Search Results (25)

Mountain regions are particularly sensitive and vulnerable to the impacts of climate change. Over the past three decades, mountain temperatures have risen significantly faster than those in lowland areas. The Hindu Kush–Karakoram–Himalaya region, often referred to as the “water tower of Asia”, is the largest freshwater source outside the polar regions. However, it is currently undergoing cryospheric degradation as a result of climatic change. In this study, the Normalized Difference Glacier Index (NDGI) was calculated using Landsat and Sentinel satellite images. The results revealed that glaciers in Chitral, located in the Eastern Hindu Kush Mountains of Pakistan, lost 816 km² (31%) of their total area between 1992 and 2022. On average, 27 km² of glacier area was lost annually, with recession accelerating between 1997 and 2002 and again after 2007. Satellite analyses also indicated a significant increase in both maximum (+7.3 °C) and minimum (+3.6 °C) land surface temperatures between 1992 and 2022. Climate data analyses using the Mann–Kendall test, Theil–Sen Slope method, and the Autoregressive Integrated Moving Average (ARIMA) model showed a clear increase in air temperatures from 1967 to 2022, particularly during the summer months (June, July, and August). This warming trend is expected to continue until at least 2042. Over the same period, annual precipitation decreased, primarily due to reduced snowfall in winter. However, rainfall may have slightly increased during the summer months, further accelerating glacial melting. Additionally, the snowmelt season began consistently earlier. While initial glacier melting may temporarily boost water resources, it also poses risks to communities and economies, particularly through more frequent and larger floods. Over time, the remaining smaller glaciers will contribute only a fraction of the former runoff, leading to potential water stress. As such, monitoring glaciers, climate change, and runoff patterns is critical for sustainable water management and strengthening resilience in the region. Full article

This study examines adaptation strategies to mitigate the risks posed by Glacial Lake Outburst Floods (GLOFs) in the Hindu Kush Himalayan (HKH) region, encompassing Pakistan, India, Nepal, Bhutan, and Afghanistan. GLOFs occur when water is suddenly released from glacial lakes and they present significant threats to communities, infrastructure, and ecosystems in high-altitude regions, particularly as climate change intensifies their frequencies and severity. While there are many studies on the changes in glacial lakes, studies on adaptation to GLOF risks are scant. Also, these studies tend to focus on case-specific scenarios, leaving a gap in comprehensive, region-wide analyses. This review article aims to fill that gap by synthesizing the adaptation strategies adopted across the HKH region. We conducted a literature review following several inclusion and exclusion criteria and reviewed 23 scholarly sources on GLOF adaptation. We qualitatively synthesized the data and categorized the adaptation strategies into two main types: structural and non-structural. Structural measures include engineering solutions such as lake-level control, channel modifications, and flood defense infrastructure, designed to reduce the physical damage caused by GLOFs. Non-structural measures include community-based practices, economic diversification, awareness programs, and improvements in institutional governance, addressing social and economic vulnerabilities. We found that Afghanistan remains underrepresented in GLOF-related studies, with only one article that specifically focuses on GLOFs, while Nepal and Pakistan receive greater attention in research. The findings underscore the need for a holistic, context-specific approach that integrates both structural and non-structural measures to enhance resilience across the HKH region. Policy-makers should prioritize the development of sustainable mechanisms to support long-term adaptation efforts, foster cross-border collaborations for data sharing and coordinated risk management, and ensure that adaptation strategies are inclusive of vulnerable communities. Practitioners should focus on strengthening early warning systems, expanding community-based adaptation initiatives, and integrating traditional knowledge with modern scientific approaches to enhance local resilience. By adopting a collaborative and regionally coordinated approach, stakeholders can improve GLOF risk preparedness, mitigate socioeconomic impacts, and build long-term resilience in South Asia’s high-altitude regions. Full article

Afghanistan is located on the Eurasian tectonic plate’s edge, a highly seismically active region. It is bordered by the northern boundary of the Indian plate and influenced by the collisional Arabian plate to the south. The Hindu Kush and Pamir Mountains in Afghanistan are part of the western extension of the Himalayan orogeny and have been uplifted and sheared by the convergence of the Indian and Eurasian plates. These tectonic activities have generated numerous active deep faults across the Hindu Kush–Himalayan region, many of which intersect Afghanistan, resulting in frequent high-magnitude earthquakes. This tectonic interaction produces ground shaking of varying intensity, from high to moderate and low, with the epicenters often located in the northeast and extending southwest across the country. This study maps Afghanistan’s tectonic structures, identifying the most active geological faults and regions with heightened seismicity. Historical earthquake data were reviewed, and recent destructive events were incorporated into the national earthquake dataset to improve disaster management strategies. Additionally, the study addresses earthquake hazards related to building and infrastructure design, offering potential solutions and directions to mitigate risks to life and property. Full article

Investigating the changes in snow cover caused by climate change is extremely important and has attracted increasing attention in cryosphere and climate research. Optimal remote sensing-based snow datasets can provide long-term daily and global spatial-temporal snow-cover distribution at regional and global scales. However, the application of these snow-cover products is inevitably limited because of the space–time discontinuities caused by cloud obscuration, which poses a significant challenge in snowpack-related studies, especially in High Mountain Asia (HMA), an area that has high-elevation mountains, complex terrain, and harsh environments and has fewer observation stations. To address this issue, we developed an improved five-step hybrid cloud removal strategy by integrating the daily merged snow-cover probability (SCP) algorithm, eight-day merged SCP algorithm, decision tree algorithm, temporal downscaling algorithm, and optimal threshold segmentation algorithm to produce a 21-year, daily cloud-free snow-cover dataset using two daily MODIS snow-cover products over the HMA. The accuracy assessment demonstrated that the newly developed cloud-free snow-cover product achieved a mean overall accuracy of 93.80%, based on daily classified snow depth observations from 86 meteorological stations over 10 years. The time series of the daily percentage of binary snow-cover over HMA was analyzed during this period, indicating that the maximum snow cover tended to change more dramatically than the minimum snow cover. The annual snow-cover duration (SCD) experienced an insignificantly increasing trend over most of the northeastern and southwestern HMA (e.g., Qilian, eastern Kun Lun, the east of Inner Tibet, the western Himalayas, the central Himalayas, and the Hindu Kush) and an insignificant declining trend over most of the northwestern and southeastern HMA (e.g., the eastern Himalayas, Hengduan, the west of Inner Tibet, Pamir, Hissar Alay, and Tien). This new high-quality snow-cover dataset will promote studies on climate systems, hydrological modeling, and water resource management in this remote and cold region. Full article

Water is the basis for human survival and growth, and it holds great importance for ecological and environmental protection. The Hindu Kush Himalaya (HKH) is known as the “Water Tower of Asia”, where water influences changes in the global water cycle and ecosystem. It is thus very important to efficiently measure the status of water in this region and to monitor its changes; with the development of satellite-borne sensors, water surface extraction based on remote sensing images has become an important method through which to do so, and one of the most advanced and accurate methods for water surface extraction involves the use of deep learning networks. We designed a network based on the state-of-the-art Vision Transformer to automatically extract the water surface in the HKH region; however, in this region, terrain shadows are often misclassified as water surfaces during extraction due to their spectral similarity. Therefore, we adjusted the training dataset in different ways to improve the accuracy of water surface extraction and explored whether these methods help to reduce the interference of terrain shadows. Our experimental results show that, based on the designed network, adding terrain shadow samples can significantly enhance the accuracy of water surface extraction in high mountainous areas, such as the HKH region, while adding terrain data does not reduce the interference from terrain shadows. We obtained the water surface extraction results in the HKH region in 2021, with the network and training datasets containing both water surface and terrain shadows. By comparing these results with the data products of Global Surface Water, it was shown that our water surface extraction results are highly accurate and the extracted water surface boundaries are finer, which strongly confirmed the applicability and advantages of the proposed water surface extraction approach in a wide range of complex surface environments. Full article

The El Nino Southern Oscillation (ENSO) phenomenon is devastating as it negatively impacts global climatic conditions, which can cause extreme events, including floods and droughts, which are harmful to the region’s economy. Pakistan is also considered one of the climate change hotspot regions in the world. Therefore, the present study investigates the effect of the ENSO on extreme precipitation events across the Upper Indus Basin. We examined the connections between 11 extreme precipitation indices (EPIs) and two ENSO indicators, the Southern Oscillation Index (SOI) and the Oceanic Niño Index (ONI). This analysis covers both annual and seasonal scales and spans the period from 1971 to 2019. Statistical tests (i.e., Mann–Kendall (MK) and Innovative Trend Analysis (ITA)) were used to observe the variations in the EPIs. The results revealed that the number of Consecutive Dry Days (CDDs) is increasing more than Consecutive Wet Days (CWDs); overall, the EPIs exhibited increasing trends, except for the Rx1 (max. 1-day precipitation) and Rx5 (max. 5-day precipitation) indices. The ENSO indicator ONI is a temperature-related ENSO index. The results further showed that the CDD value has a significant positive correlation with the SOI for most of the UIB (Upper Indus Basin) region, whereas for the CWD value, high elevated stations gave a positive relationship. A significant negative relationship was observed for the lower portion of the UIB. The Rx1 and Rx5 indices were observed to have a negative relationship with the SOI, indicating that El Nino causes heavy rainfall. The R95p (very wet days) and R99p (extreme wet days) indices were observed to have significant negative trends in most of the UIB. In contrast, high elevated stations depicted a significant positive relationship that indicates they are affected by La Nina conditions. The PRCPTOT index exhibited a negative relationship with the SOI, revealing that the El Nino phase causes wet conditions in the UIB. The ONI gave a significant positive relationship for the UIB region, reinforcing the idea that both indices exhibit more precipitation during El Nino. The above observations imply that while policies are being developed to cope with climate change impacts, the effects of the ENSO should also be considered. Full article

Ticks of the genus Dermacentor Koch, 1844 (Acari: Ixodidae) are poorly known systematically due to their habitation in harsh topographic environments and high mountains. Dermacentor ticks are diversely distributed in the Palearctic, Nearctic, and Oriental regions. There is no available information on the occurrence of Dermacentor marginatus in Pakistan; thus, the current investigation aimed the first morphological and molecular confirmation of this species and associated Anaplasma marginale and Rickettsia raoultii. Ticks were collected from goats (Capra hircus) and morphologically identified. Genomic DNA was extracted from 18/26 (69.23%) tick specimens, including 11 males and 7 females (1 unfed and 6 fed females). Extracted DNA was subjected to PCR for the amplification of genetic markers like 16S rDNA and cox1 for ticks, 16S rDNA for Anaplasma spp., and gltA and ompB for Rickettsia spp. A total of 26 D. marginatus ticks composed of 19 males (73.07%) and 7 females (26.9%) [1 (3.84%) unfed and 6 (23.07%) fed females] were collected from goats. According to amplicons via BLAST analysis, the 16S rDNA sequence showed 97.28–98.85% identity and the cox1 sequence showed 95.82–98.03% identity with D. marginatus. Additionally, the 16S rDNA sequence for Anaplasma sp. was detected in D. marginatus that showed 100% identity with Anaplasma marginale. Rickettsial gltA and ompB sequences for Rickettsia sp. showed 100% identity with Rickettsia raoultii. In phylogenetic analysis, ticks’ 16S rDNA and cox1 sequences clustered with the same species. In phylogenetic analysis, A. marginale based on 16 rDNA clustered with A. marginale, while gltA and ompB sequences clustered with R. raoultii. This is the first study on the genetic characterization of D. marginatus and associated A. marginale and R. raoultii in Pakistan. The northern areas of Pakistan, which need to be explored in terms of ticks and associated pathogens due to their zoonotic threats, have been neglected due to the inaccessible climatic conditions. Full article

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. Full article

As a major human activity, urbanization exerts a strong impact on the fragile ecosystem in the Hindu Kush Himalayas (HKH) region. To maintain sustainable development, reliable data on urban land change are required to assess the impact of urbanization. Here, the reliability evaluation of four global fine-resolution impervious surface area (ISA) products: global annual impervious area (GAIA), global annual urban dynamics (GAUD), global impervious surface area (GISA), and global urban expansion (GUE) was carried out. The characteristics of urban expansion for five representative cities including Kabul, Lhasa, Lijiang, Thimphu, and Xining were remarkably different. Based on the results of incremental analysis and the spatial difference of the ISA, it was found that the GAIA dataset at a 30-m spatial resolution could provide better ISA information than the others in characterizing urban expansion in the mountainous region. Subsequently, the changes in the urban area were analyzed using the GAIA dataset from 1993 to 2018. In general, human settlements had grown, with the transformation of small villages into larger towns and some towns into major cities. Urban expansion would continuously intensify the contradictions between human activity and sustainability and exert a more significant impact on the fragile ecosystem in the HKH region. More attention should be paid to the impact of urbanization on the fragile mountainous ecosystem. Full article

Forest cover in the Hindu Kush Himalayan (HKH) mountains of northern Pakistan has changed dramatically due to community dynamics such as population growth, household dynamics, and intensive economic activity for people’s livelihoods. Demographic development is one of the major factors influencing forest cover change in a previously sparsely populated environment. An abrupt upsurge in population exerts adverse effects on the local natural resources, specifically forests. The present research shows an increase in population from 1980 to 2017, the development of human settlements, and a long-term decline in forest cover. This study was conducted in the Palas valley in the HKH mountains using GIS and remote sensing (RS) technology. Analysis of the changes between 1980, 2000, and 2017 was done using ArcGIS and the maximum likelihood algorithm for supervised classification of Landsat MSS TM ETM+ and Sentinel 2A satellite images. We used Euclidean distances and buffer analysis techniques to identify that most changes occurred within 1 to 3 km of the settlement’s proximity in each period. We also found changes in forest cover to be much greater near settlements than elsewhere in the study area. According to the findings of the study, population explosion and other socio-economic factors have imposed excessive pressure on vegetation cover, resulting in the loss of 17,076 ha of forests in the remote Palas valley. Full article

The loess in the arid area of Xinjiang is located at the eastern end of the Central Asia Loess Belt, and paleoclimate research about it is of great importance for understanding the mechanism of interaction of the Eurasian Westerly monsoon system and the aridity of Central Asia. This review focuses on recent progress concerning the spatial distribution, material composition and provenance of loess in Xinjiang and points out the shortcomings of and challenges to provenance and dust circulation. Field investigation and previous studies indicate that loess sediments have been mainly distributed on the river terraces and windward piedmont of the Tianshan Mountains and the Kunlun Mountains since the late Pliocene (mainly late Pleistocene). Grain size and age data show that Xinjiang loess deposits at some locations are rapid and discontinuous or sedimentary hiatus. The Siberian High system largely controlled dust mobilization and loess accumulation in northern Xinjiang but not southern Xinjiang. In southern Central Asia, the intensity of dust activity may be determined by the Caspian Sea–Hindu Kush Index (CasHKI) and local circulation. However, there is not enough evidence that the CasHKI index can affect the Tarim Basin area. Consequently, ascertaining the driving mechanism of mid-latitude Westerly winds and the dynamic process of loess deposition in Xinjiang is a specific suggestion for critical future research. Many indicators have shown that the loess dust sources in Xinjiang are composed of mainly proximal materials plus some remote materials. Alluvial plains and local proluvial fans contributed more to loess deposition, while Central Asian deserts comprise a small proportion of loess deposition in northern Xinjiang. In future provenance research, new technologies and new methods should be continuously tested to facilitate an objective understanding of the provenance of the loess in Xinjiang. Full article

Glaciers are sensitive indicators of climate change and have a significant influence on regional water cycle, human survival and social development. Global warming has led to great changes in glaciers over the High Mountain Asia (HMA) region. Glacier elevation change is a measure of glacier mass balance driven by the processes of energy and mass exchange between the glacier surface and the atmosphere which are influenced by climatic factors and glacier surface properties. In this study, we estimated the inter-annual and intra-annual elevation changes of glaciers in the HMA region in 2003–2020 using Ice, Cloud and land Elevation Satellite (ICESat) data and Shuttle Radar Terrain Mission (SRTM) digital elevation model (DEM) data by developing an “elevation-aspect bin analysis method” that considered the difference of glacier elevation changes in different elevations and aspects of glacier topography. The results showed that: (1) The inter-annual change of glacier elevation in 2003–2020 had large spatial heterogeneity. Glacier elevation reduction mainly occurred in the marginal region of the HMA with the maximum decline in the Nyainqentanglha region, while glacier elevation showed increase in the West Kunlun of inner HMA regions in 2003–2020. The glacier elevation change rate showed an accelerating reduction trend in most of the HMA regions, except in the west HMA where the glacier elevation reduction rate showed slowdown tendency. Specifically, the glacier elevation change rate in the entire HMA was −0.21 ± 0.12 m/year in 2003–2008 and −0.26 ± 0.11 m/year in 2003–2020, respectively. (2) The intra-annual change of HMA glacier elevation in 2019 and 2020 showed obvious spatiotemporal heterogeneity, and the glacier thickening period was gradually delayed from the marginal area to the inner area of the HMA. The glaciers in the western marginal part of the HMA (the Tienshan Mountains, Pamir and Hindu Kush and Spiti Lahaul) and Karakoram thickened in winter or spring, the glaciers in the Nyainqentanglha Mountains exhibited spring accumulation. The glaciers in West Kunlun accumulated in two time periods, i.e., from March to June and from July to September. The glaciers in the Inner Tibetan Plateau and Bhutan and Nepal areas experienced spring or summer accumulation, especially in June or July. Moreover, we found that the inter-annual and intra-annual change of glacier elevation could be explained by the changes in temperature and precipitation. A similar analysis can be extended to mountain glaciers in other regions of the world, and glacier change trends could be further explored over a longer time span with the continuous operation of ICESat-2. Full article

The Himalayan, Karakoram, and Hindu Kush (HKH-TMHA) are the three main mountain ranges in the high-mountain Asia region, covering the China–Pakistan Economic Corridor (CPEC). In this study, we identified glacial lakes in the HKH-TMHA region based on multitemporal Landsat images taken from 1990 to 2020. We analyzed the spatial distribution and evolution of glacial lakes in the HKH-TMHA region from the perspective of their elevation, size, and terrain aspect; then, we described their temporal changes. The results showed that approximately 84.56% of the glacial lakes (84.1% of the total lake area) were located at elevations between 4000 m and 5500 m, and glacial lakes with areas ranging from 0.01–0.5 km² accounted for approximately 95.21% of the number and 63.01% of the total area of glacial lakes. The number (38.64%) and area (58.83%) of south-facing glacial lakes were largest in HKH-TMHA and expanded significantly over time. There were 5835 (664.84 ± 89.72 km²) glacial lakes in 1990; from 1990 to 2020, the number of glacial lakes in the HKH-TMHA region increased by 5974 (408.93 km²) in total; and the annual average increase in the area of glacial lakes reached 13.63 km² (11.15%). In 2020, the total number of glacial lake reached to 9673 (899.66 ± 120.63 km²). In addition, most glacial lakes were located in the Eastern Himalayan, China, and the Indus Basin. Based on the precipitation and temperature analyses performed in our study area, we found inconsistent climate characteristics and changes in the three mountain ranges. In general, the daily precipitation (temperature) increased by 1.0766 mm (1.0311 °C), 0.8544 mm (0.8346 °C), and 0.8245 mm (−0.1042 °C) on the yearly, summer, and winter scales, respectively. Glacial melting and climate change are common contributors to glacial lake expansion. The investigation of glacial lakes in this region can provide basic supporting data for research on glacial lake-related disasters, land cover, and climate change in the high-mountain Asia region. Full article

The Kabul River, while having its origin in Afghanistan, has a primary tributary, the Konar River, which originates in Pakistan and enters Afghanistan near Barikot-Arandu. The Kabul River then re-enters Pakistan near Laalpur, Afghanistan making it a true transboundary river. The catastrophic flood events due to major snowmelt events in the Hindu Kush mountains occur every other year, inundating many major urban centers. This study investigates the flood risk under 30 climate and dam management scenarios to assess opportunities for transboundary water management strategy in the Kabul River Basin (KRB). The Soil and Water Assessment Tool (SWAT) is a watershed-scale hydraulic modeling tool that was employed to forecast peak flows to characterize flood inundation areas using the river flood routing modelling tool Hydrologic Engineering Center—Analysis System -HEC-RAS for the Nowshera region. This study shows how integrated transboundary water management in the KRB can play a vital catalyst role with significant socio-economic benefits for both nations. The study proposes a KRB-specific agreement, where flood risk management is a significant driver that can bring both countries to work together under the Equitable Water Resource Utilization Doctrine to save lives in both Afghanistan and Pakistan. The findings show that flood mitigation relying on collaborative efforts for both upstream and downstream riparian states is highly desirable. Full article

The tribal belt of the Hindu Kush mountains is famous for its unique culture, ethnography, wild food plants, food systems, and traditional knowledge. People in this region gather wild plants and plant parts using them directly or in traditional cuisine, or sell them in local markets. However, there is a huge lack of documentation of the food system, particularly that related to wild food plants (WFP). In the current study, we focus on the uses and contributions of WFPs in the traditional tribal food system of the Hindu Kush valleys along the Pakistan–Afghanistan border. Ethnobotanical data were gathered through questionnaire surveys of 84 informants, including 69 men and 15 women, belonging to 21 different villages of the chosen area. In tribal societies men and women rarely mix and thus very few women took part in the surveys. We documented 63 WFP species belonging to 34 botanical families, of which 27 were used as vegetables, 24 as fruits, six in different kinds of chutneys (starters), and six as fresh food species. Fruits were the most used part (41%), followed by leaves (24%), aerial parts (24%), seeds (7%), stems (3%), and young inflorescences (1%). The reported uses of Carthamus oxyacantha, Pinus roxburghii seeds, and Marsilea quadrifolia leaves are novel for the gastronomy of Pakistan. The results reveal that WFPs provide a significant contribution to local food systems and play a role in addressing human nutritional needs, which are usually not met through farming practices. The tribal peoples of the Hindu Kush use WFPs for their nutritional value, but also as a cultural practice—an inseparable component of the tribal community’s lifestyle. This important traditional knowledge about the gathering and consumption of WFPs, however, is eroding at an alarming rate among younger generations due to the introduction of fast-food, modernization, and globalization. Therefore, appropriate strategies are imperative not only to safeguard traditional plants and food knowledge and practices, as well as the cultural heritage attached to them, but also to foster food security and thus public healthcare via local wild foods in the region. Full article