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Team 01 Presentation 2

Presentation 2: Results of 1st Week

Members: Alejandra, Arnau, Emilie, Floria, Guilhem, Humbeline, Maryam, Matthew

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Overview of work done

1. Hydrometeorological data analysis (rainfall data, land use)

2. HEC-HMS Modelling

    • Calibration and Sensitivity Analysis of HEC-HMS
    • Uncertainties

3. 2D Modelling

    • IBER Model Analysis and TELEMAC Model Analysis
    • Comparative Analysis: IBER vs TELEMAC

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Catchment La Tordera - Team 1 Presentation

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Rainfall Data analysis

  • Data treatment process: elaboration of monthly averages in order to reduce it.
  • Total daily average precipitation of 1.19 mm.
  • Distribution between wet and dry seasons:
    • Wet season: Spring (1.22 mm) and Autumn (1.55 mm).
    • Dry season: Summer (1.13 mm) and Winter (0.86 mm)
  • High precipitation irregularities along the years (maximum deviation of 59.49% from average precipitation).

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1. Hydrometeorological data analysis

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Rainfall Data analysis

  • Daily rainfall: an independent, highly random natural phenomenon, influenced only by the adjacent three days. (tag=3)
  • No significant long-term seasonal trends (between 95% confidence interval).

1. Hydrometeorological data analysis

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Land Use data analysis -

Calculation of CN Number for calibration

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  • Reclassification of the CN raster
  • Reading the classification table
  • Assigning CN values
  • Calculating average CN per sub-watershed

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1. Hydrometeorological data analysis

ONLY INFORMATIVE CN VALUES

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2. HEC-HMS Sensitivity analysis

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Curve Numbers (CN):

    • Baseline CN = 54 (lowest in the study basin).
    • QGIS-derived CN values tested, but peak discharge remained higher than observed.
    • Lower CN values (40 & 30) reduced peak discharge, improving accuracy.
    • Impactful factors : River length, Area size, Urbanization.
    • Sub-basin 4 had the highest sensitivity.

→ CN significantly reduced for better alignment.

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Volume comparison

1.521,1 [cms]

1.249,1 [cms]

982,7 [cms]

731,5 [cms]

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2. HEC-HMS Sensitivity analysis

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Lag Time (Tlag):

    • Verified using QGIS measurements (validated HEC-HMS values).
    • Sensitivity tests (+/- 10%, 20%, 30%) showed minimal impact on peak discharge.
    • Geographic factors (vegetation, urbanization) had negligible effects.

→ No modifications made.

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Volume comparison

731,5 [cms]

982,7 [cms]

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2. HEC-HMS Sensitivity analysis

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Routing Method:

    • Muskingum (Initial method).
    • Muskingum-Cunge (Best alignment with observed data).
    • Kinematic Wave (Accurate but no reduction in peak discharge).

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→ Final Decision: Muskingum-Cunge method chosen for optimal accuracy.

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Volume comparison

1.113,3 [cms]

982,7 [cms]

731,5 [cms]

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2. HEC-HMS - The factors and their impact

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Little Impact

Moderated Impact

High Impact

Curve Number

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X

Lag Time

X

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Routing method

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X

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Curve Number

Lag Time

Routing method

Peak Size

Volume influenced

Peak alignment

No volume change

Peak expansion

No volume change

Which factor have the biggest impact?

What do the factors impact?

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2. Sources of Uncertainty

Recording Errors

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  • Temporary blockages and obstructions
  • Human abstraction and insertion
  • Land Use change

Model Related Assumptions

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  • Non-dynamical representation
  • Parameter sensitivity

Data Related Errors

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  • Discharge measurement uncertainty
  • Precipitation gauge
  • Missing data (1952 - 1992)

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What's the plan?

3. 2D Modelling

Based on our results from HEC - HMS, we decided to do the following modelling plan

2D Modelling

Observed Data

Simulated Data

  • Simulated data from HEC-HMS
  • Using Telemac for model run
  • Observed data from Gloria Event
  • Using Iber for model run

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  1. Land use allocation

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  • Selected from orthophoto

observation

  • Simplified approach for

computational capacity

  • Assigns Manning's coefficient

for model

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3. 2D Modelling - IBER

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2. Mesh Sizes

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  • Finer for critical areas (River, Urban)
  • Coarser for non-critical areas (Sea, Rural)
  • Provides elevation to appropriate

resolution

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3. 2D Modelling - IBER

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3. Boundary Conditions

  • Inlet/outlet

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  • Timestep
    • 2 Hours steps
    • Provides enough resolution for a multi-day event
    • Moderately computationally non-intensive

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3. 2D Modelling - IBER

Inlet

Outlet

Discharge values of observed data

Sea

Defining Inlet/outlet boundary lines

Input of Observed Gloria event discharge data

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3. 2D Modelling - IBER

IBER output

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The building layer is integrated with the aim of :

  • Improves mesh accuracy by considering physical obstacles affecting water flow.
  • Enhances urban flood modeling by incorporating impermeable areas, runoff, and infrastructure interactions (roads, drainage networks).
  • Helps assess building vulnerability to flooding.

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3. 2D Modelling - TELEMAC

Mesh creation in BlueKenue

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3. 2D Modelling - TELEMAC

Mesh creation in BlueKenue

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3. 2D Modelling - TELEMAC

Steady Simulation

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  • Mean discharge : 4 m3/s

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  • Steady State reach in 1 hour

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  • No overtopping

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  • Weak water depth

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3. 2D Modelling - TELEMAC

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3. 2D Modelling - TELEMAC

Unsteady Simulation

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  • Simulate discharge / Observe discharge

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  • Add an Hydrogramm in the .cas

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  • Prescribed elevation at the downstream is 0

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Unsteady Simulation

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Comparative Analysis: Observed vs Simulated

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3. 2D Modelling - Observed vs Simulated

However,

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We aim for,

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  • Flood risk maps for both observed and simulated data.
  • Verify which data is better representative of reality.
  • Identify uncertainties.

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  • Outputs are still in process.
  • Model re-runs and refinement.
  • Challenges due to time constraints.�

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For next week, we are going to…

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  1. Telemac :
    1. Unsteady case analyse.
    2. Pollution tracers.

2. Iber : Pollution tracers.

3. Qual2K : Pollution analysis of the catchment.

4. Compare our pollution results.

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4. Progress on next steps

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