Combined deterministic _ stochastic forecasting of monthly river flows for water management

1st International Conference on Advances in Environmental Engineering

生态环境科学

Peksova Szolgayova, E.^1,2 ; Vyleta, R.^3 ; Szolgay, J.^3 ; Lukac, Z.^4

Na Veselí 22, Praha

14000, Czech Republic^1

Formerly at the Centre for Water Resource Systems, Vienna University of Technology, Karlsplatz 13, Vienna

1040, Austria^2

Dept. of Land and Water Resources Management, Faculty of Civil Engineering, Slovak University of Technology, Radlinského 11, Bratislava

810 05, Slovakia^3

Bratislava Water Company, Preovská 48, Bratislava

826 46, Slovakia^4

关键词: Conceptual model;    Forecasting error;    Heteroscedasticity;    Monthly rainfalls;    Non-linear time-series models;    Non-stationarities;    Rainfall-runoff modeling;    Time series models;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/92/1/012052/pdf
DOI  :  10.1088/1755-1315/92/1/012052

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Monthly discharges can be modelled and predicted by the decomposition of the runoff process model into two components - deterministic and stochastic. For such approach the term hybrid was often adopted. In this study a hybrid (deterministic-stochastic) modelling approach for one step ahead forecasting of mean monthly discharges at the gauging stations Banská Bystrica and Brehy on the Hron River in Slovakia was developed. The aim was to join the conceptual monthly rainfall runoff model KVHK and several time series models of the forecasting error time series of the conceptual model into a hybrid framework. Since these rainfall-runoff model error series may exhibit nonstationarity and heteroscedasticity, beside traditional ARMA models, GARCH type nonlinear time series models were also considered.