Research School for Socio-Economic and
Natural Sciences of the Environment
Research School for Socio-Economic and
Natural Sciences of the Environment
Agenda

Advanced Short Course on "Where there is little data: how to estimate design variables in poorly gauged basins"

Date: 28 October 2019 - 08 November 2019
Location: Delft

The estimate of design variables, for hydraulic engineering and water management purposes, is a difficult task that practitioners have to face when designing a hydraulic structure, assessing water allocation, addressing river basin planning, managing water resources. This estimate is affected by several sources of uncertainties, the most crucial being the limited availability and reliability of observed data in time and space. This is particularly true when river basins are poorly gauged. Nowadays, several new sources of data acquisition are made available by the recent applications of Remote Sensing and GIS to hydrological processes; furthermore, the scientific literature has provided engineers and practitioners with new statistical and geostatistical methods and tools to best exploit the scarce measured data at a given station and extend the local information to a larger scale.

The aim of the course on "Where there is little data: how to estimate design variables in poorly gauged basins" is to provide an advanced theoretical understanding and hands-on practical methods to cope with the estimate of hydrological variables in poorly gauged basins.

Learning objectives

At the end of this course the participants will be able:

  • To apply the latest new Open Source GIS and Remote Sensing software and data for deriving hydro-geomorphological and hydro-meteorological information
  • To apply an advanced theoretical understanding of selected hydrological variables: flow duration curves, hydrological extremes, mean annual flow
  • To evaluate, select and apply different advanced statistical and geo-statistical methods for estimating hydrological variables in poorly gauged basins

Target

This is an advanced course designed for scientists, engineers and water managers involved in water resources management of poorly gauged basins.

Pre-requisites

Working knowledge of Hydrology, and Statistics. A basic knowledge of GIS and Remote Sensing is welcome.

Contents

  1. 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 Remote Sensing to Water Resource assessment.
     
  2. Introduction to the R package
    During this session you will get familiar with the OS statistical package R, based on real-case hydrological examples.
     
  3. 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.
     
  4. 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
     
  5. 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.

Methods

  • Using of state of the art literature coupled with field experience from International professionals and academics.
  • Frontal lectures in class; individual exercises; case study analysis.
  • This course will make use of open source -freely available- software only.

Application procedure and more information

> More information on this course

Former occurrences of this course

  • 30 October - 10 November 2017
  • 31 October - 11 November 2016
  • 2-13 November 2015
  • 17-28 November 2014