Calibration of conceptual rainfall-runoff models by selected differential evolution and particle swarm optimization variants

Napiorkowski, Jaroslaw J.; Piotrowski, Adam P.; Karamuz, Emilia; Senbeta, Tesfaye B.

doi:10.1007/s11600-022-00988-0

Artykuł - szczegóły

Tytuł artykułu

Calibration of conceptual rainfall-runoff models by selected differential evolution and particle swarm optimization variants

Autorzy

Napiorkowski Jaroslaw J. , Piotrowski Adam P. , Karamuz Emilia , Senbeta Tesfaye B.

Wybrane pełne teksty z tego czasopisma

https://www.springer.com/journal/11600

Identyfikatory

DOI

10.1007/s11600-022-00988-0

Warianty tytułu

Języki publikacji

Abstrakty

The performance of conceptual catchment runoff models may highly depend on the specific choice of calibration methods made by the user. Particle Swarm Optimization (PSO) and Differential Evolution (DE) are two well-known families of Evolutionary Algorithms that are widely used for calibration of hydrological and environmental models. In the present paper, five DE and five PSO optimization algorithms are compared regarding calibration of two conceptual models, namely the Swedish HBV model (Hydrologiska Byrans Vattenavdelning model) and the French GR4J model (modèle du Génie Rural à 4 paramètres Journalier) of the Kamienna catchment runoff. This catchment is located in the middle part of Poland. The main goal of the study was to find out whether DE or PSO algorithms would be better suited for calibration of conceptual rainfall-runoff models. In general, four out of five DE algorithms perform better than four out of five PSO methods, at least for the calibration data. However, one DE algorithm constantly performs very poorly, while one PSO algorithm is among the best optimizers. Large differences are observed between results obtained for calibration and validation data sets. Differences between optimization algorithms are lower for the GR4J than for the HBV model, probably because GR4J has fewer parameters to optimize than HBV.

Słowa kluczowe

conceptual rainfall-runoff models HBV GR4J particle swarm optimization differential evolution

Wydawca

Instytut Geofizyki PAN
Springer

Czasopismo

Acta Geophysica

Rocznik

2023

Tom

Vol. 71, no. 5

Strony

2325--2338

Opis fizyczny

Bibliogr. 109 poz., rys., tab.

Twórcy

autor

Napiorkowski Jaroslaw J.

j.napiorkowski@igf.edu.pl

Institute of Geophysics, Polish Academy of Sciences, Ks. Janusza 64, 01-452 Warsaw, Poland

https://orcid.org/0000-0002-0273-4193

autor

Piotrowski Adam P.

Institute of Geophysics, Polish Academy of Sciences, Ks. Janusza 64, 01-452 Warsaw, Poland

autor

Karamuz Emilia

Institute of Geophysics, Polish Academy of Sciences, Ks. Janusza 64, 01-452 Warsaw, Poland

autor

Senbeta Tesfaye B.

Institute of Geophysics, Polish Academy of Sciences, Ks. Janusza 64, 01-452 Warsaw, Poland

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-6cf8f83b-8203-4d35-8a95-63d4db8a22a1