<abstract xmlns="http://www.w3.org/1999/xhtml">
<p>The aim of the study is to analyse changes and predict the course of mean monthly water temperatures of the Danube River at various locations for the future. The first part of the study involves conducting a statistical analysis of the annual and monthly average air temperatures, water temperatures, and discharges along the Danube River. The study examines long-term trends, changes in the trends, and multiannual variability in the time series. The second part of the study focuses on simulating the average monthly water temperatures using Seasonal Autoregressive Integrated Moving Average (SARIMA) models and nonlinear regression models (NonL), based on two RCP based incremental mean monthly air temperature scenarios. To assess the impact of future climate on stream temperatures, the historical long-term average of the monthly water temperature (1990–2020) was compared with scenarios S1 (2041–2070) and S2 (2071–2100). The simulation results from the two stochastic models, the SARIMA and NonL, showed that in scenario S1, the Danube River’s average monthly water temperature is projected to increase by 0.81/0.82°C (Passau), 0.55/0.71°C (Bratislava), and 0.68/0.56°C (Reni). In scenario S2, the models predict higher increases: 2.83/2.50°C (Passau), 2.06/2.46°C (Bratislava), and 2.52/1.90°C (Reni). Overall, the SARIMA model proved to be more stable and effective in simulating the increase in monthly water temperatures in the Danube River.</p>
</abstract>

The aim of the study is to analyse changes and predict the course of mean monthly water temperatures of the Danube River at various locations for the future. The first part of the study involves conducting a statistical analysis of the annual and monthly average air temperatures, water temperatures, and discharges along the Danube River. The study examines long-term trends, changes in the trends, and multiannual variability in the time series. The second part of the study focuses on simulating the average monthly water temperatures using Seasonal Autoregressive Integrated Moving Average (SARIMA) models and nonlinear regression models (NonL), based on two RCP based incremental mean monthly air temperature scenarios. To assess the impact of future climate on stream temperatures, the historical long-term average of the monthly water temperature (1990–2020) was compared with scenarios S1 (2041–2070) and S2 (2071–2100). The simulation results from the two stochastic models, the SARIMA and NonL, showed that in scenario S1, the Danube River’s average monthly water temperature is projected to increase by 0.81/0.82°C (Passau), 0.55/0.71°C (Bratislava), and 0.68/0.56°C (Reni). In scenario S2, the models predict higher increases: 2.83/2.50°C (Passau), 2.06/2.46°C (Bratislava), and 2.52/1.90°C (Reni). Overall, the SARIMA model proved to be more stable and effective in simulating the increase in monthly water temperatures in the Danube River.

Monthly stream temperatures along the Danube River: Statistical analysis and predictive modelling with incremental climate change scenarios

Department of Applied Mathematics and Statistics

Faculty of Civil Engineering, Department of Land and Water Resources Management

Faculty of Civil Engineering, Architecture and Geodesy

Journal of Hydrology and Hydromechanics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The aim of the study is to analyse changes and predict the course of mean monthly water temperatures of the Danube River at various locations for the future....

Monthly stream temperatures along the Danube River: Statistical analysis and predictive modelling with incremental climate change scenarios

Online veröffentlicht: 14. Nov. 2023

Seitenbereich: 382 - 398

Eingereicht: 24. März 2023

Akzeptiert: 03. Sept. 2023

DOI: https://doi.org/10.2478/johh-2023-0028

Schlüsselwörter
SARIMA models, Nonlinear regression models, Water temperature changes, Climate change, Incremental scenarios.

© 2023 Pavla Pekárová et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Monthly stream temperatures along the Danube River: Statistical analysis and predictive modelling with incremental climate change scenarios

Online veröffentlicht: 14. Nov. 2023

Seitenbereich: 382 - 398

Eingereicht: 24. März 2023

Akzeptiert: 03. Sept. 2023

DOI: https://doi.org/10.2478/johh-2023-0028

SchlüsselwörterSARIMA models, Nonlinear regression models, Water temperature changes, Climate change, Incremental scenarios.

© 2023 Pavla Pekárová et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
SARIMA models, Nonlinear regression models, Water temperature changes, Climate change, Incremental scenarios.