Improvement of lumped models in multiple infows rivers by principal component analysis and reliability analysis

• Autorzy: Pashazadeh Arash , Javan Mitra

Identyfikatory

DOI

10.1007/s11600-019-00290-6

• Języki publikacji: EN

Abstrakty

EN

Flood routing as an important part of food management is a technique for predicting the fow in downstream of a river channel or reservoir. Lumped, semi-distributed and distributed models have been devised in this regard. The convex and Att-Kin models are capable of simulating foods in single branches, while in reality, rivers and channels are multiple infows. The convex and modifed Att-Kin models as the simplest lumped models in terms of the storage equation were developed based on an equivalent infow for routing the multiple infows rivers in the present study. The genetic algorithm, a quite robust algorithm, was used for parameter estimation of the extended models. The ability of the extended models in simulating the outfow hydrograph of multiple infows systems was tested on two multiple infows case studies. The results of extended models were compared with the equivalent Muskingum infow model. Comparison of the extended models with the Muskingum model showed that the extended models with one parameter less than the Muskingum model could be suitable for use in food routing of multiple infows systems. The efect of infow hydrographs at diferent time steps was investigated by the principal component analysis (PCA) and reliability analysis. The results showed that the outfow hydrograph of the case study was precisely simulated and predicted by the gene expression programming (GEP) and multilayer perceptron (MLP) models. The PCA and reliability analysis results were adopted for the lumped, GEP and MLP models. The outfow hydrograph was precisely simulated and predicted by the GEP and MLP models, while the precision of lumped models (extended convex, extended modifed Att-Kin and Muskingum models) was not increased.

Słowa kluczowe

EN

genetic algorithm; GA; multiple infow; Convex; modifed Att-Kin; flood routing; lumped model

PL

algorytm genetyczny; GA; Convex

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2019
• Tom: Vol. 67, no. 4
• Strony: 1149--1161
• Opis fizyczny: Bibliogr. 63 poz.

Twórcy

autor

Pashazadeh Arash

• Department of Civil Engineering Razi University Kermanshah Iran

autor

Javan Mitra

• Department of Civil Engineering Razi University Kermanshah Iran

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).