Editing IPCC:AR6/WGII/Chapter-10 (section)

==== 10.4.4.3 Observed Impact ====

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The climate-change impact on different parts of freshwater ecosystems ( [[#10.4.2|Section 10.4.2]] ) has affected water supply in various sub-regions of Asia. While headwater zones are susceptible to change in snow cover, permafrost and glaciers, the downstream plain areas of these river systems are vulnerable to the increasing high demand of freshwater which will affect water availability in space and time. The observed impact of climate change has also been seen in direct physical losses such as precipitation (Mekong Delta), floods (Vietnam) and saltwater intrusion leading to low agricultural productivity ( [[#Mora--2018|Mora et al., 2018]] ; [[#Almaden--2019a|Almaden et al., 2019a]] ; [[#Pervin--2020|Pervin et al., 2020]] ).

The HKH region extends 3,500 km from Afghanistan in the west to Myanmar in the east. It is a source of major river systems originating in Asia, supporting livelihoods, energy, agriculture and the ecosystem for 240 million people in the mountains and hills and 1.65 billion people in the plains ( [[#Sharma--2019|Sharma et al., 2019]] ). The HKH region stores about half of the ice mass in HMA, provisioning freshwater to almost 869 million people in the Indus, Tarim, Ganges and Brahmaputra river basins. While the warming climate increases the melt-water runoff enhancing water supply, it is indeed at the cost of glacier-mass reduction that would eventually reduce melt water and impact the people’s livelihood downstream in the future ( [[#Nie--2021|Nie et al., 2021]] ). The melt runoff from the region plays an important role in downstream agriculture such as in the case of Indus where two-thirds of total irrigation withdrawal is from melt runoff in the pre-monsoon season ( [[#Biemans--2019|Biemans et al., 2019]] ). Changes in cryosphere and other environmental changes have already impacted people living in high-mountain areas and are ''likely'' to introduce new challenges for water, energy and food security in the future ( [[#Borodavko--2018|Borodavko et al., 2018]] ; [[#Adler--2019|Adler et al., 2019]] ; [[#Bolch--2019|Bolch, 2019]] ; [[#Hoelzle--2019|Hoelzle et al., 2019]] ; [[#Rasul--2019|Rasul and Molden, 2019]] ; [[#Shen--2020|Shen et al., 2020]] ).

With climate-change impacts resulting in the shrinking and melting of snow, ice, glacier and permafrost, and correspondingly causing an increase in melt water, the incidences of flash floods, debris flow, landslides, snow avalanches, livestock diseases and other disasters in the HKH region have become more frequent and intense. Some of the key factors that get in the way of assigning confidence levels to climate-change impacts include lack of sufficient observed data on factors such as river discharges, precipitation and glacier melt ( [[#You--2017|You et al., 2017]] ). Climate-change impacts cryospheric water sources in the Hindu Kush, Karakoram and Himalayan ranges which, in turn, carry consequences for the Indus, Ganges and Brahmaputra basins.

The combined impacts of climate change and non-climate drivers on hydrological processes and water resources in transboundary rivers in diverse regions of Asia were well noted in AR5. In Central Asia, withdrawal is approximately equal to water availability, with Turkmenistan and Uzbekistan as the most water-stressed countries in the region ( [[#Karthe--2017|Karthe et al., 2017]] ; Russell, 2018). A study on water availability in mainland South Asia has pointed in the direction of decreasing precipitation trends in recent years, which have also contributed to the increasing incidence and severity of droughts ( [[#Liu--2018b|Liu et al., 2018b]] ). There are reports of increase in occurrence and severity of different forms of droughts in the Koshi River basin (Central Himalaya) ( [[#Wu--2019a|Wu et al., 2019a]] ; [[#Hamal--2020|Hamal et al., 2020]] ; [[#Dahal--2021|Dahal et al., 2021]] ; [[#Nepal--2021|Nepal et al., 2021]] ). Figure 10.5 shows the water stress in the HKH region. The water stress is relatively higher in the western region compared with the central and eastern regions.

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[[File:136ae2baf51f825017c0165043125ac4 IPCC_AR6_WGII_Figure_10_005.png]]

'''Figure 10.5 |''' '''Water stress in the Hindu Kush Himalaya (HKH) region according to Wester et al.''' '''(2019) and [[#Hu--2018|Hu and Tan (2018)]] .'''

Climate change is also having an impact on stream flows. The changes in snowmelt water can explain 19% of the variations in rivers of arid regions like Xinjiang, China ( [[#Bai--2018|Bai et al., 2018]] ) ( ''medium confidence'' ), and the 10.6% of the runoff of the upper Brahmaputra River was contributed by snow during 2003–2014 ( [[#Chen--2017c|Chen et al., 2017c]] ) ( ''medium confidence'' ). A recent study (Chen et al., 2018 f) has shown that with the average temperature after 1998 being 1.0°C higher than that during 1960–1998 in the Tienshan Mountains, the process of glacier shrinkage and decreases in snow cover are causing earlier peak runoff and aggravated extreme hydrological events, affecting regional water availability and adding to the future water crisis in Central Asia. The magnitude and frequency of flooding have increased across the Himalayan region, such as in the Tarim basin in China ( [[#Zhang--2016c|Zhang et al., 2016c]] ) and the higher Indus, Ganges and Brahmaputra, in the past six decades ( [[#Elalem--2015|Elalem and Pal, 2015]] ). The latter also reported the highest number of flood disasters and greater spatial coverage in recent decades as compared with previous decades. In the Middle Yellow River basin, which has become much warmer and drier, climate variability accounts for 75.8% of streamflow decrease during 1980–2000, whereas during 2001–2016, change in land use and cover was the main factor in streamflow decrease, accounting for 75.5% of the decline ( [[#Bao--2019|Bao et al., 2019]] ). The changes in hydrological regime and extreme floods cause changes in river morphology and the river channel system which impact water availability.

In China, a quantitative assessment based on a multi-model dataset (six global hydrological models driven by three observation-based global forcings) during 1971–2010 suggested that climate variability dominated the changes in streamflow in more the 80% of river segments, while direct human impact dominated changes mostly in northern China ( [[#Liu--2019b|Liu et al., 2019b]] ). In the Lancang-Mekong River basin, climate variability would have contributed 45% more flood occurrences in the middle of the basin, while reservoir operation reduced it by 36% during 2008–2016 as compared with 1985–2007 ( [[#Yun--2020|Yun et al., 2020]] ).

In western China, the total annual snow mass declines at a rate of 3.3 × 10 9 pg per decade ( ''p'' &lt; 0.05), which accounts for approximately 0.46% of the mean of annual snow mass (7.2 × 10 11 pg). The loss could be valued in terms of replacement cost at 0.1 billion CN¥ (at the present value) every year (1 USD = 7 CN¥) compounded over the past 40 years ( [[#Wu--2021|Wu et al., 2021]] ). In the Mekong River Delta in Vietnam, climate-change impacts include a 30% annual increase in rainfall, shifting rainfall patterns, an average temperature increase of 0.5°C over the past 30 years and an average SLR of 3 mm yr –1 over the past three decades, resulting in a greater flooding threat ( [[#Wang--2021a|Wang et al., 2021a]] ).

A recent study ( [[#Wang--2021b|Wang et al., 2021b]] ) has shown that during 1936–2019, due largely to intensified precipitation induced by a warming climate, the streamflow of the Ob, Yenisei and Lena rivers has increased by ∼ 7.7, 7.4 and 22.0%, respectively. While rising temperatures can reduce streamflow via evapotranspiration, it can enhance groundwater discharge to rivers due to permafrost thawing. In permafrost-developed basins, the thawing permafrost will continue to result in increased streamflow. However, with further permafrost degradation in the future, the positive effect of permafrost thaw on streamflow would probably be offset by the negative effect of the increase in basin evapotranspiration. This could result in a situation where runoff reaches threshold level and then declines. This is clearly marked in the Ob River basin, which is characterised by the highest precipitation, whereas in the case of the Yenisei and Lena rivers, further research is needed.

The HKH region is susceptible to floods and related hazards caused by a cloud burst and other landscape-based processes such as glacial lake outburst floods, which can seriously damage property, lives and infrastructure ( [[#Shrestha--2010|Shrestha et al., 2010]] ). The likely increased frequency of hazards caused by abnormal glacier changes, such as the glacier collapses happened on two glaciers in western Tibetan Plateau in 2016 ( [[#Kääb--2018|Kääb et al., 2018]] ), and also surges which were frequently found in this vast region (e.g. [[#Bhambri--2017|Bhambri et al., 2017]] ; [[#Mukherjee--2017|Mukherjee et al., 2017]] ; [[#Ding--2018|Ding et al., 2018]] ), threatening the security of the local and down streaming societies (high confidence).The total amount and area of glacier lakes increased during last decade ( [[#Zhang--2015|Zhang et al., 2015]] ; [[#Chen--2017c|Chen et al., 2017c]] ) ( ''high confidence'' ). Himalayan rivers are frequently hit by catastrophic floods caused by the failure of glacial lakes ( [[#Cook--2018|Cook et al., 2018]] ; [[#Ahluwalia--2016|Ahluwalia et al., 2016]] ). In Kedarnath, India (western Himalaya), a flash flood was triggered by glacier lake outburst flood (GLOF) released from the Chorabari glacial lake in June 2013 which caused extensive flooding, erosion of riverbanks and damage to downstream villages and towns, as well as the loss of several thousand lives ( [[#Rafiq--2019|Rafiq et al., 2019]] ; [[#Das--2015|Das et al., 2015]] ). Nepal has experienced 24 GLOF events which have caused considerable loss of life and damage to property and infrastructure (Icimod, 2011). There is ''high confidence'' that current glacier shrinkages have caused more glacial lakes to form in most mountainous regions, including HMA, but there is limited evidence that the frequency of GLOF has changed ( [[#Hock--2019|Hock et al., 2019]] ). [[#Veh--2018|Veh et al. (2018)]] reported no clear trend of increasing GLOF events in the Himalayan region, although the southern Himalaya was identified as a hotspot region compared with the western Himalaya. Research has shown a decrease in glacier area of 24% in Nepal between 1980 and 2010 ( [[#Bajracharya--2014|Bajracharya et al., 2014]] ).

Climate-change impacts on both the quantity and quality of freshwater resources will hinder the attainment of SDG-6 ( [[#Water--2020|Water, 2020]] ). Contamination of drinking water is caused by wildfires and drought that contribute to elevated levels of nutrients (nitrogen, phosphorus and sulphates), heavy metals (lead, mercury, cadmium and chromium), salts (chloride and fluorides), hydrocarbons, pesticides and even pharmaceuticals. Heavy rains and flooding also increase nutrients, heavy metals and pesticides, as well as turbidity and faecal pathogens in water supplies–especially when sewage treatment plants are overwhelmed by runoff ( [[#Mora--2018|Mora et al., 2018]] ). Pharmaceuticals and personal-care products (from source to disposal) are contributing to the vulnerability of urban waters. A study of vulnerability assessment of urban waters in highly populated cities in India and Sri Lanka, through analysing the concurrence of Pharmaceuticals and Personal Care Products (PPCPs), enteric viruses, antibiotic-resistant bacteria, metals, faecal contamination and antibiotic resistance genes (ARGs), also underlines the need for a resilience strategy and action plan ( [[#Rafiq--2019|Rafiq et al., 2019]] ).

Adequate water supply for various uses is crucial for millions of people living in the mountains of Asia. Particularly in the HKH region, mountain springs play an important role in generating stream flow for non-glaciated catchments and in maintaining dry-season flows across many watersheds ( [[#Scott--2019|Scott et al., 2019]] ; [[#Stott--2014|Stott and Huq, 2014]] ). There is a good deal of evidence that the springs are drying up or yielding less discharge ( [[#Tambe--2012|Tambe et al., 2012]] ; Tiwari and [[#Joshi--2014|Joshi, 2014]] ; [[#Sharma--2016|Sharma et al., 2016]] ), threatening local communities who depend on spring water for their lives and livelihoods. Some of the main reasons for drying springs include anthropogenic impacts (deforestation, exploitative land use), infrastructure (road construction), socioeconomic changes (increasing demand and modernisation of facilities) and climatic changes (changes in rainfall regime and higher temperature) ( [[#Stott--2014|Stott and Huq, 2014]] ; Tiwari and [[#Joshi--2014|Joshi, 2014]] ; [[#Sharma--2016|Sharma et al., 2016]] ).

The Ganges–Brahmaputra region also faces the threat increased frequency of flood events ( [[#Lutz--2019|Lutz et al., 2019]] ). Floods and extreme events can impact river channel systems ( [[#Grainger--2014|Grainger and Conway, 2014]] ). One of the challenges in South Asia is the shifting boundaries of river channels. For instance, the major floods on the Indus in July 2010 altered the river’s course in Pakistan, moving it closer to the Indian district of Kutch ( [[#Grainger--2014|Grainger and Conway, 2014]] ). In the eastern tributary of the Ganges system, the alluvial fan of the Koshi River basin has shifted by more than 113 km to the west in the past two centuries ( [[#Chakraborty--2010|Chakraborty et al., 2010]] ), which may be due to heavy sediment load from the Himalayan rivers in which about 50 million tons of sediment is deposited annually in the alluvial plains ( [[#Sinha--2019|Sinha et al., 2019]] ; [[#Chakraborty--2010|Chakraborty et al., 2010]] ).

Asia is no exception to the global trend of lake ecosystems, which provide drinking water to millions of people, being degraded ( [[#Jenny--2020|Jenny et al., 2020]] ) and severely threatened at the same time by climate change ( [[#Mischke--2020|Mischke, 2020]] ). Lake surface conditions, such as ice cover, surface temperature, evaporation and water level react dramatically to this threat, and there are negative implications for water quantity and quality, food provisioning, recreational opportunities and transportation ( [[#Woolway--2020|Woolway et al., 2020]] ). Due to substantial regional variability, the quantum of future changes in lake water storage remains uncertain. A recent study ( [[#Liu--2019a|Liu et al., 2019a]] ) using Moderate Resolution Imaging Spectroradiometer 500-m spatial resolution global water product data, and applying the least squares method to analyse changes in the area of 14 lakes in Central Asia from 2001 to 2016, has shown that the area-shrinkage changes for all plains lakes in the study region could be attributed to climate change and human activities.

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