Optimisation of Water Management Prof. Graeme Dandy School of Civil, Environmental and Mining Engineering University of Adelaide

Acknowledgement of Co-Researchers Prof Holger Maier Postdocs: Matt Gibbs Postgrads: Abby Goodman Dan Partington Honours students: Fiona Paton John Baulis Ben Staniford Lisa Lloyd Rebecca Tennant Jason Nicolson Liam Harnett

Prof Holger Maier

Postdocs:

Matt Gibbs

Postgrads:

Abby Goodman

Dan Partington

Honours students:

Fiona Paton

John Baulis

Ben Staniford

Lisa Lloyd

Rebecca Tennant

Jason Nicolson

Liam Harnett

Outline Background: Optimisation Models Case Studies: Optimum planning of urban water systems (regional scale) Resource optimisation framework for the Upper South East Region of SA Optimum design of greywater reuse systems (cluster scale) Conclusions

Background: Optimisation Models

Case Studies:

Optimum planning of urban water systems (regional scale)

Resource optimisation framework for the Upper South East Region of SA

Optimum design of greywater reuse systems (cluster scale)

Conclusions

Types of Models Descriptive How does the system behave? What will be the consequences of certain actions? Simulation Models Prescriptive What are the best actions to achieve a particular objective or set of objectives? Optimisation models

Descriptive

How does the system behave?

What will be the consequences of certain actions?

Simulation Models

Prescriptive

What are the best actions to achieve a particular objective or set of objectives?

Optimisation models

Methodology Systems approach Optimisation Module Selection of Alternative Simulation of Alternative Evaluation of Alternative Selection of Objectives Results Selection of Objectives Optimisation Module

Systems approach

Form of an Optimisation Model Choose values for a set of decision variables so as to maximise (or minimise) a particular objective Subject to a set of constraints

Choose values for a set of decision variables so as to maximise (or minimise) a particular objective

Subject to a set of constraints

Genetic Algorithm Optimisation

What Are Genetic Algorithms ? Guided search procedures that work by analogy to natural selection Include embedded computer simulation Each solution is represented by a string of numbers Work with a population of solutions Algorithm can run for any length of time Can’t prove that you have reached the optimum solution

Guided search procedures that work by analogy to natural selection

Include embedded computer simulation

Each solution is represented by a string of numbers

Work with a population of solutions

Algorithm can run for any length of time

Can’t prove that you have reached the optimum solution

Typical GA string Distribution Network Pipe Material Distribution Network Pipe Diameters Pump Size Collection Network Pipe Material

Solution Cost ($ million) 30 40 50 60 70 80 90 100 0 50,000 100,000 150,000 200,000 Number of Solution Evaluations The GA conducts a directed search for optimal solutions Repeat Towards Convergence

Multi-Objective Optimisation

Multi-Objective Optimisation Pareto Optimal Front

Optimum Planning of Urban Water Systems (Regional Scale)

TEMPORAL SCENARIOS SUPPLY TYPE ALTERNATIVES

2020 – 72ML/day 2060 – 225ML/day 2100 – 300ML/day 0KL < 30GL/yr Risk Based Performance Assessment

2020 – 72ML/day

2060 – 225ML/day

2100 – 300ML/day

0KL

< 30GL/yr

Risk Based Performance Assessment

Optimisation Objectives: Minimise present value of total system cost Minimise greenhouse gas emissions Constraint: Availability of water from the Murray (30 GL/year)

Objectives:

Minimise present value of total system cost

Minimise greenhouse gas emissions

Constraint:

Availability of water from the Murray (30 GL/year)

Optimisation Decision Variables: Capacity of desalination plant (ML/day) Size of rainwater tanks for all households (kL) Operating rules for the system

Decision Variables:

Capacity of desalination plant (ML/day)

Size of rainwater tanks for all households (kL)

Operating rules for the system

Approximate trade-offs between supply types

Optimal Tradeoffs – Southern System

Breakpoint (250ML/day, 2KL) (251ML/day, 1.8KL) (248ML/day, 2.6KL) Optimal Tradeoffs – Southern System

$45/tonne $1000/tonne Breakpoint (250ML/day, 2KL) (251ML/day, 1.8KL) (248ML/day, 2.6KL) Optimal Tradeoffs – Southern System

Range depends on optimal rainwater tank size, which depends on average yearly water supply per tank: Optimisation Process

Range depends on optimal rainwater tank size,

which depends on average yearly water supply per tank:

Sensitivity Analysis of the Optimisation Process

Planned Extensions to this Research Include more objectives (reliability, social factors) Add more alternatives (e.g. stormwater reuse)

Include more objectives (reliability, social factors)

Add more alternatives (e.g. stormwater reuse)

Conclusions Future expansion of Adelaide’s water supply will use a combination of non-traditional sources including desalination, rainwater tanks and stormwater and wastewater reuse Tradeoffs exist between the costs and environmental impacts of these sources Multi-objective Optimisation can be used to quantify some of these tradeoffs

Future expansion of Adelaide’s water supply will use a combination of non-traditional sources including desalination, rainwater tanks and stormwater and wastewater reuse

Tradeoffs exist between the costs and environmental impacts of these sources

Multi-objective Optimisation can be used to quantify some of these tradeoffs

Resource Optimisation Framework for the Upper South East Region of SA

Dune and flat topology Very flat, slope of 1:6000 Prone to flooding Flats cleared for agriculture, dunes contain wetlands of high conservation value Area of 1 Million Ha 40% affected by dryland salinity Over 640 km of groundwater drains installed 100 regulators throughout the region Case Study – Upper South East 110 km

Dune and flat topology

Very flat, slope of 1:6000

Prone to flooding

Flats cleared for agriculture, dunes contain wetlands of high conservation value

Area of 1 Million Ha

40% affected by dryland salinity

Over 640 km of groundwater drains installed

100 regulators throughout the region

Management Decisions Management decisions involve movement of available water Regulators in the drainage network allow water to be directed around the landscape Decisions are based on a number of considerations: Water quantity Water quality Wetland priorities Conflicting objectives: Manage dryland salinity Maintain wetland biodiversity Mitigate flooding

Management decisions involve movement of available water

Regulators in the drainage network allow water to be directed around the landscape

Decisions are based on a number of considerations:

Water quantity

Water quality

Wetland priorities

Conflicting objectives:

Manage dryland salinity

Maintain wetland biodiversity

Mitigate flooding

Proposed Decision Support System A multidisciplinary approach is proposed to produce a dryland salinity decision support tool: Groundwater modelling Rainfall-runoff modelling Salt-transport modelling Ecological modelling Models combined to produce an integrated modeling framework to assist management decisions

A multidisciplinary approach is proposed to produce a dryland salinity decision support tool:

Groundwater modelling

Rainfall-runoff modelling

Salt-transport modelling

Ecological modelling

Models combined to produce an integrated modeling framework to assist management decisions

Integrated Modelling Framework groundwater response Regulator Decision Point shut open flow flow runoff, salinity rainfall evap. runoff, salinity runoff, salinity runoff, salinity rainfall evap. rainfall evap. rainfall evap. wetland response environmental conditions

Water Quantity Modelling Hydrologic model required Good GIS information available: Drain, wetland and regulator locations Catchment wide LiDAR elevation data are currently being processed Very sparse flow data records Historically not much data recorded Drains installed since the late 1990s Very little to measure in the last few years

Hydrologic model required

Good GIS information available:

Drain, wetland and regulator locations

Catchment wide LiDAR elevation data are currently being processed

Very sparse flow data records

Historically not much data recorded

Drains installed since the late 1990s

Very little to measure in the last few years

Hydrologic Modelling HEC-HMS adopted for modelling Different models can be selected for each component of rainfall-runoff model Loss (Infiltration) Transformation (Rainfall-Runoff) Baseflow

HEC-HMS adopted for modelling

Different models can be selected for each component of rainfall-runoff model

Loss (Infiltration)

Transformation (Rainfall-Runoff)

Baseflow

Hydrologic Modelling

Water Quality Modelling Salinity is very important variable to decision making process No water quality models in HEC-HMS CATSALT (Tuteja et al., 2003) to determine salt load Considers flow from groundwater and unsaturated zone separately Other considerations, such as evaporation in storages Q SW Q GW Unsaturated Saturated Q UW

Salinity is very important variable to decision making process

No water quality models in HEC-HMS

CATSALT (Tuteja et al., 2003) to determine salt load

Considers flow from groundwater and unsaturated zone separately

Other considerations, such as evaporation in storages

Integrated Modelling Framework groundwater response Regulator Decision Point shut open flow flow runoff, salinity rainfall evap. runoff, salinity runoff, salinity runoff, salinity rainfall evap. rainfall evap. rainfall evap. wetland response environmental conditions

Groundwater Modelling Regional groundwater flow is relatively well understood Local effects of drains on groundwater table largely unknown, and highly controversial

Regional groundwater flow is relatively well understood

Local effects of drains on groundwater table largely unknown, and highly controversial

Groundwater Modelling Groundwater modelling to answer important questions, such as: What is the zone of influence of the drain? Once a regulator is changed, how long will it take for the groundwater table to adjust? What is the expected effect on the soil salinity?

Groundwater modelling to answer important questions, such as:

What is the zone of influence of the drain?

Once a regulator is changed, how long will it take for the groundwater table to adjust?

What is the expected effect on the soil salinity?

Integrated Modelling Framework groundwater response Regulator Decision Point shut open flow flow runoff, salinity rainfall evap. runoff, salinity runoff, salinity runoff, salinity rainfall evap. rainfall evap. rainfall evap. wetland response environmental conditions

Ecological Response to Salinity A further criterion on the management problem is to sustain the wetlands in the region Project aims to answer questions such as: What are the impacts of elevated salinities on the health and survival of aquatic species? How long can elevated salinities be tolerated? How can we best use water from the drains to optimise wetland health and function? Field and laboratory studies to collect necessary data Modelling to allow expected effects to be predicted Decision making process can then make use of modelling results

A further criterion on the management problem is to sustain the wetlands in the region

Project aims to answer questions such as:

What are the impacts of elevated salinities on the health and survival of aquatic species?

How long can elevated salinities be tolerated?

How can we best use water from the drains to optimise wetland health and function?

Field and laboratory studies to collect necessary data

Modelling to allow expected effects to be predicted

Decision making process can then make use of modelling results

Bayesian Network Modelling

Interaction Between Models Rainfall, Evaporation Current Conditions Groundwater Models Wetland Models Rainfall-Runoff Models Salt Transport Models Regulator Settings Catchment Routing Environmental Response Dryland Salinity Flooding Evaluate Option Simulation/Optimization

Summary Currently, the information required to tackle the problem of dryland salinity is incomplete A multidisciplinary approach is proposed to adequately address the problem Water quality and quantity Groundwater Ecology

Currently, the information required to tackle the problem of dryland salinity is incomplete

A multidisciplinary approach is proposed to adequately address the problem

Water quality and quantity

Groundwater

Ecology

Project Outcomes Integrated simulation model of the system Considering all aspects that affect regulator operation Optimisation component to determine optimal operating scheme Multi-Objective evolutionary algorithms

Integrated simulation model of the system

Considering all aspects that affect regulator operation

Optimisation component to determine optimal operating scheme

Multi-Objective evolutionary algorithms

Outcomes (2) Novel aspects include: Ungauged catchment model calibration Groundwater modelling Ecological modelling Integrated catchment modelling Optimisation and reliability aspects

Novel aspects include:

Ungauged catchment model calibration

Groundwater modelling

Ecological modelling

Integrated catchment modelling

Optimisation and reliability aspects

Summary Whereas simulation models can be used to assess the likely effects of various actions on a system, optimisation models are useful for providing guidance in identifying the best set of actions Optimisation models require a clear definition of objectives Multi-objective optimisation models can be used to assist in managing scarce water resources

Whereas simulation models can be used to assess the likely effects of various actions on a system, optimisation models are useful for providing guidance in identifying the best set of actions

Optimisation models require a clear definition of objectives

Multi-objective optimisation models can be used to assist in managing scarce water resources

Wastewater Treatment Wetland ASR House or Cluster Mains water Stormwater Total Urban Water Management Industry

Optimum Design of Greywater Reuse Systems (Cluster Scale)

Research Objectives Develop a new methodology for the planning of greywater reuse schemes in urban areas that considers their sustainability Apply methodology to development in Streaky Bay

Develop a new methodology for the planning of greywater reuse schemes in urban areas that considers their sustainability

Apply methodology to development in Streaky Bay

Methodology Systems approach Optimisation Module Selection of Alternative Simulation of Alternative Evaluation of Alternative Selection of Objectives Results Selection of Objectives Optimisation Module

Systems approach

Case Study Scale 01 9 houses Scale 02 19 houses Scale 03 47 houses Scale 04 68 houses Scale 05 117 houses Scale 06 147 houses

System Components Individual house reuse system Treatment system Pump Storage tank

Individual house reuse system

Treatment system

Pump

Storage tank

System Components Cluster scale reuse schemes Greywater collection network Treatment system Storage tank Pump Treated greywater distribution network

Cluster scale reuse schemes

Greywater collection network

Treatment system

Storage tank

Pump

Treated greywater distribution network

Layout

Sustainability Objectives Sustainability: Environmental: Total energy consumption (GJ) Economic: Present value of life cycle cost ($) Social Technical

Sustainability:

Environmental: Total energy consumption (GJ)

Economic: Present value of life cycle cost ($)

Social

Technical

Simulation of Alternatives Many design variables Collection network material and pipe diameter Distribution network material and pipe diameters Greywater Treatment System Pump Size However, we need to simulate each component

Many design variables

Collection network material and pipe diameter

Distribution network material and pipe diameters

Greywater Treatment System

Pump Size

However, we need to simulate each component

Results

Comparison of Results Case Study Between $3 and $6 per kL Rouse Hill (Sydney) Between $3 and $4 per kL

Case Study

Between $3 and $6 per kL

Rouse Hill (Sydney)

Between $3 and $4 per kL

Sensitivity Analysis Doubling the population density Extending the available pipe materials and diameters

Doubling the population density

Extending the available pipe materials and diameters

Sensitivity Analysis

Conclusions Cluster scale is more sustainable than individual household Reuse schemes are more sustainable with: Increased population density Network design standards that allow different pipe materials and diameters

Cluster scale is more sustainable than individual household

Reuse schemes are more sustainable with:

Increased population density

Network design standards that allow different pipe materials and diameters

Further Work Include other objectives Ecological impacts Reliability Include other options Rainwater tanks Stormwater reuse Blackwater reuse Aquifer storage and recovery Apply to larger scales

Include other objectives

Ecological impacts

Reliability

Include other options

Rainwater tanks

Stormwater reuse

Blackwater reuse

Aquifer storage and recovery

Apply to larger scales

Summary Whereas simulation models can be used to assess the likely effects of various actions on a system, optimisation models are useful for providing guidance in identifying the best set of actions Optimisation models require a clear definition of objectives Multi-objective optimisation models can be used to assist in managing scarce water resources

Whereas simulation models can be used to assess the likely effects of various actions on a system, optimisation models are useful for providing guidance in identifying the best set of actions

Optimisation models require a clear definition of objectives

Multi-objective optimisation models can be used to assist in managing scarce water resources