The performance of glaciohydrological models which simulate catchment response to climate variability depends to a large degree on the data used to force the models. The forcing data become increasingly important in high‐elevation, glacierized catchments where the interplay between extreme topography, climate, and the cryosphere is complex. It is challenging to generate a reliable forcing data set that captures this spatial heterogeneity. In this paper, we analyze the results of a 1 year field campaign focusing on air temperature and precipitation observations in the Langtang valley in the Nepalese Himalayas. We use the observed time series to characterize both temperature lapse rates (LRs) and precipitation gradients (PGs). We study their spatial and temporal variability, and we attempt to identify possible controlling factors. We show that very clear LRs exist in the valley and that there are strong seasonal differences related to the water vapor content in the atmosphere. Results also show that the LRs are generally shallower than the commonly used environmental lapse rates. The analysis of the precipitation observations reveals that there is great variability in precipitation over short horizontal distances. A uniform valley wide PG cannot be established, and several scale‐dependent mechanisms may explain our observations. We complete our analysis by showing the impact of the observed LRs and PGs on the outputs of the TOPKAPI‐ETH glaciohydrological model. We conclude that LRs and PGs have a very large impact on the water balance composition and that short‐term monitoring campaigns have the potential to improve model quality considerably.

Significance: Changes in the hydrology of high-altitude catchments may have major consequences for downstream water supply. Based on model projections with a higher spatiotemporal resolution and degree of process complexity than any previous intercontinental comparative study, we show that the impacts of climate change cannot be generalized. These impacts range from a high climatic sensitivity, decreasing runoff, and significant seasonal changes in the Central Andes of Chile to increasing future runoff, limited seasonal shifts, but increases in peak flows in the Nepalese Himalaya. This study constrains uncertainty about response times and mechanisms controlling glacier and runoff response to climate and sets a benchmark for process-based modeling of the climate change impact on the hydrology of high-altitude catchments.

This study presents volume and mass changes of seven (five partially debris-covered, two debris-free) glaciers in the upper Langtang catchment in Nepal. We use a digital elevation model (DEM) from 1974 stereo Hexagon satellite data and seven DEMs derived from 2006–2015 stereo or tri-stereo satellite imagery (e.g., SPOT6/7). The availability of multiple independent DEM differences allows the identification of a robust signal and narrowing down of the uncertainty about recent volume changes. The volume changes calculated over several multiyear periods between 2006 and 2015 consistently indicate that glacier thinning has accelerated with respect to the period 1974–2006. We calculate an ensemble-mean elevation change rate of –0.45 ± 0.18 m a⁻¹ for 2006–2015, while for the period 1974–2006 we compute a rate of −0.24 ± 0.08 m a⁻¹. However, the behavior of glaciers in the study area is heterogeneous, and the presence or absence of debris does not seem to be a good predictor for mass balance trends. Debris-covered tongues have nonlinear thinning profiles, and we show that recent accelerations in thinning correlate with the presence of supraglacial cliffs and lakes. At stagnating glacier areas near the glacier front, however, thinning rates decreased with time or remained constant. The April 2015 Nepal earthquake triggered large avalanches in the study catchment. Analysis of two post-earthquake DEMs revealed that the avalanche deposit volumes remaining 6 months after the earthquake are negligible in comparison to 2006–2015 elevation changes. However, the deposits compensate about 40 % the mass loss of debris-covered tongues of 1 average year.

[1] In the headwater catchments of the main Asian rivers, glaciohydrological models are a useful tool to anticipate impacts of climatic changes. However, the reliability of their projections strongly depends on the quality and quantity of data that are available for parameter estimation, model calibration and validation, as well as on the accuracy of climate change projections. In this study the physically oriented, glaciohydrological model TOPKAPI-ETH is used to simulate future changes in snow, glacier, and runoff from the Hunza River Basin in northern Pakistan. Three key sources of model uncertainty in future runoff projections are compared: model parameters, climate projections, and natural climate variability. A novel approach, applicable also to ungauged catchments, is used to determine which model parameters and model components significantly affect the overall model uncertainty. We show that the model is capable of reproducing streamflow and glacier mass balances, but that all analyzed sources of uncertainty significantly affect the reliability of future projections, and that their effect is variable in time and in space. The effect of parametric uncertainty often exceeds the impact of climate uncertainty and natural climate variability, especially in heavily glacierized subcatchments. The results of the uncertainty analysis allow detailed recommendations on network design and the timing and location of field measurements, which could efficiently help to reduce model uncertainty in the future.