Ice cliffs can act as “hot spots” for melt on debris-covered glaciers and promote local glacier mass loss. Repeat high-resolution remote-sensing data are therefore required to monitor the role of ice cliff dynamics in glacier mass loss. Here we analyze high-resolution aerial photogrammetry data acquired during the 2007, 2018, and 2019 post-monsoon seasons to delineate and monitor the morphology, distribution, and temporal changes of the ice cliffs across the debris-covered Trakarding Glacier in the eastern Nepal Himalaya. We generate an ice cliff inventory from the 2018 and 2019 precise terrain data, with ice cliffs accounting for 4.7 and 6.1% of the debris-covered area, respectively. We observe large surface lowering (>2.0 m a−1) where there is a denser distribution of ice cliffs. We also track the survival, formation, and disappearance of ice cliffs from 2018 to 2019, and find that ∼15% of the total ice cliff area is replaced by new ice cliffs. Furthermore, we observe the overall predominance of northwest-facing ice cliffs, although we do observe spatial heterogeneities in the aspect variance of the ice cliffs (ice cliffs face in similar/various directions). Many new ice cliffs formed across the stagnant middle sections of the glacier, coincident with surface water drainage and englacial conduit intake observations. This spatial relationship between ice cliffs and the glacier hydrological system suggests that these englacial and supraglacial hydrological systems play a significant role in ice cliff formation.

Climate-induced cryospheric changes can have a significant impact on the downstream water availability. In this study, the Open Global Glacier Model (OGGM) and the Glacio-hydrological Degree-day Model (GDM) are integrated to project the response of cryospheric and hydrological systems to climate change until 2100. The study area comprises six sub-basins of glacierized Koshi River basin covering Nepalese and Chinese territories. The output from OGGM is provided as input to GDM along with the spatial and hydro-meteorological data. The average glacier area change in all the sub-basins from 2021 to 2100 is estimated as 65 and 85% decrease and the average glacier volume change is estimated as 76 and 86% decrease for RCP 4.5 and 8.5 scenarios, respectively. The future simulated discharge shows an increasing trend in pre-monsoon and monsoon seasons and a decreasing trend in post-monsoon and winter seasons after 2060 in all the sub-basins, which can lead to wetter wet seasons and drier dry seasons in the far future. A shift in peak flow is observed from August to July in most of the sub-basins. The coupled modelling technique used in this study can largely improve our understanding of glacio-hydrological dynamics in the Himalayan region.

No abstract

An assessment of the water supply and its seasonal and annual changes over the century in the High Mountain Asia (HMA) region is of increasing interest due to its potential impact on one-sixth of the global population. In order to understand the changing hydrology and snow and ice melt, we used remotely sensed Advanced Scatterometer (ASCAT) observations of glacier melt (GM) and a distributed and gridded Glacio-hydrological Degree-day Model (GDM) in three river basins: Tamor, Trishuli and Marsyangdi. The GDM-estimated contribution of snowmelt, icemelt, rainfall and baseflow in river flows is found to be most accurate in the Trishuli River basin, with Nash-Sutcliffe efficiency (NSE) between the estimated and observed discharges of 0.81 and volume differences of −0.5%, and reasonably accurate in the Tamor River basin, with NSE of 0.69 and volume difference of −7.51%. Similarly, NSE of 0.81 and volume difference of 4.64% in Marsyangdi River basin. We find strong similarities in the timing of glacier melting using the GDM and from observations from the ASCAT GM, determining the seasonal start of glacier melting to within 6 days on average. In all basins ASCAT GM observes melting at higher elevations relative to GDM, average of 5,328 m a.s.l. Systematic differences in glacier melting area determined by modeling and satellite observations indicate ASCAT may have suboptimal resolution, view geometry and/or polarimetry for delineating glacier melting at the process-scale in complex topography, especially in the ablation zone. This is the first step in examining the remote sensing products that could potentially be incorporated into hydrologic models to increase the accuracy of the hydrologic flow as well as the ability to estimate river discharge in other basins with limited data.

The Bagmati River, which lies in central Nepal, originates in Bagdwar at an altitude of 2690 m and flows south through the Kathmandu valley. The river basin covers an area of 3750 sq. km and includes eight districts of Nepal. Flooding along this river is a common occurrence during the monsoon season. In this study, we compared rainfall events with river discharge, predicted the rate of future flooding events, and assessed the probable causes and socioeconomic impacts of flooding in the Bagmati River Basin. Data used to compare rainfall and discharge were based on rain gauge stations with the highest 24‐h records and also contributed directly to the run‐off at the Pandhera Dobhan discharge station, the lowest elevation water discharge gauge, in order to facilitate a direct comparison between basin rainfall and river discharge. Future trends in extreme 24‐h rainfall events and peak flood values were calculated for 2‐, 5‐, 10‐, 25‐, 50‐ and 100‐year recurrence intervals. Extreme 24‐h rainfall events varied between 195 mm to 552 mm among the different rain gauges, corresponding to a peak discharge at Pandhera Dobhan of 16 523 m3/s for the 100‐year return interval. We also elaborate on the probable causes of flooding in the central basin and summarise major past flood events and their impacts.

ABSTRACT:The hydrology of Upper Indus basin is not recognized well due to the intricacies in the climate and geography, and the scarcity of data above 5000 m a.s.l where most of the precipitation falls in the form of snow. The main objective of this study is to measure the contributions of different components of runoff in Upper Indus basin. To achieve this goal, the Modified positive degree day model (MPDDM) was used to simulate the runoff and investigate its components in two catchments of Upper Indus basin, Hunza and Gilgit River basins. These two catchments were selected because of their different glacier coverage, contrasting area distribution at high altitudes and significant impact on the Upper Indus River flow. The components of runoff like snow-ice melt and rainfall-base flow were identified by the model. The simulation results show that the MPDDM shows a good agreement between observed and modeled runoff of these two catchments and the effects of snow and ice are mainly reliant on the catchment characteristics and the glaciated area. For Gilgit River basin, the largest contributor to runoff is rain-base flow, whereas large contribution of snow-ice melt observed in Hunza River basin due to its large fraction of glaciated area. This research will not only contribute to the better understanding of the impacts of climate change on the hydrological response in the Upper Indus, but will also provide guidance for the development of hydropower potential and water resources assessment in these catchments.

No abstract

Analyzing climate change impacts on hydrology and future water supply projections is essential for effective water resource management and planning in the large river basins of Asia. In these regions, streamflow and glacier melt remain subject to significant uncertainties due to the lack of confidence in climate change projections and modeling methods. In this study, a glacier dynamics model (the Open Global Glacier Model was coupled with a glacio-hydrological model [the Glacio-hydrological Degree-day Model (GDM)] to predict possible hydrological changes in the head watershed of the Urumqi River under three shared socioeconomic pathways SSP2-4.5, SSP3-7.0, and SSP5-8.5. The GDM was calibrated and validated against in situ observed discharge data for the 2007–2011 and 2012–2018 periods. The resulting Nash–Sutcliffe efficiency (NSE) values were 0.82 and 0.81, respectively. The GDM was driven with an ensemble of five downscaled CMIP6 datasets to examine the potential impacts of climate change on hydrologic processes in the basin. Four runoff components were simulated with the GDM: base flow, rainfall, ice melt, and snow melt. It was determined that rainfall constituted the predominant source of runoff, followed by baseflow and ice melt. During the calibration and validation periods, snow and ice melt contributed 25.14 and 25.62%, respectively, to the total runoff. Under all SSP scenarios, the projected runoff decline indicated that the peak runoff time had passed. It was revealed that a 2°C increase in the monthly average temperature could result in a 37.7% increase in the total discharge of the basin. Moreover, the GDM was more responsive to changes in air temperature than to changes in glacier extent.