A Framework to Identify Rock Glaciers and Model Mountain Permafrost in the Jhelum Basin, Kashmir Himalaya, India

Abstract

Deglaciation has led to the transformation of glaciers into rock glaciers in various mountainous regions worldwide. However, the science of permafrost and rock glaciers remains under‐researched in the Himalayan region. This study presents a detailed inventory, dynamics, and permafrost distribution map for the Jhelum basin in the Kashmir Himalaya. The Permafrost Zonation Map (PZM) is created using a Logistic Regression Model based on topographic and climatic variables. High‐resolution satellite images are used to identify rock glaciers as visual indicators. Active and relic rock glaciers are classified based on surface topography and geomorphology. Results reveal 207 rock glaciers in the Jhelum basin, covering ∼50 km², with over 100 falling into the active category. The PZM aligns well with the global permafrost zonation index map. Slope, aspect, and elevation of rock glaciers are computed using the ASTER Digital Elevation Model. The average elevations range from 3,700 m to 4,550 m, and the average surface slope ranges from 12° to 26°, with maximum slopes from 25° to 65°. Most rock glaciers are oriented toward the south or southeast. Field investigations confirm that these rock glaciers occur in highly elevated regions with steep slopes. This study provides valuable information on the high areal abundance of permafrost in the Himalayan region and suggests increased risks of thawing permafrost due to climate warming in the future. The findings contribute to the understanding of permafrost and rock glaciers, filling knowledge gaps in the Himalayan context.

Full text

1. Introduction
1.1. Background Information on Rock Glaciers and Permafrost
Glaciated regions around the world have experienced significant deglaciation, leading to the formation of rock
glaciers (Barsch,1996; Bolch etal.,2022). Rock glaciers are unique landforms characterized by the presence of
ice-rich permafrost within their bodies (Chakravarti etal.,2022; Harris etal.,2009). Permafrost refers to ground
that remains at or below 0°C for at least two consecutive years (Haeberli etal.,1993). It plays a crucial role in regu-
lating hydrological processes, slope stability, and carbon storage in mountainous regions (Ali & Pandey,2023;
Jansson etal.,2003). In the context of the Himalayan region, the study of permafrost and rock glaciers is rela-
tively limited compared to the glaciers (Mukherjee etal.,2020). This knowledge gap is particularly concerning
due to the region's vulnerability to the impacts of climate change (Pandey etal.,2022;P.Sharma etal.,2019; R.
Sharma etal.,2019). The Himalaya is home to vast water resources, with glaciers and permafrost contributing
Abstract Deglaciation has led to the transformation of glaciers into rock glaciers in various mountainous
regions worldwide. However, the science of permafrost and rock glaciers remains under-researched in the
Himalayan region. This study presents a detailed inventory, dynamics, and permafrost distribution map for
the Jhelum basin in the Kashmir Himalaya. The Permafrost Zonation Map (PZM) is created using a Logistic
Regression Model based on topographic and climatic variables. High-resolution satellite images are used
to identify rock glaciers as visual indicators. Active and relic rock glaciers are classified based on surface
topography and geomorphology. Results reveal 207 rock glaciers in the Jhelum basin, covering ∼50km
2,
with over 100 falling into the active category. The PZM aligns well with the global permafrost zonation index
map.Slope, aspect, and elevation of rock glaciers are computed using the ASTER Digital Elevation Model.
The average elevations range from 3,700m to 4,550m, and the average surface slope ranges from 12° to 26°,
with maximum slopes from 25° to 65°. Most rock glaciers are oriented toward the south or southeast. Field
investigations confirm that these rock glaciers occur in highly elevated regions with steep slopes. This study
provides valuable information on the high areal abundance of permafrost in the Himalayan region and suggests
increased risks of thawing permafrost due to climate warming in the future. The findings contribute to the
understanding of permafrost and rock glaciers, filling knowledge gaps in the Himalayan context.
Plain Language Summary In this study, we focused on understanding how glaciers turn into rock
glaciers and how permafrost is distributed in the Jhelum basin of the Kashmir Himalaya. We found that many
glaciers in mountainous regions around the world have transformed into rock glaciers due to deglaciation.
However, there is limited research on permafrost and rock glaciers in the Himalayan region. Using satellite
images and on-the-ground investigations, we created a detailed inventory and map of rock glaciers in the
Jhelum basin. We also developed a permafrost distribution map by considering factors like temperature, solar
radiation, and slope aspect. This map helps us understand where permafrost is located in the area. Our findings
revealed that there are 207 rock glaciers in the Jhelum basin, covering an area of approximately 50 square
kilometers. More than 100 of these rock glaciers are active. The map we created aligns well with existing global
permafrost maps, showing the accuracy of our approach. This study enhances our knowledge of permafrost and
rock glaciers in the Himalayan region, providing important information about their presence and the potential
risks associated with thawing permafrost due to climate change.
REMYA ETAL.
© 2023 The Authors. Earth and Space
Science published by Wiley Periodicals
LLC on behalf of American Geophysical
Union.
This is an open access article under
the terms of the Creative Commons
Attribution License, which permits use,
distribution and reproduction in any
medium, provided the original work is
properly cited.
A Framework to Identify Rock Glaciers and Model Mountain
Permafrost in the Jhelum Basin, Kashmir Himalaya, India
S. N. Remya1 , Tirthankar Ghosh2 , Vivek Agarwal3 , Zahid Majeed4, Babu Govindha Raj K5 ,
Aanchal Sharma6, Anil V. Kulkarni6, Muneer Ahmad Mukhtar7, and Rakesh Mishra7
1Amrita School for Sustainable Futures, Amrita Vishwa Vidyapeetham, Amritapuri, India, 2Indian Institute of Technology
Bombay-Monash Research Academy, Bombay, India, 3Northumbria University, Newcastle, UK, 4Geological Survey of India,
Kashmir Office, Srinagar, India, 5Indian Space Research Organisation Headquarters, Bangalore, India, 6Divecha Centre for
Climate Change, Indian Institute of Science, Bangalore, India, 7Geological Survey of India, Lucknow, India
Key Points:
• Study investigates glacier-to-rock
glacier transformation in Jhelum
basin, Kashmir Himalaya due to
deglaciation
• Presents detailed rock glacier
inventory, dynamics, and permafrost
distribution map using satellite images
and field investigations
• Highlights high permafrost abundance
in Himalayan region, indicating
increased thawing risks with climate
warming
Supporting Information:
Supporting Information may be found in
the online version of this article.
Correspondence to:
V. Agarwal,
vivek.agarwal@northumbria.ac.uk
Citation:
Remya, S. N., Ghosh, T., Agarwal, V.,
Majeed, Z., Govindha Raj K, B., Sharma,
A., etal. (2024). A framework to identify
rock glaciers and model mountain
permafrost in the Jhelum Basin, Kashmir
Himalaya, India. Earth and Space
Science, 11, e2023EA003170. https://doi.
org/10.1029/2023EA003170
Received 13 JUL 2023
Accepted 8 DEC 2023
Author Contributions:
Conceptualization: S. N. Remya,
Tirthankar Ghosh, Vivek Agarwal, Zahid
Majeed, Babu Govindha Raj K, Aanchal
Sharma, Anil V. Kulkarni, Muneer
Ahmad Mukhtar, Rakesh Mishra
Data curation: Zahid Majeed, Babu
Govindha Raj K, Aanchal Sharma
Formal analysis: S. N. Remya, Vivek
Agarwal, Anil V. Kulkarni, Rakesh
Mishra
10.1029/2023EA003170
RESEARCH ARTICLE
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significantly to the hydrological systems (Bolch etal., 2012). Understanding the distribution, dynamics, and
characteristics of rock glaciers and permafrost in this region is essential for effective water resource management,
hazard assessment, and adaptation strategies (Bajracharya etal., 2007; Majeed et al., 2022; Nel et al., 2015).
Permafrost and rock glaciers in the Himalayan region face several challenges. The rapidly changing climate poses
a substantial threat, with rising temperatures causing permafrost degradation, altering the hydrological regime,
and increasing the likelihood of slope failures (Bajracharya etal.,2014; M. L. Shrestha etal.,2019). Additionally,
the region's complex topography and limited accessibility make field investigations challenging, highlighting the
importance of remote sensing and modeling techniques in studying these frozen landforms (Kargel etal.,2011).
1.2. Importance of Studying Permafrost and Rock Glaciers in the Himalayan Region
Studying permafrost and rock glaciers in the Himalayan region is of paramount importance for several reasons.
First, permafrost acts as a natural storage reservoir for water, regulating streamflow and providing water supplies
during dry periods (Haggerty etal.,2013). Understanding the distribution and characteristics of permafrost is
crucial for accurate water resource assessments and projections, especially in the context of changing climatic
conditions (Pandey etal., 2015; Q. Zhang et al., 2022). Second, rock glaciers play a significant role in slope
stability. The presence of ice-rich permafrost within these landforms influences their mechanical properties
and potential for creep or sliding (Deline, Delaloye, etal.,2012; Deline, Gruber, etal., 2012). Assessing the
dynamics of rock glaciers is essential for identifying areas prone to slope failures, which have the potential
to cause devastating landslides and pose risks to infrastructure and communities (Sridharan & Gopalan,2019;
Thirugnanam etal.,2020; Thompson etal.,2018; Wadhawan etal.,2023). Third, the Himalayan region is a biodi-
versity hotspot, with unique ecosystems adapted to extreme mountain environments. Permafrost and rock glaciers
contribute to the maintenance of these ecosystems by providing habitats for specialized flora and fauna (Schmidt
etal.,2011). Understanding the impact of permafrost degradation on these ecosystems is crucial for conserva-
tion efforts and mitigating potential biodiversity losses (Jaboyedoff etal.,2018). Lastly, the Himalayan region is
densely populated, with millions of people relying on water resources originating from glaciers and permafrost
areas. Changes in the hydrological regime, such as altered meltwater contributions and increased frequency of
glacial lake outburst floods (GLOFs), can have severe socio-economic implications (A. B. Shrestha etal.,2015).
Studying permafrost and rock glaciers helps in assessing and managing the associated risks, contributing to disas-
ter risk reduction and sustainable development in the region (Khadka etal.,2019).
1.3. Purpose of the Study and Research Objectives
The primary purpose of this study is to provide a comprehensive inventory and analysis of rock glaciers, as well
as to map the distribution of permafrost in the Jhelum basin located in the Kashmir region of Himalaya, India. By
utilizing a combination of remote sensing data, field investigations, and geospatial analysis, this research aims to
achieve the following objectives:
1. Develop a Permafrost Zonation Map (PZM) using logistic regression modeling based on topographic and
climatic variables. Mean Annual Air Temperature (MAAT), Potential Incoming Solar Radiation (PISR), and
slope aspect near the initiation line of rock glaciers are considered as predictor variables. Logistic Regression
Model (LRM) is employed to classify permafrost zones based on the probability of their presence.
2. Analyze the spatial distribution, characteristics, and dynamics of rock glaciers within the study area. This
includes assessing the number, size, elevation, and slope of rock glaciers. The slope, aspect, and elevation of
rock glaciers are calculated using the Advanced Spaceborne Thermal Emission and Reflection Radiometer
(ASTER) Digital Elevation Model (DEM).
3. Validate the findings of this study through field investigations and observations. Field visits are conducted
to verify the presence and activity status of rock glaciers. Direct measurements, including ground tempera-
ture measurements and ice content assessments, provide ground truth data for validating remote sensing and
modeling results.
4. Assess the agreement between the PZM generated in this study and the global Permafrost Zonation Index
(PZI) map.By comparing the zonation results, the study evaluates the regional applicability and accuracy of
the model, providing insights into the unique permafrost characteristics of the Himalayan region.
5. Discuss the implications of the findings in relation to the abundance of permafrost and the potential risks
associated with thawing permafrost under climate warming in the Himalayan region. The study highlights
Investigation: S. N. Remya, Tirthankar
Ghosh, Vivek Agarwal, Muneer Ahmad
Mukhtar, Rakesh Mishra
Methodology: S. N. Remya, Tirthankar
Ghosh, Vivek Agarwal, Zahid Majeed,
Babu Govindha Raj K, Aanchal Sharma,
Anil V. Kulkarni, Muneer Ahmad
Mukhtar, Rakesh Mishra
Resources: Babu Govindha Raj K,
Aanchal Sharma, Anil V. Kulkarni
Software: S. N. Remya, Tirthankar
Ghosh, Vivek Agarwal, Zahid Majeed,
Babu Govindha Raj K, Aanchal Sharma,
Anil V. Kulkarni, Rakesh Mishra
Validation: S. N. Remya, Vivek Agarwal,
Babu Govindha Raj K, Muneer Ahmad
Mukhtar
Visualization: S. N. Remya, Vivek
Agarwal, Zahid Majeed, Anil V. Kulkarni,
Muneer Ahmad Mukhtar, Rakesh Mishra
Writing – original draft: S. N. Remya,
Tirthankar Ghosh, Vivek Agarwal,
Aanchal Sharma, Anil V. Kulkarni,
Muneer Ahmad Mukhtar, Rakesh Mishra
Writing – review & editing: S. N.
Remya, Tirthankar Ghosh, Vivek
Agarwal, Zahid Majeed, Babu Govindha
Raj K, Aanchal Sharma, Anil V. Kulkarni,
Rakesh Mishra

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the importance of permafrost preservation for maintaining water resources, slope stability, and ecological
systems. It also emphasizes the need for adaptive strategies to address the impacts of climate change on
permafrost and rock glaciers in the region.
By accomplishing these objectives, this research aims to contribute to the scientific understanding of permafrost
and rock glaciers in the context of the Himalayan region. The findings will provide valuable information for
regional planning, sustainable development, and adaptation strategies, helping to mitigate the potential risks
associated with permafrost degradation and climate change impacts.
2. Study Area
The study is conducted in the Upper Jhelum Basin in the Pir Panjal region of the Indian Himalaya (pink region in
Figure1), located between latitudes 34° and 35°N and longitudes 73° and 75°E. Pir Panjal Range is a mountain
range of the Western (Punjab) Himalaya. The range spans 900 square kilometers and is home to 27 lakes and 12
meadows, all situated at an elevation of over 12,000 feet (Malik etal.,2019). The slopes of the Pir Panjal Range
are steep, with elevations ranging from 3,000 to 5,000m (Mir etal.,2022). The Jhelum Basin is situated in the
north-western part of the Jammu and Kashmir Union Territory (UT). The basin covers an area of approximately
1,920 square kilometers and is mainly characterized by rugged terrain, steep valleys, and high mountains, with
elevations ranging from approximately 3,700m to 4,550m (Ahmed, Rawat, etal.,2022). Upper Jhelum Basin is
a complex and dynamic geological region that has been shaped by the movement of tectonic plates, the intrusion
of magma, and the erosive action of rivers and glaciers. Upper Jhelum Basin is comprised of metamorphic rocks
such as gneiss, schist, and quartzite, among others (Ahmed, Ahmad, etal.,2022).
The climate in the basin has significant variations in temperature, rainfall, and snowfall. Lone etal. (2022)
reported that the basin experiences a high variability in precipitation, with the monsoon season contributing to
most of the rainfall. Another study by Wani etal.(2017) reported that the temperature decreases by 0.6–0.7°C for
every 100m increase in altitude, and the precipitation increases by 82–118mm for every 1,000m increase in the
altitude of the basin. The climate of the Upper Jhelum Basin is characterized by a high altitude, cold desert-like
Figure 1. Study area map of the Jhelum basin. The inset map shows the location of the study area in Jammu and Kashmir
Union Territory (UT).

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conditions (Rather etal.,2022) with significant variations in temperature, rainfall, and snowfall, which are influ-
enced by the altitude, topography, and location of the basin in the Indian Himalaya.
3. Method and Data
3.1. Data Collection
3.1.1. Remote Sensing Data
Identifying rock glaciers in the Himalaya using remote sensing methods can be a challenging task due to the
complex and rugged terrain characterized by steep slopes and high peaks, which makes it difficult to accu-
rately differentiate between rock glaciers and the surrounding terrain (Table1). In addition, the availability and
resolution of the satellite imagery used also play a crucial role in identifying rock glaciers (Jones etal.,2018).
High-resolution satellite images from Google Earth Pro were used as the base to identify and map rock glaciers
within the study area (Jones etal.,2021). Google Earth images were selected for the years 2019–2022 depending
on the availability of clear images based on the fraction of cloud and snow cover. These images provide a valuable
visual indicator of the presence of rock glaciers. Remote sensing data enables easy and comprehensive survey-
ing of challenging terrains, covering vast spatiotemporal scales (Agarwal,2022; Agarwal etal., 2021, 2023;
Qin etal.,2021). Satellite imagery allows for the identification of geomorphological features such as ridge and
furrow topography (Kääb & Weber,2004), ice content, and surface characteristics that distinguish active and relic
rock glaciers. The identification of rock glaciers based on remote sensing data is supported by previous studies
(Barsch,1996; Deline, Delaloye, etal.,2012; Deline, Gruber, etal.,2012).
3.1.2. Digital Elevation Model (DEM)
The ASTER DEM is utilized to calculate the slope, aspect, and elevation of rock glaciers (ASTER GDEM,2023).
The DEM data provide detailed information about the topography of the study area, enabling the analysis of the
spatial distribution and characteristics of rock glaciers. The DEM data are widely used in permafrost and glacial
studies (Jaboyedoff etal.,2018; Jansson etal.,2003).
3.1.3. Climatic and Topographic Data
Climatic and topographic variables are essential in modeling permafrost distribution. MAAT, PISR, slope aspect,
and elevation are considered as predictor variables. The MAAT data are obtained from the WorldClim database
which uses data from meteorological stations located in the study area, while the PISR data are derived from solar
radiation models using the ASTER DEM on ArcMap.The modeled PISR values were given in watthours per square
meter (Wh m
−2), which were then converted to kilowatthours per square meter (KWh m
−2) for further analysis
and logistic regression modeling. The slope aspect and elevation data are derived from the ASTER DEM using the
“Aspect (Spatial Analyst)” tool on ArcMap.These variables have been widely used in permafrost modeling studies
(Jaboyedoff etal.,2018; Nel etal.,2015). All the spatial maps of topo-climatic variables are given in Figure2.
3.2. Rock Glacier Identification and Classification
The identification and classification of rock glaciers are conducted using a combination of remote sensing analy-
sis and geomorphological features. High resolution satellite images on Google Earth Pro are used to identify rock
glaciers and manually digitize their boundary and rooting zone. Active rock glaciers are identified based on the
Data Resolution Purpose Reference
WorldClim ∼1km MAAT layer Fick and Hijmans(2017)
ASTER GDEM 30 m PISR, aspect layer ASTER GDEM (2023)
GTOPO 30 ∼1km MAAT layer https://earthexplorer.usgs.gov/
Google Earth images 80cm to 15m Visualization/Representation Google Earth Pro
GPS points cm accuracy Validate the boundary Garmin Extrex 10
Climate Research Unit Time Series (CRU TS) 4.03 a 0.5 latitude-longitude grid Temperature and precipitation trend http://www.cru.uea.ac.uk/cru/data/hrg
Note. It includes climatic as well as satellite data sets acquired from different sources including their spatial resolutions.
Table 1
Represents Different Types of Data Used for the Study

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presence of prominent ridge and furrow topography (Kääb etal.,2004), indicative of internal deformation due
to creep movement, as well as the presence of ice near the rooting zone of the rock glaciers. Active rock glaciers
also exhibit sharp-crested frontal slopes as well as swollen body structures (Wahrhaftig & Cox,1959). Whereas,
relic rock glaciers are identified based on presence of vegetation cover, flattened and deflated bodies, and less
prominent furrow and ridge topography (Kääb etal.,2004). These criteria are consistent with previous studies
on rock glacier identification (Barsch,1996; Deline, Delaloye, etal.,2012; Deline, Gruber, etal.,2012; Fleischer
etal.,2023).
3.3. Permafrost Zonation Mapping
A LRM is employed to map the distribution of permafrost in the study area. The LRM utilizes the climatic and
topographic variables (MAAT, PISR, slope aspect) as predictor variables to classify permafrost zones based
on the probability of their presence (Ponziani etal., 2023). The logistic regression approach has been widely
used in permafrost modeling studies (Baral etal., 2020; Jaboyedoff etal.,2018; Pandey etal.,2022; Schmidt
etal.,2011). Figure2 represents the prepared input for running the LRM in the study area.
Mathematically, LRM can be represented using the equation,

(=1)= 

0
+
1

1
+
2

2
+
...




1+

0
+
1

1
+B
2
x
2
+...



In the above equation, β0 is the intercept, βn is the coefficient of the predictor variables Xn and e is the base of the
natural logarithm whose value is 2.7182.
The logistic regression modeling was carried out using the IBM SPSS Statistics software. Subsequently, all the
GIS procedures were executed utilizing the ArcMap tools to produce the map depicting the spatial distribution
of permafrost.
3.4. Field Investigations
Field investigations were conducted in July 2022 to validate the remote sensing and modeling results and provide
ground truth data. Field visits were made to selected rock glacier sites to verify their presence and activity status.
Figure 2. Different topo-climatic variables used in the study. Specifically, panels show (a) Mean Annual Air Temperature for
1970–2000; (b) PISR; and (c) Aspect of the study area.

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Direct measurements using the Global Positioning System and content assessments were carried out to confirm
the existence of permafrost within the rock glaciers. The field investigations provide valuable in-situ data for cali-
bration and validation of the remote sensing and modeling results (Haggerty etal.,2013; Mukherjee etal.,2020).
4. Results
4.1. Rock Glacier Inventory
The high-resolution satellite images obtained from Google Earth allowed the identification and mapping of rock
glaciers in the Jhelum basin. The process of digitization involved the manual mapping of each individual rock
glacier by identifying its boundaries and geomorphological features on high-resolution satellite imagery. All the
digitized files were exported as Keyhole Markup Language files for further processing. This manual process is
time-consuming and requires a skilled analyst with a good understanding of the terrain and the different features
that are used to identify rock glaciers.
The inventory classified the rock glaciers into two categories: active and relic. Active rock glaciers exhibited
ridge and furrow topography, indicating internal deformation due to creep movement. The presence of swollen,
bulged bodies suggested the presence of ice-rich permafrost. In contrast, relic rock glaciers displayed flattened
and deflated bodies with a vegetation cover, indicating the absence of permafrost. Figures3a and3b illustrate the
geomorphological features used to identify active and relic rock glaciers, respectively, by the study.
Considering the various geomorphological features used to identify active and relic rock glaciers (Figure3), a
manual inventory has been compiled of all rock glaciers within the study area resulting in a total of 207 rock
glaciers being identified. The presence of ridge and furrow topography on the surface of rock glaciers, as depicted
in Figure3a, is indicative of internal deformation resulting from downward creep movement. These features are
highlighted by yellow dotted lines. Also, the presence of ice near the rooting zone of the rock glacier is an indi-
cation of the existence of permafrost. The distinctive morphology of active rock glaciers, characterized by their
inflated and bulged body shape, is indicative of the presence of ice-rich permafrost material within their compo-
sition. The frontal part of active rock glaciers has a high degree of slope and a crested frontal lobe.
Figures3b and3c exhibit the existence of vegetation cover on the surface of relict rock glaciers, along with their
flattened and deflated morphology, suggesting the absence of permafrost within them. Gentle frontal slope and
less prominent furrow and ridge topography over the rock glacier body shows its inactive state.
Figure4 presents the rock glacier inventory and shows their spatial distribution. Along with the manual mapping
process, an inventory table (TableS1) has been created to provide extensive details of each rock glacier identified
within the study area. The table includes several parameters, which are glacier area, location details (latitude and
longitude), type of rock glacier (active or relic), whether the glacier is terminating in a lake or not, and elevation
details. The slope and aspect of each rock glacier have also been recorded.
The analysis of the inventory table (TableS1) reveals that the rock glaciers within the study area have varying
areas, ranging from 0.01 to 2.7km
2. Out of these rock glaciers, 15 are terminating with a lake, while one is
surrounded by a cirque lake, and one has a supra-glacial lake on its surface. The remaining 190 rock glaciers are
land terminating glaciers.
4.2. Characteristics of Rock Glaciers
The analysis of the ASTER DEM data allowed for the characterization of the identified rock glaciers in terms
of elevation, surface slope, and orientation (TableS1). The average elevations of the rock glaciers ranged from
3,700m to 4,550m, while the average surface slopes ranged from 12° to 26°. The maximum slope of the glaciers
ranged from 25° to 65°. Figure5a illustrates the number of glaciers at different elevations with the maximum
distribution of rock glaciers found in the elevation band of 4000–4,200m (N=114). Figure5b displays the distri-
bution of rock glaciers based on their orientations. The predominant orientation of the rock glaciers is toward the
south or southwest direction.
4.3. Permafrost Zonation Mapping
LRM was employed to map the distribution of permafrost within the Jhelum basin. The model utilized climatic
and topographic variables, including MAAT, PISR, slope aspect, and elevation (Figure2). These variables were

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used to classify permafrost zones based on their probability of occurrence. The resulting PZM provided valu-
able insights into the spatial distribution of permafrost within the study area. Figure6 indicates the probability
of permafrost presence. The mapping results are compared with the global PZI map (Gruber,2012) (Figure7),
demonstrating a consistent agreement between the two. This comparison indicates the reliability and accuracy of
the developed PZM.
4.4. Field Investigations
Field investigations were conducted to complement the remote sensing and modeling results and provide a direct
observation of the glacio-geomorphic features in the study area. Figure8 illustrates some of the key findings from
the field visits.
Field observations of the Chirsar glacier valley (Figure8a) revealed the presence of a proglacial lake formed in
front of receding glaciers in the upper catchment. The existence of huge lateral moraines provided evidence of
the past extent of glaciation in the valley. The Chirsar group of glaciers, which was once a single valley glacier,
has bifurcated into two glaciers. In the Bramsar glacier valley (Figure8b) field observations showed the ongo-
ing process of glacier bifurcation. The clean hanging glaciers have been receding over time, leaving behind a
wide U-shaped glacial valley and a larger proglacial Bramsar lake. A small glacier lake near the snout was also
Figure 3. (a) Represents the geomorphological features used to identify active rock glaciers; (b) represents the
geomorphological features used to identify relic rock glaciers showing gentle frontal slope; (c) represents the
geomorphological features used to identify relic rock glaciers showing gentle frontal slope highlighting vegetation on surface.

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reported during the field visit, which presents an interesting opportunity for further study, particularly in terms of
glacial lake outburst flood research. A significant finding was the discovery of a massive glacial erratic (basalt)
boulder previously deposited by the Bramsar glacier (Figure8c). The dimensions of the boulder were measured to
be 24.9m along the longer axis, 16.3m in width, and 13.5m in height. Its presence provides valuable information
about the past glacial activity and transportation of large rock masses by the glacier. Field observations revealed
a series of paired lateral moraines in the proglacial area of Chirsar Glacier valley (Figure8d). These moraines,
including the oldest and highest lateral moraines and subsequent recessional moraines, were deposited during
the shrinking of the glacier. Their presence indicates the retreat and changing dynamics of the glacier over time.
Further, the field investigations identified a small rock glacier formed as a result of the recession and melting of
a former glacier in the same valley (Figure8e). The rock glacier exhibited distinct ridge and furrow topography,
characteristic of its active state. The presence of massive lateral and recessional moraines in the proglacial area
further confirmed the history of glacial activity in the region. The upper catchment area of a rock glacier revealed
Figure 4. Represents the spatial distribution of active and relic rock glaciers in the Jhelum Basin.
Figure 5. (a) Distribution of rock glaciers across different elevation zones in the study area. (b) A radar plot showing the
distribution of rock glaciers in different slope aspects. Most number of the active (N=22) and relic (N=30) rock glaciers
(Figure4) are found in the western aspect as shown in the figure.

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clean snow and ice in the accumulation area and a significant debris cover in the ablation area as shown in
Figure8f. The surface texture of the debris cover resembled a lava flow, indicating the presence of a rock glacier.
The ridge and furrow surface topography further confirmed the active state of the rock glacier.
Figure 6. Permafrost zonation map of Jhelum Basin from the study.
Figure 7. The study area was extracted from the Global Permafrost Zonation Index map of Gruber(2012).

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4.5. Temporal Distribution of Temperature and Precipitation
Figures9a and9b display the temporal distribution of temperature and precipitation in the study area. These
figures provide an overview of the climatic conditions and variations over time, which are essential factors influ-
encing permafrost and rock glacier dynamics. The temporal distribution of temperature and precipitation in the
Jhelum basin was analyzed using the Mann-Kendall test for trend significance and Sen's slope values (Table2).
This analysis provides insights into the long-term changes in temperature and precipitation patterns, which are
crucial for understanding the impacts of climate change on the region.
The Mann-Kendall test results for the annual mean temperature indicate a significant increasing trend (p<0.05).
The calculated Sen's slope value of 0.005°C per year suggests a gradual rise in temperature over the study
period. This warming trend has important implications for the hydrological regime, glacial melt, and perma-
frost stability in the Jhelum basin. In terms of annual mean precipitation, the Mann-Kendall test also reveals a
significant increasing trend (p<0.05). The Sen's slope value of 0.127mm per year indicates a gradual increase
in precipitation. These findings have implications for water availability, runoff patterns, and potential changes in
the glacial and hydrological systems in the region.
The rising temperatures can accelerate glacier melt, leading to changes in the glacial and hydrological regimes.
Increased precipitation can affect water resources, including glacial meltwater contributions, river flows, and
Figure 8. Evidence of rock glaciers and associated landforms observed during the field visits. (a) Represents upper catchment of Chirsar glacier valley. (b) Represents
the bifurcation of glaciers in progress in the Bramsar glacier valley. (c) Massive glacial boulder on the lateral moraine of Bramsar glacier (d) Paired lateral moraines in
the proglacial area of Chirsar glacier valley (e) Represents a small rock glacier and associated landforms (f) The upper catchment area of a rock glacier.

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the overall water balance in the basin. These changes in temperature and precipitation patterns have significant
implications for ecosystem dynamics, water resource management, and the livelihoods of communities in the
Jhelum basin. It is essential to monitor these trends continuously and develop adaptation strategies to address the
potential impacts of climate change on the region.
Further research is needed to investigate the spatial and temporal variability of temperature and precipitation
within the Jhelum basin and their specific impacts on glacial and hydrological systems. Understanding these
dynamics will contribute to improved water resource management, hazard
assessment, and climate change adaptation strategies in the region. The
temperature and precipitation data, along with the other variables used in the
LRM, contribute to a comprehensive understanding of the factors influencing
permafrost distribution and the behavior of rock glaciers in the Jhelum basin.
5. Discussion and Implications of Results
The present study was able to achieve its objectives by employing a combi-
nation of remote sensing, field investigations, and modeling techniques. The
Figure 9. (a) Annual Mean Temperature trend plot for the study area (1901–2019). (b) Annual Mean Precipitation trend plot for the study area (1901–2019).
Data p-value Sen's slope
Annual Mean Temperature (1901–2019) 0.00028 0.005°C/yr
Annual Mean Precipitation (1901–2019) 0.00012 0.127mm/yr
Table 2
Represents the Trend Significance and Sen's Slope Values for the Temporal
Distribution of Temperature and Precipitation Analysis in the Jhelum Basin
Using the Mann-Kendall Test

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findings provide valuable insights into the spatial distribution, characteristics, and dynamics of permafrost and
rock glaciers in the study area. The PZM generated in this study is a valuable data set for understanding perma-
frost distribution and vulnerability to climate change. The implications of the findings are further discussed in
relation to the abundance of permafrost and the potential risks associated with thawing permafrost under climate
warming in the Himalayan region. The analysis of the results obtained from the rock glacier inventory, permafrost
zonation mapping, characteristics of rock glaciers, field investigations, and the temporal distribution of tempera-
ture and precipitation provide valuable insights into the dynamics of permafrost and rock glaciers in the Jhelum
basin, Kashmir Himalaya.
5.1. Rock Glacier Distribution and Dynamics
The study provides a detailed valuable insight and understanding of the distribution and dynamics of rock glaciers
in the Jhelum basin of the Kashmir Himalaya. The analysis of high-resolution satellite images from Google
Earth revealed a total of 207 rock glaciers in the study area, covering an approximate area of 50km
2. Among
these, over 100 rock glaciers were categorized as active based on their surface topography and geomorphology,
indicating ongoing movement and the presence of ice-rich permafrost content. The distribution of rock glaciers
showed a strong correlation with the slope aspect, elevation, and climatic variables such as MAAT and PISR.
The LRM utilized in this study demonstrated its effectiveness in predicting the permafrost probability distribu-
tion based on these environmental and topographical factors. The distribution of active and relic rock glaciers
provides evidence of ongoing permafrost-related processes and past periglacial activity (Tielidze etal.,2023).
The identification of active rock glaciers based on their ridge and furrow topography, swollen bodies, and high
degree of surface slope suggests that these landforms are still experiencing creep movement and are likely under
the influence of ice-rich permafrost (Kaldybayev etal.,2023). The presence of relic rock glaciers characterized
by flattened bodies, deflation, and a lack of permafrost indicators, indicates their inactive state. This information
is crucial for understanding the spatial patterns and factors influencing the presence of rock glaciers in the region
(Joshi etal.,2022).
5.2. Permafrost Zonation and Environmental Factors
The PZM developed using the LRM offers important insights into the spatial distribution of permafrost in the
Jhelum basin. The map indicates varying probabilities of permafrost occurrence across the study area, influenced
by climatic and topographic variables. The agreement between the PZM and the global PZI map demonstrates the
reliability and accuracy of the LRM in capturing the distribution patterns of permafrost. The variables used in the
model, such as MAAT, PISR, slope aspect, and elevation, contribute to our understanding of the environmental
factors that influence permafrost presence and stability. The findings highlight the importance of environmental
factors in controlling permafrost occurrence and its relationship with rock glacier formation. The elevated regions
with steeper slopes were found to be favorable for the development of rock glaciers and the presence of perma-
frost (X. Zhang etal.,2021). The spatial distribution and zonation of permafrost provide essential information for
understanding the vulnerability of the region to climate warming and the potential risks of thawing permafrost.
5.3. Characteristics and Behavior of Rock Glaciers
Field investigations and observations further enhanced the understanding of the characteristics and behavior of
rock glaciers in the Jhelum basin. The field photographs (Figure7) revealed important features such as proglacial
lakes, lateral moraines, and U-shaped valleys, indicating past glacial activity and the transformation of glaciers
into rock glaciers. The presence of ridge and furrow topography, swollen bulged bodies, and crested frontal lobes
in active rock glaciers confirmed their dynamic nature and ongoing creep movement. Relic rock glaciers, on
the other hand, exhibited flattened and deflated bodies with vegetation cover, indicating their non-active state.
Field observations also identified a massive glacial erratic boulder previously deposited by the Bramsar glacier,
providing evidence of the glacial history and extent of past glaciations in the area. The analysis of the character-
istics of rock glaciers, including elevation, surface slope, and orientation, contributes to our understanding of the
formation and dynamics of these landforms in the Jhelum basin. The average elevations ranging from 3,700m
to 4,550m indicate the high-altitude nature of the rock glaciers. The surface slope analysis reveals moderate to
steep slopes, which influence the movement and behavior of the rock glaciers. The predominant orientation of

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the rock glaciers in a south or southwestern direction suggests the influence of solar radiation and slope aspects
on their formation and evolution. These findings align with previous studies highlighting the importance of
elevation, slope, and aspect in shaping the characteristics and behavior of rock glaciers (Barsch,1996; Deline,
Delaloye, etal.,2012; Deline, Gruber, etal.,2012). Field observations, combined with the remote sensing data
and geomorphological analysis, contribute to a comprehensive understanding of rock glacier characteristics and
their evolution in response to climate and environmental changes (Pandey,2019).
5.4. Implications and Future Research
The findings of this study have several implications for understanding permafrost dynamics and associated
hazards in the Jhelum basin, Kashmir Himalaya. The identification of numerous active rock glaciers and the
presence of ice-rich permafrost suggest potential risks associated with thawing permafrost under the influence
of climate warming. The PZM provides valuable information for land use planning, infrastructure development,
and climate change adaptation strategies in the region. Understanding the distribution and characteristics of
permafrost can help inform decision-making processes related to slope stability, water resource management,
and mitigating the impacts of climate change. Future research efforts should focus on long-term monitoring of
rock glaciers and permafrost dynamics using a combination of remote sensing techniques, field observations,
and modeling approaches. Additionally, studies exploring the hydrological impacts of rock glaciers, such as their
contribution to water resources and potential glacial lake outburst floods (GLOFs), are crucial for understand-
ing the broader implications of these landforms. Continuous monitoring will enable a better understanding of
the response of permafrost and rock glaciers to changing environmental conditions and further improve hazard
assessment and prediction models.
6. Conclusions
The present study presents a comprehensive analysis of rock glaciers and permafrost in the Jhelum basin,
Kashmir Himalaya, India. The inventory of rock glaciers identified a total of 207 landforms, with a distinction
between active and relic rock glaciers based on their geomorphological characteristics. The identification of
lake-terminating rock glaciers is crucial in assessing their potential impact on the surrounding areas, including the
possibility of glacial lake outburst floods which can pose significant risks to human settlements, infrastructure,
and natural ecosystems. The inventory will help researchers and policymakers in identifying high-risk areas and
prioritizing mitigation measures to reduce the impact of such events. The PZM developed using logistic regres-
sion modeling provided insights into the spatial distribution of permafrost, which exhibited agreement with the
global PZI map.
The analysis of rock glaciers encompassed characteristics such as elevation, surface slope, and orientation. It
revealed that these features are typically found at high altitudes, on steep slopes, and predominantly oriented
toward the south or southwest direction.
Field investigations corroborated the remote sensing and modeling results, confirming the presence of rock
glaciers in elevated regions with steep slopes. The findings have significant implications for understanding
permafrost dynamics and associated hazards in the Jhelum basin. The identification of active rock glaciers and
the presence of ice-rich permafrost indicate potential risks of thawing permafrost due to climate warming. The
PZM serves as a valuable tool for land use planning, infrastructure development, and climate change adaptation
strategies in the region. Future research should focus on long-term monitoring of rock glaciers and permafrost
dynamics to enhance our understanding of their response to changing environmental conditions. Improved moni-
toring will aid in the development of more accurate hazard assessment and prediction models, facilitating effec-
tive mitigation strategies.
Data Availability Statement
The data used in the study is publicly available at https://zenodo.org/records/10421020 (Remya etal., 2023).
The MAAT data collected is available at https://www.worldclim.org/data/worldclim21.html (last accessed on
10 September 2023). The Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital
Elevation Model (ASTER GDEM) is available at https://lpdaac.usgs.gov/products/astgtmv003/ (last accessed

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on 05 October 2023). The Global 30 Arc-Second Elevation (GTOPO30) is available at: https://www.usgs.gov/
centers/eros/science/usgs-eros-archive-digital-elevation-global-30-arc-second-elevation-gtopo30 (last accessed
on 21 September 2023) (GTOPO30,2023). The CRU Climate Dataset is available at Harris etal.,2020 (https://
doi.org/10.1038/s41597-020-0453-3). We encourage researchers to access and reuse this data to further advance
climate research in the Himalaya.
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Acknowledgments
The authors are thankful to the Amrita
School for Sustainable Futures, Amrita
Vishwa Vidyapeetham (Amrita Univer-
sity), Kerala, India for the invaluable
support for the successful completion
of the work. Furthermore, they express
sincere gratitude to Divecha Centre for
Climate Change, IISc, Bangalore. We
are also grateful to Geological Survey of
India for the assistance to conduct field
work for the study.

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