High Mountain Asia Research Articles

Quantified spatial-temporal variation of the fine-scale frozen soils during 1980–2014 in the headwaters of the Yellow River (HWYR) in High Mountain Asia

Global warming has aggravated the problem of permafrost degradation, the long-term variation of which is not well estimated. In this study, a fully coupled hydrothermal dynamics cold region hydrologic model was used to quantify the historical spatial–temporal characteristics of permafrost degradation by estimating the depth to permafrost table (DPT), taliks in different subbasins, maximum frozen depth (MFD) for seasonally frozen ground (SFG), thaw date (TD), and annual number of frozen days (NFD) in the headwaters of the Yellow River (HWYR) in eastern High Mountain Asia. The model considered the taliks and successfully estimated four historical fine-scale permafrost maps. Permafrost degradation began with the enlargement of active layer thickness (ALT), formation of taliks, rise in the permafrost bottom, and merging of the permafrost table and bottom, and ended with a decrease in MFD. From 1980 to 2014, the permafrost area (PA) in the study area decreased by a total of 17,849 km2 at a rate of more than −7100 km2/decade (−5.8 %/decade). The mean DPT increased by 0.8 m at 31.76 cm/decade and more than 100 cm/decade at the grid scale. The absolute MFD (AMFD) decreased by 0.11 m at −14.47 cm/decade. The mean TD decreased by 14.28 days at −5.56 days/decade and more than −20 days/decade at the grid scale. The mean NFD decreased by 25.51 days at −9.97 days/decade. The lowland area had a smaller NFD and an earlier TD than the mountainous area. Basins with a large air temperature (AT) and small elevation had a small DPT, MFD, TD, NFD, a large rate of decrease in TD and NFD, and increase in absolute DPT (ADPT), and a small rate of decrease in AMFD. The rates of increase in ADPT and decrease in AMFD were close to 0 when the change in AT was lower than 0.55 °C/decade.

A new projection for glacier mass and runoff changes over High Mountain Asia

A new projection for glacier mass and runoff changes over High Mountain Asia

Diurnal Variation of Precipitation over the High Mountain Asia: Spatial Distribution and Its Seasonality

Abstract Using abundant rainfall gauge measurements and Global Precipitation Mission (GPM) data, spatial patterns of rainfall diurnal cycles and their seasonality over high mountain Asia (HMA) were examined. Spatial distributions of rainfall diurnal cycles over the HMA have a prominent seasonality regulated by circulations at different spatiotemporal scales, within which large regional contrasts are embedded. Rainfall diurnal variability is relatively weak in the premonsoon season, with larger amplitude over the western HMA, the southeastern HMA, as well as southern periphery regions, characterized by a dominant late afternoon to morning rainfall preference. The pattern of rainfall spatial distributions is closely related to the midlatitude westerlies. Both the mean rainfall and amplitudes of diurnal cycles become more pronounced with the advance of monsoon season but weaken during postmonsoon. The widespread late afternoon to night pattern over HMA migrating with seasonal atmospheric circulation is consistent with the lifetime of convective systems, which become active from the afternoon due to radiative heating and decay during the night. Stationary terrain-dependent night-to-morning rainfall patterns are visible in those east–west-orientated valleys over HMA and the Qaidam basin throughout the seasons. This salient geographical dependence is associated with local circulation produced by the strong differential thermal conditions over mountains and valleys, which can lift the warm moist air at the mouth of the valley and trigger nocturnal convection. Significance Statement The main purpose of this study is to explore how spatial patterns of rainfall diurnal cycles over high mountain Asia vary with the seasons. Our results show that the widespread late afternoon to night rainfall over high mountain Asia migrating with seasonal atmospheric circulation is consistent with the lifetime of convective systems. Stationary terrain-dependent night-to-morning rainfall patterns are visible in those east–west-orientated valleys over high mountain Asia and the Qaidam basin throughout the seasons. These results highlight the importance of large-scale atmospheric circulation and local circulation on precipitation, which is critical for water resources over high mountain Asia.

Retrospective analysis and hazard assessment of Gega glacial lake in the eastern Himalayan syntaxis

The frequency of glacier related hazards like Glacial Lake Outburst Flood (GLOF) is increasing in the High Mountain Asia due to global climate warming. The extreme floods generated by glacial lake outburst aggravate the risk to people, towns and infrastructure in downstream regions. However, little attention is paid to the destructive potential of the lakes in the southeastern margin of the Tibet in spite of recent rapid increases in population, infrastructure, and economic investment. With retrospective investigation of the Gega lake, we found historical overtopping flood(s) impacted by landslides based on the lake dam consists of landslide deposits on both sides and bedrock in the middle, manifesting the GLOF risk in future. BRCH-J model is used to simulate the flow hydrographs after dam break, then, the HEC-RAS software is used to simulate the propagation of outburst floods. Finally, the GLOF risk is evaluated with a semi-quantitative approach considering overtopping and piping failure scenarios. The peak discharge after dam failure would reach up to 17,000 ​m3 ​s−1 (at dam site), which is about two times greater than the average seasonal flood peak near Gega village in the trunk river. Piping failure attains a larger peak discharge and quicker peak time (∼0.13 ​h) compared to the overtopping failure (∼0.5 ​h). The sensitivity analysis of materials properties (like internal friction angle and porosity etc.) shows geotechnical properties of the dam material affect the magnitude of peak discharge. The 1D steady flood routing of the peak flow indicates the flow depth is larger than 35 ​m at the Yarlung Tsangpo - Gega confluence. The extreme flow through narrow and steep terrain could even trigger debris flow along the Gega stream. The results can be useful for mitigating risk of GLOFs in the eastern Himalayan syntaxis and neighboring alpine areas.

Glacial lake outburst flood hazard under current and future conditions: worst-case scenarios in a transboundary Himalayan basin

Abstract. Glacial lake outburst floods (GLOFs) are a major concern throughout High Mountain Asia, where societal impacts can extend far downstream. This is particularly true for transboundary Himalayan basins, where risks are expected to further increase as new lakes develop. Given the need for anticipatory approaches to disaster risk reduction, this study aims to demonstrate how the threat from a future lake can be feasibly assessed alongside that of worst-case scenarios from current lakes, as well as how this information is relevant for disaster risk management. We have focused on two previously identified dangerous lakes (Galongco and Jialongco), comparing the timing and magnitude of simulated worst-case outburst events from these lakes both in the Tibetan town of Nyalam and downstream at the border with Nepal. In addition, a future scenario has been assessed, whereby an avalanche-triggered GLOF was simulated for a potential large new lake forming upstream of Nyalam. Results show that large (>20×106 m3) rock and/or ice avalanches could generate GLOF discharges at the border with Nepal that are more than 15 times larger than what has been observed previously or anticipated based on more gradual breach simulations. For all assessed lakes, warning times in Nyalam would be only 5–11 min and 30 min at the border. Recent remedial measures undertaken to lower the water level at Jialongco would have little influence on downstream impacts resulting from a very large-magnitude GLOF, particularly in Nyalam where there has been significant development of infrastructure directly within the high-intensity flood zone. Based on these findings, a comprehensive approach to disaster risk management is called for, combining early warning systems with effective land use zoning and programmes to build local response capacities. Such approaches would address the current drivers of GLOF risk in the basin while remaining robust in the face of worst-case, catastrophic outburst events that become more likely under a warming climate.

Sub-seasonal variability of supraglacial ice cliff melt rates and associated processes from time-lapse photogrammetry

Abstract. Melt from supraglacial ice cliffs is an important contributor to the mass loss of debris-covered glaciers. However, ice cliff contribution is difficult to quantify as they are highly dynamic features, and the paucity of observations of melt rates and their variability leads to large modelling uncertainties. We quantify monsoon season melt and 3D evolution of four ice cliffs over two debris-covered glaciers in High Mountain Asia (Langtang Glacier, Nepal, and 24K Glacier, China) at very high resolution using terrestrial photogrammetry applied to imagery captured from time-lapse cameras installed on lateral moraines. We derive weekly flow-corrected digital elevation models (DEMs) of the glacier surface with a maximum vertical bias of ±0.2 m for Langtang Glacier and ±0.05 m for 24K Glacier and use change detection to determine distributed melt rates at the surfaces of the ice cliffs throughout the study period. We compare the measured melt patterns with those derived from a 3D energy balance model to derive the contribution of the main energy fluxes. We find that ice cliff melt varies considerably throughout the melt season, with maximum melt rates of 5 to 8 cm d−1, and their average melt rates are 11–14 (Langtang) and 4.5 (24K) times higher than the surrounding debris-covered ice. Our results highlight the influence of redistributed supraglacial debris on cliff melt. At both sites, ice cliff albedo is influenced by the presence of thin debris at the ice cliff surface, which is largely controlled on 24K Glacier by liquid precipitation events that wash away this debris. Slightly thicker or patchy debris reduces melt by 1–3 cm d−1 at all sites. Ultimately, our observations show a strong spatio-temporal variability in cliff area at each site, which is controlled by supraglacial streams and ponds and englacial cavities that promote debris slope destabilisation and the lateral expansion of the cliffs. These findings highlight the need to better represent processes of debris redistribution in ice cliff models, to in turn improve estimates of ice cliff contribution to glacier melt and the long-term geomorphological evolution of debris-covered glacier surfaces.

Supraglacial debris thickness and supply rate in High-Mountain Asia

Supraglacial debris strongly modulates glacier melt rates and can be decisive for ice dynamics and mountain hydrology. It is ubiquitous in High-Mountain Asia, yet because its thickness and supply rate from local topography are poorly known, our ability to forecast regional glacier change and streamflow is limited. Here we combined remote sensing and numerical modelling to resolve supraglacial debris thickness by altitude for 4689 glaciers in High-Mountain Asia, and debris-supply rate to 4141 of those glaciers. Our results reveal extensively thin supraglacial debris and high spatial variability in both debris thickness and supply rate. Debris-supply rate increases with the temperature and slope of debris-supply slopes regionally, and debris thickness increases as ice flow decreases locally. Our centennial-scale estimates of debris-supply rate are typically an order of magnitude or more lower than millennial-scale estimates of headwall-erosion rate from Beryllium-10 cosmogenic nuclides, potentially reflecting episodic debris supply to the region’s glaciers.

Biophysical impacts of vegetation dynamics largely contribute to climate mitigation in High Mountain Asia

Satellite-driven and site observational data show that global warming has greatly enhanced vegetation activity (greening), with a broad upward trend in vegetation indices (VIs). However, the biophysical impact of vegetation on land surface temperature (Ts) is widely unknown, particularly in High Mountain Asia (HMA). In this study, we assessed vegetation dynamics in HMA from 2000 to 2020 and used intrinsic biophysical mechanism (IBM) models to quantify the biophysical feedback effects of vegetation on Ts. The results illustrate that, during the study period, HMA has undergone greening at a rate of 0.505 × 10−3 W m−2 μm−1 sr−1 yr−1 (solar-induced chlorophyll fluorescence: SIF) and 1.7 × 10−3 yr−1 (normalized vegetation index: NDVI), accounting for 52.75% and 47.24% of the total number of pixels, respectively. However, vegetation browning has occurred in areas such as the central Tien Shan and southeastern Tibet. Meanwhile, 64.22% (SIF) and 53.68% (NDVI) of the vegetation area in HMA showed a negative sensitivity of Ts to vegetation activity, particularly herbaceous and scrub vegetation in Inner Tibet and eastern Kun Lun. Additionally, the Bovine ratio and aerodynamic drag (ra) exhibited a negative sensitivity to vegetation activity. Most importantly, the vegetation activity-induced temperature changes were -0.278 K (ΔTNDVICIBM), -0.538 K (ΔTSIFCIBM), 0.028 K (ΔTNDVISIBM), and 0.024 K (ΔTSIFSIBM). Moreover, in the sensitivity method (ΔTVegSIBM), vegetation cooling was detected in more than half of the pixels in HMA and was even more pronounced with SIF, accounting for 64.22% compared to 53.68% with NDVI. Enhanced vegetation activity alters the original balance of latent and sensible heat fluxes (Le,H) and increases the turbulent heat transfer between land and atmosphere, particularly Le. Our findings have important implications for understanding the response and feedback of vegetation dynamics to climate change in arid alpine regions.

A robust glacial lake outburst susceptibility assessment approach validated by GLOF event in 2020 in the Nidu Zangbo Basin, Tibetan Plateau

As reports on glacial lake outburst floods (GLOFs) have increased with global warming, a robust GLOF susceptibility assessment approach is critical for disaster prevention and damage reduction. A robust GLOF susceptibility assessment approach, using the Analytic Hierarchy Process (AHP) to assess the potential hazard grades of glacial lakes combined with data from a digital elevation model (DEM), glaciers, remote sensing images, and field investigations, was constructed and applied in the Nidu Zangbo Basin in Nagqu, Tibetan Plateau. From 1988 to 2016, the total number and area of glacial lakes increased in this basin. There were 71 glacial lakes in the Nidu Zangbo Basin with a total area of 3.42 km2 in 2016, among which 14 lakes, accounting for an area>0.05 km2, were considered to be potentially dangerous glacial lakes (PDGLs) in this study. At the end of 2017, the proposed approach identified 6 of 14 PDGLs as high potentially hazardous, among which Jinwucuo, with the highest hazardous score, occurred GLOF event on June 26, 2020, which proves the robustness of the approach. Thus, the GOLF susceptibility in the Nidu Zangbo Basin was suggested to be evaluated regularly with the approach and update monitoring data and remote sensing images. The study provides valuable clues to assess the GLOF susceptibilities in High Mountain Asia (HMA).

Trends and spatial variations of rain-on-snow events over the High Mountain Asia

Rain-on-snow (ROS) events can greatly affect the snow process and cause severe snowmelt-related hazards. It is important to monitor the spatiotemporal distribution of ROS events over the ungauged High Mountain Asia (HMA). This study investigated the spatiotemporal variability of ROS events over the HMA and its potential influencing factors from 1981 to 2020 based on stand-alone Noah-MP land surface model simulations forced by hourly HARv2 reanalysis dataset. The results demonstrated that ROS activity occurred more frequently in the higher-elevation (2500–4000 m and 5500–6000 m a.s.l) regions of the Tianshan Mountains, Pamir, eastern Hindu Kush, Himalayas, and the western Hengduan Shan, with an annual maximum ROS frequency exceeding 15 days and a maximum intensity reaching 40 mm concentrated in spring and summer. ROS frequency experienced a significant decrease in the high-elevation (3000–4500 m a.s.l) regions of the eastern Hindu Kush, West Himalaya, and western Hengduan Shan with a rate exceeding −1.5 days/decade. The decrease in ROS frequency could be explained by a shifting of precipitation type from snowfall to rain driven by dramatic warming and resulting in a decline in snowfall and shortened snow cover persistence, particularly in spring and summer. On the contrary, significantly increasing trend mainly prevailed in the high-elevation (5000–6000 m a.s.l) regions of Transhimalaya and East Himalaya, exceeding 0.9 days/decade. The attribution of the increased ROS frequency was related to the significant increase in summer precipitation over the Inner Tibetan Plateau, along with an absolute increase in snowfall, which was beneficial to snow accumulation with frequent transition of the precipitation phase. The above outcomes improve our understanding of ROS events and highlight the importance of ROS in extreme snowmelt events and water resources management under a warming climate.

Ice thickness distribution of Himalayan glaciers inferred from DInSAR-based glacier surface velocity.

Retrieval of glacier ice thickness is extremely important for monitoring water resources and predicting glacier dynamics and changes. The inter-annual glacier ice thickness observations (more than 5years) exploit the glacier mass changes. Ice thickness is one of the important parameters to predict the future sea-level rise. Without adequate knowledge and precise information of glacier ice thickness distribution, future sea-level changes cannot be accurately assessed. In this study, we use an existing flow model to estimate the ice thickness of the High Mountain Asia (HMA) glaciers, using remote sensing techniques. The glacier ice velocity is one of the significant parameters in the Laminar flow model to retrieve the ice thickness. The glacier ice velocity is derived by utilizing the Differential SAR Interferometry (DInSAR) technique. The most optimum DInSAR data (ALOS-2/PALSAR-2) is used for estimating the ice velocity of the HMA glaciers. The ice thickness is mainly estimated for five different states in the HMA region, namely Himachal Pradesh, Uttarakhand, Sikkim, Bhutan, and Arunachal Pradesh. Most of the states are observed with a mean ice thickness of 100m. Five benchmark glaciers (Samudra Tapu, Bara Shigri, Chhota Shigri, Sakchum, and Gangotri glaciers) are also selected for validating our results with the existing thickness information. The issues related to velocity-based ice thickness inversion are also emphasized in this study. The high-velocity rate due to the influx of melting water from adjacent glaciers causes an increment in the flow rate. This abnormal velocity derives erroneous ice thickness measurements. This is one of the major problems to be considered in the velocity-based thickness-derived procedures. Finally, the investigation suggests the inclusion of the velocity influencing parameters in the physical-based models for an accurate ice thickness inversion.

Spatial and temporal dynamics of aufeis in the Tso Moriri basin, eastern Ladakh, India

AbstractAufeis is a common phenomenon in cold regions of the Northern Hemisphere that develops during winter by successive water overflow and freezing on ice‐covered surfaces. Most studies on aufeis occurrence focus on regions in North America and Siberia, while research in High Mountain Asia (HMA) is still in an exploratory phase. This study investigates the extent and dynamics of icing processes and aufeis in the Tso Moriri basin, eastern Ladakh, India. Based on a combination of 235 Landsat 5 TM/8 OLI and Sentinel‐2 imagery from 2008 to 2021 the occurrence of icing and aufeis was classified using a random forest classifier. A total of 27 frequently occurring aufeis fields with an average maximum extent of 9 km2 were identified, located at a mean elevation of 4,700 m a.s.l. Temporal patterns show a distinct accumulation phase (icing) between November and April, and a melting phase lasting from May until July. Icing is characterized by high seasonal and inter‐annual variability. Successive water overflow mainly occurs between January and March and seems to be related to diurnal freeze–thaw‐cycles, whereas higher daytime temperatures result in larger icing areas. Aufeis feeding sources are often located within or in close vicinity to wetland areas, while vegetation is largely absent on surfaces with frequent aufeis formation. These interactions require more attention in future research. In addition, this study shows the high potential of a machine learning approach to monitor icing processes and aufeis, which can be transferred to other regions.

‘Asian water towers’ are not a sustainable solution to the downstream water crisis

Quantifying climate change- and socioeconomic development-induced changes in the ‘water tower’ function is a major challenge in high-mountain Asia (HMA), especially when considering the affected downstream areas. This study applies historical monsoon-influenced rainfall patterns and the water stress index to quantify the climate change- and socioeconomic growth-induced changes in the ‘Asian water tower’ function through the middle of the 21st century by nonparametric empirical quantile mapping and empirical orthogonal function analysis. Water pressures are predicted to intensify in 25.84 ± 7.87 % of ‘water tower’ downstream watersheds. Enhancements in the ‘Asian water tower’ function are vulnerable to help stop the deterioration of downstream water pressure while increasing the water sufficiency probability by 7.97 ± 15.52 %. Water withdrawals are projected to explain 55.90 ± 21.77 % of water security in the ‘water tower’ function-affected watersheds in 2050; thus, this study calls for more effective policies and the development of technologies to reduce the water crisis in downstream HMA.

Polar amplification comparison among Earth’s three poles under different socioeconomic scenarios from CMIP6 surface air temperature

The polar amplification (PA) has become the focus of climate change. However, there are seldom comparisons of amplification among Earth’s three poles of Arctic (latitude higher than 60 °N), Antarctica (Antarctic Ice Sheet) and the Third Pole (the High Mountain Asia with the elevation higher than 4000 m) under different socioeconomic scenarios. Based on CMIP6 multi-model ensemble, two types of PA index (PAI) have been defined to quantify the PA intensity and variations, and PAI1/PAI2 is defined as the ratio of the absolute value of surface air temperature linear trend over Earth’s three poles and that for global mean/over other regions except Earth’s three poles. Arctic warms fastest in winter and weakest in summer, followed by the Third Pole, and Antarctica warms least. The similar phenomenon proceeds when global warming of 1.5–2.0 °C, and 2.0–3.0 °C above pre-industrial levels. After removing the Earth’s three poles self-influence, all the PAI2s increase much more obviously relative to the PAI1s, especially the Antarctic PAI. Earth’s three poles warm faster than the other regions. With the forcing increasing, PA accelerates much more over Antarctica and the Third Pole, but becomes weaker over Arctic. This demonstrates that future warming rate might make a large difference among Earth’s three poles under different scenarios.

Irrigation and warming drive the decreases in surface albedo over High Mountain Asia

Human and climate induced land surface changes resulting from irrigation, snow cover decreases, and greening impact the surface albedo over High Mountain Asia (HMA). Here we use a partial information decomposition approach and remote sensing data to quantify the effects of the changes in leaf area index, soil moisture, and snow cover on the surface albedo in HMA, home to over a billion people, from 2003 to 2020. The study establishes strong evidence of anthropogenic agricultural water use over irrigated lands (e.g., Ganges–Brahmaputra) which causes the highest surface albedo decreases (≤ 1%/year). Greening and decreased snow cover from warming also drive changes in visible and near-infrared surface albedo in different areas of HMA. The significant role of irrigation and greening in influencing albedo suggests the potential of a positive feedback cycle where albedo decreases lead to increased evaporative demand and increased stress on water resources.

On the Relevance of Aerosols to Snow Cover Variability Over High Mountain Asia

AbstractWhile meteorology and aerosols are identified as key drivers of snow cover (SC) variability in High Mountain Asia, complex non‐linear interactions between them are not adequately quantified. Here, we attempt to unravel these interactions through a simple relative importance (RI) analysis of meteorological and aerosol variables from ERA5/CAMS‐EAC4 reanalysis against satellite‐derived SC from Moderate Resolution Imaging Spectroradiometer across 2003–2018. Our results show a statistically significant 7% rise in the RI of aerosol‐meteorology interactions (AMI) in modulating SC during late snowmelt season (June and July), notably over low snow‐covered (LSC) regions. Sensitivity tests further reveal that the importance of meteorological interactions with individual aerosol species are more prominent than total aerosols over LSC regions. We find that the RI of AMI for LSC regions is clearly dominated by carbonaceous aerosols, on top of the expected importance of dynamic meteorology. These findings clearly highlight the need to consider AMI in hydrometeorological monitoring, modeling, and reanalyses.

Estimating glacier mass balance in High Mountain Asia based on Moderate Resolution Imaging Spectroradiometer retrieved surface albedo from 2000 to 2020

AbstractGlacier surface albedo is a key parameter of the glacier mass and energy balance process. Many scholars have used the albedo method to study mass balance for an individual glacier, but less attention has been given to large‐area glaciers. Based on Moderate Resolution Imaging Spectroradiometer (MODIS) retrieved glacier surface albedo and in situ mass balance, the correlations between albedo and mass balance are reported. The minimum/mean method (the whole glacier albedo is calculated by averaging the minimum/mean albedo of each grid cell), the MODIS snow albedo products (MxD10A1) and the MCD43A3 shortwave albedo were tested during the melt season (June–August) for four glaciers in the High Mountain Asia (HMA). Results reveal that albedo is well correlated with mass balance, the correlation (r) ranging from 0.41 to 0.90. Overall, the minimum method is better than the mean method, and MxD10A1 is better than MCD43A3. The albedo changes were calculated based on the MxD10A1 and the mean method, and a linear relationship is established between albedo changes and digital elevation models (DEMs) calculated mass balance from 2000 to 2016. A strong linear correlation (r = .9) is found between albedo changes and mass balance while excluding some areas that have insignificant seasonal variation in albedo, and the reconstructed albedo–mass balance relationship can be used to retrieve mass balance in large‐scale glaciers. Furthermore, the average loss of mass from 2000 to 2020 is calculated as −0.225 ± 0.040 m w.e.a−1. The greatest glacier mass loss is concentrated in the southeastern part of HMA, the mass loss in the north and west is less than that in the southeast, and the glacier mass is in a state of aggravated loss in recent years. Our study also offers a new method for estimating the large‐scale glacier mass balance.

Quantifying the Impact of the Billion Tree Afforestation Project (BTAP) on the Water Yield and Sediment Load in the Tarbela Reservoir of Pakistan Using the SWAT Model

The live storage of Pakistan’s major reservoirs, such as the Tarbela reservoir, has decreased in recent decades due to the sedimentation load from the Upper Indus Basin, located in High Mountain Asia. The government of Khyber Pakhtunkhwa took the initiative in 2014 and introduced the Billion Tree Afforestation Project (BTAP). They planted one billion trees by August 2017, mostly in hilly areas. In 2018, the Government of Pakistan also launched a project of 10 billion trees in five years. We assessed the effect of different land-use and land-cover (LULC) scenarios on the water yield and sediment load in the Tarbela reservoir of Pakistan. The soil and water assessment tool (SWAT) model was used to predict the impacts of the LULC changes on the water yield and sediment load under three distinct scenarios: before plantation (2013), after planting one billion trees (2017), and after planting ten billion trees (2025). The model calibration and validation were performed from 1984 to 2000 and 2001 to 2010, respectively, using the SUFI2 algorithm in SWAT-CUP at the Bisham Qila gauging station. The statistical evaluation parameters showed a strong relationship between observed and simulated streamflows: calibration (R2 = 0.85, PBIAS = 11.2%, NSE = 0.84) and validation (R2 = 0.88, PBIAS = 10.5%, NSE = 0.86). The validation results for the sediment load were satisfactory, indicating reliable model performance and validity accuracy (R2 = 0.88, PBIAS = −19.92%, NSE = 0.86). Under the LULC change scenarios, the water yield’s absolute mean annual values decreased from 54 mm to 45 mm for the first and second scenarios, while the third scenario had an estimated 35 mm mean annual water yield in the Tarbela reservoir. The sediment load results for the second scenario (2017) showed a 12% reduction in the sediment flow in the Tarbela reservoir after 1 billion trees were planted. In the third scenario (2025), following the planting of 10 billion trees, among which 3 billion were in the Tarbela basin, the sediment load was predicted to decrease by 22%. The overall results will help to inform the water managers and policymakers ahead of time for the best management and planning for the sustainable use of the water reservoirs and watershed management.

Distributional Validation of Precipitation Data Products with Spatially Varying Mixture Models

The high mountain regions of Asia contain more glacial ice than anywhere on the planet outside of the polar regions. Because of the large population living in the Indus watershed region who are reliant on melt from these glaciers for fresh water, understanding the factors that affect glacial melt along with the impacts of climate change on the region is important for managing these natural resources. While there are multiple climate data products (e.g., reanalysis and global climate models) available to study the impact of climate change on this region, each product will have a different amount of skill in projecting a given climate variable, such as precipitation. In this research, we develop a spatially varying mixture model to compare the distribution of precipitation in the High Mountain Asia region as produced by climate models with the corresponding distribution from in situ observations from the Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE) data product. Parameter estimation is carried out via a computationally efficient Markov chain Monte Carlo algorithm. Each of the estimated climate distributions from each climate data product is then validated against APHRODITE using a spatially varying Kullback–Leibler divergence measure. Supplementary materials accompanying this paper appear online.

Involving Turc-Budyko formula in evaluating gridded precipitation datasets in glaciated catchments

Recently, gridded precipitation datasets (GPDs) have become an essential input in hydrological modeling. Evaluation of their performance is a priori step before their application. When they are applied to a glaciated catchment, the glacier mass balance adds another dimension to the evaluation. This study has attempted to introduce the Turc-Budyko formula for validating the GPDs in glaciated catchments. This approach can identify the over- or under-estimation of catchment precipitation input by the GPDs. As a case study, the approach was applied in Upper Indus Basin (UIB), located in High Mountain Asia. The Turc-Budyko formula and other commonly used evaluation techniques found that APHRODITE underestimated the precipitation by 40 %, although it captured most of inter- and intra-annual variations of local climatology (CC > 0.6). CFSR and HAR were overestimated (106 % and 77 %) and characterize UIB as “Leaky” catchment, whereas underestimated GPDs characterize UIB as “Gaining” catchment. In leaky conditions, glacier storage changes were positive (0.21–0.37 m w.e. yr−1); while gaining conditions made negative glacier storage changes (-0.44 to −0.34 m w.e. yr−1) in UIB. None of the GPDs represented true conditions of glacio-hydrology in UIB. Introducing the Turc-Budyko formula confirmed that direct application of GPDs in hydrological modeling is implausible because GPDs generally cannot produce rational output of streamflow and mass balance simultaneously. It is recommended to locally correct the GPDs before any hydrological application in glacierized catchments.