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Upper Indus Basin (UIB) streamflow originates largely from glacier and snow melt in the upstream Himalaya, Karakoram, and Hindu Kush mountain ranges and is extremely vulnerable because of its projected climate changes, dense populations, and hydropolitical tensions. Accurate knowledge of streamflow constituents is required for resilient water resources management; this is precluded by a paucity of measurement as well as climatological and topographic complexity. Here we integrate citizen scientist acquired geochemical samples, collected from October 2018 through September 2019 in the Shimshal watershed of the Karakoram Mountains of Pakistan, with Sentinel‐1 (S1) synthetic aperture radar (SAR)‐derived wet snow maps, to better understand streamflow constituents for the high altitude and heavily glaciated catchment. We use Bayesian end‐member mixture analysis to separate river flows into baseflow and meltwater constituents, using fixed and time‐variant melt end‐member values. We compare river hydrograph separation results with S1 wet snow time series maps for the same timeframe. We then utilize S1 imagery to inform end‐member mixture analysis to separate meltwaters into snow and glacier melt. For the Shimshal catchment, we find that about 85% of annual river flows are derived from snow and glacier melt; 45% of annual flows are derived from snow melt and 40% glacier melt. Engaged and committed citizen scientists enabled geochemical sample collection and analysis on a significant temporal and spatial scale. In the future, co‐produced knowledge that both implements local expertise and that is also planned and utilized by diverse stakeholders may increase climatological awareness and resilience in the UIB. Plain Language Summary: The Indus River Basin is home to about 300 million people that rely on streamflow for their livelihoods. Streamflow in the Indus is largely derived from snow and glacier melt from upstream mountain ranges. As populations increase and climate changes, understanding the role of snow and glacier melt in Indus streamflow is important for water resources management. Because of the rugged and remote nature of these mountain ranges, these important factors are not well understood. In this study, we work with local citizens in the Karakoram Mountains of Pakistan, who collected water samples from October 2018 through September 2019. We analyze these samples to better understand the role of meltwater in streamflow. We find that about 85% of streamflow is derived from snow and glacier meltwater. We also incorporate satellite remote sensing to better understand the role of snow versus glacier melt in streamflow. Snowmelt contributes 45% to streamflow; glacier melt contributes 40%. Improved knowledge of the role of snow and glacier melt in streamflow is important for sustainable water resources management in an area that is extremely vulnerable to water scarcity. Working with citizen scientists may improve our understanding of important variables to understand climate change in the region. Key Points: Citizen scientist acquired geochemical tracers are integrated with Sentinel‐1 synthetic aperture radar remote sensing to examine streamflow constituentsMeltwater provides about 85% of the annual hydrograph in the Shimshal catchment: 45% snowmelt and 40% glacier meltCo‐produced knowledge holds the potential to address challenges with sparse climatological measurement in remote and rugged terrain [ABSTRACT FROM AUTHOR]

Glaciers are generally believed to be subjugating by global warming but the Karakoram glaciers are reportedly maintaining their balance. Earlier studies in the Karakoram and its sub-basins have mostly addressed a short span of time and used complex models to understand the phenomenon. Thus, this study is based on a long-term trend analysis of the computed runoff components using satellite data with continuous spatial and temporal coverage incorporated into a simple degree day Snowmelt Runoff Model (SRM). The trends of melt runoff components can help us understanding the future scenarios of the glaciers in the study area. The SRM was calibrated against the recorded river flows in the Hunza River Basin (HRB). Our simulations showed that runoff contribution from rain, snow, and glaciers are 14.4%, 34.2%, and 51.4%, respectively during 1995–2010. The melting during the summer has slightly increased, suggesting overall but modest glacier mass loss which consistent with a few recent studies. The annual stream flows showed a rising trend during the 1995–2010 period, while, rainfall and temperatures showed contrasting increasing/decreasing behavior in the July, August, and September months during the same period. The average decreasing temperatures (0.08 °C per annum) in July, August, and September makes it challenging and unclear to explain the reason for this rising trend of runoff but a rise in precipitation in the same months affirms the rise in basin flows. At times, the warmer rainwater over the snow and glacier surfaces also contributed to excessive melting. Moreover, the uncertainties in the recorded hydrological, meteorological, and remote sensing data due to low temporal and spatial resolution also portrayed contrasting results. Gradual climate change in the HRB can affect river flows in the near future, requiring effective water resource management to mitigate any adverse impacts. This study shows that assessment of long-term runoff components can be a good alternative to detect changes in melting glaciers with minimal field observations. [ABSTRACT FROM AUTHOR]

We estimate future changes in precipitation over the entire Indus basin of Pakistan with a particular focus on the high‐elevation upper indus basin (UIB). A statistical downscaling approach is used. We consider the spatial variability of observed precipitation on seasonal scales. Large‐scale atmospheric patterns are employed for general circulation model (GCM) selection and subsequent projections. Firstly, we identify the precipitation governing predictors from ERA‐Interim reanalysis. We further quantify the robustness of governing predictors against other reanalysis datasets (ERA5 and NCEP‐NCAR‐II) to assess future projections' fidelity. We perform S‐mode Principal Component Analysis on predictor fields and compare loading patterns using Taylor diagrams to assess predictor correspondence between different reanalysis. Similarly, we compare ERA‐Interim variables with model‐simulated fields during the historical period to select better performing GCMs and quantify model uncertainty. The regional suitability of available GCMs in our study is also demonstrated. Ensemble (median) changes in regional precipitation derived through atmospheric fields show an elevation‐dependent response of the UIB at representative concentration pathway (RCP) scenarios RCP4.5 and RCP8.5, where increased precipitation will mostly fall at high elevations. However, the positive signals are more distinct during the winter and monsoon seasons, particularly over the central Karakoram. Meanwhile, a decrease in precipitation is robust during the pre‐monsoon period, particularly over the northwestern regions. These signals intensify and become more robust during 2071–2100 under RCP8.5, and the better‐performing models and signal‐to‐noise ratios further support this finding. The spatial patterns of projected changes suggest stronger (weaker) and further northward penetrating westerly systems during the winter (pre‐monsoon) season. Increased warming will also strengthen monsoon circulations, and these will penetrate further into the northwestern and trans‐Himalayan regions. The Lower Indus shows a mixed seasonal response that is more uncertain. The present analysis provides an alternative perspective to the ongoing research of assessing climate responses in complex regions. [ABSTRACT FROM AUTHOR]

This study investigates the projections of precipitation and temperature at the local scale in the Upper Indus Basin (UIB) in Pakistan using six Regional Climate Models (RCMs) from CORDEX under two Representative Concentration Pathways (RCP 4.5 and RCP 8.5). For twenty-four stations spread across the study area, the Long Ashton Research Station Weather Generator, version six (LARS-WG6), was used to downscale the daily data from the six different RCMs for maximum temperature (T max ), minimum temperature (T min ), and precipitation (pr) at a spatial resolution of 0.44°. Investigations were made to predict changes in mean annual values of T max , T min , and precipitation during two future periods, i.e., the mid-century (2041-2070) and end-century (2071-2100). The model results from statistical and graphical comparison validated that the LARS-WG6 can simulate the temperature and the precipitation in the UIB. Each of the six RCMs and their ensemble revealed a continuously increased temperature projection in the basin; nevertheless, there is variation in projected magnitude across RCMs and between RCPs. The rise in average T max and T min was more significant under RCP 8.5 than RCP 4.5, possibly due to unmitigated greenhouse gas emissions (GHGs). The precipitation projections follow the non-uniform trend, i.e., not all RCMs agree on whether the precipitation will increase or decrease in the basin, and no orderly variations were detected during any future periods under any RCP. However, an overall increase in precipitation is projected by the ensemble of RCMs., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

This study presents a map reporting valuable information on the cryosphere of the Central Karakoram National Park (CKNP, the largest protected area of Pakistan and the highest park in the world). All the information is provided considering the CKNP as a whole, and in detail by dividing it into five basins (i.e. Shigar, Hunza, Shyok, Upper Indus, and Gilgit). The glacier inventory reports 608 ice bodies covering 3680 km2 (∼35% of the CKNP area), with a total glacier volume of ca. 532 km3. In addition, we modeled the meltwater from glacier ice ablation over the period 23 July to 9 August 2011. The total melt amount is ca. 1.5 km3. Finally, we considered glacial lakes (202 water-bodies, covering 4 km2). For these latter glacier features, we also analyzed their potentially dangerous conditions and two lakes were found having such conditions. [ABSTRACT FROM AUTHOR]

Abstract: There is a high degree of uncertainty about the state and fate of Pakistan's Karakoram glaciers due to data scarcity in high altitude regions. They are thought to be less vulnerable to climatic change because they behave differently as compared with eastern Himalayas. This study measures the decadal temporal changes in the glacial ice area of Karakoram's Hunza River Basin, one of the eight subbasins of Upper Indus Basin. An attempt has been made to investigate the relationship between glacial ice area changes and calculated values of precipitation, temperature and run‐off. A combination of satellite and field‐based approach is applied. Output includes maps of glacial ice hypsometries of eight glacial ice subregions of Hunza River Basin for 3 years (i.e., 1989, 2002, and 2010). The results show a decreasing trend in the glacial ice‐covered area signifying a reduction of 20.47% with the largest reduction being in the lower elevation bands. There is presently no conclusive answer as to why glacial ice in the Karakoram is acting differently from the near‐global indication of glacial ice changes. Climate data from high altitudes are needed to find answer for this anomalous behaviour. [ABSTRACT FROM AUTHOR]

Upper Indus Basin (UIB) is critical for Pakistan's economy as it is glacial in composition and snow melt that provides 80% of the fresh water to Indus River. Decadal fluctuations in the precipitation in UIB during 1980-2010, using interpolation technique in Arc Map were explored in present study. The results provided a positive correlation between the winter precipitation and summer runoff in middle elevation basins of UIB. The map of decadal difference of mean annual rainfall (1980-2010), prepared in Arc Geographic Information System 9.0, revealed that around Gilgit, Skardu, Astore, Chilas and Bunji, was found the least difference in mean annual rainfall, i.e. of -1.68 to-2.14mm, whereas area around Kakul experienced maximum rainfall decadal difference ranged from -13.63 to -17.45mm. The study suggested that south of lesser Himalayan areas experienced maximum rainfall variability during the period 1980-2010, whereas, lesser variability in north of Himalayan areas inferred safer addition in fresh water in Indus from its glacial reserve. [ABSTRACT FROM AUTHOR]

A systematic increase in global temperature since the industrial revolution has been attributed to anthropogenic forcing. This increase has been especially evident over the Himalayas and Central Asia and is touted as a major contributing factor for glacier mass balance declines across much of this region. However, glaciers of Pakistan's Karakorum region have shown no such decline during this time period, and in some instances have exhibited slight advance. This discrepancy, known as the 'Karakorum Anomaly', has been attributed to unusual amounts of debris covering the region's glaciers; the unique seasonality of the region's precipitation; and localized cooling resulting from increased cloudiness from monsoonal moisture. Here we present a tree-ring based reconstruction of summer (June-August) temperature from the Karakorum of North Pakistan that spans nearly five centuries (1523-2007 C.E.). The ring width indices are derived from seven collections (six- Picea smithiana and one- Pinus gerardiana) from middle-to-upper timberline sites in the northern Karakorum valleys of Gilgit and Hunza at elevations ranging from 2850 to 3300 meters above mean sea level (mean elevation 3059 m asl). The reconstruction passes all traditional calibration-verification schemes and explains 41 % of the variance of the nested Gilgit-Astore instrumental station data (Gilgit-1454 m asl, 1951-2009; Astore-2167 m asl, 1960-2013). Importantly, our results indicate that Karakorum temperature has remained decidedly out of phase with hemispheric temperature trends for at the least the past five centuries, highlighting the long-term stability of the Karakorum Anomaly, and suggesting that the region's temperature and cloudiness are contributing factors to the anomaly. [ABSTRACT FROM AUTHOR]

Motivated by the potential flood outburst of Lake Gojal in the ungauged highly glacierized (27%) upper Hunza River Basin (HRB) in Pakistan that was dammed by a massive landslide on 4 January 2010, we attempt to analyze the characteristics of water inflow to the lake employing remote sensing data, two hydrological models, and sparsely observed data. One of the models (Model I) is a monthly degree-day model, while another (Model II) is the variable infiltration capacity (VIC) model. The mixture of glacier runoff output from Model I and runoff over unglacierized areas calculated by Model II has a similar seasonal variation pattern as that estimated from data recorded at a downstream station. This suggests that glacier runoff is the main source (87%) of runoff inflow into the lake. A sensitivity analysis suggests that the water inflow to the lake is highly sensitive to an increase in air temperature. Runoff in May is predicted to sharply increase by 15% to more than two-fold if the air temperature increases by 1 to 7, but it is predicted to increase only from 9% to 34% if the precipitation increases by 10% to 40%. The results suggested that the water inflow into Lake Gojal will not sharply rise even if there is heavy rain, and it needs to be in caution if the air temperature sharply increases. Analysis on long-term air temperature record indicates that the water inflow into the lake in May 2010 was probably less than average owing to the relatively low air temperature. Consequently, the flood outburst did not occur before the completion of the spillway on 29 May 2010. [ABSTRACT FROM AUTHOR]

Mountainous areas in the northern Pakistan are blessed by numerous rivers that have great potential in water resources and hydropower production. Many of these rivers are unexploited for their water resource potential. If the potential of these rivers are explored, hydropower production and water supplies in these areas may be improved. The Indus is the main river originating from mountainous area of the Himalayas of Baltistan, Pakistan in which most of the smaller streams drain. In this paper, the hydrology of the mountainous areas in northern Pakistan is studied to estimate flow pattern, long-term trend in river flows, characteristics of the watersheds, and variability in flow and water resource due to impact of climate change. Eight watersheds including Gilgit, Hunza, Shigar, Shyok, Astore, Jhelum, Swat, and Chitral, Pakistan have been studied from 1960 to 2005 to monitor hydrological changes in relation to variability in precipitation, temperature and mean monthly flows, trend of snow melt runoff, analysis of daily hydrographs, water yield and runoff relationship, and flow duration curves. Precipitation from ten meteorological stations in mountainous area of northern Pakistan showed variability in the winter and summer rains and did not indicate a uniform distribution of rains. Review of mean monthly temperature of ten stations suggested that the Upper Indus Basin can be categorized into three hydrological regimes, i.e., high-altitude catchments with large glacierized parts, middle-altitude catchments south of Karakoram, and foothill catchments. Analysis of daily runoff data (1960-2005) of eight watersheds indicated nearly a uniform pattern with much of the runoff in summer (June-August). Impact of climate change on long-term recorded annual runoff of eight watersheds showed fair water flows at the Hunza and Jhelum Rivers while rest of the rivers indicated increased trends in runoff volumes. The study of the water yield availability indicated a minimum trend in Shyok River at Yogo and a maximum trend in Swat River at Kalam. Long-term recorded data used to estimate flow duration curves have shown a uniform trend and are important for hydropower generation for Pakistan which is seriously facing power crisis in last 5 years. [ABSTRACT FROM AUTHOR]

A major proportion of flow in the Indus River is contributed by its snow- and glacier-fed river catchments situated in the Himalaya, Karakoram and Hindukush ranges. It is therefore essential to understand the cryosphere dynamics in this area for water resource management. The MODIS MOD10A2 remote-sensing database of snow cover products from March 2000 to December 2009 was selected to analyse the snow cover changes in the Hunza River basin (the snow- and glacier-fed sub-catchment of the Indus River). A database of daily flows for the Hunza River at Dainyor Bridge over a period of 40 yr and climate data (precipitation and temperature) for 10 yr from three meteorological stations within the catchment was made available to investigate the hydrological regime in the area. Analysis of remotely sensed cryosphere (snow and ice cover) data during the last decade (2000-2009) suggest a rather slight expansion of cryosphere in the area in contrast to most of the regions in the world where glaciers are melting rapidly. This increase in snow cover may be the result of an increase in winter precipitation caused by westerly circulation. The impact of global warm- ing is not effective because a large part of the basin area lies under high altitudes where the temperature remains negative throughout most of the year. [ABSTRACT FROM AUTHOR]