Development of a daily scale hydrological forecasting system for the Júcar river basin
[EN] The present work aims to develop a prediction system for the future hydrological conditions of the river Júcar. The HBV model and 7 month-lead daily weather forecasts (precipitation and temperature) provided by the ECMWF (European Center for Medium-Range Weather Forecasts) are the pillars of th...
| Author: | |
|---|---|
| Format: | master thesis |
| Publication Date: | 2019 |
| Country: | España |
| Institution: | Universitat Politècnica de València (UPV) |
| Repository: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Language: | English |
| OAI Identifier: | oai:riunet.upv.es:10251/122498 |
| Online Access: | https://riunet.upv.es/handle/10251/122498 |
| Access Level: | Open access |
| Keyword: | Meteorology Quantile mapping HBV model Forecasting Xúquer Previsions Júcar Meteorología Modelo HBV Predicción INGENIERIA HIDRAULICA Máster Universitario en Ingeniería de Caminos, Canales y Puertos-Màster Universitari en Enginyeria de Camins, Canals i Ports |
| Summary: | [EN] The present work aims to develop a prediction system for the future hydrological conditions of the river Júcar. The HBV model and 7 month-lead daily weather forecasts (precipitation and temperature) provided by the ECMWF (European Center for Medium-Range Weather Forecasts) are the pillars of this research. The sub-basins considered are those competent to the reservoirs of Alarcón, Contreras and Bellús. The model is calibrated with historical data. The evaporation time series, input necessary to the model, was calculated with the Thornthwaite equation. The ECMWF forecasts are manipulated through a statistical method of post-processing, the quantile mapping. The post-processing operation is carried out with the help of the software MATLAB: the amount of data to deal with is considerable and several hundreds of lines of code have been written for that scope. The calibrated model is then run with the bias-corrected forecasts and tested over a limited period of time, to assess its predictive ability. The results observed show a very promising picture: the system reliably simulated, month in advance, the general trend of the runoff time series, especially for dry periods. |
|---|