Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Physically-Based Streamflow Predictions in Ungauged Basin with Semi-Arid Climate
Rainfall-runoff models that utilize reanalysis datasets as driving variables have been widely applied for generating hydrological responses in data-sparse regions. Apparently, there are various requirements that affect the choice of a particular method of hydrologic investigation. In the present study, Soil and Water Assessment Tool (SWAT) and precipitation-runoff (MIKE 11-NAM) models were selected to simulate streamflows from a small watershed with semi-arid climate, using Climate Forecast System Reanalysis (CFSR) as driving inputs. As such, models that provide reliable streamflow predictions from regions with similar climate settings, whose errors and uncertainties are within acceptable ranges, can be identified. The main characteristics of performance criteria indicate that the SWAT model relatively outperform the MIKE 11-NAM model. However, while most of the statistical evaluations prove the acceptable performance of the SWAT model, broad range of prediction uncertainties during calibration and validation were also reflected. Among the possible sources of errors, errors due to forcing data are most likely to be accounted for the unsatisfactory portions of both models. Therefore, to minimize model uncertainty and thereupon improve its performance, in-situ data collection need to be incontestably boosted up. The study also highlights the need for further investigation on the possible mechanisms of proper application of CFSR that avoid erroneous streamflow predictions from similar regions.
Physically-Based Streamflow Predictions in Ungauged Basin with Semi-Arid Climate
Rainfall-runoff models that utilize reanalysis datasets as driving variables have been widely applied for generating hydrological responses in data-sparse regions. Apparently, there are various requirements that affect the choice of a particular method of hydrologic investigation. In the present study, Soil and Water Assessment Tool (SWAT) and precipitation-runoff (MIKE 11-NAM) models were selected to simulate streamflows from a small watershed with semi-arid climate, using Climate Forecast System Reanalysis (CFSR) as driving inputs. As such, models that provide reliable streamflow predictions from regions with similar climate settings, whose errors and uncertainties are within acceptable ranges, can be identified. The main characteristics of performance criteria indicate that the SWAT model relatively outperform the MIKE 11-NAM model. However, while most of the statistical evaluations prove the acceptable performance of the SWAT model, broad range of prediction uncertainties during calibration and validation were also reflected. Among the possible sources of errors, errors due to forcing data are most likely to be accounted for the unsatisfactory portions of both models. Therefore, to minimize model uncertainty and thereupon improve its performance, in-situ data collection need to be incontestably boosted up. The study also highlights the need for further investigation on the possible mechanisms of proper application of CFSR that avoid erroneous streamflow predictions from similar regions.
Physically-Based Streamflow Predictions in Ungauged Basin with Semi-Arid Climate
Lecture Notes in Civil Engineering
Akimov, Pavel (Herausgeber:in) / Vatin, Nikolai (Herausgeber:in) / Kozlov, Dmitry (Autor:in) / Ghebrehiwot, Anghesom (Autor:in)
09.11.2021
17 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
| DOAJ | 2021
Daily flow modeling in arid ungauged basin
| British Library Online Contents | 2009
Modeling Streamflow Dominated by Snowmelt in an Ungauged Basin in Northwestern China
| British Library Conference Proceedings | 2014
Hydrological modelling for ungauged basins of arid and semi-arid regions: review
| DOAJ | 2019
Streamflow Prediction in Ungauged Basins: Review of Regionalization Methods
| British Library Online Contents | 2013