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Over recent years, numerous open catchment datasets have been published. In 2017, the first CAMELS (catchment attributes and meteorology for large-sample studies) dataset was released for the continental US by Addor et al. (2017). It comprises data for several hundreds of catchments including dynamic time series of daily resolution over several decades for discharge, precipitation and temperature - originally compiled by Newman et al. (2015) - as well as static basin attributes such as indices on topography, soil, geology and climate. Subsequently, similar datasets for several other countries were made or will be made publicly available. Some of these also contain additional data such as attributes on glaciers or human influence like, e.g., the CAMELS datasets for Chile (Alvarez-Garreton et al., 2018) and Great Britain (Coxon et al., 2020). Such datasets build an accessible and unified basis for reproducible and complementary research. They led to a high stimulation of hydrological research with methodologies that could not be applied before, like the joint evaluation of a large number of catchments.We present CAMELS-CH, a new dataset for about 200 basins in Switzerland that will be released in 2022. In this collaborative project, several academic institutions and agencies work together to publish a hydro-meteorological dataset that covers both dynamic and static catchment data, and that accounts for the wide range of hydrological regimes in Switzerland, e.g., alpine environment, hydropower usage, densely populated and cultivated regions, etc. We summarize the current state of the project, remaining challenges, in particular regarding translating base data into the CAMELS format, and the final steps toward dataset publication. ReferencesAddor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies. Hydrology and Earth System Sciences, 21, 5293-5313, 2017Alvarez-Garreton, C., Mendoza, P. A., Boisier, J. P., Addor, N., Galleguillos, M., Zambrano-Bigiarini, M., Lara, A., Cortes, G., Garreaud, R., McPhee, J., Ayala, A.: The CAMELS-CL dataset: catchment attributes and meteorology for large sample studies-Chile dataset, Hydrology and Earth System Sciences, 22, 5817–5846, 2018Coxon, G., Addor, N., Bloomfield, J., Freer, J., Fry, M., Hannaford, J., Howden, N., Lane, R., Lewis, M., Robinson, E., Wagener, T.,and Woods, R.: CAMELS-GB: Hydrometeorological time series and landscape attributes for 671 catchments in Great Britain, Earth System Science Data 12, 2459–2483, 2020Newman, A., Clark, M., Sampson, K., Wood, A., Hay, L., Bock, A., Viger, R., Blodgett, D., Brekke, L., Arnold, J.: Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance. Hydrology and Earth System Sciences, 19, 209-223, 2015

We present a new ensemble of daily runoff simulations for meso-scale catchments in Switzerland for the period 1981–2099: The Hydro-CH2018-Runoff ensemble. The ensemble contains runoff simulations for 93 catchments in Switzerland covering a wide range of different catchment characteristics governed by pluvial, nival and glacial runoff regimes. The hydrological modelling system PREVAH was thoroughly calibrated and validated for each catchment. The simulations show satisfactory performance with a median Nash-Sutcliffe efficiency of 0.82 in the calibration and validation period. The calibrated parameters were then used to simulate runoff under climate change for each of the 93 catchments. These simulations were driven by the high-resolution new Swiss climate change scenarios (CH2018) consisting of 68 GCM-RCM combinations covering 3 different emission scenarios: RCP2.6, RCP4.5 and RCP8.5. The simulations show good agreement between simulated and observed runoff regimes in the reference period. The Hydro-CH2018-Runoff ensemble is publicly available under http://doi.org/10.5281/zenodo.3937485 (Muelchi, R., Rossler, O., Schwanbeck, J., Weingartner, R., and Martius, O. (2020) Hydro-CH2018-Runoff ensemble (version v1). Zenodo) and can be used for further impact studies.

Future changes in runoff impact many sectors such as agriculture, energy production, or ecosystems. Therefore, assessments of runoff characteristics under climate change are crucial for decision-makers and water management planners. We study changes in moderate runoff extremes, i.e. low and high flows that occur once every year or season in today's climate. Daily runoff is simulated for 93 Swiss catchments for the period 1981–2099 under the Representative Concentration Pathway 8.5 using 20 downscaled regional climate models from the newest transient Swiss climate change scenarios. The magnitude of moderate annual low flows is projected to decrease in lower lying catchments and to increase in Alpine catchments. Seasonal low flows in summer are projected to decrease and seasonal low flows in winter to increase. Moderate annual high flows are projected to slightly increase in most catchments but to decrease in high Alpine catchments. However, the climate model agreement on the sign of change in moderate high flows is not robust. The projected decrease in Alpine catchments contradicts results for extreme high flows from previous studies. This difference may be due to different indicators used (moderate extremes vs. extremes). The time of emergence indicates the timing of significant changes in the flow magnitudes. For low flows the time of emergence is early in 21st century in high Alpine catchments due to early changes in winter low flows. In lower lying catchments, significant changes in low flows emerge later in the century. For moderate high flows, only few catchments indicate a significant change. Shifts in the seasonality of moderate low flows due to climate change are found in many catchments. By end of the 21st century, low flows are projected to occur in late summer and early autumn in most catchments indicating that the lack of precipitation in summer and autumn exceeds the contributions from other processes such as snow and glacier melt contributions. For moderate high flows, changes in seasonality are found in Alpine catchments with a shift towards earlier occurrence in summer due to a reduced contribution of snow and glacier melt in summer. In the projections, low flows occur more frequently in lower lying catchments and less frequently in Alpine catchments. For high flows the frequency increases slightly in most catchments, but models often disagree on the sign of change. Changes in the annual co-occurrence of moderate low and high flows are mainly due to changes in the frequency of low flows that increases in lower lying catchments and decreases in Alpine catchments.

Summary With the aim of calibrating a large number of catchments for a semi-distributed, process-based conceptual hydrological model, we introduce a straightforward yet robust automatic calibration procedure. Since identification of a global parameter optimum is not feasible in practical terms, the procedure presents a trade-off between computational time and algorithm complexity to identify, with reasonable effort, a parameter set that is well representative of the catchment’s dynamics. In its standard mode, the calibration combines three efficiency scores which are evaluated both for the entire calibration period and in terms of their annual and monthly variations. These scores are furthermore assessed only in their relevant value range, producing a comprehensive overall acceptability score which is used to guide an iterative parameter search algorithm. An additional set of four flood-sensitive scores is added, thereby improving results in the peak-flow range. Calibration was done for 140 mesoscale (roughly 10–1000 km2) catchments in Switzerland, using the hydrological modelling system PREVAH (Precipitation–Runoff-EVApotranspiration-HRU related model) in hourly time steps. For 49 representative catchments with long gauge records, a median Nash–Sutcliffe efficiency (NSE) of 0.75 was achieved for the calibration period in standard mode. The limited loss in efficiency when moving to the validation period (median NSE: 0.72) proves the stability and representativity of the parameter sets identified, while a Monte-Carlo analysis underscores the effectiveness of our procedure. The Nash–Sutcliffe efficiencies for the additional flood calibration are slightly lower, but again almost equally high for the calibration (0.69) and the validation (0.67) period. Despite the concessions made to improve peak-flow results, the simulation’s hydrological plausibility was not compromised. The ultimate goal of our study is flood estimation in ungauged Swiss catchments through continuous simulation using PREVAH. With the extensive calibration task presented in this article, the foundation is laid for regionalisation of the tuneable model parameters, which will be addressed in the companion paper ( Viviroli et al., 2009a ), along with detailed flood estimation results.

Determining the role of different precipitation periods for peak discharge generation is crucial for both projecting future changes in flood probability and for short- and medium-range flood forecasting. We analyze catchment-averaged daily precipitation time series prior to annual peak discharge events (floods) in Switzerland. The high amount of floods considered – more than 4000 events from 101 catchments have been analyzed – allows to derive significant information about the role of antecedent precipitation for peak discharge generation. Based on the analysis of precipitation times series, we propose a new separation of flood-related precipitation periods: (i) the period 0 to 1 day before flood days, when the maximum flood-triggering precipitation rates are generally observed, (ii) the period 2 to 3 days before flood days, when longer-lasting synoptic situations generate "significantly higher than normal" precipitation amounts, and (iii) the period from 4 days to one month before flood days when previous wet episodes may have already preconditioned the catchment. The novelty of this study lies in the separation of antecedent precipitation into the precursor antecedent precipitation (4 days before floods or earlier, called PRE-AP) and the short range precipitation (0 to 3 days before floods, a period when precipitation is often driven by one persistent weather situation like e.g. a stationary low-pressure system). Because we consider a high number of events and because we work with daily precipitation values, we do not separate the "antecedent" and "peak-triggering" precipitation. The whole precipitation recorded during the flood day is included in the short-range antecedent precipitation. The precipitation accumulating 0 to 3 days before an event is the most relevant for floods in Switzerland. PRE-AP precipitation has only a weak and region-specific influence on flood probability. Floods were significantly more frequent after wet PRE-AP periods only in the Jura Mountains, in the western and eastern Swiss plateau, and at the exit of large lakes. As a general rule, wet PRE-AP periods enhance the flood probability in catchments with gentle topography, high infiltration rates, and large storage capacity (karstic cavities, deep soils, large reservoirs). In contrast, floods were significantly less frequent after wet PRE-AP periods in glacial catchments because of reduced melt. For the majority of catchments however, no significant correlation between precipitation amounts and flood occurrences is found when the last three days before floods are omitted in the precipitation amounts. Moreover, the PRE-AP was not higher for extreme floods than for annual floods with a high frequency and was very close to climatology for all floods. The weak influence of PRE-AP is a clear indicator of a short discharge memory of Prealpine, Alpine and Southalpine Swiss catchments. Our study nevertheless poses the question whether the impact of long-term precursory precipitation for floods in such catchments is not overestimated in the general perception. We conclude that the consideration of a 3–4 days precipitation period should be sufficient to represent (understand, reconstruct, model, project) Swiss Alpine floods.