This is an advanced course designed for scientists, engineers and water managers involved in water resources management of poorly gauged basins.
Dates, Fee, ECTS
Start: 30 October 2017
End: 10 November 2017
Deadline IHE application: 30 September 2017 - 23.59 (CET)
Course fee: € 1900
Start: 31 October 2016
End: 11 November 2016
Deadline IHE application: 30 September 2016 - 23.59 (CET)
Course fee: € 1900
Working knowledge of Hydrology, and Statistics. A basic knowledge of GIS and Remote Sensing is welcome.
- New methods and tools of hydrological data collection: OS GIS and Remote Sensing. During this section you will learn how to use QGIS and GRASS software, to download and analyse two different freely available DEM, derive watershed, sub-basins, drainage network and basic morphometric properties of a basin at a specific outlet. You will also learn how to apply a Remote Sensing based Evapotranspiration model, using ILWIS.
- Introduction to the R package. During this session you will get familiar with the OS statistical package R, based on real-case hydrological examples.
- Hydrological variables: annual flows, flow duration curves, hydrological extremes, rainfall-runoff. During this session you will review and get into the depth of deriving the hydrological variables mentioned above, using R and some real case-studies of drainage basins in Italy.
- Geostatistics. During this session you will review in depth the concepts of Uni- and Bivariate variables, Linear Regression models, Stochastic processes, basics of Geostatistics, Variogram, Ordinary Kriging, Topological Kriging and apply them using R to some real case-studies of medium size basins in Italy
- Index Value Methods (Example of regional analysis). During this session you will review in depth the concepts of Frequency analysis of hydrological extremes with focus on floods, Estimation of the design-flood with possible approaches, At-site flood-frequency analysis, Regional flood frequency analysis, Setting-up a regional model, L-moments: definition, estimation and use; and apply them using R to some real case-studies.
- Use of state of the art literature coupled with field experience from International professionals and academics.
- Frontal lectures in class; individual exercises; group exercises; case study analysis.
- This course will make use of open source -freely available- software only.