A Monthly Water Balance Model for Assessing Streamflow Uncertainty in Hydrologic Studies
The accurate assessment of streamflow is crucial for operational water resource management projects. The aim of this study was to estimate the uncertainties in the surface runoff simulated by a monthly water balance model in a mountainous watershed of the Portaikos river, a tributary of the Pinios r...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Environmental Sciences Proceedings |
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| Online Access: | https://www.mdpi.com/2673-4931/25/1/39 |
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| author | Lampros Vasiliades Ioannis Mastraftsis |
| author_facet | Lampros Vasiliades Ioannis Mastraftsis |
| author_sort | Lampros Vasiliades |
| collection | DOAJ |
| description | The accurate assessment of streamflow is crucial for operational water resource management projects. The aim of this study was to estimate the uncertainties in the surface runoff simulated by a monthly water balance model in a mountainous watershed of the Portaikos river, a tributary of the Pinios river, Thessaly, Greece. The University of Thessaly (UTHBAL) monthly water balance model was developed in the R statistical computing environment language, named ‘R-UTHBAL’, to estimate surface water balance in data-scarce watersheds. Two sources of uncertainties in hydrological modelling were considered: the uncertainties in input data estimation and in model parameters. The uncertainties were estimated with the use of the R-package ‘<i>hydroPSO</i>’, a global Particle Swarm Optimisation (PSO) algorithm for the calibration of environmental models. The R-UTHBAL was integrated with the <i>hydroPSO</i> algorithm and advanced sensitivity analyses, and user-friendly evaluation plots were estimated to facilitate the interpretation and assessment of the calibration results. Application of R-UTHBAL with the <i>hydroPSO</i> showed that the uncertainty in streamflow estimation should always be accounted for and evaluated in operational water resources management projects. |
| first_indexed | 2024-03-11T02:29:50Z |
| format | Article |
| id | doaj.art-8cc327fa23824f5bbdaf1a3a7ed77f58 |
| institution | Directory Open Access Journal |
| issn | 2673-4931 |
| language | English |
| last_indexed | 2024-03-11T02:29:50Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Environmental Sciences Proceedings |
| spelling | doaj.art-8cc327fa23824f5bbdaf1a3a7ed77f582023-11-18T10:19:29ZengMDPI AGEnvironmental Sciences Proceedings2673-49312023-03-012513910.3390/ECWS-7-14192A Monthly Water Balance Model for Assessing Streamflow Uncertainty in Hydrologic StudiesLampros Vasiliades0Ioannis Mastraftsis1Department of Civil Engineering, School of Engineering, University of Thessaly, Pedion Areos, 38334 Volos, GreeceDepartment of Civil Engineering, School of Engineering, University of Thessaly, Pedion Areos, 38334 Volos, GreeceThe accurate assessment of streamflow is crucial for operational water resource management projects. The aim of this study was to estimate the uncertainties in the surface runoff simulated by a monthly water balance model in a mountainous watershed of the Portaikos river, a tributary of the Pinios river, Thessaly, Greece. The University of Thessaly (UTHBAL) monthly water balance model was developed in the R statistical computing environment language, named ‘R-UTHBAL’, to estimate surface water balance in data-scarce watersheds. Two sources of uncertainties in hydrological modelling were considered: the uncertainties in input data estimation and in model parameters. The uncertainties were estimated with the use of the R-package ‘<i>hydroPSO</i>’, a global Particle Swarm Optimisation (PSO) algorithm for the calibration of environmental models. The R-UTHBAL was integrated with the <i>hydroPSO</i> algorithm and advanced sensitivity analyses, and user-friendly evaluation plots were estimated to facilitate the interpretation and assessment of the calibration results. Application of R-UTHBAL with the <i>hydroPSO</i> showed that the uncertainty in streamflow estimation should always be accounted for and evaluated in operational water resources management projects.https://www.mdpi.com/2673-4931/25/1/39water balance modelUTHBAL<i>hydroPSO</i>optimisationsensitivity analysisuncertainty analysis |
| spellingShingle | Lampros Vasiliades Ioannis Mastraftsis A Monthly Water Balance Model for Assessing Streamflow Uncertainty in Hydrologic Studies Environmental Sciences Proceedings water balance model UTHBAL <i>hydroPSO</i> optimisation sensitivity analysis uncertainty analysis |
| title | A Monthly Water Balance Model for Assessing Streamflow Uncertainty in Hydrologic Studies |
| title_full | A Monthly Water Balance Model for Assessing Streamflow Uncertainty in Hydrologic Studies |
| title_fullStr | A Monthly Water Balance Model for Assessing Streamflow Uncertainty in Hydrologic Studies |
| title_full_unstemmed | A Monthly Water Balance Model for Assessing Streamflow Uncertainty in Hydrologic Studies |
| title_short | A Monthly Water Balance Model for Assessing Streamflow Uncertainty in Hydrologic Studies |
| title_sort | monthly water balance model for assessing streamflow uncertainty in hydrologic studies |
| topic | water balance model UTHBAL <i>hydroPSO</i> optimisation sensitivity analysis uncertainty analysis |
| url | https://www.mdpi.com/2673-4931/25/1/39 |
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