THT303 Analysis and design of systems for urban drainage

The course includes methods for analysis, planning and design of urban drainage systems. The course is divided into three sections:

1. Transport systems for wastewater: System understanding, functional requirements and legislation, efficiency, discharge of pollution via overflows and leaks, risk of flooding and inflow/infiltration, measurement data and measurement technology.
2. Runoff modelling: Precipitation-runoff models, terrain analyses, precipitation statistics, extreme value statistics and frequency analysis, climate change, infiltration and other catchment processes, groundwater, analysis of uncertainty and sensitivity, calibration and validation of models.
3. Urban stormwater management: Stormwater in legislation, regulations, application of the three-step strategy, analysis and design of nature-based solutions, calculations of production, dispersion and removal of stormwater contaminants, flow control and detention/retention, floodways, hydraulic surface modeling and erosion, added values ​​and multi-objective optimization.

Relevant analysis tools and methods: SCALGO Live, SWMM, HEC-RAS 2D, Python, R, Excel and machine learning methods (artificial neural networks and evolutionary algorithms).

Compulsory assignments associated with the three modules will give the students a good introduction to the analysis tools.

1. Transport systems for wastewater

The candidate:

• Has an in-depth understanding of transport systems for wastewater
• Can process, analyze and assess the quality of measurements
• Has knowledge of the consequences of leaks, capacity exceedance and inflow/infiltration water in the wastewater system, and can apply methods to identify and reduce risk
• Can model drainage systems and analyze results in relation to functional requirements

2. Runoff modelling

The candidate:

• Has a good understanding of rainfall-runoff modeling and catchment processes
• Can process observations and carry out frequency analyses
• Can calculate runoff using several models and assess results against the necessary input data, assumptions, range of validity and uncertainty
• Can apply machine learning methods for calibrating models

3. Urban stormwater management

The candidate:

• Can identify requirements in legislation, planning and building matters and propose, assess and design solutions that meet requirements and promote sustainability
• Can design both single measures and complex stormwater systems for different steps of the three-step strategy, and can identify and reduce weaknesses in such systems
• Has knowledge of water quality in stormwater and knows methods for assessing sources, dispersion and removal of pollution
• Knows the added value of stormwater management, can carry out a cost-benefit assessment and apply machine learning to solve multi-objective optimization tasks