The multiple scales of uncertainty: an engineer's perspective

E. Belia, Ph.D., P.Eng.Primodal Inc.

Quantifying Uncertainty in Integrated Catchment Studies (QUICS)

Final Dissemination Event, Amsterdam International Water Week

Thursday 2nd November 2017

Overview

• Current practice

• Drivers moving us to a new analysis framework

• Example

• The big picture – a complex system

• Things to think about

Engineering approaches

Critical states engineering• Based on worst-case analysis

• Static environment and resource

allocation

• Guaranteed availability of infrastructure

• Redundancy

Best effort engineering• Average case analysis

• Dynamic resource management

• No guaranteed performance

Design guidelines

Models

Statistical analysis of past data

Scenarios

Sensitivity analysis

The new WRRF: a node within a complex system

The usual:

• Role of environmental protection

• Subject to catchment dynamics

The new:

• Obligation to provide a product

• Interdependency with other industries

Adaptive engineering

• Deliver service in interaction with uncertain environments

• Integrating both critical and best effort engineering

• Sufficient resources to cover critical events

• Optimal use of available resources

• No regret measures

Example: achieving reclaimed water qualityJ. Weiss, LACD Senior Engineer, Rtd.E. Belia, Primodal Inc.

East and West WRRF

Flow

236,600 (m3/d)

62.5 (MGD)

COD

295 (mg/L)

142800 (lb/d)

Ammonia

20 (mg/L)

9750 (lb/d)

Regulatory constraints

Water Reclamation Permit• CT of no less than (90x5) 450

milligram-minutes per liter at all times with a modal contact time of at least 90 minutes, based on peak dry weather design flow; or

• inactivate and/or remove 99.999 percent (5-log) of the plaque forming units of F-specific bacteriophage MS2, or polio virus in the wastewater

0

2

4

6

8

10

12

14

Fin

al E

fflu

ent A

mm

onia

(m

g/L

)

DateMonthly average

NPDES permit for one of the plant

discharge locationsParameter Average

monthly

Average

weekly

Maximum

daily

BOD 20 30 45

TSS 15 40 45

Ammonia-N 4 - 6

NO2-N 1 - -

NOx-N 8 - -

Steps to meet reclamation permit

• Implementation of sequential chlorination• secondary effluent must not exceed 1 mg N/L

• EQ tank construction for flow equalization• will not be operational until 2020

• Optimization of the aeration system

0

0.5

1

1.5

2

2.5

3

0

5

10

15

20

25

30

35

40

45

0 4 8 12 16 20 24

Eff

lue

nt

am

mo

nia

(m

g/L

)

Pri

ma

ry e

fflu

en

t a

mm

on

ia (

mg

/L)

Hours

Primary

Effluent

Reduce flow

Adaptive approach

‘What is the risk of a disinfection failure caused by excessive secondary effluent ammonia bleed through?’

Environmental - Social - Economic

Sources of variability and uncertainty

Influent variability

μmax, AOB

Flow distribution

DO control

Blower limitations

Settling

parameter

MLSS distribution

Process model

Histogram Burr

qmax0.120.1150.110.1050.10.0950.090.0850.080.0750.070.065

Parametric uncertainty

Jeffrey Weiss, LACD Senior Engineer, Rtd.

Calculating the probability of non-compliance (PONC)

1. Estimating the CDFs for wastewater

constituents 2. Calculation of PONC

1. Output analysis

2. Calculation of statistical parameters for each effluent constituent

Convergence of the statistical characteristics

of effluent?

Uncertainty propagation using the model under dynamic conditions

Random generation of

model parameter vectors

Synthetic

generation of

influent time series

YES

Talebizadeh, 2015. Probabilistic design of wastewater treatment plants. PhD Thesis

NO

A complex problem

Catchment events

Equipment failures & human errors

Air compressor filter failure

• filter on compressor suction side failed

• got sucked into compressor destroying inlet guide vanes

• causing an imbalance in the unit

Human error destroys a pump

• failure to cut off reclaimed water users during hydraulic shutdown

• water level in the chlorine contact tank got drawn down

• Nalgene sample bottle sucked into pump

A tragedy

The next treatment target

District objectivesSanitation

District Manager

Public health & environmental

protection

Meet NPDES permit

Treat as much flow as

possible

Meet reclaimed

water permit

Reduce plant flow

Social responsibility

Maximize water reuse

Maximise reclaimed

water

Fiscal responsibility

Increase revenue

Maximise reclamed

water

Reduce operational

costs

Operate close to permit

Take into account future

needs

Best use of available

land

Future shifts in treatment needs

New technologies requiring expensive

modifications

Treatment division

Reclaimed water division

Planning division

Treatment division

Treatment division

Reclaimed water division

Level of uncertaintyDeterminism Indeterminacy

Statistical uncertainty

Scenario uncertainty

Recognised

ignorance

Total ignorance

Quantified outcomes

Range of plausible outcomes

We are aware that there is something we do not know

We do not know what we do not know

5 years 10 years 30 years

DOUT uncertainty analysis framework

Systems

analysis

Contract

type

Project stage

Stakeholder

Modeling

phase

DOUTDesign and operations uncertainty task group

Tackling Uncertainty Analysis (UA)

Reduce:→ Sampling

→ Experimental design

Model:→ Influent quality

→ CFD

→ Integrated modeling

→ Model predictive real time control

Scenario analysis

→ Fore sighting methods

→ Life cycle assessment

→ Multi-attribute-utility theory

→ Benefit-cost-risk approach

→ Benchmarking and auditing

Synthesize and communicate results

Uncertainty propagation:

→ Influent variability

→ Parametric uncertainty

→ PONC and PSE estimates

Jakeman, A.J., Letcher, R.A. and Norton J.P. (2006) Ten iterative steps in development and evaluation of environmental models. Environmental Modelling & Software. 21, pp 602-614.

Identify problem:→ Metrics

→ Sources

Prioritize:→ Identify drivers

→ Sensitivity analysis

Steps to accelerated adoption

PDF selection

Incorporate expert knowledge

Correlation

Incorporating human error & equipment failures

Accounting for temporal and spatial variability (3-D space vs. simulation space)

Meaningful composition of heterogeneous components (different sources, large variety of interaction mechanisms, different levels of abstraction)

Generating additional key process indicators such as process stability

Method development

Variability vs. uncertainty

Moving from single parameter values to distributions

Communicating key concepts - PONC

Scenario development

Visualization

Psychology and preferential engineering

Concept communication

Incorporating existing design concepts e.g. “max month”

Linking SF in guidelines to sources of uncertainty

Developing MOP for methods

Case studies

Post project audits

Collaboration: engineer-modeler-statistician

Software tools

Method adoption

Things to think about

Contract delivery

mechanism

Engaging with

regulators

SoftwareHuman

psychology

Evangelina Belia

Primodal Inc.USA&Canadacell: (269) 873-0243

belia@primodal.comhttp://www.primodal.com

Presenter contact information