An overview of the applications of wavelet transform for discharge and suspended sediment analysis
Kristina Potočki
orcid.org/0000-0002-2681-776X
; University of Zagreb, Faculty of Civil Engineering, Fra Andrije Kačića-Miošića 26, 10 000 Zagreb, Croatia
Gordon Gilja
orcid.org/0000-0002-8796-5264
; University of Zagreb, Faculty of Civil Engineering, Fra Andrije Kačića-Miošića 26, 10 000 Zagreb, Croatia
Duška Kunštek
; University of Zagreb, Faculty of Civil Engineering, Fra Andrije Kačića-Miošića 26, 10 000 Zagreb, Croatia
APA 6th Edition Potočki, K., Gilja, G. i Kunštek, D. (2017). An overview of the applications of wavelet transform for discharge and suspended sediment analysis. Tehnički vjesnik, 24 (5), 1561-1569. https://doi.org/10.17559/TV-20160613095312
MLA 8th Edition Potočki, Kristina, et al. "An overview of the applications of wavelet transform for discharge and suspended sediment analysis." Tehnički vjesnik, vol. 24, br. 5, 2017, str. 1561-1569. https://doi.org/10.17559/TV-20160613095312. Citirano 23.01.2021.
Chicago 17th Edition Potočki, Kristina, Gordon Gilja i Duška Kunštek. "An overview of the applications of wavelet transform for discharge and suspended sediment analysis." Tehnički vjesnik 24, br. 5 (2017): 1561-1569. https://doi.org/10.17559/TV-20160613095312
Harvard Potočki, K., Gilja, G., i Kunštek, D. (2017). 'An overview of the applications of wavelet transform for discharge and suspended sediment analysis', Tehnički vjesnik, 24(5), str. 1561-1569. https://doi.org/10.17559/TV-20160613095312
Vancouver Potočki K, Gilja G, Kunštek D. An overview of the applications of wavelet transform for discharge and suspended sediment analysis. Tehnički vjesnik [Internet]. 2017 [pristupljeno 23.01.2021.];24(5):1561-1569. https://doi.org/10.17559/TV-20160613095312
IEEE K. Potočki, G. Gilja i D. Kunštek, "An overview of the applications of wavelet transform for discharge and suspended sediment analysis", Tehnički vjesnik, vol.24, br. 5, str. 1561-1569, 2017. [Online]. https://doi.org/10.17559/TV-20160613095312
APA 6th Edition Potočki, K., Gilja, G. i Kunštek, D. (2017). Pregled primjene valićne transformacije u analizi protoka i suspendiranog nanosa. Tehnički vjesnik, 24 (5), 1561-1569. https://doi.org/10.17559/TV-20160613095312
MLA 8th Edition Potočki, Kristina, et al. "Pregled primjene valićne transformacije u analizi protoka i suspendiranog nanosa." Tehnički vjesnik, vol. 24, br. 5, 2017, str. 1561-1569. https://doi.org/10.17559/TV-20160613095312. Citirano 23.01.2021.
Chicago 17th Edition Potočki, Kristina, Gordon Gilja i Duška Kunštek. "Pregled primjene valićne transformacije u analizi protoka i suspendiranog nanosa." Tehnički vjesnik 24, br. 5 (2017): 1561-1569. https://doi.org/10.17559/TV-20160613095312
Harvard Potočki, K., Gilja, G., i Kunštek, D. (2017). 'Pregled primjene valićne transformacije u analizi protoka i suspendiranog nanosa', Tehnički vjesnik, 24(5), str. 1561-1569. https://doi.org/10.17559/TV-20160613095312
Vancouver Potočki K, Gilja G, Kunštek D. Pregled primjene valićne transformacije u analizi protoka i suspendiranog nanosa. Tehnički vjesnik [Internet]. 2017 [pristupljeno 23.01.2021.];24(5):1561-1569. https://doi.org/10.17559/TV-20160613095312
IEEE K. Potočki, G. Gilja i D. Kunštek, "Pregled primjene valićne transformacije u analizi protoka i suspendiranog nanosa", Tehnički vjesnik, vol.24, br. 5, str. 1561-1569, 2017. [Online]. https://doi.org/10.17559/TV-20160613095312
Sažetak Analysis and modelling of discharge and suspended sediment time series is of great importance in hydrology and water management. Discharge and suspended sediment time series are the result of complex physical processes and characterized by non-stationarity. Wavelet transform enables representation of non-stationarities in time-frequency domain, decomposition and reconstruction of series and de-noising of series, and therefore represents powerful tool for analysis of hydrological time series. Overview of mentioned wavelet transform advantages is given in this paper with focus on discharge and suspended sediment time series, presented through: (i) multi-temporal scale analysis of series variability; (ii) multi-scale trend analysis; (iii) prediction and forecasting of series with wavelet based hybrid black-box models, and (iv) wavelet-aided simulation of synthetic series.