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We present CAMELS-CH (Catchment Attributes and MEteorology for Large-sample Studies – Switzerland), a large-sample hydro-meteorological data set for hydrologic Switzerland in central Europe. This domain covers 331 basins within Switzerland and neighboring countries. About one-third of the catchments are located in Austria, France, Germany and Italy. As an Alpine country, Switzerland covers a vast diversity of landscapes, including mountainous environments, karstic regions, and several strongly cultivated regions, along with a wide range of hydrological regimes, i.e., catchments that are glacier-, snow- or rain dominated. Similar to existing data sets, CAMELS-CH comprises dynamic hydro-meteorological variables and static catchment attributes. CAMELS-CH (; available at 10.5281/zenodo.7784632) encompasses 40 years of data between 1 January 1981 and 31 December 2020, including daily time series of stream flow and water levels, and of meteorological data such as precipitation and air temperature. It also includes daily snow water equivalent data for each catchment starting from 2 September 1998. Additionally, we provide annual time series of land cover change and glacier evolution per catchment. The static catchment attributes cover location and topography, climate, hydrology, soil, hydrogeology, geology, land use, human impact and glaciers. This Swiss data set complements comparable publicly accessible data sets, providing data from the "water tower of Europe". [ABSTRACT FROM AUTHOR]

Goodness-of-fit measures are important for an objective evaluation of runoff model performance. The Kling-Gupta efficiency (RKG), which has been introduced as an improvement of the widely used Nash-Sutcliffe efficiency, considers different types of model errors, namely the error in the mean, the variability, and the dynamics. The calculation of RKG is implicitly based on the assumptions of data linearity, data normality, and the absence of outliers. In this study, we propose a modification of RKG as an efficiency measure comprising non-parametric components, i.e. the Spearman rank correlation and the normalized flow-duration curve. The performances of model simulations for 100 catchments using the new measure were compared to those obtained using RKG based on a number of statistical metrics and hydrological signatures. The new measure resulted overall in better or comparable model performances, and thus it was concluded that efficiency measures with non-parametric components provide a suitable alternative to commonly used measures. [ABSTRACT FROM AUTHOR]

Abstract: In scientific communication, ambiguities in term usage can go unnoticed due not only to the distance between reader and writer but also to the existence of highly specialized scientific subcommunities. This commentary therefore aims at raising awareness about the use of terms that have different meanings within different hydrological subcommunities such as field hydrology, hydrological modelling, or statistical hydrology. To do so, we discuss the use of the following commonly used hydrological terms: sample, runoff, discharge, and streamflow. We performed three types of analyses to provide evidence of term usage and understanding, including both qualitative and quantitative approaches: a drawing exercise, a survey, and a literature corpus analysis. These analyses allow for a comparison of spontaneous definitions and the actual use of these terms in scientific publications. Our various information sources revealed that the dialogue between hydrologists within and across subdisciplines is substantially influenced by personal conceptualizations of terms that are not always shared across conversational partners. The terms discussed and illustrated in this commentary have to be seen as a small sample used to demonstrate the need for a thoughtful use of hydrological terms when communicating research, not only to a general audience but even across subdisciplines within hydrology. [ABSTRACT FROM AUTHOR]

Applications of runoff models usually rely on long and continuous runoff time series for model calibration. However, many catchments around the world are ungauged and estimating runoff for these catchments is challenging. One approach is to perform a few runoff measurements in a previously fully ungauged catchment and to constrain a runoff model by these measurements. In this study we investigated the value of such individual runoff measurements when taken at strategic points in time for applying a bucket-type runoff model (HBV) in ungauged catchments. Based on the assumption that a limited number of runoff measurements can be taken, we sought the optimal sampling strategy (i.e. when to measure the streamflow) to obtain the most informative data for constraining the runoff model. We used twenty gauged catchments across the eastern US, made the assumption that these catchments were ungauged, and applied different runoff sampling strategies. All tested strategies consisted of twelve runoff measurements within one year and ranged from simply using monthly flow maxima to a more complex selection of observation times. In each case the twelve runoff measurements were used to select 100 best parameter sets using a Monte Carlo calibration approach. Runoff simulations using these ‘informed’ parameter sets were then evaluated for an independent validation period in terms of the Nash-Sutcliffe efficiency of the hydrograph and the mean absolute relative error of the flow-duration curve. Model performance measures were normalized by relating them to an upper and a lower benchmark representing a well-informed and an uninformed model calibration. The hydrographs were best simulated with strategies including high runoff magnitudes as opposed to the flow-duration curves that were generally better estimated with strategies that captured low and mean flows. The choice of a sampling strategy covering the full range of runoff magnitudes enabled hydrograph and flow-duration curve simulations close to a well-informed model calibration. The differences among such strategies covering the full range of runoff magnitudes were small indicating that the exact choice of a strategy might be less crucial. Our study corroborates the information value of a small number of strategically selected runoff measurements for simulating runoff with a bucket-type runoff model in almost ungauged catchments. [ABSTRACT FROM AUTHOR]