04 GMP TG Unified Protocol

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From existing guidelines to a unified protocol

IWA Task Group on “Good Modelling Practice”Workshop, 13 September 2006, Beijing, PR China

Good Modelling Practice in AS modelling

From existing guidelines to a unif ied protocol

Sylvie Gillot

IWA Task Group on Good Modelling Practice

http://www.modeleau.org/GMP_TG/



Introduction

Quality assurance is essential to increase the use of AS

models in practice

AS modelling: 4 main protocols (BIOMATH, HSG, STOWA, WERF)

Japanese Sewage Works protocol

others more or less visible (case studies)

General guidelines (water management) HarmoniQuA project (MoST)





Introduction

Objectives:

Combining existing protocols developed in the

WWT field (AS modelling)

Taking into account key elements of general

Quality Assurance Guidelines

A unified protocol



Introduction - Table of content

Introduction to GMP

Unified Protocol

Objectives, application, pitfalls, model limitations

How to run a model

Wastewater characterisation

Data collection, evaluation and reconciliation

Plant model set-up

Calibration (sub-models)

Model prediction quality

Use of models

Documentation and reportingIndustrial wastewater

Appendix (Methods, parameter sets, etc.)

Unified Protocol





Outline

Brief comparison of existing protocols

Towards a unified protocol

Overview of the proposed protocol

Implications for The GMP Guidelines



Similarities in AS modelling guidelines

mainly practical protocols

definition of the project objectives calibration/validation step

data quality checking important

Existing protocols (1/4)

BIOMATH HSG STOWA WERF





Main differences

structured overview vs reference manual practical protocols

- design of measuring campaigns

- experimental methods

- calibration procedures


BIOMATH HSG STOWA WERF



Main differences may be explained by the rationale for

the development of the guidelines

- BIOMATH: modelling methodologies

- HSG: practical framework

- STOWA, WERF: practical procedures,

experimental methods







Requirements to a practical use and acceptance

(Refsgaard et al., 2005, HarmoniQuA project):

Scientific maturity

Market maturity

Specific aspects on the interaction modeller and client



In addition to practical protocols, guidance of the

interaction between modeller and client:

Define the objectives

Define the performance criteria

(model accuracy vs objectives)

Review the different steps

Towards a unified protocol (1/3)





Key elements: a structured overview, including feedback loops

data requirements (objectives)

practical methodologies:

- characterisation of: influent WW, biomass,

settling, hydraulics and biological

processes

- data quality checking methods




Key elements:

calibration/validation procedures - parameterselection, in relation to the objectives

(calibration level)

model accuracy

examples, including pitfalls






Proposed protocol – 5 stepsProject definition

Data collection andmodel structure

Model set up and

evaluation

Calibration and

validation

Simulation and result

interpretation

Agreement on the objectives and

budget?

Requirements (data, model accuracy, …)

Problem statement

Objectives

Model structure definition (process, boundaries)

Data collection(process description, historical data,

additional data)

Data and process evaluation

Calibration / validation OK ?

Selection of the parameters and stop criteria

Model implementation

(input file construction; model selection)

Calibration

Simulation and result analysis

Model evaluation

Report

Project evaluation OK ?

Model OK ?

Data and model structure OK ?

Validation

Data sufficient and validated?

Calibration OK ?

Validation OK ?

PROJECT

DEFINITION

D ATA

COLLECTION

AND MODEL

STRUCTURE

MODEL SET UP

AND

EVALUATION

C ALIBRATION

AND VALIDATION

SIMULATION ANDRESULT

INTERPRETATION

yes

no

yes

yes

yes

yesyes

yes

yes

no

no

no

no

no

no

no

no

(HarmoniQuA structure)





Agreement on theobjectives and budget?

Requirements (data, model accuracy)

Problem statement

Objectives

yes

no

Define data requirements and model accuracy, in relation to the objectives

Define scope and set milestones

Step 1



Step 2

Model structure definition

(process, boundaries)

Data collection(process description, historical data,

additional data)

Data and process evaluation

Data and model struct ureOK ?

Data suff icient and

validated?

yes

yes

no

no

Calibration

Model set up

Validation

Specific measuring campaigns Data quality checking procedures





Step 3

Model implementation

(input file construct ion; model selection)

Model evaluation

Model OK ?

yes

no

Datacollection

o Procedures/guidance for model selection

(model structure, settling model, biological model)



Step 4

Calibration / validation

Selection of the parameters and stop criteria

Calibration

Validation

Calibration OK ?

Validation OK ?

yes

yes

no

no

no

no

Datacollection

o Calibration/validation procedures

(Define performance criteria, Sensitivity analysis (if required))





Step 5

Simulation and result analysis

Report

Project evaluation OK ?

yes

no



Conclusion

Proposed unified protocol, 5 main steps

Definition of the project

Data collection and model structure

Model set up and evaluation

Calibration and validation

Simulation and result interpretation





Conclusion

IWA Guidelines on Good Modelling Practice

Guidance of the interaction modeller and client(Objectives, Performance criteria, Reviews)

Practical guidance

(Data requirements, Practical methodologies,Calibration/validation procedures, model accuracy)

A way to present the different levels (of datarequirements, calibration, …) as a function of the definedobjectives



An application matrix ?

Objective 1

Objective 3

Objective 2

Objectives Requirements

Model

accuracy

DataCalibration p rocedure

±x % on SProd

±y % on Snh

…

COD

TSS

Effluent

Side stream

Influent

Aeration

tank

TKN

Decision

Interpretation





Sylvie Gillot

[email protected]

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