{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T06:44:24Z","timestamp":1772261064276,"version":"3.50.1"},"reference-count":60,"publisher":"Copernicus GmbH","issue":"7","license":[{"start":{"date-parts":[[2019,7,9]],"date-time":"2019-07-09T00:00:00Z","timestamp":1562630400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002341","name":"Research Council of Finland","doi-asserted-by":"publisher","award":["283101"],"award-info":[{"award-number":["283101"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Geosci. Model Dev."],"abstract":"<jats:p>Abstract. The question of the environmental risks of social and\neconomic infrastructure has recently become apparent due to an increase in\nthe number of extreme weather events. Extreme runoff events include floods\nand droughts. In water engineering, extreme runoff is described in terms of\nprobability and uses methods of frequency analysis to evaluate an exceedance\nprobability curve (EPC) for runoff. It is assumed that historical\nobservations of runoff are representative of the future; however, trends in\nthe observed time series show doubt in this assumption. The paper describes a\nprobabilistic hydrological MARCSHYDRO (the MARkov Chain System) model that can be applied to\npredict future runoff extremes. The MARCSHYDRO model simulates\nstatistical estimators of multi-year runoff in order to perform future\nprojections in a probabilistic form. Projected statistics of the\nmeteorological variables available in climate scenarios force the model.\nThis study introduces the new model's core version and provides a user guide\ntogether with an example of the model set-up in a single case study. In this\ncase study, the model simulates the projected EPCs of annual runoff under\nthree climate scenarios. The scope of applicability and limitations of the\nmodel's core version 0.2 are discussed.<\/jats:p>","DOI":"10.5194\/gmd-12-2767-2019","type":"journal-article","created":{"date-parts":[[2019,7,9]],"date-time":"2019-07-09T01:38:56Z","timestamp":1562636336000},"page":"2767-2780","source":"Crossref","is-referenced-by-count":0,"title":["The probabilistic hydrological MARCS\n                    <sup>HYDRO<\/sup>\n                    (the MARkov Chain System) model: its structure and core version 0.2"],"prefix":"10.5194","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0739-9977","authenticated-orcid":false,"given":"Elena","family":"Shevnina","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrey","family":"Silaev","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"3145","published-online":{"date-parts":[[2019,7,9]]},"reference":[{"key":"ref1","unstructured":"Andreev, A., Kanto, A., and Malo, P.: Simple approach for distribution\nselection in the Pearson system, Working papers of Helsingin\nkauppakorkeakoulu, Helsinki, Finland, 25 pp., 2005."},{"key":"ref2","doi-asserted-by":"crossref","unstructured":"Arheimer, B. and Lindstr\u00f6m, G.: Climate impact on floods: changes in\nhigh flows in Sweden in the past and the future (1911\u20132100), Hydrol. 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