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High- mountain Asia (HMA) is referred to as the Asian
water tower1,2, as it hosts the greatest number of glaciers
(95,500) and largest ice volume (7.02 ± 1.82 × 103 km3)
outside of the polar regions3–7. Approximately 2 billion
people benefit in some way from HMA glaciers, as they
regulate climate, support ecosystems, have cultural
significance8,9 and modulate the release of freshwater
into rivers10,11, sustaining irrigated agriculture, munic-
ipal water supplies, hydropower and other industries12.
The Himalaya and Karakoram mountain ranges
(the H- K) extend across Afghanistan, Pakistan, China,
India, Nepal and Bhutan, and cover areas of 650,000 km2
and 90,000 km2, respectively11. Together, they harbour
almost half (47%) of the glacial ice volume in HMA5
(FIG.1). Approximately 869 million people living in the
Indus, Tarim, Ganges and Brahmaputra river basins13 rely
on the water and climate modulation provided by the H- K.
Under a changing climate, most HMA glaciers are
losing mass, although the response has varied between
individual glaciers and catchments14–18, making regional
assessments and projections of glacier change19–21 and
their environmental impacts12,22 complex. The great-
est rates of loss in the twenty- first century are in the
Himalaya and Nyainqêntanglha (Nyenchen Tanglha)
Mountains3,16,22, whereas glaciers in the Karakoram,
Pamir Mountains and western Kunlun Mountains have
exhibited unusually little change relative to most of the
world’s mountain glaciers, a phenomenon known as
the Karakoram anomaly15,16,22–24. These diverse H- K
glacier changes are affecting their hydrological role
and, in places, the frequency, intensity and duration
of glacier-related hazards, such as glacial- lake outburst
floods (GLOFs), glacier floods and debris flows8,25,26.
With the exception of the glaciers of the Karakoram
anomaly23, ice loss across the H- K has been increasing
for several decades11,17,27,28 and is driving an increase
in summer meltwater release that is already reaching
a peak in some catchments29. Under the representa-
tive concentration pathway (RCP) 4.5 scenario, this
‘peak water’ is predicted to be reached by around 2050
in all four of the H- K river basins (the Ganges, the
Indus, the Tarim and the Brahmaputra)4,29. Peak water
will be followed by a decline in summer flows as the
glacier- covered area shrinks, even if summer temper-
atures continue to increase12,29, and will be followed,
ultimately, by the loss of the H- K glacier ice reserve12,30.
Glacial change and hydrological
implications in the Himalaya and
Karakoram
YongNie
1 ✉ , HamishD.Pritchard
2, QiaoLiu1, ThomasHennig3, WenlingWang4,
XiaomingWang5, ShiyinLiu4, SantoshNepal6, DenisSamyn6, KennethHewitt7
and XiaoqingChen1
Abstract | Glaciers in the Himalaya–Karakoram mountain ranges harbour approximately half of
the ice volume in High- mountain Asia and modulate the flow of freshwater to almost 869 million
people within the Indus, Tarim, Ganges and Brahmaputra river basins. Since the mid- twentieth
century, rising temperatures have led to unsustainably high melting rates for many glaciers,
particularly in the Himalaya, temporarily increasing summer meltwater run- off but continuously
reducing the ice- storage volume. In this Review, we discuss how and why glaciers and meltwater
supplies have changed, how they will likely evolve in the future and how these changes impact
water resources and water- related hazards. Heterogeneous glacier retreat is changing streamflow
patterns, in turn, affecting the incidence of glacial- lake outburst floods and exacerbating the risk
of flooding and water shortages associated with future climate change. These changes could
negatively impact downstream populations and infrastructure, including the thriving hydropower
sector and some of the world’s largest irrigated agriculture systems, by making water flow more
extreme and unpredictable. An improved insitu monitoring network for weather, hydrology and
glacier change is a crucial requirement for predicting the future of this resource and associated
hazards, and their impact on regional water, energy and food security.
✉e- mail: nieyong@imde.ac.cn
https://doi.org/10.1038/
s43017-020-00124- w
ReVIewS
Nature reviews
|
Earth & EnvironmEnt
This progressive deglaciation will mark a transition
from the glacier- modulated hydrological regime exper-
ienced throughout much of the Holocene and twenti-
eth century, which supported the major societies and
hydro- economies of the H- K basins throughout a con-
tinuing period of rapid growth12,29, to a regime depen-
dent on fluctuating summer rainfall31–33. Furthermore,
the processes of glacier retreat3,11,22 (along with periodic
surging behaviour34,35) might increase the likelihood of
glacial and hydrological hazards, such as GLOFs, river
flooding and glacier debris flows, and, indeed, the H- K
is one of the most vulnerable regions to glacier- related
disasters8,36–39.
The impact of this glacio- hydrological transition on
the vulnerability of downstream societies to drought12,
natural hazards, the output of hydropower plants40 and
the productivity of agriculture in Central Asia and on the
Indo- Gangetic Plain10,12 will vary temporally and spa-
tially over this complex terrain, in ways that are not
yet well understood. Indeed, any changes in biophys-
ical socio- economic conditions of the H- K, including
water supply, demand, climate change and water- sharing
mechanism, can affect the large populations living in the
major river basins of the H- K region2. Moreover, rapid
population growth12 and socio- economic development
increase the exposure to glacier hazards faced by people
and major infrastructure, such as planned hydropower
projects (HPPs)41 and the Sino- Nepal and Sino- Pakistan
railways. A thorough understanding of glacier dyna mics
and their hydrological impacts in the H- K is, there-
fore, increasingly important to regional strategies for
adaptation to climate change.
In this Review, we discuss observed H- K glacier
changes, their drivers and likely future trends, empha-
sizing the hydrological impact of these changes on
river run- off and GLOFs. The consequences for water
resources and hydropower infrastructure relied upon
by downstream societies are then outlined. Finally, we
discuss the needs for increased survey and continuous
monitoring in the H- K to improve hazard and resource
forecasting in an area with remarkably few measure-
ments of, for example, weather and river flow, the thick-
ness of glacier ice and debris, rates of glacier and lake
change, and the associated stability of mountain slopes
and moraine dams.
Glacier distribution and change
The 32,637 glaciers in the H- K cover a total area of
41,514 km2 (REF.6) and are distributed heterogene-
ously (FIG.1). Cold, polythermal and temperate glacier
types are all present and exhibit the diverse, typical
characteristics of HMA, with clusters of surging gla-
ciers, debris-free and debris- covered areas, and both
land-terminating and lake- terminating margins17,42,43.
Contemporary glaciation is more extensive in the
Karakoram (12,206 glaciers covering 21,835 km2, around
24% glacier cover) than in the Himalaya (20,431 glaciers
covering 19,679 km2, around 3% glacier cover) (FIG.1).
Moreover, Karakoram glaciers are, on average, twice the
size of those in the Himalaya, and the estimated ice vol-
ume is greater, at ~2,130 km3 compared with ~1,200 km3
(REF.5). In total, the H- K glaciers account for 100%, 93%,
31% and 22% of the total ice volumes in the Ganges,
Indus, Brahmaputra and Tarim river basins, respectively.
The contrasting distributions of Himalayan and
Karakoram glaciers at comparable altitudes (5,360 m
mean elevation versus 5,420 m, respectively) results
from differences in the dominant precipitation- bearing
atmospheric circulation patterns in these ranges, namely,
the winter westerlies and the Indian summer mon-
soon, and their interactions with the region’s extreme
topography3,27,44. The influence of the Indian summer
monsoon decreases from east to west and from south to
north in the Himalaya, whereas the influence of the west-
erlies declines from west to east in the Karakoram11,45,46
(FIG.1). As a result, Himalayan snowfall arrives primarily
in the summer and is restricted to higher altitudes than
snowfall in the Karakoram, which arrives primarily in
the winter46.
Notably, some uncertainties remain in mapped gla-
cier extent in the H- K7,15,16,47, and glacier inventories such
as the Randolph Glacier Inventory (RGI) and Glacier
Area Mapping for Discharge from the Asian Mountains
(GAMDAM)5–7,15,18 show differences as a result of, for
example, the variety of data sources and methods used
to distinguish glacier margins (Supplementary Table1).
For instance, the total glacier area in GAMDAM is ~2%
less than that in RGI 6.0, and there is a 10% uncertainty
in area related to the limited availability of contempo-
raneous and recent cloud- free and shadow- free satellite
images18. These discrepancies highlight the ongoing
need to continue regional glacier mapping11 to bet-
ter analyse the contribution of H- K glaciers and their
hydrological impact at a regional scale.
Key points
•Himalayanglaciershavelostmassatanacceleratingrateinrecentdecades,
incontrastwithrelativelystableKarakoramglaciers.
•Underarangeofclimatechangescenarios,therun-offofglaciermeltwaterinthe
HimalayaandKarakoramislikelytopeakinthenextfewdecades.
•Afterglacialrun-offpeaks,run-offwilldeclineastheglaciersinbothmountainranges
shrink,althoughthemagnitudeandtimingofthepeakandtherateofsubsequent
declineareuncertain.
•Basinrun-offregimeswillbecomemorerain-dominatedasthemodulatingeffectof
glaciersdecreases,andthisislikelytoincreasetheimpactofdroughtsandfloods.
•Thefrequencyofglacial-lakeoutburstfloodsandrun-offfloodshaveincreased
recentlyandcouldincreasefurtherincomingdecades,threateningexistingand
plannedhydropowerinfrastructuredownstream.
•Alower-emissionsclimatechangepathwaywouldreducetherateofglacierloss,
increasingthetimeavailableforadaptation.Thispathwaywouldhaveconsiderable
socio-economicbenefits.
Author addresses
1InstituteofMountainHazardsandEnvironment,ChineseAcademyofSciences,
Chengdu,China.
2BritishAntarcticSurvey,Cambridge,UK.
3Philipps-UniversitätMarburg,FacultyofGeography,Marburg,Germany.
4InstituteofInternationalRiversandEco-security,YunnanUniversity,Kunming,China.
5StateKeyLaboratoryofCryosphericSciences,NorthwestInstituteofEco-Environment
andResources,ChineseAcademyofSciences,Lanzhou,China.
6InternationalCentreforIntegratedMountainDevelopment,Kathmandu,Nepal.
7DepartmentofGeographyandEnvironmentalStudies,WilfridLaurierUniversity,
Waterloo,Canada.
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Glacial change
Observed glacier changes in the H- K vary temporally and
spatially. Historical records of 154 glacier termini since the
mid- nineteenth century were compiled in 2018, revealing
that most Himalayan glaciers retreated, whilst glacier ter-
mini in the Karakoram stayed either unchanged, retreated
or advanced11,27, and some surged35,36. When considering
total glacial areas, shrinking is extensive in the Himalaya,
with a decline in area at a mean annual rate of −0.36% per
year between 1960 and 2010 (REF.27). Similarly, Himalayan
glaciers were estimated to have lost mass (thinned) at an
average rate of 0.37 ± 0.15 m water equivalent (w.e.) per
year from 2000 to 2016 (REF.15, FIG.2a) or 0.40 ± 0.10 m
w.e. per year from 2000 to 2018 (REF.16). Moreover, various
studies have found an accelerating rate of loss since 2000
(REF.14), between the 1975–2000 period (0.22 ± 0.13 m w.e.
per year) and the 2000–2016 period (0.43 ± 0.14 m w.e. per
year)17, and between the 1974–2000 period (0.25 ± 0.09 m
w.e. per year) and the 2000–2015 period (0.39 ± 0.12 m w.e.
per year)28.
In the Karakoram, 1,219 glacier termini were studied
from 1976 to 2012, showing that 969 were unchanged
(79%), 93 retreated, 56 advanced and 101 glaciers (8%)
surged over that time period48. Several studies have
found that shrinking is not significant for Karakoram
glaciers: areal growth at +0.06% per year was reported
in the central Karakoram from 2001 to 2010 (REF.49),
at +0.004% per year in the Shyok Valley from 1973 to
2011 (REF.50) and −0.002% per year for the Siachen Glacier
(East Karakoram) from 1980 to 2014 (REF.51). Indeed, the
mean 2000–2016 mass loss rate of Karakoram glaciers
was only 0.03 ± 0.07 m w.e. per year15 or 0.09 ± 0.12 m w.e.
per year from 2003 to 2008 (REF.20) and 0.04 ± 0.04 m
w.e. per year from 2000 to 2018 (REF.16). Similarly, mass
budgets were nearly balanced for glaciers in the Hunza
catchment (loss of 0.06 ± 0.08 m w.e. per year, North
Karakoram) between the 1970s and 2009 (REF.24) and the
Siachen Glacier (loss of 0.03 ± 0.21 m w.e. per year, East
Karakoram) between 1999 and 2007 (REF.51). Recent posi-
tive mass balances since 2000 at the north- east of the
Karakoram have also been observed15,20,52 (FIG.2a).
Drivers of changes
The heterogeneity of spatial change in H- K glaciers
is mainly explained as a result of enhanced westerlies
(which bring more precipitation), a weakened summer
monsoon (less precipitation) and warmer summers in
the context of global warming3,34. Himalayan glaciers
are rapidly losing mass because of rising temperatures
and decreasing precipitation at high altitude53, whereas
≥5,001 ≥6
4–6
2–4
1–2
0.5–1
0.1–0.5
<0.1
Capital
River
Basin boundary
2,501–5,001
501–2,500
101–500
51–100
26–50
6–25
1–5
0
Westerlies
Indian monsoon
East Asian
monsoon
65° E
300 km0
45° N
40° N
35° N
30° N
25° N
20° N
70° E75° E80° E85° E90° E95° E100° E
Population per km2
Almaty
Bishkek
Tashkent
Karakoram
Himalaya
Dushanbe
Kabul
Islamabad
Indus
Tarim
Ganges
Brahmaputra
New Delhi
Kathmandu
Dhaka
Thimphu
Glacier volume (km3)
Fig. 1 | High-mountain Asia population and glacier volume. Population13 per km2 and glacier volume aggregated by
a 0.05 × 0.05 degree grid5, and the Indus, Tarim, Ganges and Brahmaputra river basins supplied by Himalaya–Karakoram
glaciers. Outlines of the Himalaya–Karakoram are referenced to Bolch etal. (2012)11. The Himalaya and Karakoram
mountain ranges harbour 47% of the glacial ice volume in High- mountain Asia, nourishing densely populated
downstream areas.
Nature reviews
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Earth & EnvironmEnt
Reviews
Karakoram glaciers are relatively stable because of a ser-
endipitous balance between changes in accumulation
and ablation11,34. The mechanisms that have led to this
balance are still not fully understood but arise from the
interplay between a broader regional- warming- induced
increase in mass loss and more localized winter
mass gain and summer cooling due to enhanced
snowfall11,27,34,54–56.
The regional drivers are superimposed upon the
diversity of glacier sizes, types, morphological variables
(such as elevation, slope and elevation-dependent war-
ming)34,42,57, extent of debris cover17,22, lake evolution17,28,42
and tendency to surge. For example, about 13% of the
H- K glacial area is debris-covered (Himalaya 16%,
Karakoram 9%)58,59 and debris cover is particularly
prevalent on both the larger Karakoram glaciers and
south- facing Himalayan glaciers, where over 20% are
debris- covered60,61. Debris cover directly affects ice melt
rate and, indirectly, changes in length and area, forma-
tion of ice cliffs62 and supraglacial lakes and ponds63,
River
Basin boundary
Himalaya ranges
Karakoram ranges
40° N
35° N
30° N
25° N
40° N
35° N
30° N
25° N
65° E 70° E 75° E 80° E 85° E 90° E 95° E 100° E
Ganges
Ganges
Indus
Indus
Tarim
Tarim
Brahmaputra
Brahmaputra
Glacier mass change
(m w.e. per year)
Volume
remaining
rate (% )
–0.79 120.0–500.0
500.1–1,000.0
1,000.1–1,500.0
1,500.1–3,447.7
–0.40
–0.30
–0.20
–0.06
+0.06
+0.26
Total glacier
area (km2)
Total glacier
area (km3)
0 300 km
b
5
15
25
40
55
84
00–10.0
10.1–40.0
40.1–120.0
120.1–512.0
a
Fig. 2 | Glacial change in the Himalaya–Karakoram. a | Glacier area and mass balance between 2000 and 2016 for a
1 × 1 degree grid15 (note, the exclusion of individual glaciers of less than 2 km2 led to no data for some grids where there is
data in panel b). b | Glacier volume and predicted volume change59 in High- mountain Asia by the end of the twenty- first
century under the representative concentration pathway (RCP) 4.5 model ensemble, aggregated by a 1 × 1 degree grid.
Total glacier volume was calculated by the GlabTop2 model182 using Randolph Glacier Inventory (RGI) data 5.0 and Shuttle
Radar Topography Mission (SRTM) digital elevation model data59, and the glacier evolution model was described in detail
by Kraaijenbrink etal. (2017)59. Himalayan glaciers have lost their mass at an unsustainable rate, whereas Karakoram
glaciers have been nearly balanced, and a larger fraction of the Karakoram glacier area will survive until the end of the
twenty- first century than in the Himalaya. w.e., water equivalent.
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ultimately influencing the glacial response to climatic
change60. Its direct influence on ice melt rate is strongly
dependent on its thickness58,59,61, however, and both
debris extent and thickness change with time and
space58,59,61. Debris reduces the surface albedo, leading
to enhanced melt when the cover is thin (upto a few
centimetres), but also insulates, slowing or preventing
melt when the cover is thicker than this threshold59.
At the regional scale, these countervailing effects have
led to overall similar average thinning rates for debris-
covered and clean ice17,28,42. Prediction of future melt rates
and meltwater discharge from debris- covered areas is
hindered by an almost universal lack of debris thickness
measurements, however, because observing this parame-
ter over large areas remains a significant challenge60,64 and
because debris cover has been increasing in the Himalaya
in the past decades27,65,66.
Supraglacial ponds and proglacial lakes also impact
glacial changes, as the lakes and ponds absorb and
transmit thermal energy to glacier ice67,68, enhanc-
ing the local melt rate and promoting cliff collapse or
calving69–71. The buoyancy introduced by proglacial
lakes can also reduce effective pressure at the glacier
bed, enhancing flow and causing dynamic thinning.
These lake- driven feedbacks are accelerating Himalayan
glacier mass loss, with higher rates of melt and retreat for
lake- terminating than land- terminating glaciers
for periods between the mid-1970s, 2000 and the
mid-2010s17,28,42. For the Karakoram, the almost
unchanged area in glacial lakes72 corresponds with the
relatively stable mass balance. However, short- lived
(weeks to months) ice- dammed lakes periodically form
following surges73, and the melting of ice dams can lead
to GLOFs. Better understanding of the dynamics of
glacier- lake systems is fundamental to predicting the
evolution of lakes and contacted glaciers, and their
potential role in outburst- flood events.
Future glacier change
Increasing temperatures and slightly increasing pre-
cipitation (albeit highly variable and uncertain) are
predicted for the H- K region, consistently leading to
glacier mass loss but with variability among various
climate models and RCPs4,59,74. Even if global temper-
ature is limited to 1.5 °C above pre- industrial levels,
a projected warming of 2.1 ± 0.1 °C under the conser-
vative RCP2.6 scenario for HMA will result in an
overall 36 ± 7% mass loss by the end of the twenty- first
century (EOC)59. For the RCP4.5 scenario, mass loss
in HMA as a whole reaches 46 ± 11% (REF.4) or 49 ± 7%
(REFS59,75,76) (depending on the inputs and models used),
with only 74% of the Karakoram glacier area and
32% of the Himalayan glacier area remaining by the
EOC59 (FIG.2b). With these glacier changes, debris
cover and the abundance and volume of supraglacial
ponds and lakes are likely to increase across the H- K
in coming decades28,58,65,77. Though improvements are
needed in quantifying glacier surge dynamics and in
the impacts of debris, ponds and lakes on ice mass
change and run-off, the predicted changes will sub-
stantially alter both the hydrological regime and glacier
hazards3,8,14,30 in H-K river basins.
Hydrological impacts
Glacial change directly affects meltwater run- off and,
consequently, the composition and seasonal variability
of river flows descending from the mountains. Together,
these changes impact the incidence and magnitude of
lake- outburst floods in H- K basins. In this section, the
impacts of glacial changes on hydrology are discussed.
Glacier and basin run- off
Glacier run- off contributes to basin total run- off, which
is composed of rainfall run- off, snowmelt, base flow
(groundwater) and glacier melt74 (FIG.3a–c). Part of the
glacier run- off and snowmelt also infiltrates into soil and
contributes to groundwater flow. There are substantial
differences in glacial run-off and its contribution to basin
total run-off amongst the H-K basins, owing to variations
in glacier- covered area and volume, accumulation and
melting periods, atmospheric circulation and the mag-
nitude of other contributing components74,76,78,79. Based
on the percent contribution to total run- off, glacier
meltwater is more important in the arid and semi- arid
westerlies- controlled Tarim (42%, annual glacier melt-
water of 14 km3)78 and the Upper Indus Basin (33%)79
than the monsoon- controlled Upper Brahmaputra
Basin (16%) and Upper Ganges Basin (12%)74. It should
be noted, though, that differences in definition of gla-
cier run- off affects the specific contributing rate76. The
glacier melt contribution to streamflow decreases
substantially with decreasing altitude from the gla-
cier terminus to the lowlands74,80,81, particularly in
monsoon- dominated mountain ranges. For example,
precipitation dilutes the fraction of meltwater in the river
leaving the Langtang catchment (area of 36 km2)82 in the
Upper Ganges Basin from ~58% to just a few percent by
the time it reaches the river mouth12.
Recent trends. In HMA, the Indus, Ganges and
Brahmaputra river basins had the greatest total excess
glacier meltwater run- off due to the loss of glacier ice
(4.55, 3.26 and 5.23 Gt per year between 2000 and 2018,
respectively, above the volume released if the glaciers were
in balance)16. Temperature- controlled seasonal glacier
melt occurs mainly during June–September and sustains
seasonal streamflow among the H- K basins. The sea-
sonal melt plays a dominant role in the Tarim and Indus
basins74,83,84 but a secondary role in the Brahmaputra and
Ganges basins, where the melt season coincides with
monsoon precipitation74,85.
Temperature- controlled glacier run- off shows a posi-
tive trend in most heavily glacierized sub- basins because
of warming. For instance, increasing discharge in the
central Karakoram (Shigar gauging station) was obse-
rved from 1985 to 2010, particularly during the melt
season, where flow is dominated by glacial melt,
which has increased by ~14.54 m3 s−1 during July and
August55. From 1961 to 2012, the June and August dis-
charges at Yogo (eastern Karakoram) and Shigar gaug-
ing stations increased by ~20.73 m3 s−1 (REF.86). Over the
same period, discharge at Astore River basin (western
Himalaya) slightly increased for all months except July86.
Consequently, long- term discharges in the Upper Indus
Basin significantly increased from October to May86
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River
Basin boundary
Himalaya ranges
Karakoram ranges
40° N
35° N
30° N
25° N
65° E 70° E 75° E 80° E 85° E 90° E 95° E 100° E
1990
2000
2010
2020
2030
2040
2050
2060
2070
2080
d
TR PTR BF GMSMRR
4000 800 1,200
TR PTR BF
Year of glacier
run-off peak
GMSMRR
4000 800 1,200
b UGB c UBB
TR PTR BF GMSM
RR
4000 800 1,200
Annual run-off (mm)
a UIB
2005 2025 2050 2075
4000 800
Annual run-off (mm)
1,200
2000
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
0
5
10
15
20
25
Q (m3 s–1)
Q (m3 s–1)
2075
0
5
10
15
20
25 mk l
BF
GM
SM
RR
0
100
200
0
100
200
100
200
0
100
200
2000 2020 2040 2060
Years Years
2080 2100
0
2000 2020 2040 2060 2080 2100
e Indus f Tarim
g Brahmaputra h Ganges
80
40
0
–40
–80
GR change (%) GR change (%)GR change (%)
Jun. Jul. Aug. Sep.
80
40
0
–40
–80
Change (%) of GR ratio
Jul. Aug. Sep. Oct.
Indus Tarim
Brahmaputra Ganges
ij
Almaty
Bishkek
Tashkent
Dushanbe
Kabul
Islamabad
Indus
Tarim
Ganges Brahmaputra
New Delhi
Kathmandu
Dhaka
Thimphu
0 300 km
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over the 1961–2012 period. The trend was particu-
larly strong for May, which had a maximum increas-
ing rate of 12.97 m3 s−1. Similarly, in the Tarim Basin,
glacier total run- off during 1991–2006 increased by
12.8% and its contribution rate to total basin run- off
increased by 5.0% relative to 1961–1990 (REF.78), leading
to rising streamflow87. In several unmanaged glacier- fed
sub- basins of the Upper Ganges Basin (Himalaya),
streamflow also increased during 1990–2010 (REF.88).
Not all (sub-)basins and catchments have experience
increased run- off in recent decades. In the Ganges and
Brahmaputra basins, streamflow is controlled by mon-
soon precipitation and influenced strongly by human
activities74,85,89,90. Mean surface run- off decreased in the
majority of the Lower Ganges Basin88 and total water
storage in the Upper Brahmaputra Basin91 decreased.
Moreover, anomalous hydrological trends are observed
in a few sub- basins where glaciers have grown. For
instance, in the northern Karakoram, annual and sum-
mer run- off decreased in recent decades86,92 in the Hunza
River basin (the northernmost Indus tributary), showing
a ~12.74 m3 s−1 decrease in July and August86, associated
with summer cooling, increasing snowfall and decreas-
ing net radiance56. Understanding the run- off response
of glacierized catchments to climatic changes is, there-
fore, complex, particularly in the Karakoram anom-
aly region, given its varied discharge changes, and the
uncertainties are considerable.
Projected trends. The predicted hydrological response
from the projected continuous glacier wastage is
substantial25,29 in H- K basins. Annually, glacier run- off
is projected to rise and then fall this century (FIG.3d and
Supplementary Fig.1) as the glaciers retreat, with the
timing varying amongst basins29 as a result of the stored-
ice volume and glacier areal fraction (FIG.3e–h). Onset of
peak glacier melt run- off among H- K basins is consist-
ently estimated to appear by around 2050 from simula-
tions at regional4,29,74,83 and local33,84 scales under RCP4.5.
Peak run- off of glacier melt is delayed under RCP8.5,
as the greater atmospheric warming will generate a
melt rate high enough to make up for a larger shrink-
ing glacier area, thus, delaying glacial run- off decline29
(Supplementary Fig.1). This effect is seen in the Upper
Indus Basin, for example, where the appearance of peak
water is estimated to occur in the year 2064 ± 19 under
RCP8.5 (REF.29), in contrast to 2045 ± 17 under RCP4.5.
Spatially, Karakoram peak run- off of glacier meltwa-
ter is projected to persist longer than in the Himalaya,
whereas peak water is thought to have already been
reached for some lower- altitude glacierized basins29
(Supplementary Fig.1).
Seasonally, glacier run- off is predicted to increase in
June and decrease in July–September by the EOC rela-
tive to 1990–2010 (REF.29) (FIG.3i,j). This seasonal shift in
meltwater release is of particular concern in the Tarim
and Indus basins, given the large meltwater contribution
to river discharge and, hence, large predicted impact on
summer water availability for irrigation in these basins12.
For example, the reduction in glacier melt contribution
could exceed 25% for September and October in the
Tarim and Indus basins between 2000 and 2090 (REF.29).
Moreover, a predicted shift from glacier run- off to rain
run- off in the Ganges is notable during the summer
months32. However, the monthly streamflow hydrograph
could remain relatively unchanged (FIG.3k,l) because
of the coincidence of decreasing summer melt and
increasing summer precipitation in the Ganges Basin32.
Overall, glacier retreat will directly cause changes in
basin run- off that vary temporally and spatially. These
changes will occur in the context of a projected regional
increase in overall streamflow by 2100, driven by melt
and precipitation. By the EOC, streamflow under RCP8.5
is projected to increase by 28% for the Upper Tarim
Basin (based on a reference period of 1966–1995)83,
51% for the Upper Indus Basin and 49% for the Upper
Brahmaputra Basin (reference period of 1981–2010)80
and 33% for the Ganges Basin (reference period of
1979–2003)93 or 41% for the Upper Ganges Basin
(reference period of 1981–2010)80. In the melt- dominated
Tarim and Indus basins, accelerated glacier melt is the
main contributor to rising twenty- first century stream-
flow, which increases before peak water, then declines
despite increasing precipitation31,83. In contrast, increas-
ing precipitation is the dominant contributor to the
rainfall- dominated Ganges and Brahmaputra basins,
where the contribution of glacier melt will continue to
decline32,79,80,94. Run- off regimes will, therefore, become
more rain- dominated, such as at the Upper Indus Basin31
and upper Langtang catchment32,33 (FIG.3m), and the
modulating effect of glaciers will decline and may ulti-
mately be lost in the future beyond the EOC. Changing
climate and glacier processes in the high- altitude areas
affect inter- annual and intra- annual water supply and
the likelihood of extreme hydrological events (such as
floods95 and droughts12), threatening the livelihoods of
downstream populations.
Uncertainties in future run- off are, however, large
and poorly quantified across the complex hydrologi-
cal system of the H- K. These result from the scarcity of
hydro- meteo- cryospheric observations in high- altitude
areas80; spatial fragmentation of studies; non- uniformity
Fig. 3 | Basin run-off, projected glacier peak water, and annual and seasonal run-off
changes under RCP4.5. a | Mean annual total run- off (TR) for the reference period
(1998–2007; first column), projected total run- off (PTR) and their components (base flow
(BF), rainfall run- off (RR), snowmelt (SM) and glacier melt (GM)) for the future (2041–2050)
for the Upper Indus Basin (UIB). b | TR and PTR for the Upper Ganges Basin (UGB).
c | TR and PTR for the Upper Brahmaputra Basin (UBB)74. d | Projected glacial run- off (GR)
peak years based on the modelled year of maximum glacier meltwater emergence29 in a
0.5 × 0.5 grid cell. e | Projected annual GR change in 2001–2100 in the Indus Basin, relative
to 1980–2000 (REF.29). The shaded area shows the standard deviation of computed glacier
run- off from 14 general circulation modes. The y- axis represents the rate of projected GR
relative to the reference time period. f | Projected annual GR change in the Tarim Basin.
g | Projected annual GR change in the Brahmaputra Basin. h | Projected annual GR
change in the Ganges Basin. i | Projected monthly changes in GR in June through
September in 2080–2100 compared with in 1990–2010 under the representative
concentration pathway (RCP) 4.5 scenario29. A positive percentage indicates that there
will be more run- off relative to the reference period and a negative percentage indicates
less. j | Fractional changes of glacier run- off to basin total run- off in July through October
in 2080–2100 relative to the change in the period 1990–2010 (REF.29). k | Upper Langtang
catchment seasonal discharge (Q) composition in 2000. l | Upper Langtang catchment
seasonal discharge in 2075 (REF.32). m | Simulated streamflow of the upper Langtang
catchment, Ganges Basin in 2005, 2025, 2050 and 2075. All values based on RCP4.5.
Parts a–c adapted from REF.74, Springer Nature Limited. Parts k–m adapted from REF.32,
Springer Nature Limited.
◀
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of methods; the absence of observations for water
stores and fluxes other than river flows; the difficulties
in accessing hydrology datasets that exist; the biases
(up to a factor of 3 in precipitation)96, low resolution and
poor constraint of gridded weather, soil and vegetation
datasets; and simplifications and limitations in models of
hydrology and of both regional and global climate. These
factors are overlain by the substantial inherent uncer-
tainty in future climate change scenarios4,31,74,79,83,94,97,
producing a cascade of uncertainty that constrains the
accuracy of predicted hydrological change98,99. A recent
review of 68 hydrological modelling studies in the
Himalayan region published in peer- reviewed journals
between 2010 and 2017 found, however, that 25% con-
ducted no uncertainty assessment, and, of those that did,
82% of studies analysed only either one or two sources
of uncertainty, suggesting that the true uncertainty in
future run- off is unknown99.
Lake- outburst floods
Glacial- lake and landslide- lake outburst floods (LLOFs)
are severe water- related hazards in the H- K26,100 (FIG.4a)
that drive fluvial erosion and geomorphological evolu-
tion. Glacial lakes typically form behind moraine dams
(sometimes also containing stagnant glacier ice) as gla-
ciers retreat or, particularly in the Karakoram, behind
a surging glacier as it advances across a channel100.
Landslide- dammed lakes form behind landslide depos-
its that block a valley37,101, and, here, we only discuss
LLOFs referring to glacier- related landslides or melt-
water as a dominant supply. In both cases, these dams
are poorly consolidated, inherently unstable and prone
to collapse, leading to outburst floods101. Large LLOFs,
such as from the Yarlung Tsangpo (dammed by a Gyalha
glacier- debris landslide) in the eastern Himalaya in 2018
(REF.102) and the Hunza River (blocked by the Attabad
landslide) in the Karakoram in 2010 (REF.103) (FIG.4a), have
caused extensive damage and affected river flow.
Moraine- dam failure leading to GLOFs is often trig-
gered by heavy rain (particularly on the south slope
of the Himalaya)37, earthquakes104, ice avalanche105,
calving37 or a landslide106 into the lake. The mechanism
of failure is typically through water overtopping the
earthen dam, causing incision of a channel, then more
rapid drainage and more incision in a positive feedback,
rather than minor piping through the dam induced by
ice- cored moraine- dam degradation107. Surging- glacier
dams, consisting largely of ice, can also fail through
Basin boundary
75° E
25° N
30° N
35° N
80° E 85° E 90° E 95° E
Tarim
Basin
Ganges
Basin
Brahmaputra
Basin
Indus Basin
a
GLOFs
Sutlej
Islamabad
Kathmandu
Karnali
Yarlung Tsangpo
Jinsha (Yangtze)
Dhaka
Yamuna
Ganges
Indus
Indus
Hotan
Yarkand
Ganges
Koshi
Teesta
Manas
Brahmaputra
New Delhi
Hydropower projects
Hydropower storage dam
40–99 MW Existing (before 2000)
Existing (since 2000)
Under construction
100–299 MW
300–999 MW
>1,000 MW >0.1 km3
>1 km3
Ravi
Chenab
Jhelum
Glacial lake
Capital
River
Karakoram ranges
Himalaya ranges
0 200 km
Shaksgam Valley
Attabad Lake
2018 Gyalha LLOF
Himalaya Karakoram Shaksgam Valley
15
10
5
01950s 1960s 1970s 1980s 1990s 2000s 2010s 1950s 1960s 1970s 1980s
YearYear Year
1990s 2000s 2010s 1960s 1970s 1980s 1990s 2000s 2010s
Frequency
bc d
Thimphu
Fig. 4 | GLOFs and hydropower projects in the Himalaya–Karakoram. a | Distribution of historical glacial- lake outburst
floods (GLOFs)37,73,112, glacial lakes72 and hydropower plants in the Himalaya–Karakoram. b | Frequency of GLOFs in the
Himalaya since 1950 (data grouped by decade). c | GLOFs in the Karakoram since 1950. d | GLOFs in the Shaksgam Valley
since 1960 (note, no data available for the 1950s). Further information on the collection of the hydropower data is listed
in the Supplemental Material. The hydropower projects construction is gradually moving upstream and is threatened
by observed and predicted increases in GLOFs. LLOF, landslide- lake outburst flood.
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ice detachment as hydrostatic pressure builds behind
the dam100 via subglacial drainage formed by subaerial
melting, water- line melting and ice calving67,108. Major
GLOFs originating from moraine- dammed lakes have
led to catastrophic losses downstream, including loss
of life and destruction of infrastructure, such as hydro-
power facilities, roads and bridges37,109. Heavy rain com-
bined with GLOFs led to the Chorabari lake disaster in
2013, which killed more than 6,000 people109, and the
Gongbatongsha Tsho disaster in 2016, which destroyed
a Nepalese hydropower plant101. Minor outbursts from
supraglacial lakes can cause less severe socio- economic
impacts due to limited discharges, such as the GLOFs
on the Lhotse Glacier in 2015 and 2016 (REF.110) and on
the Changri Shar Glacier in 2017 (REF.63). However, even
minor outbursts can trigger a hazard chain by causing
downstream moraine- dam failure, as seen in the 2015
Bhutanese Lemthang Tsho GLOF111.
A total of 65 GLOFs in the Himalaya since 1930 have
been observed and recorded in documents, field surveys
and satellite observations37,106,112. An increasing trend of
GLOFs in the Himalaya since 1950 has been reported37
(FIG.4b). However, this trend is controversial, as it var-
ies between studies examining different time periods
and GLOF data (FIG.4b–d). For example, a 2019 study
argues that the frequency of moraine- dammed GLOFs
remains unchanged during 1988–2017 (REF.112). It is
conclusive, though, that both the number and the area
of moraine- dammed and supraglacial lakes increased
between 1990 and 2015 in the Himalaya53. Indeed, the
observed and predicted glacial- lake expansion heigh-
tens GLOF hazard because it increases the possibility
of mass movement from the mother glacier and sur-
rounding topography entering the lake and causing
overtopping, and enhances the hydrostatic pressure on
the dam as the lakes deepen68,77. The proglacial lake Imja
Tsho is an example of increasing hazard risk because
of its continuous expansion and deepening113–115, and
growing possibility of mass movement entering the
lake in the next decades116,117. A socio- economic risk
assessment of GLOFs in the Nepal Himalaya118 indi-
cates that the modelled GLOF- induced total losses are
US$12 million for Imja Tsho and US$407 million for
Thulagi Lake. Combined with growing rainfall and
glacier run- off33,74,119 (and considering the lag between
an increase in glacier recession and in GLOFs), the fre-
quency of Himalayan GLOFs is likely to increase in the
next decades to 2100, and even in the twenty- second
century120.
In the Karakoram, a total of 150 ice- dammed GLOF
events are reported by ground records or satellite obser-
vation since 1533 (REFS73,121), and show an increasing
trend between 1950 and 2020 (FIG.4c). The inaccessibility
of heavily glacierized areas, frequent cloudiness hinder-
ing optical remote sensing122 and the short duration of
ice- dammed lake occurrence, however, mean that this
could be a substantial underestimate in this area73. Nearly
all Karakoram GLOFs are generated by ice- dam failure
as a result of glacier advances or surges blocking the
valleys123. Repeated glacial surges result in frequent GLOF
occurrence at the same ice- dam site; more than 90% of
recorded Karakoram GLOFs occurred in five clusters
of ice dams (Shimshal, Karambar- Ishkoman, Hunza
Central, Kumdan- Shyok and Shaksgam)73. Seven con-
secutive GLOFs during 2015–2019 occurred (S.Leinss,
personal communication, 2019, FIG.4d), owing to surges
of the Kyagar Glacier in the Shaksgam Valley, where
recent GLOF incidence is far greater than the local mean
frequency (4.8 times per decade) since 1960 (REFS124,125).
The ongoing surge of the Shisper Glacier in Hunza
Central since 2018 already caused one GLOF in 2019
(REFS36,121) and one in 2020, based on recent satellite
observations.
The incomplete record of GLOFs and the rela-
tively small trends in glacier mass in the Karakoram
mean that it is difficult to predict future GLOF risk in
this area. However, if the projected glacier recession
occurs4,59, a transition from predominantly ice- dam to
moraine- dam GLOFs could occur (as in the Himalaya),
and moraine- dam GLOFs could become more frequent
in the next decades and centuries.
Monitoring and early warning systems based on
insitu and remotely sensed observations37,122 contribute
importantly to glacier- related hazard assessment and
management but, currently, are still scarce for hun-
dreds of H- K lakes126–128. A prior risk assessment for
lake- outburst floods, more consideration of the fre-
quency and magnitude of triggers112, along with the pro-
vision of free, open data on coupled glacier- lake systems
and the adoption of state- of- the- art models and tools are
urgently needed for better disaster- risk reduction.
Run- off flooding
The H- K basins are especially prone to flooding
(FIG.5a), which has caused catastrophic losses, such
as the 2010 flood in Pakistan with 2,000 fatalities129 and
the 2013 flood in Uttarakhand- Upper Ganges, India,
with 6,000 fatalities109,130. Besides GLOFs and LLOFs,
flooding is mainly extreme- rainfall- induced or from
temperature- induced melt (of seasonal snow and gla-
cierice). Rainstorm- induced flooding is the primary
cause across the monsoon- dominated catchments, nota-
bly, in the lower floodplains of Brahmaputra, Ganges and
Indus129,130. Temperature- induced melt flooding is dis-
tributed in the glacierized mountainous catchments, par-
ticularly in the Upper Indus Basin, the Ganges Basin and
the Tarim Basin131. The mixed effect of those two types
of flooding exacerbates flood hazards in the transition
zones between mountainous areas and floodplains, for
example, the 2013 flood in India38,39,109. Flooding disas-
ters mainly occur during June–September, controlled by
summer monsoon rainfall, whereas meltwater- induced
floods occur during May–September132.
The magnitude and frequency of floods have incre-
ased across the H- K basins in the past decades, such as
in Tarim Basin during the 1950s to 2009 (REF.131) and
similarly in the Brahmaputra, Ganges and Indus basins
during 1951–2013 (REF.132), and economic losses have also
increased. This increase in flooding has been caused by
extreme weather patterns that have induced intense
monsoonal rainstorms129,133 and by a warming- induced
increase in meltwater130. Floods in both summer and
winter seasons have increased and floods are occurring
earlier among melt- dominated catchments, as observed
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in recent decades as a result of warming in, for example,
the Tarim Basin131.
The magnitude and frequency of floods within the
H- K basins are projected to increase by the EOC as a
consequence primarily of increasing precipitation and
precipitation extremes, plus a further increase in ice
melt80,83,134,135. Floods will be more frequent and of greater
magnitude at 2 °C global warming than at 1.5 °C in the
Brahmaputra, Ganges and Indus basins134,136. Similarly,
floods are predicted to be more severe under RCP8.5
than under RCP4.5. For example, the peak flow of a
50- year- return flood is likely to increase by about 51%
for the Upper Indus Basin, 108% for the Upper Ganges
Basin and 80% for the Upper Brahmaputra Basin under
RCP8.5 (REF.80). The Brahmaputra and Ganges basins
would be particularly vulnerable, given the predicted
peak discharge, duration, inundated area and depth
of flooding134,137. For instance, an increase of 20% in
precipitation threatens Bangladesh with an increased
flood- affected area138. In the Upper Indus Basin and the
Tarim Basin, the magnitudes of high flows are predicted
to increase not only during summer but also during
spring and winter, and the timing of high flow will pos-
sibly shift earlier83,139, indicating more severe and larger
floods. The review of 68 hydrological modelling studies
described above99 found, however, than none used spe-
cific performance criteria to model peak (or low) flows,
hence, flood predictions should be considered more
uncertain than predicted average flows.
The projected increase in floods (possibly associated
with enhanced landslides, soil erosion and sedimentation)
will have more negative impact on human lives and
infrastructure, and dealing with increasing flood events
is one of the largest hydrological challenges for the
H- K region in the future, especially for transboundary
events. To mitigate this, regional cooperation among
the H- K- basin- related countries should be enhanced
by sharing data, information and risk assessment
approaches130.
Societal impacts
Changes to hydrology in the H- K will have far- reaching
impacts on societies who depend on water supplied by
glacial melt. The agriculture and energy sectors could be
especially hard hit, as both depend on local and regional
hydrology.
Impacts on hydropower projects
Hydropower is known as a power source for economic
development that is low carbon (especially for low-
storage, run- of- the- river projects), reliable and cost-
effective in the long term40,140. It is increasingly important
to the H- K glacier- fed basins, where a shortage of elec-
tricity supply is a severe issue (particularly for Pakistan,
Ganges Ganges
Ganges Ganges
Indus
Indus
Indus
Indus
Tarim
Tarim
Tarim
Tarim
Brahmaputra Brahmaputra
Brahmaputra Brahmaputra
ab
cd
Riverine flood risk
Baseline water
stress
Water stress 2040
(RCP8.5)
Drought risk
Extremely high
Medium–high
Low–medium
Medium–high
Medium
Low–medium
0 300 km
No data
Low
High
Extremely high
Medium–high
Low–medium
Low
Arid and low
water use
High Extremely high
Medium–high
Low–medium
Low
Arid and low
water use
High
High
Fig. 5 | Hydrological risks and water stress in the Himalaya and Karakoram basins. a | Riverine flood risk in terms of
average annual impact, where a higher risk indicates a greater proportion of population to be impacted. b | Drought risk.
c | Baseline water stress. d | Future water stress in 2040 under the representative concentration pathway (RCP) 8.5scenario.
Source data are from Aqueduct 3.0 released in 2019 (REF.156). Large parts of the Himalaya and Karakoram basins are prone
to floods and droughts, and are under severe water stress, particularly on the Indo- Gangetic Plain.
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Nepal and India)12. The H- K ranges have some of the
world’s largest hydropower potentials (FIG.4a), though
hydropower in this region has been little studied and
lacks reliable and comparable data141,142. We identify
105 existing HPPs (≥40 MW) with an installed capa-
city of 36.6 GW, 61 projects (≥40 MW) currently under
construction (39.1 GW) and 890 projects (≥10 MW) in
various stages of planning (242 GW) (Supplementary
Table2). These planned developments would utilize
almost all suitable river sections of the H- K region.
However, considering the various environmental,
technical and economic barriers (including expected
power demand), it is likely that only a fraction of
those 890planned projects will be implemented in the
near future.
Hydropower development in the H- K has grown
rapidly but heterogeneously. Most existing HPPs were
built in the past two to three decades, mainly starting in
downstream sections and gradually moving upstream
(FIG.4a). Current HPPs are not evenly distributed among
basins, with almost half of the projects and more than
half of the capacity in the Indus Basin143, and about
three- quarters of potential future projects and capacity
in the Brahmaputra and Ganges basins. This develop-
ment is heavily affected by the sediment loads of the
source rivers and by the risk from extreme hydrolog-
ical events. The up- river progression of hydropower
developments41, for example, brings them closer to
glacial lakes and increases their potential exposure
to GLOFs41 (FIG.4a). Historically, of the 166 current HPPs
(existing and under construction), few have been
directly affected by the 215 recorded GLOFs (including
the 45- MW Bhotekoshi hydropower plant destroyed in
Nepal by a GLOF in 2016 (REF.101)). However, the spread
of HPPs into upstream sections of watersheds such as
Nepal’s Gandaki and Koshi substantially increases the
threat to infrastructure from GLOFs.
The performance of hydropower generation is
directly affected by inflow run- off, with strongly shift-
ing seasonal and inter- annual variations that are con-
trolled by both meltwater and precipitation29,31,80,83.
Generally, the glacier meltwater in dry seasons con-
tributes between 15% and 40% of the H- K’s annual
hydrogeneration. In the monsoon- controlled Ganges
and Brahmaputra basins, the share is lower than in the
melt- dominant Tarim and Indus basins. The projected
increase in water availability might not be universally
advantageous for HPPs because the predicted increasing
magnitude and frequency of floods and meteorological
droughts30,134,144–146 will negatively alter the efficiency of
hydropower generation. Additionally, hydrological and
glacial changes are likely to further increase the hitherto
high and globally above- average sedimentcon centration
of many H- K streams147. This sediment increases hydro-
abrasive erosion, resulting in frequent production losses
and shorter lifetime of hydropower components134,148and
in the rapid sedimentation of reservoirs, which lowers the
efficiency of HPPs149.
It is notable that most of the HPPs have little stor-
age capacity138. We identified only 13 storage reservoirs
(≥0.1 km3) and another 16 under construction, most
of which are located at the bottom end of hydropower
cascades and designed primarily to serve downstream
irrigation150, rather than at the upstream end to sustain
power generation. The absence of upstream storage
and flow regulation strongly increases the dependence
of HPPs on local hydrology. On the one hand, cloud-
bursts or flash floods become more serious for HPPs:
a flash flood in India’s Upper Ganges and Mahakali
catchments in 2013 damaged several cascading small
hydropower stations109. Future floods80 are more likely
to cause cascading damages for HPPs, and could result
in large- scale power- grid instability. On the other hand,
a drought- induced decrease in the generation of elec-
tricity would need to be compensated for by power
imports or a more diverse portfolio of power genera-
tion. Such issues suggest that both single and cascading
hydropower structures should be flexibly designed to
adapt to future droughts and floods. However, concerns
over storage arise from the experience of shared rivers,
where obligatory minimum- flow agreements are often
not fulfilled151,152, leading to artificially low, dewatered
seasonal flows for long river sections that impact not
only the downstream cascade production of electricity
but also biological diversity of the river ecosystem153.
The H- K is set to continue to exploit and expand
upon its huge hydropower potential for the foreseeable
future. For example, Nepal has a 43,000- MW hydro-
power potential but less than 2% is being harnessed so
far. Indeed, nearly 8,000 MW of HPPs are under vary-
ing stages of construction and are likely to be com-
pleted in the next ~5 years130,154. Rapid hydropower
development commonly causes multiple negative con-
sequences, however, such as power- grid bottlenecks,
seasonal over capacity and river fragmentation150–152.
Objectively, the H- K’s hydropower energy is designated
to primarily serve distant cities and economic centres,
leading to inequality of benefit sharing between urban
and rural areas40. Taking into account the substantial
hydrological and glacial changes predicted for the H- K,
we highly recommend a balanced strategy for hydro-
power development with improved transboundary
cooperation.
Droughts
Perhaps the greatest value that glaciers have to society
is in protecting downstream communities and hydro-
economies from the worst effects of droughts (FIG.5b) by
sustaining river flow when other water sources fail. In the
last century, meteorological droughts in HMA afflicted
several neighbouring river basins simultaneously
and lasted for up to three consecutive years, affecting
1.1 billion people and causing 6 million deaths12. To day,
a much larger and increasingly vulnerable population
is exposed to the drought hazard: the H- K basins have
among the world’s fastest- growing water demands and
the lowest per capita water supplies155, and water stress is
already ‘extremely high’ for around 200 million people156
(FIG.5c,d). This vulnerability is exacerbated by economics
and politics: externalized water costs are exceptionally
high across the H- K’s agriculture, power and public
water supply sectors. Water charges in Pakistan, for
example, recover only a quarter of the maintenance and
operating costs of its irrigation systems157. Such large
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externalities make the price of water prone to abrupt
and socially destabilizing price shocks that could be
triggered by drought12. Superimposed on this economic
landscape is a river network shared between multiple
rival and ‘ethnically fractionalized’ communities that are
prone to increased risk of conflict under the added stress
of a natural disaster158. The year- to- year persistence of
glacier ice, as distinct from the fluctuating, unreliable
seasonal snowpack and summer rainfall, makes this a
uniquely valuable surface water resource but one that
will ultimately be lost as the glaciers vanish.
The extensive glaciers of the Indus and Tarim basins
stand out as a particularly important buffer against
drought. Lying at the north- western extremity of the
Indian summer monsoon’s variable path, these basins
are both more arid than the Ganges- Brahmaputra
and have less reliable annual precipitation, with very
high coefficients of variation (0.7 and 4.1, compared
with 0.2 for the Ganges- Brahmaputra)12. Whereas a
1- in-30- year drought provides 81% and 84% of the
average precipitation in the Ganges and Brahmaputra
basins, it provides only 70% and 74% in the Tarim and
Indus12,159, respectively, and it is the occasional shock of
such large relative declines in water supply (rather than
their general aridity) that is particularly destabilizing for
communities160.
Over the second half of the twentieth century, the
Indus and Tarim glaciers released 10.7 ± 2.2 km3 of water
per year, which was around half of all surface water reach-
ing these basins’ rivers in the height of drought sum-
mers12. The less extensive Ganges- Brahmaputra glaciers
released 1.4 ± 0.3 km3 per year, but monsoon failure in an
extreme drought in Nepal, for example, can lead to sum-
mer months with almost no precipitation and glacier melt
providing almost all of the river flow12. With the transi-
tion to unsustainably high rates of glacier melt, these con-
tributions have been boosted further — by an additional
7.5 ± 2.9 km3 per year in the Ganges-Brahmaputra and
4.2 ± 2.2 km3 per year in the Indus over the 2000–2016
period12,15. These river flows sustain large irrigation
schemes, the importance of which is illustrated by the
contrasting impact of drought on wheat yields in irri-
gated and unirrigated agriculture in the region. In the
largely unirrigated Pakistan provinces of Balochistan
and Khyber Pakhtunkhwa, for example, a drought led to
a 40–50% drop in yields, while in irrigated Punjab and
Sindh, no decline in yield occurred161.
Meteorological droughts might become more fre-
quent in the Indus144,146 through the twenty- first cen-
tury, though drought trends are highly uncertain80.
Three other trends are, however, expected to affect the
importance of glacier meltwater as a drought buffer:
the increase to and decline from peak meltwater; the
decline of groundwater resources due to over- extraction,
particularly in the Indus and Ganges basins10,162,163; and
the increase in water demand due to population growth
and the impact of a warming climate on agriculture2,164.
In Pakistan, for example, where 47% of the population is
already food- insecure165, the demand for domestic drink-
ing water is expected to quadruple by 2050 (anincrease
of around 30 km3)166 and groundwater use will double165,
lowering the water table in Pakistan’s Punjab by tens
of metres162. Helping to compensate for this, the Indus
glaciers meltwater flux will rise from 14.9 ± 3.1 km3 per
year today12 to a peak that is a quarter to a half higher
(approximately 18 to 23 km3 per year)12 sometime in
mid- twenty- first century, dependent on the climate sce-
nario29. However, retreat of the Indus glaciers potentially
to half their area by the EOC59 will produce a higher June
meltwater peak than observed now but then a meltwater
decline of around a quarter later in the summer29. This
late- summer glacial meltwater supply currently meets
around half of the demand from sugarcane, cotton and
rice crops10. Continuing losses after the EOC will ulti-
mately deprive the Indus of almost all of this water flux,
which can be half of all Indus water inputs at the height of
an ‘extreme’ drought, and is equivalent to the basic water
needs of 87 ± 19 million people12.
After peak meltwater, the reduction in meltwater
flows will increase pressure to extract more ground-
water, particularly in droughts, while simultaneously
reducing the rate of recharge of groundwater aquifers
and, thereby, accelerating their decline. Groundwater
serves as the region’s other major buffer against water
shortages161,167. It currently supplies about half of the
average water consumption in the Indus Basin, almost
all going to agriculture168,169, and its informal extraction
by millions of farmers supports crop yields that are twice
as high as those on farms with access only to less reliable
irrigation- canal water supplies161. Groundwater extrac-
tion from the Indus and the Tarim aquifers is unsustain-
ably high170 and both are classed as overstressed163, and
salinization171,172 and arsenic contamination173 are
decreasing the usable groundwater resource. Furth-
ermore, groundwater at its current levels in these basins
is far from self- sustaining: its recharge is highly reliant
on the regular diversion of surface water from rivers into
the irrigation system. In Pakistan’s Punjab, for example,
80% of extracted groundwater originates as irrigation
water from the Indus tributaries161. Any prolonged
period of low river flows, combined with the projected
doubling in groundwater use, therefore, implies an even
larger groundwater deficit, an increasingly deep and
inaccessible water table, and, therefore, a greater vulner-
ability to drought for the millions of people dependent
on it. As groundwater supply declines and river flows
become more variable, drought- resilient glacier melt-
water will become an ever more valuable but dwindling
resource later this century.
In total, the H-K glaciers currently produce 27.4 ±
7.3 km3 of meltwater each summer, which is 3.6 times
the live storage capacity of Pakistan’s large Tarbela
reservoir, potentially rising to 36 km3 (equivalent to
4.7 Tarbelas) around mid- century under RCP4.5
(REFS12,29). Potentially, additional reservoir storage could
be used to replace the drought- buffering role of the gla-
ciers, and, indeed, around half of existing glacier run- off
could plausibly be stored solely by dams within the
troughs left behind by glacier retreat174. Drought occur-
rence, severity and duration are difficult to predict, how-
ever, and the three- year duration of the worst recorded
droughts of the twentieth century12 could be exceeded.
If the practical difficulties to dam- building could be
overcome to construct sufficient buffer reservoirs on
www.nature.com/natrevearthenviron
Reviews
these shared rivers, their water stores would need to be
preserved for emergency use, rationed to maintain river
flows for several consecutive summers and be released
to downstream users, rather than diverted to other
catchments, a substantial economic and management
challenge.
Future perspectives
The H- K is arguably the most critical of the world’s
mountain water towers2, nourishing the large, heavily
irrigated and densely populated areas of the Indus, Tarim,
Ganges and Brahmaputra basins9. Glaciers in the H- K are
very sensitive to the changes in climate already under-
way and accelerating, and unsustainable glacier melt is
drawing down the H- K ice reserve12,16,17. Meltwater flows
will peak in the next decades before declining, imply-
ing that the role of glaciers in modulating the region’s
water supply will also decline on this timescale, and that
the run- off regime will become more rain- dominated
and, therefore, more variable. Ultimately, the hydrolog-
ical role of H- K glaciers will largely disappear (FIG.6),
impacting downstream agriculture and ecosystem
services.
Although total basin run- off is projected to increase
by the EOC and bring socio- economic benefits to a
growing population, more extreme precipitation and
the loss of glacier modulation could likely increase the
impact of droughts and floods, including GLOFs. Such
an increase in flood and drought impacts threatens
local water–energy–food security175. These stressors
have the potential to aggravate hydro- political tension
among riparian countries where transboundary coop-
eration176 plays an increasingly urgent and important
role in water sharing and disaster reduction. This risk
strongly suggests that water demand, over which socie-
ties have direct control, must be managed to build better
resilience to a more variable future water supply. It is
encouraging that numerous management approaches,
such as developing low- water- requirement crops, exist
to increase the efficiency of water use in this region161.
Substantial diplomatic challenges are likely to remain,
however, between water- sharing neighbours who are
confronted with an uncertain and changing water
supply, and unpredictable and evolving hazards.
To provide the best possible predictions of how moun-
tain run- off and glacier- related natural hazards will
change in the near future, it is crucial to understand how
glaciers are responding to climate change and what
effects it is having on the region’s hydrological systems
(FIG.6). Although remote sensing is now yielding valuable
insights into these remote mountain catchments, there are
substantial knowledge gaps in the cryosphere of the H- K.
Few long- term records or ongoing field measurements
are available of H- K glaciers, weather or hydrology, even
fewer are made publicly available and fundamental data-
sets are lacking. Almost none of the region’s glaciers has
been surveyed for ice thickness or debris depth, almost
no observations are routinely made of high- altitude pre-
cipitation and few process studies of glacier–lake–weather
interactions and hazard triggers have been conducted or
models developed. There is also more to do to understand
better the impact of changes in glacier volume and melt
Climate change:
• Temperature (+)
• Precipitation (?)
Glacier run-off:
• Total volume ( )
• Seasonal shift
Water supply,
excess/shortage:
• Floods (+)
• GLOFs (+)
• Droughts (+)
Suggestions:
• In situ observation
network (+)
• Mitigate climate
change (+)
• Sustainable water
use (+)
Water demand:
• Population (+)
• Energy (+)
• Agriculture (+)
Basin run-off:
• Streamflow (?)
• Variation (+)
Glacier functions:
• Provisioning ( )
• Regulating (–)
• Supporting ( )
• Culture (–)
Glacier loss in the H-K
Water stress (+)
Future glacier (–) Slight ice loss
Ice-dammed
GLOFs (+)
Accelerated ice loss
Sediment
flux (+)
Sediment flux (+)
Precipitation (+)
Glacier run-off ( )
Basin run-off (?)
Glaciers Glaciers
Glacial lake
Upstream HPPs (+)
Upstream HPPs (+)
Irrigation (+)
Hydropower
Settlements (+)
Settlements (+)
Agriculture (+)
Population (+)
Population (+)
Flood (+)
Drought (+)
Flood (+)
Moraine-dammed
GLOFs (+)
Future glacier (–)
Himalaya
Karakoram
Rain
Rain Snow
Snow
Challenges of HPPs
• GLOFs
• Floods
• Droughts
• High sediment
content
• Geopolitical
conditions
Fig. 6 | Hydrologic impacts and risks from glacier changes in the Himalaya–Karakoram. For each process or state,
the symbols ‘−’, ‘+’ and ‘?’ in brackets represent a decreasing, increasing and unclear trends, respectively, and up and down
arrows represent a transition from initial increase to decrease. Glacier changes directly cause annual and seasonal shifts
in glacier melt and basin run- off, and possibly exacerbate hazard risks from floods (including glacial-lake outburst
floods (GLOFs)) and droughts that directly or indirectly impact downstream water–energy–food security. H- K, Himalaya
and Karakoram mountain ranges; HPPs, hydropower projects.
Nature reviews
|
Earth & EnvironmEnt
Reviews
patterns on downstream sectoral water uses and the over-
all water–energy–food nexus, particularly as strong future
socio- economic development and the associated increase
in water demand might play a larger role in worsening
water shortages in the Himalayan region177.
To narrow the knowledge gap and constrain weather,
climate, glacier, hydrology and hazard models, a wide-
spread array of open- data weather stations, river- flow
gauges and glacier mass- balance monitoring sites is
needed178. A focus on monitoring high- altitude rain and
snowfall, together with new surveys of ice and debris
thickness64,179,180 and moraine- dam integrity181, would
help greatly to improve process- based understanding
of regional climate change, glacier evolution and hydro-
logical impacts for downstream uses99. These sensors,
surveys and better- constrained models would be a
particularly potent contribution in combination with
an efficient transboundary hazard- warning system.
Together, these new findings could play a fundamental
part in the H- K nations achieving water–energy–food
security and meeting the United Nations’ Sustainable
Development Goals.
More broadly, this Review highlights the dangers
to these nations that will come from continued loss of
the H- K glaciers, and, therefore, the tremendous eco-
nomic and social benefits to be gained from choosing
a lower- emission climate change pathway that will
minimize their losses. Under the RCP2.6 scenario, for
example, 83% of the glacier area is projected to sur-
vive until the EOC in the Karakoram and 52% in the
Himalaya but only 57% and 16%, respectively, under
the RCP8.5 scenario59. For the Asian societies that depend
so much on these glacial water towers, the imperative for
a low- emissions scenario is abundantly clear.
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Acknowledgements
We acknowledge Fanny Brun for providing data on glacier
change in Fig. 2 and Lu Zeng for technical support in creating
Figs. 3,6. This study was supported by the Strategic Priority
Research Program of the Chinese Academy of Sciences (grant
no. XDA20030301), the second Tibetan Plateau Scientific
Expedition and Research Program (grant 2019QZKK0603),
the Chinese Academy of Sciences Light of West China and
Key Lab of Mountain Environment Programs, the National
Natural Science Foundation of China (grants 41571104
and 41971153) and Foundation of Youth Innovation Promo-
tion Association, Chinese Academy of Sciences (grant no.
2017425).
Author contributions
Y.N., H.D.P., Q.L. and T.H. researched data for the article. Y.N.,
H.D.P., Q.L., T.H., W.W. and X.W. wrote the article. All authors
reviewed and edited the manuscript before submission.
Competing interests
The authors declare no competing interests.
Peer review information
Nature Reviews Earth & Environment thanks Tobias Bolch,
who co- reviewed with Owen King, and the other, anonymous,
reviewer(s) for their contribution to the peer review of this
work.
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Supplementary information
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https://doi.org/10.1038/s43017-020-00124- w.
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