{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T06:54:40Z","timestamp":1772261680162,"version":"3.50.1"},"reference-count":42,"publisher":"Copernicus GmbH","issue":"4","license":[{"start":{"date-parts":[[2018,4,20]],"date-time":"2018-04-20T00:00:00Z","timestamp":1524182400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Hydrol. Earth Syst. Sci."],"abstract":"<jats:p>Abstract. This paper proposes a systematic assessment of the performance\nof an analytical modeling framework for streamflow probability distributions\nfor a set of 25 Swiss catchments. These catchments show a wide range of\nhydroclimatic regimes, including namely snow-influenced streamflows. The\nmodel parameters are calculated from a spatially averaged gridded daily\nprecipitation data set and from observed daily discharge time series, both in\na forward estimation mode (direct parameter calculation from observed data)\nand in an inverse estimation mode (maximum likelihood estimation). The\nperformance of the linear and the nonlinear model versions is assessed in\nterms of reproducing observed flow duration curves and their natural\nvariability. Overall, the nonlinear model version outperforms the linear\nmodel for all regimes, but the linear model shows a notable performance\nincrease with catchment elevation. More importantly, the obtained results\ndemonstrate that the analytical model performs well for summer discharge for\nall analyzed streamflow regimes, ranging from rainfall-driven regimes with\nsummer low flow to snow and glacier regimes with summer high flow. These\nresults suggest that the model's encoding of discharge-generating events\nbased on stochastic soil moisture dynamics is more flexible than previously\nthought. As shown in this paper, the presence of snowmelt or ice melt is\naccommodated by a relative increase in the discharge-generating frequency, a\nkey parameter of the model. Explicit quantification of this frequency\nincrease as a function of mean catchment meteorological conditions is left\nfor future research.<\/jats:p>","DOI":"10.5194\/hess-22-2377-2018","type":"journal-article","created":{"date-parts":[[2018,4,20]],"date-time":"2018-04-20T02:21:45Z","timestamp":1524190905000},"page":"2377-2389","source":"Crossref","is-referenced-by-count":19,"title":["Analytical flow duration curves for summer streamflow in Switzerland"],"prefix":"10.5194","volume":"22","author":[{"given":"Ana Clara","family":"Santos","sequence":"first","affiliation":[]},{"given":"Maria Manuela","family":"Portela","sequence":"additional","affiliation":[]},{"given":"Andrea","family":"Rinaldo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1140-6244","authenticated-orcid":false,"given":"Bettina","family":"Schaefli","sequence":"additional","affiliation":[]}],"member":"3145","published-online":{"date-parts":[[2018,4,20]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","unstructured":"Addor, N. and Fischer, E.\u00a0M.: The influence of natural variability and\ninterpolation errors on bias characterization in RCM simulations, J.\nGeophys. 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