POLLUTEv10 Example 20 Sensitivity Analysis Model Overview

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Introduction

POLLUTEv10 Example 20 introduces Sensitivity Analysis as a powerful tool to evaluate how uncertainty in system performance impacts contaminant transport. In this case, the focus is on the service life of a Primary Leachate Collection System (PLCS) and how variations in its failure timing influence contaminant migration.

Building on the framework established in Examples 15 and 16, this model incorporates both:

Variable Properties
Passive Sink

to simulate changing hydraulic conditions as the leachate collection system degrades over time.

⚠️ Important Note: This is a hypothetical example intended for instructional purposes only. It should not be used directly for real-world landfill design or risk assessment without expert guidance.

Conceptual Model Overview

The modeled system consists of:

A landfill source with constant contaminant concentration
A Primary Leachate Collection System (PLCS) subject to failure over time
Multiple subsurface layers
An underlying aquifer system

The key variable is the time at which the PLCS begins to fail, which directly affects flow and contaminant migration.

Objective of the Sensitivity Analysis

The purpose of this example is to evaluate how uncertainty in PLCS failure timing impacts:

Contaminant breakthrough timing
Concentration levels in the aquifer
Long-term system performance

Failure Time Range

Minimum failure start time: 15 years
Maximum failure start time: 50 years

By varying this parameter, the model generates a range of possible outcomes, helping quantify risk and uncertainty.

Key Input Parameters

The model uses the same parameters as Example 15, with the addition of sensitivity analysis variables.

Transport and Material Properties

Property	Symbol	Value	Units
Diffusion Coefficient	D	0.02	m²/a
Dispersivity	α	0.4	m
Distribution Coefficient	K	0	cm³/g
Soil Porosity	n	0.3	–
Granular Layer Porosity	n	0.3	–
Dry Density	ρd	1.5	g/cm³

Geometric Parameters

Layer	Thickness
Layer 1	1 m
Layer 2	0.3 m
Layer 3	2 m
Aquifer Thickness	1 m

Source and System Properties

Parameter	Symbol	Value
Source Concentration	c₀	1000 mg/L
Reference Height of Leachate	Hr	7.5 cm³/g
Landfill Length	L	200 m
Landfill Width	W	1 m

Flow Parameters (Variable)

Parameter	Symbol	Description
Darcy Velocity	va	Varies with PLCS performance
Sink Outflow Velocity	vs	Varies with system degradation
Leachate Collection Rate	Qc	Variable

Aquifer Properties

Parameter	Symbol	Value
Aquifer Porosity	nb	0.3
Aquifer Velocity	vb	4 m/a

Modeling Approach in POLLUTEv10

Step 1: Base Model Setup

Use the configuration from Example 15
Ensure Variable Properties and Passive Sink features are enabled

Step 2: Define Sensitivity Parameter

Set failure start time as the variable parameter
Define range: 15 to 50 years

Step 3: Link Failure to System Behavior

Adjust:
- Darcy velocity (va)
- Sink outflow velocity (vs)
- Leachate collection rate (Qc)

These parameters evolve as the PLCS degrades.

Step 4: Run Multiple Simulations

POLLUTE automatically evaluates scenarios across the defined range
Results represent a spectrum of possible outcomes

Graphical Output: Probability vs Concentration

PDF Report

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Why Sensitivity Analysis Matters

Sensitivity analysis is critical in environmental modeling because:

Real-world systems involve uncertainty
Material degradation is time-dependent
Field conditions are rarely uniform

This approach helps:

Identify critical parameters
Quantify risk ranges
Support decision-making and design optimization

Key Takeaways

The service life of leachate systems is a critical control on contaminant migration
POLLUTEv10 enables robust uncertainty analysis through sensitivity tools
Combining Variable Properties and Passive Sink features allows realistic system degradation modeling
Sensitivity analysis provides insight into best-case and worst-case scenarios

Final Thoughts

Example 20 highlights the importance of moving beyond single deterministic simulations toward probabilistic and sensitivity-based approaches. By evaluating a range of failure scenarios, engineers can better understand the risk envelope associated with landfill performance.

However, applying these tools in practice requires: