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Mapping of Freshwater Ecosystem Services (FES)
FES across different parts of Himalayas were mapped through systematic review of literature.
Surface water (for drinking and non-drinking) is the highest-ranking FES in the Western, Central, and Eastern Himalayas.
Despite a generally fair regional spread of studies, research is oriented toward provisioning (43.54%), with regulating (36.48%) and cultural ES (19.98%) understudied.
The majority of research identifies FES (73.68%), but fewer quantify (39.47%) and value them (23.68%), indicating significant research gaps.
Regulating ES have a greater average monetary value (1,128.81 $/ha/year) than Provisioning (446.75 $/ha/year) and Cultural (457.51 $/ha/year).
Quantification of FES
All the basins experience a slight increase in Flood Retention Index (FRI) within +10%.
Nitrogen retention showed a strong improvement in Marshyangdi (~+49%), but remained within +10% of the baseline in other basins.
Water yield increased slightly in Beas (~+2%), while other basins experienced declines (−6% to −20%).
Sediment retention remained almost the same as baseline in Beas, but showed slight declines in the other three basins (−5% to −11%).
Habitat quality remained within the baseline range in all basins, but showed declines in regions along the river (urbanised areas).
Carbon storage decreased across all basins: a small decline in Beas (~−2%), large decreases in Marshyangdi and Punatsangchu (~−51%), and a very large decline in Teesta (~−100%).
Monsoon Variability
Beas basin receives 42% of annual precipitation during Dec–May due to western disturbances while others are influenced by summer monsoon and orographic influences.
Decreasing trends of winter precipitation, no. of rainy days and annual precipitation, indicating weakening effect of western disturbances in Beas.
In Marshyangdi, the winter precipitation and rainy days are following statistically decreasing trends.
Teesta experienced an increasing trend in pre-monsoon precipitation while Punatsangchhu observed no significant trends.
The interannual variability (IAV) of monsoon rainfall is higher in Beas (27.22%) and Punatsangchhu (25.01%).
Strengthening of monsoon occurs late in Beas (21–30th Jul) compared to others (1st–20th Jul).
Daily rainfall during monsoon reaches to maximum early in Teesta basin (1st week–Jul) compared to others (2nd week onwards).
Water Balance Studies
In all the basins, >60% of annual water yield is contributed by lateral flow and baseflow.
Beas experienced lower (~10%) evapotranspiration losses (ET/P) compared to Marshyangdi (23.5%), Teesta (17%) and Punatsangchhu (27.6%).
Snowmelt contribution to water yield is higher in Beas (~40%) compared to remaining basins (<15%).
Beas basin relies heavily on snowmelt so future changes in the snowpack accumulation can affect the water availability in the basin.
Precipitation and water yield are projected to increase in all the subbasins of the four basins while ET response is mixed.
Annual water yield is projected to increase in all the basins under SSP2-4.5 and SSP5-8.5 scenarios.
Teleconnections of Large-scale Atmospheric Circulations
Teleconnection analysis revealed that Nino3.4 and DMI exhibit 2–5 and 2–4 year oscillations respectively, while NAO shows inter-annual and inter-decadal patterns, and PDO is characterized by inter-decadal oscillations.
Rainfall showed significant oscillations at 8–16 months scale in all the basins.
In Beas, significant coherence of monthly rainfall with Nino3.4 (2–4 years) and PDO (8–10 & 16–20 years) was observed, while coherence with DMI declined post-1991, and NAO showed coherence at 3–5 years during 1978–85.
In Teesta, significant coherence was found with Nino3.4 (2, 3–5, and 5–7 years), and coherence with NAO (8–16 months and 3–5 years) was found to be increasing since 1981.
In Marshyangdi, coherence of Nino3.4 was at 2–5 years scale, while that of DMI is increasing at 2–5 years and 5–10 years scale since 1991. NAO showed coherence at 2–8 years scale and no significant coherence of PDO was observed.
In Punatsangchhu, significant coherences of Nino3.4, DMI and NAO were found at 2–5 years while coherence of PDO was observed at decadal scale since 1981.
Impact of Climate Change on FES
Scenario differences are minor for FRI, mixed for HQ, and pronounced for WY, SR, and CS; SSP5-8.5 generally amplifies WY and CS gains by 2050, whereas SR improves under SSP2-4.5 but declines under SSP5-8.5.
Flood Retention Index declines slightly (−5% to −3%) in all basins, stable across years and scenarios.
Water Yield increases with time, stronger under SSP5-8.5.
Habitat Quality improves in Beas and Teesta under SSP5-8.5 (~+15–27%), but declines in Marshyangdi (−13%) and stays near baseline in Punatshangchhu; SSP2-4.5 shows only modest gains or slight declines.
Soil Retention shows contrasting results: large gains under SSP2-4.5 (Punatshangchhu >+200%, Beas and Teesta ~+50–70%), but declines across all basins under SSP5-8.5 (−15% to −25%).
Carbon Storage increases everywhere under SSP5-8.5 (Beas ~+77%, Teesta ~+57%), while SSP2-4.5 is smaller and mixed (Beas +14%, Marshyangdi and Teesta near baseline, Punatshangchhu declines ~−12%).
Compound Extremes
Various types of compound extremes: Compound Dry & Cold Extremes (CDCE), Compound Wet & Cold Extremes (CWCE), Compound Dry & Hot Extremes (CDHE), and Compound Wet & Hot Extremes (CWHE) are investigated for the baseline & future scenarios.
The figure illustrates the relative change in the frequency of these compound extremes.
A pronounced decline in cold extremes (CDCE & CWCE) contrasts with a substantial escalation in hot extremes (CDHE & CWHE) under SSP2-4.5 and SSP5-8.5 scenarios relative to the historical baseline.
A statistically significant increasing trend in CWHE is evident, and by the end of the 21st century an overall rise of approximately 8–10 CWHE days per decade is projected.
The spatial footprint of CWHE is projected to expand dramatically, increasing from approximately 50 % of the region in 2014 to nearly complete coverage by the end of the 21st century.
Impact of Compound Extremes on FES
The region shifts from cold-dominated extremes to heat-dominated extremes through the century, with WY tending to rise where wet-hot and dry-hot conditions expand, especially under SSP5-8.5.
Hot extremes (CWHE, CDHE) expand across all seasons and decades, strongest under SSP5-8.5; by mid–late century, they dominate monsoon and pre-monsoon with widespread increases (+30–100%).
CDCE declines steadily in every season and scenario, while CWCE shows limited mid-century pockets that fade later; the retreat is earlier and stronger under SSP5-8.5.
Monsoon and pre-monsoon show the largest shifts (heat extremes surge, cold extremes recede); post-monsoon changes are moderate; winter is mixed and patchy with only localized growth of heat extremes after 2040.
SSP5-8.5 consistently amplifies and advances these extremes relative to SSP2-4.5—earlier onset, larger affected area, and stronger magnitudes.
WY increases under both scenarios and grows with time, larger under SSP5-8.5.
Policy Review
Review of 21 policies in 3 countries revealed that none of the policies incorporated the IPCC scenarios in the adaptation planning clearly.
Economic valuation of FES and Payment for Ecosystem Services (PES) were not discussed through formal mechanisms in India and Bhutan while they were discussed under watershed and forest conservation policies (REDD+, PES) and Carbon finance in Nepal.
Compound extremes were not discussed in any of the policies explicitly.
Data sharing among the Himalayan countries and cross-border collaboration mechanisms were not established.
No national level inventory of critical and vulnerable freshwater ecosystems was listed for adaptation planning and risk reduction.
Although the policies acknowledge that climate variability and change effect the Freshwater quantity and quality, climate projections of hydrological changes were not incorporated in the policy frameworks.
Policies have discussed that water quality is declining due to pollution and rising temperatures but mechanisms for real-time quality monitoring remain underdeveloped.
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