Abstract. Floods have strong impacts in the Mediterranean region and there are concerns about a possible increase in their intensity due to climate change. In this study, a large database of 171 basins located in southern France with daily discharge data with a median record length of 45 years is considered to analyze flood trends and their drivers. In addition to discharge data, outputs of precipitation, temperature, evapotranspiration from the SAFRAN reanalysis and soil moisture computed with the ISBA land surface model are also analyzed. The evolution of land cover in these basins is analyzed using the CORINE database. The trends in floods above the 95th and 99th percentiles are detected by the Mann–Kendall test and quantile regression techniques. The results show that despite the increase in extreme precipitation reported by previous studies, there is no general tendency towards more severe floods. Only for a few basins is the intensity of the most extreme floods showing significant upward trends. On the contrary, most trends are towards fewer annual flood occurrences above both the 95th and 99th percentiles for the majority of basins. The decrease in soil moisture seems to be an important driver for these trends, since in most basins increased temperature and evapotranspiration associated with a precipitation decrease are leading to a reduction in soil moisture. These results imply that the observed increase in the vulnerability to these flood events in recent decades is mostly caused by human factors such as increased urbanization and population growth rather than climatic factors.

Abstract. In a context of climate change and water demand growth, understanding the origin of water flows in the Himalayas is a key issue for assessing the current and future water resource availability and planning the future uses of water in downstream regions. Two of the main issues in the hydrology of high-altitude glacierized catchments are (i) the limited representation of cryospheric processes controlling the evolution of ice and snow in distributed hydrological models and (ii) the difficulty in defining and quantifying the hydrological contributions to the river outflow. This study estimates the relative contribution of rainfall, glaciers, and snowmelt to the Khumbu River streamflow (Upper Dudh Koshi, Nepal, 146 km2, 43 % glacierized, elevation range from 4260 to 8848 m a.s.l.) as well as the seasonal, daily, and sub-daily variability during the period 2012–2015 by using the DHSVM-GDM (Distributed Hydrological Soil Vegetation Model – Glaciers Dynamics Model) physically based glacio-hydrological model. The impact of different snow and glacier parameterizations was tested by modifying the snow albedo parameterization, adding an avalanche module, adding a reduction factor for the melt of debris-covered glaciers, and adding a conceptual englacial storage. The representation of snow, glacier, and hydrological processes was evaluated using three types of data (MODIS satellite images, glacier mass balances, and in situ discharge measurements). The relative flow components were estimated using two different definitions based on the water inputs and contributing areas. The simulated hydrological contributions differ not only depending on the used models and implemented processes, but also on different definitions of the estimated flow components. In the presented case study, ice melt and snowmelt contribute each more than 40 % to the annual water inputs and 69 % of the annual stream flow originates from glacierized areas. The analysis of the seasonal contributions highlights that ice melt and snowmelt as well as rain contribute to monsoon flows in similar proportions and that winter outflow is mainly controlled by the release from the englacial water storage. The choice of a given parametrization for snow and glacier processes, as well as their relative parameter values, has a significant impact on the simulated water balance: for instance, the different tested parameterizations led to ice melt contributions ranging from 42 % to 54 %. The sensitivity of the model to the glacier inventory was also tested, demonstrating that the uncertainty related to the glacierized surface leads to an uncertainty of 20 % for the simulated ice melt component.

Reliable precipitation data in the Himalayas are essential for the study of the water resources, the evolution of glaciers, and the present and future climate. Although several types of precipitation datasets are available for the Himalayan region, all of them have limitations, which hamper the quantification of the precipitation fluxes at high elevations. This study compares different types of precipitation datasets issued from (i) in situ data, (ii) satellite-based data [TRMM, Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS)], and (iii) a reanalysis product [High Asia Refined analysis (HAR)] for a small headwater catchment at high elevations (Upper Dudh Koshi, Nepal) and assesses the impact of the precipitation uncertainty on the result of the modeling of the glacio-hydrological system. During the analyzed period from 2010 to 2015, large differences between the precipitation datasets occur regarding annual amounts (ranging from 410 to 1190 mm yr−1) as well as in seasonal and diurnal cycles. The simulations with the glacio-hydrological model Distributed Hydrological Soil Vegetation Model–Glaciers Dynamics Model (DHSVM-GDM) show that the choice of a given precipitation dataset greatly impacts the simulated snow cover dynamics and glacier mass balances as well as the annual, seasonal, and diurnal streamflows. Due to the uncertainty in the precipitation, the simulated contribution of the ice melt to the annual outflow also remains uncertain and simulated fractions range from 29% to 76% for the 2012–13 glaciological year.