancing, receding, and surging. Many geographers came to the opinion that surging is a thermally controlled activity in the Karakoram as opposed to a hydrologically controlled activity as a result of characteristics including high-altitude warmth, precipitation, and accumulation patterns of these glaciers. But the main surge mechanism is still a mystery. The current study used Landsat multispectral satellite datasets to examine and investigate the glaciers' vulnerability to surging activity in the Hunza basin based on the annual surface ice flow rate and frontal snout advancement of the glaciers from 1990 to 2021. Around 80 glaciers in the Hunza basin have been researched, and based on interannual surface flow rates, it has been determined that Batura, Hassanabad II, Barpu, Gharesa, Hispar, Khurdopin, Minapin, Virjerab, Yazgil, and Ghulkin glaciers are more vulnerable to surging. The findings show that during the research period, these glaciers had surged and advanced along their snouts. The frontal snout of these glaciers advances, and moraines are deposited closer to the glacier terminus as a consequence of active surge points over the ablation region. The Hunza basin's topography, precipitation, and thermal regimes regulate the glaciers' surging phenomena causing successive acceleration in the glaciers. Field-based measurements made with a differential global positioning system are used to corroborate the obtained results.

Seasonal Variability of Snow/Ice Facies Using Four Years of RISAT-1 MRS Data Over Glaciers in Himalayan–Karakoram Region

Seasonal Variability of Snow/Ice Facies Using Four Years of RISAT-1 MRS Data Over Glaciers in Himalayan–Karakoram Region

Hydrological and dynamical response of glaciers to climate change based on their dimensions in the Hunza Basin, Karakoram

Glaciers of different dimensions respond differently to climate change, resulting in variations in glacier dynamics and runoff. Differentiation of these responses is critical for the Karakoram region (in context to Karakoram anomalies) where glaciers contribute significantly to runoff. Herein, the Open Global Glacier Model is used to quantify these variabilities in the Hunza basin, and thereby develop a comprehensive understanding of how glaciers respond to past and future climate change. Basin glaciers were classified into six classes based on their terminus elevation and area (Z1-Z6). Annual mass balance (MB) time series were reconstructed from 1960 to 2019. The results indicate that the average MB is −0.09 ± 0.21 m w.e.a−1, which has been accelerated in 2000 s (average: −0.16 ± 0.20 m w.e.a−1). Cumulative MB between classes varies from −4.55 m w.e. (Z1) to −5.92 m w.e. (Z3), indicating that the medium classes (Z3, Z4) glaciers MB is comparatively more negative. Monthly glacier runoff explains the sensitivity of small glaciers to summer temperature, as they only contribute to runoff in the summer season. However, glacier runoff per unit area per year remains almost the same across these groups. Future climate change scenarios under CMIP6 illustrate that small (Z5/Z6) and large (Z1) glaciers will lose up to 90 % and 10 % of their volume, area, and length, respectively. The results identified that basin glacier runoff will increase till the year 2060 and will start decreasing after that to 2100. Projected glacier runoff suggests that the Basin runoff is mediated by Z4 glaciers. Whereas, the peak water supply from small size glaciers has occurred in past (Z6) or would occur in near future (Z5) while large size glaciers (Z1-Z3) runoff keeps on increasing till 2100. These findings indicate that immediate mitigation measures are required to deal with glacier change and ensure long-term water security in this region.

The Karakoram Anomaly: Validation through Remote Sensing Data, Prospects and Implications

Millions of people rely on river water originating from snow- and ice-melt from basins in the Hindukush-Karakoram-Himalayas (HKH). One such basin is the Upper Indus Basin (UIB), where the snow- and ice-melt contribution can be more than 80%. Being the origin of some of the world’s largest alpine glaciers, this basin could be highly susceptible to global warming and climate change. Field observations and geodetic measurements suggest that in the Karakoram Mountains, glaciers are either stable or have expanded since 1990, in sharp contrast to glacier retreats that are prevalently observed in the Himalayas and adjoining high-altitude terrains of Central Asia. Decreased summer temperature and discharge in the rivers originating from this region are cited as supporting evidence for this somewhat anomalous phenomenon. This study used remote sensing data during the summer months (July–September) for the period 2000 to 2017. Equilibrium line altitudes (ELAs) for July, August and September have been estimated. ELA trends for July and September were found statistically insignificant. The August ELA declined by 128 m during 2000–2017 at a rate of 7.1 m/year, testifying to the Karakoram Anomaly concomitant with stable to mass gaining glaciers in the Hunza Basin (western Karakoram). Stable glaciers may store fresh water for longer and provide sustainable river water flows in the near to far future. However, these glaciers are also causing low flows of the river during summer months. The Tarbela reservoir reached three times its lowest storage level during June 2019, and it was argued this was due to the low melt of glaciers in the Karakoram region. Therefore, using remote sensing data to monitor the glaciers’ health concomitant with sustainable water resources development and management in the HKH region is urgently needed.

Hydrometeorological progression of the Himalayan cryosphere: The Karakoram predicament

• Formulation of AI for glaciers using snowfall, snowmelt and temperature trends. • AI-based sorting of glacier-negative (losing mass) and glacier-positive (gaining mass). • Meteorological, stable isotope and geomorphic proof for glacier-positive behaviour in Karakoram. • Investigation of glacier-positive behaviour outside of the Karakoram region. • Linking AI to Himalayan precipitation periodicity via IOD, ISM and MLW connectivity. The anomalous behaviour of the Karakoram glaciers has been a decade-long discussion. While a lot of effort has been given to understanding this phenomenon, little has been explored with respect to the factors that govern glacier accumulation rates. We performed a time-series analysis of 17 Himalayan glaciers to evaluate the Accumulation Index (AI), examine the ice accumulation/ablation balance of each glacier, and investigate the natural periodicities in regional climatic behaviour. Based on the AI, the Himalayan glaciers have been characterised as ‘glacier-positive’ and ‘glacier-negative’. Glacier-positive behaviour in the Karakoram is favoured by global meteorological and local topographical factors. Analysis of 120 years of meteorological data shows a significant positive trend in winter and annual precipitation in the northwestern Himalayas, linked to surfacial warming and the Indian Ocean Dipole, while local factors such as slope, aspect and supraglacial debris constrain summer ablation. Additionally, the Karakoram precipitation is periodic in nature, demonstrating anti-correlation with decadal-scale precipitation records from the remaining Himalayan glaciers. Both local and global factors explain the anomaly in the Karakoram or the lack of it in other Himalayan glaciers. In a potentially warming planet, glacial accumulation rates are becoming increasingly sensitive to ambient temperatures, where glacier mass budget turns sharply negative at temperatures above 263 K due to accelerated summer ablation which overcompensates wintertime accumulation. This makes the Karakoram more sensitive to global meteorology than local factors. Therefore, it is important to address whether the Karakoram anomaly is an isolated climatic event or will it succumb to global climate change like the remainder of the Himalayan glaciers.

Trend of snow cover under the influence of climate change using Google Earth Engine platform: A case study of Astore (Western Himalayas) and Shigar (Karakoram region)

Freshwater resources present in the Upper Indus Basin (UIB) supply water to Pakistan’s irrigation. Half of the annual water discharge in the UIB is contributed from the glacier and snow-fed basins in the Hindu Kush, Karakoram, and Himalaya (HKH) region, and it is currently under the threat of climate change. Therefore, it is very necessary to study and monitor the spatiotemporal changes in the snow cover area (SCA) and its response to climate variables to efficiently manage water reservoirs. Thus, keeping this problem in mind, we conducted this study using the Google Earth Engine Application Programming Interface (GEE API) for Astore and Shigar. We used mean annual Landsat data between 1991 and 2021 to derive the SCA using the normalized difference snow index (NDSI). ASTER GDEM data was used to extract the elevation and analyze the distribution of SCA on different elevation zones. Eventually, we used the climate research unit (CRU) data (rainfall and temperature) to analyze them with SCA. The results revealed that SCA in Astore and Shigar has an increasing trend with a rate of 11.16 km2/year and 4.27 km2/year, respectively. Mean annual precipitation and temperature also confirmed the increasing trend of SCA because mean annual precipitation is increasing and temperature is decreasing in both regions. SCA and elevation analysis revealed that SCA is decreasing on foothills while increasing at the valley top. This is because temperature is increasing and precipitation is decreasing from zone 1 to zone 3 and vice versa for zone 4. It is found that Astore and Shigar in UIB have an increasing trend of SCA and are not affected by global warming. Therefore, it is necessary to conduct studies on large scale to efficiently evaluate the impact of climate change on SCA.

Impact of Climate Change on Spatio-Temporal Distribution of Glaciers in Western Karakoram Region since 1990: A Case Study of Central Karakoram National Park

Glaciers in the Upper Indus Basin (UIB) in Pakistan are the major source of water, irrigation, and power production for downstream regions. Global warming has induced a substantial impact on these glaciers. In the present study, Landsat images were utilized to evaluate the glaciers for the period from 1990–2020 in the Central Karakoram National Park (CKNP) region to further correlate with climate parameters. The results reveal that glaciers are retreating and the highest (2.33 km2) and lowest (0.18 km2) recession rates were observed for Biafo and Khurdopin glaciers, respectively. However, a minor advancement has also been observed for the period from 1990–2001. More than 80% of glacier recession was recorded between 2009–2020 because mean summer temperature increased at both Skardu and Gilgit meteorological stations, while precipitation decreased at both stations from 2005–2020. The increase in mean summer temperature and decrease in winter precipitation resulted in glacial retreat, which will lead to water scarcity in the future as well as affect the agriculture sector and hydropower production in downstream areas of the Indus River basin.

Large-Scale Monitoring of Glacier Surges by Integrating High-Temporal- and -Spatial-Resolution Satellite Observations: A Case Study in the Karakoram

Glacier surges have been increasingly reported from the mountain and high-latitude cryosphere. They represent active glaciological processes that affect the evolution of natural landscapes, and they possibly lead to catastrophic consequences, such as ice collapse, which threatens the downstream communities. Identifying and monitoring surge-type glaciers has been challenging due to the irregularity of the behavior and limitations on the spatiotemporal coverage of remote-sensing observations. With a focus on the Karakoram region, with concentrated surge-type glaciers, we present a new method to efficiently detect glacier-surging activities by integrating the high temporal resolution of MODIS imagery and the long-term archived medium spatial resolution of Landsat imagery. This method first detects the location and initial time of glacier surges by trend analysis (trend and breakpoint) from MODIS data, which is implemented by the Breaks for Additive Seasonal and Trend (BFAST) tool. The initial location and time information is then validated with the detailed surging features, such as the terminus-position changes from Landsat, and the thickness-change patterns from surface-elevation-change maps. Our method identified 74 surging events during 2000–2020 in the Karakoram, including three tributary-glacier surges, and seven newly detected surge-type glaciers. The surge-type glaciers tend to have longer lengths and smaller mean slopes compared with nonsurge-type glaciers. A comparison with previous studies demonstrated the method efficiency for detecting the surging of large-scale and mesoscale glaciers, with limitations on small and narrow glaciers due to the spatial-resolution limitation of MODIS images. For the 38 surge-type nondebris-covered glaciers, we provide details of the surging, which depict the high variability (heavy-tailed distribution) in the surging parameters in the region, and the concentration of the surge initiation during 2008–2010 and 2013–2015. The updated glacier-surging information solidifies the basis for a further investigation of the surging processes at polythermal glaciers, and for an improved assessment of the glacier-mass balance and monitoring of glacier hazards.

Ice thickness and morphological analysis reveal the future glacial lake distribution and formation probability in the Tibetan Plateau and its surroundings

Owing to intense glacial retreat and melting, it is anticipated that numerous glacial lakes will be formed in the next few decades. However, their development and distribution patterns in the Tibetan Plateau and its surroundings still need to be elucidated. In this study, a published glacier ice thickness distribution dataset was employed to fully detect overdeepened glacier beds as potential glacial lakes. We selected and expanded four morphological metrics to determine the formation probability of potential glacial lakes: surface slope, break in slope, lake area, and position on the glacier. The results revealed that 15,826 potential glacial lakes with areas >0.02 km 2 exist in the Tibetan Plateau and its surroundings, covering an area of 2253.95 ± 1291.29 km 2 with a water volume of 60.49 ± 28.94 km 3 that would contribute to an equivalent sea level rise of 0.16 ± 0.08 mm. The experimental comparison and uncertainty assessment for the overdeepening processing showed that the different extraction methods and basic digital elevation models used could lead to non-negligible errors in the results (at least ±30%), which were ignored in previous studies, contributing to major divergences between the several current inventories of potential glacial lakes in the plateau. Notably, approximately 90% of the total area of the potential glacial lakes is concentrated in the lower half of the individual glaciers in the Tibetan Plateau and its surroundings. >70% of the potential glacial lakes and contemporary glacial lakes in this region were found to be concentrated within the 4000–5800 m elevation range. Moreover, the study identified 5361 potential glacial lakes with high or very high exposure probabilities, and their distribution was mostly determined by regional glacier resources. However, the numbers and sizes of some potential glacial lakes that are found in the Karakoram region are considered to be exaggerated because of the presence of numerous surge-type glaciers, which have not been discussed in previous studies. These results can improve our understanding of future glacial lake formation and distribution in the Tibetan Plateau and its surroundings and have implications for further implementation of effective prevention, mitigation, and adaptation measures for glacial lake outburst floods and water security. • 15,826 PGLs with areas >0.02 km 2 exist in the Tibetan Plateau and its surroundings, covering an area of 2253.95 ± 1291.29 km 2 with a water volume of 60.49 ± 28.94 km 3 . • Approximately 90% of the total area of the Potential Glacial Lakes is concentrated in the lower half of the individual glaciers in the Tibetan Plateau and its surroundings. • The number and size of some Potential Glacial Lakes found in the Karakoram region are considered exaggerated because of the presence of numerous surge-type glaciers.

ASSESSMENT OF GLACIER MASS BALANCE IN THE HIMALAYAN-KARAKORAM REGION

Mountain glaciers are susceptible to climate change. Most high-elevation glaciers, including the Himalayan glaciers, have been receding at an unprecedented rate in recent decades. Moreover, most mountain glaciers are found in the Himalayan areas, but field sampling and research efforts are limited due to logistical and financial constraints. From 1997 to 1999, just 6.8 km² of the 33,000 km² were examined in the Himalayan region. Previous studies indicated that Himalayan glaciers have been melting at an alarming rate over the past few decades. The objective of this paper is to review glacier changes, with an emphasis on mass balance changes in the Himalayan-Karakoram ranges, using 15 ISI journal articles published between 2008 and 2017. The acquired data on glacier mass balance was used to create a glacier mass balance change map for quantification using ArcGIS software and Landsat map as base map. The majority of the glaciers in the study area melted at various rates, with the most extensive glacier loss occurring in the west Himalayan highlands and the lowest occurring in the Karakoram region. Therefore, additional scientific research have to be conducted, and significant actions have to be taken at many different levels to prevent the continued loss of glaciers in this area.

Climate change and spatio-temporal trend analysis of climate extremes in the homogeneous climatic zones of Pakistan during 1962-2019.

Climate extremes, such as heat waves, droughts, extreme rainfall can lead to harvest failures, flooding and consequently threaten the food security worldwide. Improving our understanding about climate extremes can mitigate the worst impacts of climate change and extremes. The objective here is to investigate the changes in climate and climate extremes by considering two time slices (i.e., 1962–1990 and 1991–2019) in all climate zones of Pakistan by utilizing observed data from 54 meteorological stations. Different statistical methods and techniques were applied on observed station data to assess changes in temperature, precipitation and spatio-temporal trends of climatic extremes over Pakistan from 1962 to 2019. The Mann-Kendal test demonstrated increasing precipitation (DJF) and decreasing maximum and minimum temperatures (JJA) at the meteorological stations located in the Karakoram region during 1962–1990. The decadal analysis, on the other hand, showed a decrease in precipitation during 1991–2019 and an increase in temperature (maximum and minimum) during 2010–2019, which is consistent with the recently observed slight mass loss of glaciers related to the Karakoram Anomaly. These changes are highly significant at 5% level of significance at most of the stations. In case of temperature extremes, summer days (SU25) increased except in zone 4, TX10p (cold days) decreased across the country during 1962–1990, except for zones 1 and 2. TX90p (warm days) increased between 1991–2019, with the exception of zone 5, and decreased during 1962–1990, with the exception of zones 2 and 5. The spatio-temporal trend of consecutive dry days (CDD) indicated a rising tendency from 1991 to 2019, with the exception of zone 4, which showed a decreasing trend. PRCPTOT (annual total wet-day precipitation), R10 (number of heavy precipitation days), R20 (number of very heavy precipitation days), and R25mm (very heavy precipitation days) increased (decreased) considerably in the North Pakistan during 1962–1990 (1991–2019). The findings of this study can help to address some of the sustainable development goals related climate action, hunger and environment. In addition, the findings can help in developing sustainable adaptation and mitigation strategies against climate change and extremes. As the climate and extremes conditions are not the uniform in all climate zone, therefore, it is suggested to the formers and agriculture department to harvest crops resilient to the climatic condition of each zone. Temperature has increasing trend in the northern Pakistan, therefore, the concerned stakeholders need to make rational plans for higher river flow/flood situation due to snow and glacier melt.