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Pregled bibliografske jedinice broj: 1029498

Long term variations of river temperature and the influence of air temperature and river discharge: case study of Kupa River watershed in Croatia


Senlin, Zhu; Bonacci, Ognjen; Oskoruš, Dijana; Hadzima-Nyarko, Marijana; Shiqian, Wu
Long term variations of river temperature and the influence of air temperature and river discharge: case study of Kupa River watershed in Croatia // Journal of Hydrology and Hydromechanics, 67 (2019), 4; 305-313 doi:10.2478/johh-2019-0019 (međunarodna recenzija, članak, znanstveni)


Naslov
Long term variations of river temperature and the influence of air temperature and river discharge: case study of Kupa River watershed in Croatia

Autori
Senlin, Zhu ; Bonacci, Ognjen ; Oskoruš, Dijana ; Hadzima-Nyarko, Marijana ; Shiqian, Wu

Izvornik
Journal of Hydrology and Hydromechanics (0042-790X) 67 (2019), 4; 305-313

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Climate change ; Machine learning models ; River water temperature

Sažetak
The bio-chemical and physical characteristics of a river are directly affected by water temperature, which therefore affects the overall health of aquatic ecosystems. In this study, long term variations of river water temperatures (RWT) in Kupa River watershed, Croatia were investigated. It is shown that the RWT in the studied river stations increased about 0.0232–0.0796ºC per year, which are comparable with long term observations reported for rivers in other regions, indicating an apparent warming trend. RWT rises during the past 20 years have not been constant for different periods of the year, and the contrasts between stations regarding RWT increases vary seasonally. Additionally, multilayer perceptron neural network models (MLPNN) and adaptive neuro-fuzzy inference systems (ANFIS) models were implemented to simulate daily RWT, using air temperature (Ta), flow discharge (Q) and the day of year (DOY) as predictors. Results showed that compared to the individual variable alone with Ta as input, combining Ta and Q in the MLPNN and ANFIS models explained temporal variations of daily RWT more accurately. The best accuracy was achieved when the three inputs (Ta, Q and the DOY) were included as predictors. Modeling results indicate that the developed models can well reproduce the seasonal dynamics of RWT in each river, and the models may be used for future projections of RWT by coupling with regional climate models.

Izvorni jezik
Engleski

Znanstvena područja
Geofizika, Građevinarstvo



POVEZANOST RADA


Projekt / tema
083-0831510-1511 - Proučavanje ekstremnih hidroloških situacija i vodnih rizika u kršu (Ognjen Bonacci, )

Ustanove
Državni hidrometeorološki zavod,
Fakultet građevinarstva, arhitekture i geodezije, Split,
Građevinski i arhitektonski fakultet Osijek

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


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