ECMM124 - Hydroinformatics Tools (2018)

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MODULE TITLEHydroinformatics Tools CREDIT VALUE15
MODULE CODEECMM124 MODULE CONVENERProf Guangtao Fu (Coordinator)
DURATION: WEEKS 12 weeks 0 34
Number of Students Taking Module (anticipated) 0
DESCRIPTION - summary of the module content

Hydroinformatics (or water informatics) can be seen as a synergetic use of modelling tools and Information and Communication Technologies (ICT) within a single methodological approach dealing with physical, social and economic aspects of sustainable water management. This interdisciplinary field, which transcends traditional boundaries of water/environmental science and engineering, informatics/computer science (including Artificial Intelligence, data mining and optimisation techniques) and environmental engineering, has applications in various areas of water management, including:

  • development and application of decision-support systems, simulation and optimization models to improve understanding and provide solutions to water engineering problems;
  • computational tools and techniques and their effective application to managing risk and uncertainties associated with water systems;
  • cross-disciplinary complex system approaches to water resource management;
  • understanding of water systems, including technical, socio-economic and environmental issues.

On this module, you will improve your understanding of water systems (supply, drainage, flood management, structural/non-structural measures, risk management, their impact on social structures/interactions, etc), ICT and operations research techniques (simulation, optimisation, data mining/ machine learning, Geographic Information Systems, Bayesian Belief Networks, etc.) with a view of integrating them into a systems analytic context to analyse and solve problems in water resource design, planning and management practice.

By the end of this module, you should have a strong grasp of a number of Hydroinformatics tools and be able to develop or use the developed tools to model and optimise various water resource systems, as well as present your findings making sure the content is accurate, teaches the audience something, but in a way that is new, updated and technologically advanced. 

AIMS - intentions of the module

This module aims to give you a basic understanding of tools in the emerging field of hydroinformatics for the practising engineer. It also offers practical experience in using these tools within the water management context.

In addition, this module covers the topics of water systems modelling and optimisation, using a problem-based learning approach in the case studies, and examining them through the exercises and assignments. You will hone your independent learning skills through investigating these topics through a combination of background reading, private study and computational analysis.

INTENDED LEARNING OUTCOMES (ILOs) (see assessment section below for how ILOs will be assessed)

This is a constituent module of one or more degree programmes which are accredited by a professional engineering institution under licence from the Engineering Council. The learning outcomes for this module have been mapped to the output standards required for an accredited programme, as listed in the current version of the Engineering Council’s ‘Accreditation of Higher Education Programmes’ document (AHEP-V3).

This module contributes to learning outcomes: SM1m, SM1fl, SM4m, SM2fl, SM6m, SM3fl, EA3m, EA1fl, EA5m, EA2fl, EA6m, EA3fl, D3m, D1fl, D7m, D2fl, D8m, D3fl, ET2m, ET2fl, ET4m, ET4fl, G1m-G4m and G1-G4fl

A full list of the referenced outcomes is provided online:

The AHEP document can be viewed in full on the Engineering Council’s website, at

On successful completion of this module, you should be able to:

 Module Specific Skills and Knowledge: SM1m, SM1fl, SM6m, SM3fl, EA3m, EA1fl, EA5m, EA2fl

1 understand the systems analysis approach to solving complex problems in water systems engineering;

2 comprehend a number of hydroinformatics methods and tools;

3 critically appraise the use of hydroinformatics methods and tools for a variety of water management problems.

Discipline Specific Skills and Knowledge: SM4m, SM2fl, SM6m, SM3fl, EA6m, EA3fl, D3m, D1fl, D7m, D2fl, D8m, D3fl, ET2m, ET2fl, ET4m, ET4fl

4 be aware of physical, social and economic aspects of sustainable water management;

5 identify suitable methods and tools for water problem solving;

6 critically assess research results;

7 evidence some practical experience of using hydroinformatics methods and tools.

Personal and Key Transferable/ Employment Skills and Knowledge: G1m-G4m, G1fl-G4fl

8 show enhanced independent learning;

9 demonstrate strong report and presentation skills;

10 reveal improved skills in using computer software.

SYLLABUS PLAN - summary of the structure and academic content of the module
  • systems approach to water management, simulation and optimisation methodologies, multicriteria decision making;
  • classical and intelligent optimisation strategies – linear programming, modern metaheuristic methods, including evolutionary computing;
  • data mining methods, predictive data mining, knowledge discovery, rule-based methods, artificial neural networks, fuzzy sets and systems, Bayesian belief networks;
  • decision support systems (DSS), software tools, water management DSS;
  • complexity - cellular automata and grid-based methods;
  • modelling and models, typology, scale, forward and inverse modelling, calibration, validation and verification;
  • application examples in water management: complex water network design, rehabilitation and management, reservoir operation and planning, alternative project appraisal and selection.
Scheduled Learning & Teaching Activities 40.00 Guided Independent Study 110.00 Placement / Study Abroad
Category Hours of study time Description
Scheduled learning activities 40 Lectures and tutorials
Guided independent study 110 Assessment preparation; private study


FORMATIVE ASSESSMENT - for feedback and development purposes; does not count towards module grade
Form of Assessment Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Questions posed and answered in the class Various durations All Verbal (in class)


Coursework 30 Written Exams 70 Practical Exams
Form of Assessment % of Credit Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Written exam 70 2 hours - January Exam All Written (on request)
Assignment on practical application of hydroinformatics tools 30 1,000-1,500 words, including graphs and tables All Written


DETAILS OF RE-ASSESSMENT (where required by referral or deferral)
Original Form of Assessment Form of Re-assessment ILOs Re-assessed Time Scale for Re-reassessment
All above Written exam (100%) All August Ref/Def period



If a module is normally assessed entirely by coursework, all referred/deferred assessments will normally be by assignment.

If a module is normally assessed by examination or examination plus coursework, referred and deferred assessment will normally be by examination. For referrals, only the examination will count, a mark of 50% being awarded if the examination is passed. For deferrals, candidates will be awarded the higher of the deferred examination mark or the deferred examination mark combined with the original coursework mark.

INDICATIVE LEARNING RESOURCES - The following list is offered as an indication of the type & level of
information that you are expected to consult. Further guidance will be provided by the Module Convener


Web based and Electronic Resources:

Loucks, D P van Beek, E; Stedinger, J R; Dijkman, J P M; Villars, M . Water Resources Systems Planning and Management: An Introduction to Methods, Models and Applications.
Online (available through ELE) - UNESCO 2005 - 9231039989

Other Resources:

Reading list for this module:

Type Author Title Edition Publisher Year ISBN Search
Set Pyle D Data Preparation for Data Mining Morgan Kaufmann 1999 978-1558605299 [Library]
Set Ross T J Fuzzy Logic with Engineering Applications 2nd John Wiley 2004 978-0470860755 [Library]
ORIGIN DATE Thursday 06 July 2017 LAST REVISION DATE Wednesday 27 February 2019
KEY WORDS SEARCH Hydroinformatics; optimisation; modelling; machine learning; neural networks; genetic algorithms; cellular automata.