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Kashmir Valley has been witnessing erratic snowfall events in recent autumns which severely impacted apple orchards and harvests. Here, we combine remotely sensed data and field observations to map snowfall distribution and snow depths during the recent snowfall events in November 2018 and November 2019. Besides, we used ERA-5 reanalysis climate datasets to investigate the causes of these erratic snowfall events, pointing to an early arrival of Western Disturbances (WD) to the area. Analysis of these untimely snowfall episodes indicates that snow depths varied from 5-122 cm and 31-152 cm during the 2018 and 2019 snowfall events, respectively. In turn, satellite data analysis reveals that the apple orchards cover roughly 9.8% (1329 km 2) of the entire surface of Kashmir Valley, out of which 32.6% were mildly to severely damaged by snow. The areas in South Kashmir suffered the most from the untimely snowfall with an area affected estimated to~264 km 2 , followed by North Kashmir (~151 km 2) and Central Kashmir (18 km 2). The snowfall caused substantial harvest losses in orchards ranging from 4-50% with an average of~35%. The geopotential analysis from the ERA-5 dataset provides insights into the synoptic weather patterns leading to the snowfall events and point to a trough in the high-troposphere (200 mb), along with a col at lower levels (850 mb) over the Kashmir Valley from November 2-5, 2018. The lower levels (850 mb) experienced intense cyclonic circulation which favored advection of moisture from the Arabian Sea during the November 6-7, 2019, snowfall event. The large economic losses related to early arrival of WD led to a virtual grounding of the horticultural sector in 2018 and 2019. Therefore, more baseline research is critically needed along with a comprehensive evaluation of the suitability of horticulture as an economically viable sector that is being promoted over the Kashmir region, also under climate change.
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sustainability
Article
Impacts of Erratic Snowfall on Apple Orchards in
Kashmir Valley, India
Irfan Rashid 1, * , Ulfat Majeed 1, Sheikh Aneaus 1, Juan Antonio Ballesteros Cánovas 2,3,
Markus Stoel 2,3,4, Nadeem Ahmad Najar 1, Imtiyaz Ahmad Bhat 1and Sonam Lotus 5
1Department of Geoinformatics, University of Kashmir,
Hazratbal Srinagar 190006, Jammu and Kashmir, India; ulfatmgis@gmail.com (U.M.);
sheikh.aneaus19@gmail.com (S.A.); nadeemgis17@gmail.com (N.A.N.); bhatimtiyaz463@gmail.com (I.A.B.)
2Climatic Change and Climate Impacts, Institute for Environmental Sciences, University of Geneva,
Boulevard Carl-Vogt 66, CH-1205 Geneva, Switzerland; Juan.Ballesteros@unige.ch (J.A.B.C.);
Markus.Stoel@unige.ch (M.S.)
3Dendrolab.ch, Institute for Environmental Sciences, University of Geneva, Boulevard Carl-Vogt 66,
CH-1205 Geneva, Switzerland
4Department F.A. Forel for Environmental and Aquatic Sciences, University of Geneva,
Boulevard Carl-Vogt 66, CH-1205 Geneva, Switzerland
5India Meteorological Department, Srinagar 190008, Jammu and Kashmir, India; lotusladakh@gmail.com
*Correspondence: irfangis@kashmiruniversity.ac.in; Tel.: +91-901-888-5992
Received: 19 October 2020; Accepted: 3 November 2020; Published: 5 November 2020


Abstract:
Kashmir Valley has been witnessing erratic snowfall events in recent autumns which severely
impacted apple orchards and harvests. Here, we combine remotely sensed data and field observations
to map snowfall distribution and snow depths during the recent snowfall events in November 2018 and
November 2019. Besides, we used ERA-5 reanalysis climate datasets to investigate the causes of these
erratic snowfall events, pointing to an early arrival of Western Disturbances (WD) to the area. Analysis
of these untimely snowfall episodes indicates that snow depths varied from 5–122 cm and 31–152 cm
during the 2018 and 2019 snowfall events, respectively. In turn, satellite data analysis reveals that the
apple orchards cover roughly 9.8% (1329 km
2
) of the entire surface of Kashmir Valley, out of which
32.6% were mildly to severely damaged by snow. The areas in South Kashmir suered the most
from the untimely snowfall with an area aected estimated to ~264 km
2
, followed by North Kashmir
(~151 km
2
) and Central Kashmir (18 km
2
). The snowfall caused substantial harvest losses in orchards
ranging from 4–50% with an average of ~35%. The geopotential analysis from the ERA-5 dataset
provides insights into the synoptic weather patterns leading to the snowfall events and point to a
trough in the high-troposphere (200 mb), along with a col at lower levels (850 mb) over the Kashmir
Valley from November 2–5, 2018. The lower levels (850 mb) experienced intense cyclonic circulation
which favored advection of moisture from the Arabian Sea during the November 6–7, 2019, snowfall
event. The large economic losses related to early arrival of WD led to a virtual grounding of the
horticultural sector in 2018 and 2019. Therefore, more baseline research is critically needed along
with a comprehensive evaluation of the suitability of horticulture as an economically viable sector
that is being promoted over the Kashmir region, also under climate change.
Keywords:
snowfall variability; western disturbances; erratic snow precipitation; Kashmir Himalaya;
horticulture
1. Introduction
The Himalayan region constitutes one of the most vulnerable areas as it suers from extreme
weather events under present climate conditions and also in light of climate projections [1]. Over the
Sustainability 2020,12, 9206; doi:10.3390/su12219206 www.mdpi.com/journal/sustainability
Sustainability 2020,12, 9206 2 of 14
last few decades, changing climate has had adverse impacts on several processes and key ecosystems to
human wellbeing across the Himalayan arc, including the quantity and seasonality of snow cover
[24]
,
glacier changes
[5,6]
, natural disasters
[7,8]
, and land degradation and vegetation cover changes
[9,10]
,
with repercussions on strategic socio-economic sectors, such as hydropower [
11
,
12
], tourism [
13
,
14
], and,
ultimately, on local livelihoods [
15
17
]. According to the observational records and climate projections,
the ongoing climatic change over the Himalayas has not only impacted the pristine ecosystems and
earth surface processes but also altered weather circulation patterns over the region [18,19].
Kashmir Valley, with an area of ~15,000 km
2
, is a nappe zone interlaced between the Greater
Himalayas and the Pir Panjal Range (Lat: 33
22
0
–34
42
0
N; Lon: 73
54
0
–75
35
0
E) in northern India
(Figure 1).
Sustainability 2020, 12, x FOR PEER REVIEW 2 of 14
1. Introduction
The Himalayan region constitutes one of the most vulnerable areas as it suffers from extreme
weather events under present climate conditions and also in light of climate projections [1]. Over the
last few decades, changing climate has had adverse impacts on several processes and key ecosystems
to human wellbeing across the Himalayan arc, including the quantity and seasonality of snow cover
[2–4], glacier changes [5,6], natural disasters [7,8], and land degradation and vegetation cover changes
[9,10], with repercussions on strategic socio-economic sectors, such as hydropower [11,12], tourism
[13,14], and, ultimately, on local livelihoods [15–17]. According to the observational records and
climate projections, the ongoing climatic change over the Himalayas has not only impacted the
pristine ecosystems and earth surface processes but also altered weather circulation patterns over the
region [18,19].
Kashmir Valley, with an area of ~15,000 km2, is a nappe zone interlaced between the Greater
Himalayas and the Pir Panjal Range (Lat: 33°22–34°42 N; Lon: 73°54–75°35 E) in northern India
(Figure 1).
Figure 1. Location of the study area. Top Panel: Location of Kashmir Valley (shown as a red rectangle)
with relevant cities found across the western Himalayas. Background elevation data is from Global
Topography 30 Arc Second (GTOPO30). Bottom Panel: Shuttle Radar Topographic Mission (SRTM)
Digital Elevation Model (DEM) of Kashmir Valley, a region that is interspersed between the Pir Panjal
and the Greater Himalayan Mountain ranges. Stars indicate locations of the six weather stations used
in this study: 1- Gulmarg, 2- Kokernag, 3- Kupwara, 4- Pahalgam, 5- Qazigund, 6- Srinagar.
Figure 1.
Location of the study area.
Top Panel:
Location of Kashmir Valley (shown as a red rectangle)
with relevant cities found across the western Himalayas. Background elevation data is from Global
Topography 30 Arc Second (GTOPO30).
Bottom Panel:
Shuttle Radar Topographic Mission (SRTM)
Digital Elevation Model (DEM) of Kashmir Valley, a region that is interspersed between the Pir Panjal
and the Greater Himalayan Mountain ranges. Stars indicate locations of the six weather stations used
in this study: 1—Gulmarg, 2—Kokernag, 3—Kupwara, 4—Pahalgam, 5—Qazigund, 6—Srinagar.
The Kashmir region, located toward the western part of the Himalayan arc, has experienced
erratic weather patterns frequently in the past [
20
22
]; with further warming, erratic weather events
are projected to become much more frequent by the end of this century [
23
]. Erratic weather regimes
Sustainability 2020,12, 9206 3 of 14
have—among others—caused the megaflood of 2014 during which the Kashmir Region suered massive
economic losses totaling 1 trillion INR (corresponding to roughly US$13.7 billion) [
24
]. Besides floods [
25
],
the Kashmir Region is also affected by other weather-related events, including the heavy snowfall event
in February 2005 which caused widespread damage to infrastructure [26,27].
Climatologically, the Kashmir area belongs to the temperate zone [
28
,
29
] characterized by four
seasons (spring, summer, autumn, and winter). Srinagar, the region’s capital, is located in the center of the
valley at an altitude of 1580 m asl. The city receives an annual precipitation of ~750 mm, predominantly
during Western Disturbances (WDs), but a weak influence from the Indian summer monsoon exists,
as well [
30
]. The mountains experience more precipitation. Mean seasonal temperatures range from
5–25
C at Srinagar and decrease along an altitudinal gradient [
31
,
32
]. The elevation of the valley ranges
from 1073 to 5400 m asl. Kashmir Valley witnessed untimely, widespread snowfall on
3–4 November 2018
and
6–7 November 2019
, driven by WDs. These two erratic snowfall events were not only surprising to
the residents but also severely dented the horticultural sector in Kashmir. It is pertinent to mention
that the six meteorological stations maintained by the India Meteorological Department in the Kashmir
Valley do not gather any information about the snowfall records over the region.
WDs are known to produce severe weather over the northern Indian subcontinent [
33
]. These
synoptic-scale weather systems occur at mid-latitudes during the winter season and originate from
frontal systems in the Mediterranean Region [
34
] before reaching the north-western part of India with
the subtropical jet stream [
35
,
36
]. WDs advect moisture not only from the Mediterranean basin and
the Caspian Sea, but occasionally are also supplied with fresh moisture from the Arabian Sea, which
may then cause extreme weather with snowfall or intense rain [
33
,
37
]. WDs can also interfere with
monsoon activity, which again can enhance the intensity of precipitation events [
38
]. Much of the
snowfall and precipitation recorded in the Himalayas can be attributed to the passage of WD [
36
,
39
],
and even more so in Jammu and Kashmir where the occurrence of spells of snowfall has been linked to
the occurrence and persistence of WDs, which often last from 2 to 4 days [
40
]. Besides, the occurrence
of WDs has also been linked to the occurrence of floods or snow avalanches [
41
]. Linking such extreme
events with the intra-seasonal occurrence of WDs is important, not only to forecast future events [
34
],
but also to anticipate intra-sectoral impacts in a context of climate change, for which enhanced WD
activity is expected in the region [42].
In this paper, we focus on the causes and impacts of the erratic snowfall events that took place
in early November 2018 and November 2019. By doing so, we provide insights into their climate
causative factors and analyze snowfall data obtained through the physical surveying of the area at the
end of the snowfall event. This was done through the combination of observations with outputs from
the European Centre for Medium-Range Weather Forecasts Re-analyses (ERA-5) climate dataset.
2. Materials and Methods
This study relies on a suite of data from remote sensing platforms, ground surveys, as well as
ancillary data of damage assessment (Table 1).
Whereas satellite data of 2018 (Sentinel 2A with a spatial resolution of 10m) and 2019 (Landsat 8
Operational Land Imager, OLI) with a spatial resolution of 30 m) provided first-hand insights into the
extent of the areas aected by snowfall over the Kashmir Valley, snow depth was measured manually
at 65 locations across the Kashmir Region (Figure 1) using a handheld GPS device and a meter scale.
Optical satellite data from Sentinel 2A and Landsat 8 OLI was used since none of the datasets captured
both the snowfall events. In addition, long-term precipitation data for November have been collected
from six meteorological stations across the Kashmir Valley and for the period 1980–2019, so as to gain
more insights into the dynamics of late autumn precipitation over the region. Data was collected
from the regional center of the India Meteorological Department located at Srinagar. The area under
apple orchards was mapped using freely available high-resolution satellite imagery (Basemap in ESRI
ArcMap 10.1) for 2016–18 at a scale of 1:5000 employing manual digitization. Since the apple trees are
planted in rows and columns, we identified apple orchards based on the pattern using high-resolution
Sustainability 2020,12, 9206 4 of 14
ESRI Base map. Damage assessment data from the orchards aected by the November 2018 snowfall
was procured from the Directorate of Horticulture, Kashmir. As damage assessment data for the
November 2019 event are still under compilation, we inferred information remotely by using a kriging
interpolation [
43
,
44
] to locate hotspots of damage for 2018 snowfall event. Additionally, we employed
reanalysis data from ERA-5 to draw inferences about weather circulation patterns prevalent over the
region during the first week of November 2018 and November 2019. The ERA-5 reanalysis dataset
constitutes the fifth state-of-the-art reanalysis generated by European Centre for Meduim-Range
Weather Forecasts (ECMWF, https://www.ecmwf.int/). It is based on data assimilation from model
and observations across the world with a spatial resolution of 0.25
and temporal (12-h) coverage
from 1979 to present. To evaluate the synoptic situation related to the snow spell, synoptic charts
were investigated. A more detailed description about the ERA-5 global reanalysis is provided in
Hersbach et al. [45].
Table 1. Details of the datasets used in the study.
Dataset Scene ID/Acquisition Date Spatial Resolution
A. Remote Sensing Imagery
Basemap in ESRI ArcMap 10.1
2016–2018 1:5000 scale
ECMWF Re-Analysis (ERA-5)
1–7 November 2018
1–7 November 2019 0.25
B. Precipitation Data November (1980–2019) Point data
C. Field Data
GPS measurements 5 November 2018 Point data
7 November 2019 Point data
Photographs 5 November 2018 Point data
7 November 2019 Point data
Damage assessment data November 2018 Point data
3. Results
The satellite images of both severe weather episodes indicated widespread snowfall across the
Kashmir Valley (Supplementary Information Figure S1); however, optical remote sensing data used
in this study did not yield any information on the quantity of snow. Consequently, snow depth was
measured manually at 65 locations across Kashmir Valley and interpolated in ArcMap 10.1, to produce
a seamless snow depth map for the events of 2018 and 2019 (Figure 2). During November 2018,
snow varied from 5 cm (areas in central and north Kashmir) to 122 cm (south Kashmir), whereas the
November 2019 snowfall event left between 30 cm (in central and north Kashmir) and 152 cm (in south
and south-west Kashmir) of snow. Although the amount of snowfall was temporally variable during
the two events, spatial variability was similar between the events with the southern part of the valley
receiving substantially more snow. Details of field-based snow depth measurements are provided in
Table S1.
Analysis of long-term November precipitation data over the Kashmir Valley indicates consistently
increasing precipitation (Figure 3) across time for the 5 stations located at lower altitudes (<2400 m asl).
This increasing trend is heterogeneous across the five stations in Kashmir Valley but most pronounced
at Pahalgam (R
2
: 0.087; Figure 3d), followed by Srinagar (R
2
: 0.059; Figure 3c), Kokernag (R
2
: 0.048;
Figure 3f), Kupwara (R
2
: 0.014; Figure 3a) and Qazigund (R
2
: 0.006; Figure 3e). By contrast, precipitation
data of the high-altitude station Gulmarg showed a weak declining trend (Figure 3b).
Sustainability 2020,12, 9206 5 of 14
Sustainability 2020, 12, x FOR PEER REVIEW 5 of 14
has the highest land under apple orchards (305 km
2
), while Srinagar has the smallest area (15.7 km
2
).
The zone-wise statistics of area under orchards is provided in Table S3. South Kashmir accounts for
~56% of the total orchard area followed by north Kashmir (32%) and central Kashmir (12%).
Figure 2. Snow depth during (top) November 2018 and (bottom) November 2019.
The assessment of snowfall data specifically over orchards suggests that snow depth varied from
2–80 cm during the snowfall episodes. During the November 2018 event, orchards experienced 2.7–
80 cm of snowfall with a mean of 20.7 cm, whereas, in November 2019, snowfall was more severe
ranging from 29–76.5 cm with a mean of 40 cm. Noteworthy, south Kashmir received substantially
more snow compared to other areas of the valley during both events. The apple orchards suffered
massive damage during both the 2018 and 2019 snowfall events. The damage ranged from damage
to the foliage, crumbling of branches and also uprooting of apple tree in certain areas. Data compiled
Figure 2. Snow depth during (top) November 2018 and (bottom) November 2019.
Apple orchards cover 1330 km
2
and are spread over 10 districts of the Kashmir Valley as mapped
from the satellite data (Figure 4). The district-wise land under orchards is provided in Table S2. Analysis
suggests that out of the ten districts of Kashmir Valley, Baramulla District in north Kashmir has the highest
land under apple orchards (305 km
2
), while Srinagar has the smallest area (15.7 km
2
). The zone-wise
statistics of area under orchards is provided in Table S3. South Kashmir accounts for ~56% of the total
orchard area followed by north Kashmir (32%) and central Kashmir (12%).
The assessment of snowfall data specifically over orchards suggests that snow depth varied
from 2–80 cm during the snowfall episodes. During the November 2018 event, orchards experienced
2.7–80 cm of snowfall with a mean of 20.7 cm, whereas, in November 2019, snowfall was more severe
ranging from 29–76.5 cm with a mean of 40 cm. Noteworthy, south Kashmir received substantially
more snow compared to other areas of the valley during both events. The apple orchards suered
Sustainability 2020,12, 9206 6 of 14
massive damage during both the 2018 and 2019 snowfall events. The damage ranged from damage to
the foliage, crumbling of branches and also uprooting of apple tree in certain areas. Data compiled
by the Directorate of Horticulture, Kashmir for the 2018 (Supplementary Information Table S2) event
revealed that 433.55 km
2
of orchards were aected across Kashmir Valley by the weather event with the
highest damage reported for Kulgam District (99.45 km
2
) and the lowest impacts around Srinagar (1.76
km
2
). The interpolated data for damage to orchards, expressed as percentage, for the 2018 snowfall is
shown in Figure 5. Analysis indicates that areas in south Kashmir suered most damage followed
by north Kashmir and central Kashmir. Our results also suggest that orchards got damaged between
4–50% with an average damage of ~35%.
Figure 3.
Historical Precipitation data (1980–2020) ofNovemberoverthe Kashmir Valley from sixmeteorological
stations. (a): Kupwara, (b): Gulmarg, (c): Srinagar, (d): Pahalgam, (e): Qazigund, and (f): Kokernag.
Sustainability 2020,12, 9206 7 of 14
Sustainability 2020, 12, x FOR PEER REVIEW 7 of 14
Figure 4. District-wise area under orchards in Kashmir Valley (in km
2
). AN: Anantnag, KU: Kulgam,
SH: Shopian, PU: Pulwama, BU: Budgam, SR: Srinagar, GA: Ganderbal, BA: Baramulla, BN:
Bandipora, and KP: Kupwara.
Figure 5. District-wise damage to orchards in Kashmir Valley during November 2018 (in %). AN:
Anantnag, KU: Kulgam, SH: Shopian, PU: Pulwama, BU: Budgam, SR: Srinagar, GA: Ganderbal, BA:
Baramulla, BN: Bandipora, and KP: Kupwara.
Figure 4.
District-wise area under orchards in Kashmir Valley (in km
2
). AN: Anantnag, KU: Kulgam,
SH: Shopian, PU: Pulwama, BU: Budgam, SR: Srinagar, GA: Ganderbal, BA: Baramulla, BN: Bandipora,
and KP: Kupwara.
Sustainability 2020, 12, x FOR PEER REVIEW 7 of 14
Figure 4. District-wise area under orchards in Kashmir Valley (in km
2
). AN: Anantnag, KU: Kulgam,
SH: Shopian, PU: Pulwama, BU: Budgam, SR: Srinagar, GA: Ganderbal, BA: Baramulla, BN:
Bandipora, and KP: Kupwara.
Figure 5. District-wise damage to orchards in Kashmir Valley during November 2018 (in %). AN:
Anantnag, KU: Kulgam, SH: Shopian, PU: Pulwama, BU: Budgam, SR: Srinagar, GA: Ganderbal, BA:
Baramulla, BN: Bandipora, and KP: Kupwara.
Figure 5.
District-wise damage to orchards in Kashmir Valley during November 2018 (in %). AN: Anantnag,
KU: Kulgam, SH: Shopian, PU: Pulwama, BU: Budgam, SR: Srinagar, GA: Ganderbal, BA: Baramulla, BN:
Bandipora, and KP: Kupwara.
Sustainability 2020,12, 9206 8 of 14
Synoptic analysis of the two weather events leading to unseasonal snowfall across the Kashmir
Valley was related to the early arrival of WDs. In the case of the November 2018 event, geopotential
analysis from the ERA-5 dataset points to the formation of a trough at high tropospheric levels (200 mb)
around 67
E and 40
N on 2 November 2018 (Figure 6). In the following days, this trough evolved
steadily to reach northern Pakistan and north-western India where it persisted at 75
E and 35
N until 6 November 2018. At lower atmospheric levels (850 mb), a col situation formed between
2–5 November 2018
around 75
E and 34
N (see Figure S2). This synoptic situation induced a cyclonic
circulation in north-eastern Pakistan and south-west of the Tibetan plateau and led to positive potential
vorticity over the region. The lack of ventilation, typical during such situations, likely favored the
accumulation of moisture originating from northern and western Pakistan (Figure S2). At the same
time, colder air masses from northern latitudes were transported over the Kashmir Region, where they
led to a significant drop of average surface temperatures (Figure 7). Temperature and geopotential
values recovered partially 4–5 days after the events (Table S4).
Sustainability 2020, 12, x FOR PEER REVIEW 8 of 14
Synoptic analysis of the two weather events leading to unseasonal snowfall across the Kashmir
Valley was related to the early arrival of WDs. In the case of the November 2018 event, geopotential
analysis from the ERA-5 dataset points to the formation of a trough at high tropospheric levels (200
mb) around 67° E and 40° N on November 2, 2018 (Figure 6). In the following days, this trough
evolved steadily to reach northern Pakistan and north-western India where it persisted at 75° E and
35° N until November 6, 2018. At lower atmospheric levels (850 mb), a col situation formed between
November 2–5, 2018 around 75° E and 34° N (see Figure S2). This synoptic situation induced a
cyclonic circulation in north-eastern Pakistan and south-west of the Tibetan plateau and led to
positive potential vorticity over the region. The lack of ventilation, typical during such situations,
likely favored the accumulation of moisture originating from northern and western Pakistan (Figure
S2). At the same time, colder air masses from northern latitudes were transported over the Kashmir
Region, where they led to a significant drop of average surface temperatures (Figure 7). Temperature
and geopotential values recovered partially 4–5 days after the events (Table S4).
Figure 6. Geopotential (200 mb and 850 mb) and surface temperature fields from ERA-5 at the start of
the snowfall spells in November 2018 (left panels) and November 2019 (right panels).
Similar to the 2018 event, on November 6–7, 2019, we observe again the arrival of a WD;
identification of a trough at high tropospheric levels (200 mb) is even clearer in this case and localized
Figure 6.
Geopotential (200 mb and 850 mb) and surface temperature fields from ERA-5 at the start of
the snowfall spells in November 2018 (left panels) and November 2019 (right panels).
Sustainability 2020,12, 9206 9 of 14
Similar to the 2018 event, on 6–7 November 2019, we observe again the arrival of a WD; identification
of a trough at high tropospheric levels (200 mb) is even clearer in this case and localized at 67.5
E and
35
N. At lower levels (850 mb), a more intense cyclonic circulation (72
E and 32.5
N) formed to favor
advection of moisture from the Arabian Sea. Associated to the arrival of the WD, the incursion of low
temperatures from higher latitudes can be observed, favoring the snowfall episode further (Figure S3).
The satellite imagery from Indian National Satellite (INSAT-3D, Figures S2 and S3) and the ERA-5
derived upper-level winds support the presence of convective cloud bands with the arrival of the WD
in both years; the eects were, however, more intense during the 2019 snowfall due to advection of
moisture from the north Arabian Sea.
Sustainability 2020, 12, x FOR PEER REVIEW 9 of 14
at 67.5° E and 35° N. At lower levels (850 mb), a more intense cyclonic circulation (72° E and 32.5° N)
formed to favor advection of moisture from the Arabian Sea. Associated to the arrival of the WD, the
incursion of low temperatures from higher latitudes can be observed, favoring the snowfall episode
further (Figure S3). The satellite imagery from Indian National Satellite (INSAT-3D, Figure S2 and
S3) and the ERA-5 derived upper-level winds support the presence of convective cloud bands with
the arrival of the WD in both years; the effects were, however, more intense during the 2019 snowfall
due to advection of moisture from the north Arabian Sea.
Figure 7. Pre- and post-event evolution of average surface temperatures (°C) and geopotential (z500)
with the snowfall events based on ERA-5 dataset (data represent average values over the region 33.3°–
34.3° N and 74.3°–75° E).
4. Discussion
In this study, we assessed the causes and impacts of untimely, strong snowfall events in Kashmir
in November 2018 and November 2019, as well as looked into the consequences they have had on
apple orchards in the valley. The orchard areas in south Kashmir have been affected most by the
erratic snowfall in 2018 and 2019, with the latter being more intense and hence resulting in colossal
damage to the apple production in the valley. Noteworthy, the occurrence of these two recent events
is in line with a general tendency for the more frequent occurrence of extreme weather events over
Kashmir [46,47]. Whereas the Department of Horticulture estimated losses after the November 2018
snowfall at INR 5 billion (https://bit.ly/2TDATpR), damage observed following the November 2019
snowfall was more pronounced and resulted in the losses amounting to INR 22.5 billion (or c. US$302
million; https://bit.ly/3aJxmvN). Even if meteorological records are lacking to confirm the statement,
reports suggest that the 2019 snowfall was the heaviest that Kashmir experienced over the past six
decades, claiming 7 lives (https://bit.ly/2wInowb) and damaged power infrastructure worth INR 220
million (or c. US$2.95 billion; https://bit.ly/2TG99Rj). Historical precipitation data from India
Meteorological Department (IMD) also point to a consistent increase in precipitation totals across the
valley, and are thus in line with what is projected to occur in the Kashmir Region by the end of this
century [23].
The horticultural sector of the Kashmir Valley, dominated by apple orchard, contributes 27%
(INR 50 billion or US$670 million) to the economy of Jammu and Kashmir [48], and the government
is contemplating to strengthen the sector further. This study indicates that of the total area of 1330
km
2
under apple orchards in Kashmir Valley, more than half of orchards (56%) are located in south
Kashmir. Given the stark promotion of the horticultural sector, massive areas under irrigation-
intensive rice paddy currently undergo conversion to seemingly more viable apple orchards [49–52].
However, we argue that the ever-increasing area under orchards may well become unsustainable in
Figure 7.
Pre- and post-event evolution of average surface temperatures (
C) and geopotential (z500)
with the snowfall events based on ERA-5 dataset (data represent average values over the region
33.3–34.3N and 74.3–75E).
4. Discussion
In this study, we assessed the causes and impacts of untimely, strong snowfall events in Kashmir
in November 2018 and November 2019, as well as looked into the consequences they have had on
apple orchards in the valley. The orchard areas in south Kashmir have been aected most by the
erratic snowfall in 2018 and 2019, with the latter being more intense and hence resulting in colossal
damage to the apple production in the valley. Noteworthy, the occurrence of these two recent events
is in line with a general tendency for the more frequent occurrence of extreme weather events over
Kashmir [
46
,
47
]. Whereas the Department of Horticulture estimated losses after the November 2018
snowfall at INR 5 billion (https://bit.ly/2TDATpR), damage observed following the November 2019
snowfall was more pronounced and resulted in the losses amounting to INR 22.5 billion (or c. US$302
million; https://bit.ly/3aJxmvN). Even if meteorological records are lacking to confirm the statement,
reports suggest that the 2019 snowfall was the heaviest that Kashmir experienced over the past six
decades, claiming 7 lives (https://bit.ly/2wInowb) and damaged power infrastructure worth INR
220 million (or c. US$2.95 billion; https://bit.ly/2TG99Rj). Historical precipitation data from India
Meteorological Department (IMD) also point to a consistent increase in precipitation totals across the
valley, and are thus in line with what is projected to occur in the Kashmir Region by the end of this
century [23].
The horticultural sector of the Kashmir Valley, dominated by apple orchard, contributes 27% (INR
50 billion or US$670 million) to the economy of Jammu and Kashmir [
48
], and the government is
contemplating to strengthen the sector further. This study indicates that of the total area of 1330 km
2
under apple orchards in Kashmir Valley, more than half of orchards (56%) are located in south Kashmir.
Sustainability 2020,12, 9206 10 of 14
Given the stark promotion of the horticultural sector, massive areas under irrigation-intensive rice
paddy currently undergo conversion to seemingly more viable apple orchards [
49
52
]. However,
we argue that the ever-increasing area under orchards may well become unsustainable in economic
(but also in environmental) terms given the challenges of changing climate [
31
,
53
] and the related
exacerbation of extreme weather events. In addition, a massive increase of orchards could ultimately
result in serious health repercussions [
54
] as a result of the reckless use of pesticides [
55
]. While the
changing climate may shift the flowering patterns of apples in the long term [
56
58
], the erratic snowfall
events like those of 2018 and 2019 have already resulted in unprecedented losses that have been
aecting local economy seriously (Figures S4 and S5). Any further developments in the horticultural
sector should thus be studied carefully using state-of-the-art scientific approaches to consider whether
the promotion of horticulture in Kashmir will be socio-economically and ecologically viable in the
long run.
Analyzing data made available by the Department of Horticulture, we find that the November 2018
snowfall damaged 35% of the orchards in Kashmir Valley. Data for the November 2019 snow episode
has not been made available yet, but it is highly likely that damage will be more pronounced than the
2018 erratic snowfall event. This assumption is supported by information from the Kashmir Valley
Fruit Growers cum Dealers Union who estimated that a stunning 80% of the fruit plants of all orchards
of the Kashmir Valley were uprooted during the November 2019 snowfall (https://bit.ly/2TItfKR).
Analysis of ERA-5 reanalysis datasets suggest that the November 2018 and 2019 snowfalls were
formed after a trough (i.e., a low-pressure system) developed with the arrival of a WD. Weather in Kashmir
was influenced further by a cyclonic circulation that developed south of Jammu-Kashmir, as well as the
intrusion of cold air masses from northern latitudes. The situation was especially intense in November
2019. Whereas the influence of WD on winter precipitation and snowfall over the Himalaya [
59
,
60
]
including the Kashmir Region [
40
,
61
] is pronounced, it is more so the early arrival of the snowfall
episodes in November 2018 and 2019 that made these two events special. Although snowfall linked to
WDs normally occur in Kashmir between November and April, large intense events are rare in the early
season and normally occur in February and March [
40
]. According to the records and our observation,
the large snowfall events in the first weeks of November 2018 and 2019 can be considered anomalies
based on existing records [
39
]. Some existing studies suggest that the occurrence of WD is increasing
under current conditions already in winter [
39
], and that the frequency of WDs may increase further
under climate change [
62
], resulting in increased winter snow precipitation [
42
]. Other studies, however,
have found a decreasing or unchanged trend of WD over the last decades [
63
,
64
]. While it was not
the goal of this study to identify changes in the occurrence of WD situations, we find that the earlier
arrival of WD in early winter—along with cold temperatures arriving from northern latitudes and the
advection of moisture from the still-warm Arabian Sea—indeed pose a serious threat to the agriculture
and horticulture sectors in the region, even more so should the incidence of such early-season events
become more frequent. We, therefore, call for research on intra-seasonal changes of WD occurrences or
more reliable indicators to predict these events [
34
] to mitigate further economic losses in the agricultural
sectors and possibly by diversifying (cash) crops with more and more resilient species.
5. Conclusions
The untimely and extreme weather patterns over Kashmir in recent years have not only impacted
ecosystems but also severely dented the economic sectors. Over the past few years, Kashmir Valley
witnessed two such erratic snowfall events in late autumn 2018 and 2019—both events destroyed apple
orchards across the valley. This assumes importance since the government is contemplating to expand
the horticulture sector from INR 60 billion to 300 billion. As a result of recent losses and to boost the
production of apple, government has recently introduced a highly-subsidized High Density Apple
Plantation (HDAP) scheme with plant protection mechanism (like anti-hail nets and trellis system
comprising of metallic/wooden stakes and wiring). This set up minimizes damage to the apple trees in
case of heavy snowfall and is getting popular among the apple orchardists of Kashmir. However, many
Sustainability 2020,12, 9206 11 of 14
experts fear that the HDAP might altogether wipe out local apple cultivars in this highly competitive
business, with negative impacts on local varieties and diversity of species.
Using data from multiple sources (remote sensing, ERA-5 reanalysis, field data, and ancillary
information), we characterize the two erratic snowfall events to conclude that the snow depths recorded
during the November 2019 snowfall were not only larger (mean snow depth =47 cm) than during
the November 2018 event (mean snow depth =26 cm), but that the most recent event on record was
probably also unique in terms of magnitude and timing over the last 60 or so years. The installation of
snow gauges at all IMD-managed weather observatories are critically needed to get credible baseline
data on snowfall in the region and on event-specific snowfall patterns, not only to inform policy but
also to facilitate the decision makers with scientifically sound information.
Supplementary Materials:
The following are available online at http://www.mdpi.com/2071-1050/12/21/9206/s1,
Figure S1: Figure S1: (a) November 2018 snow extent and (b) November 2019 snow extent as observed from
Sentinel 2A and Landsat satellites, Figure S2: Left column: Temporal evolution of the cloud as observed by
INSAT-3D imagery for 0000UTC for 2nd, 3rd, and 4th, November 2018. Right column: ERA-5 derived upper-level
winds at the same moment, Figure S3: Left column: temporal evolution of the cloud as observed by INSAT-3D
imagery for 0000UTC of 6th and 7th November 2019. Right column: ERA-5 derived upper-level winds at the
same moment, Figure S4: Field photographs showing damages to the Apple orchards in the snowfall events
of 2018 and 2019, and Figure S5: Field photographs showing damage caused by untimely snowfall to the fruit
during harvesting. Table S1: Field-measured snow depth for 2018 and 2019 November snowfall events, Table S2:
District-wise area under orchards in Kashmir Valley, and Table S3: Zone-wise orchards area of Kashmir Valley.
Author Contributions:
Conceptualization, I.R., U.M. and J.A.B.C.; methodology, I.R., U.M., S.A., J.A.B.C.; software,
I.R., U.M., S.A., J.A.B.C.; validation, I.R., U.M., S.A., J.A.B.C.; formal analysis, I.R., U.M., S.A., J.A.B.C.; investigation,
I.R., U.M., S.A., J.A.B.C.; resources, I.R., U.M., J.A.B.C., N.A.N., I.A.B., S.L.; data curation, I.R., U.M., J.A.B.C.,
N.A.N., I.A.B., S.L.; writing—original draft preparation, I.R., U.M.; writing—review and editing, I.R., U.M.,
J.A.B.C., M.S.; visualization, I.R., U.M., J.A.B.C.; supervision, I.R., J.A.B.C.; project administration, I.R. All authors
have read and agreed to the published version of the manuscript.
Funding: This research received no external funding
Acknowledgments: The authors express gratitude to United States Geological Survey (USGS) for freely hosting
the Sentinel and Landsat satellite data used in this analysis. The authors are grateful to European Centre for
Medium-Range Weather Forecasts (ECMWF) for freely providing the reanalysis data. The authors acknowledge
the Directorate of Horticulture, Kashmir, for providing the horticulture damage data analyzed in this study.
The second author also acknowledges the support of Department of Science and Technology, Government of India
(DST, GoI) for the INSPIRE fellowship (Grant Number: IF180682) for pursuing Ph.D. The suggestions from the
two anonymous reviewers helped in improving the manuscript content and structure.
Conflicts of Interest: The authors declare no conflict of interest.
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... However, most of the evidences of impacts of extreme climatic events on plants have been reportedfrom the variousagro-ecosystems (particularly the commercially cultivated crops). For example, in Kashmir valley, extreme snowfall events (frosty conditions) are reported to affect the flower parts, pollination process and fruit setof many horticulture crops such as apple, almond, peach, plum, apricot and cherry (Rashid et al., 2020;Kumawat et al., 2022). Besides this, no other efforts have been initiated to knowabout theconsequences of extreme events on natural plant communities in the region. ...
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There is aprojected intensification of extreme climatic events under future climate, however our general understanding of impacts of such events to plant communities in mountain ecosystems is limited. Among such extreme events, untimely/un- seasonal snowfall at the time of growing season when it is unusual, can damage plant reproductive and vegetative structures and result in population dieback in the high-altitude ecosystems. Here, we report the findings from observation following an untimely snowfall event during the growing season (13 September 2021) in alpine region (Rohtang: ~ 4450 m amsl) of west- ern Himalaya. In this study, we report on major damage to11 snowbed-restricted plant species and show that a short extreme event could have potential detrimental effects that can have long-term ecological impacts. An assessment of plant damage for vegetative (leaves and stem) and reproductive (flower and fruits) structures was made by visual inspection on 30 individuals per species. Additionally, the mortality and adaptation pattern (recovery after event) of an individual was also estimated in terms of “sub-lethal” (reversible) or “lethal” (irreversible) damage to the tissues by re-surveying the site and reviewing the status of individuals after a period of one week. We observed thatvarious species, suffered damagein the range of 20-100% of individuals/specieswith injuries to leaves, 10-100% to stems, 23.33- 100% to flowers and 53.33-76.67% to fruit-set. Further, recovery from damages after injuries indicate that, among various species, plant stem (46.67-100%) has a high revival po- tential, followed by flowers (10-90.91%), leaves (13.33-86.67%), and fruits (18.18-82.60%). Further, the mortality percentage of individuals ranged between 3.33-16.67% for various species, while some species (Sibbaldia cuneata, Sibbaldia purpurea, Saussurea gossypiphora and Saxifraga jacquemontiana) exhibited almost nil mortality. Our results suggest that the reproduc- tive structure of alpine plant species are more vulnerable to short-term extreme climatic events than the vegetative structures. Consequently, such extreme events have the potential towards catastrophic reproductive failure and population die-back in the alpine plants communities in the long-term, if the extent, intensity and harshness of these events increased in the future.
... The study was carried out in the Kashmir Himalaya, a region located in the northwest corner of the Himalaya biodiversity hotspot, covering an area of ~15,000 km 2 (Rashid et al., 2020). The climate of the region is mainly continental temperate, with chilly and snowy winters and hot and dry summers . ...
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... Our study was conducted in Kashmir Himalaya, which has an area of approximately 15,000 km 2 with 64% of it mountainous (Fig. 1). The climate is primarily continental and temperate, with cold, wet winters and relatively dry, hot summers (Rashid et al. 2019(Rashid et al. , 2020. The region's temperature ranges from an average daily maximum of 31 °C and minimum of 15 °C during summer to an average daily maximum of 4 °C and minimum of −4 °C during winter. ...
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Symphyotrichum subulatum (Michx.) G.L.Nesom (Asteraceae) is reported as a new alien plant record for Kashmir Himalaya. The taxonomic identification of species is confirmed on the basis of shape of involucre, floral and seed characters. Detailed description, distribution map, and comments on distribution and ecology are also provided along with photographic illustration to facilitate easy identification of this species.
... Besides, high-resolution imagery provided by ESRI as basemap was used for the year 2020. Manual delineation in a GIS environment at a 1:30,000 scale was adopted to map different land cover categories (Malik et al., 2015;Rashid, Majeed, Aneaus, Cánovas, et al., 2020). Detailed ground truth surveys were carried out for validation and accuracy assessment of delineated LULC of 2020 using Trimble Juno 5B handheld GPS receiver (Trimble Juno 5B; Horizontal accuracy: ±5 m). ...
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Chapter
This Manual is based on the research work carried out by the authors in the Kashmir Himalaya. For documentation of the alien flora, we regularly surveyed the study region for field sampling, collection of data and plant specimens from 2019 to 2021. The study region lies between coordinates 33° 20′ to 34° 50′ North Latitude, 73° 55′ to 75° 35′ East Longitude and altitude of the region ranges from 1600 to 5420 m amsl [74]. Kashmir Himalaya covers an area of ~15,000 km2 with 64% of the area being mountainous [85]. The 'Karawas’, which are plateau-like tablelands developed during the Pleistocene Ice Age and made of clay, sand, and silt of lacustrine origin, are a prominent geological feature of the region [86]. The region, located at the junction of the Holarctic and Paleotropical Floristic Realms, is home to a rich floristic diversity of considerable scientific interest and economic promise [87]. The stunning scenery of this biodiversity-rich area has drawn visitors from far and wide from very early times. This is one of the key reasons for the intentional or unintentional introduction of various floral elements from various phytogeographical regions of the world, which have been supported by distinct bioclimates, a wide range of elevations, and habitat heterogeneity. In fact, the region has long served as a major halting point for historical trade routes travelling from far-east Asia to the Mediterranean coast via Central Asia and vice versa [88]. The climate is primarily of continental temperate type with cold and wet winters and relatively dry and hot summers [89]. The temperature of the region ranges from an average daily maximum of 31°C and minimum of 15°C during summer to an average daily maximum of 4°C and minimum of -4°C during winter and receives an average annual precipitation of 1055 mm, mostly in the form of snow. The natural vegetation of the region mostly consists of alpine meadows and coniferous forests [74] (Fig. 2.1).
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Western Himalaya receives heavy precipitation due to western disturbances embedded in the eastward moving upper tropospheric Rossby wave train, especially in the winter months. The interaction of intricate topography and large-scale atmospheric dynamics plays an essential role in determining the amount of precipitation over this region. The cold air intrusion causes the middle troposphere to be baroclinically unstable and develop a sharp gradient of potential temperature which in turn is responsible for non-conservation of Ertel potential vorticity. Baroclinic instability provided energy of the disturbance (latent heating) by strengthening the influence of baroclinicity on the vertical component of relative vorticity causing intense convection. The increase in the baroclinic influence on the vertical component of relative vorticity in the moist middle and upper troposphere led to extreme precipitation over Jammu and Kashmir region during 24–27 January 2017 and can be considered as one of the prognostic parameters for predictions of such event.
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