Development of a Nonparametric Model for Multivariate Hydrological Monthly Series Simulation Considering Climate Change Impacts

Salman Sharifazari () and Shahab Araghinejad ()

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2015, vol. 29, issue 14, 5309-5322

Abstract: One of the water resources modeling requirements is sufficient knowledge of long-term series of meteorological and hydrological parameters especially normal discharge in structural position and specific points of the basin. In this study, based on the nearest neighbor resampling method, a non-parametric model has been developed for a contemporaneous and correlated series simulation. To evaluate the performance of the developed model, hydrological basin time series of the Sirwan River located in west of Iran were simulated. The results obtained from the developed model were compared with the results of parametric models, PARMA and MPAR. Assessment of the compared results showed that the developed model had a better efficiency and performance in simulating time series than the parametric models. Also, the simulated time series statistical characteristics had a better conformity with the observed time series. Moreover, simulated time series with the concern of climate scenarios, e.g., increase or decrease annual discharge, showed that the developed model had a good efficiency in considering these changes and effects in time series simulation. Copyright Springer Science+Business Media Dordrecht 2015

Keywords: K-nearest neighbor; Simulation; Stochastic processes; Sirwan River (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s11269-015-1119-3

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