Modeling Water Demand During Droughts

Modeling Water Demand in Droughts
(in England & Wales)
(Estimating Scenarios for Domestic Water Demand Under Drought
Conditions in the UK: Application of an Agent-Based Microsimulation Model)
Magesh Nagarajan & Ben Anderson
Sustainable Energy Research Group
Energy & Climate Change Division, Faculty of Engineering & Environment

@dataknut: Modeling Water Demand in Droughts
Contents
 The problem
 Model Framework
 Concepts & Implementation
 Preliminary Results
 Next Steps
2

The problem: water
3
205
0
 With no ‘behaviour’ change and no flow controls:
Source: DEFRA, 2011

The problem: water
4
 Supply:
 Locally/regionally scarce
 Climate change effects?
 Demand:
 50% used by households
 Drivers not well understood
 Climate change effects?
 Demographic
 Population growth
 Increasing single person
households
Source: Environment Agency, 2008

The problem: drought is normal
5
Source: Water UK (2016) Water resources long term planning framework (2015-2065)
Water Resources Long Term Planning Framework
Water UK
Atkins | Mott MacDonald | Nera | HR Wallingford | Oxford University
Technical Report | Final | 20 July 2016 53
5. Is there a problem?
5.1. Analysis of Drought Coherence, patterns and severity
5.1.1. Evidence from Historic Droughts
By using the aridity indices described in Section 4.3.1.2, it was possible to examine the spatial nature of the
significant droughts that occurred within the 20th Century. Nearly all water companies now plan their
resources to be able to meet these events, with a ‘median’ allowance for expected climate change impacts.
However, it is important to understand the nature and patterns of the droughts within the historic record in
order to create ‘plausible’ Drought Configurations for the portfolio evaluation and resilience testing. A
summary of some of the most informative findings from the analysis of historic droughts is provided below. It
should be noted that these representations sometimes contain different years in the same plot – e.g. the
1932-34 and 1995/96 ‘worst’ point in time varied across the country. This is commented upon where
appropriate in the figures.
Drought Event:
Short Duration Aridity Index (12 months
ending summer or late autumn)
Drought Event:
Longer Duration Aridity Index (24
months)
Notes/Comments
1901-03: worst point for
short duration was
December 1901; worst
point for long duration
was December 1902.
Short duration not
severe enough to
challenge resources.
1921-22: worst point for
short duration was
December 1921, worst
point for long duration
was December 1922.
Long duration not
sufficient to challenge
resources – drought
stress was exacerbated
by the ‘extension’ of the
1921 event into early
1922.
1932-34: Multi-dry
winter event; worst
short duration occurred
at different points
spatially (hence
apparent coherence).
Short duration not
sufficient to cause
stress – 2 year event in
all areas, but varying
between 1932/33 in
some areas versus
1933/34 in others.
Water UK
Figure 6-19 Demand growth under upper population scenario, BAU Base strategy, 2040 (left) and
2065 (right) – by Supply Area (top) and Region (bottom)1901-03
1921-22
1932-34
1976
1995/6
+ others (including 2011/12)
And it may get worse…

The problem: current practice
6
Sources: Water UK (2016) Water resources long term planning framework (2015-2065), Essex & Suffolk Water,
Daily Mail
Water UK
Figure 3-4 Illustration of typical sequence of drought interventions (taken from the Affinity Water
Drought Plan)
Example diagram of a drought trigger-response system. The purple and blue lines represent theoretical
monitored groundwater levels during a two or three year event respectively. The green, yellow, orange and
red bands represent ‘thresholds’ that are based on an analysis of historic records, and are used to help
inform the company when it is making decisions on the level of demand restrictions and supply side
interventions to take.
The y-axis in this indicative diagram, presents the groundwater level (in metres above ordnance datum,
mAOD).

Contents
 The problem
 Model Framework
 Next Steps
7

IMPETUS: joined-up modelling…
8
RCUK Funded under the UK Droughts & Water Scarcity Programme 2014-2017
IMPETUS: Improving Predictions of Drought for User Decision-Making
Meteorological
Models
Hydrological
models
Demand
models

The Water Demand Model
9
• ‘Normal’ demand
• Drought phase
Inputs
• Impact of ‘drought’
• Impact of ‘interventions’
Microsimulation Model
• Estimated demand under drought
Outputs
For a given catchment…
Drought phase Label Interventions
Normal All indicators normal
Developing
Heightened risk of water
deficit
Voluntary abstraction
restriction & efficiency
measures
Drought Stress on water supply
Temporary use bans &
efficiency measures
Severe Failure of water supply
Restrictions on non-
essential use
Recovery Returning to normality Efficiency measures

The Water Demand Model
10
Q1 2011
•Drought phase X -> Estimated demand
Q2 2011
Q3 2011
Q4 2011
…
•…
Q4 2030
For a given catchment…
Drought phase Label Interventions
Normal All indicators normal
Developing
Heightened risk of water
deficit
Voluntary abstraction
restriction & efficiency
measures
Drought Stress on water supply
efficiency measures
Severe Failure of water supply
Restrictions on non-
essential use
Recovery Returning to normality Efficiency measures

Contents
 The problem
 Model Framework
 Next Steps
11

Framework: Water Cultures
12
Water Cultures
(after Stephenson et al, (2010) Energy Cultures - doi: 10.1016/j.enpol.2010.05.069)
Materiality
Cognitive/Cultural
norms
Water practices
Cleanliness
Cooling
Greenness Income
Occupancy
Metering
Price
Garden infrastructure
Appliances
Washing & laundry habits
Garden watering
Cleaning habits

‘Normal’ usage model
 Ownership of devices (Pullinger et
al, 2013)
 Appliance litres/day (Parker, 2014)
– With household attributes
– With weather
– By season
 Water efficiency installations
(EST, 2013)
– 41% of HH have dual-flush toilet.
– 25% of HH have efficient
shower heads.
13
Data source: “At home water needs” EST (2013, p13)
So what’s the point of an external use ban??

Intervention ‘impact’ model
Impact of efficiency & temporary use bans, UKWIR
2013 report
14
Water-use
appliance
Usage Water-
use
saving
% switch
per year
Dual-flush toilet 5 l/flush 47% 2%
Other-flush
toilet
9.5 l/flush
Eco-shower 5 l/min 61% 1%
Power-shower
(Others)
13 l/min
Initial values: (EST, 2013)
• Key assumptions:
• No change in practices (the user experience
is unchanged)
• Efficiency does not degrade over time
• Water efficiency uptake can be varied
• Key parameters:
• External use ~= 11% households
• TUB compliance can be varied
Type of
household
% Water-use
saving
Compliance
High flow
user
14% 10-18% 44% (6% of
total)
Other 86% ? ?

R NetLogo
Model v1 flow diagram
15

Contents
 The problem
 Model Framework
 Next Steps
16

Model v1: Retrospective
17
Census
2011
N households
Household
size
Age distribution
Work
status
Synthetic survey

Retrospective: With(out) drought
18
Without drought
With drought response
Drought phase Interventions
Normal Water efficiency
Developing Water efficiency
Drought
efficiency measures
Severe
efficiency measures
Recovery Water efficiency

Retrospective: Sensitivity
19
For every 0.25% increase in “dual
flush” uptake, average incremental
saving in water was c.55 million litres
For every 0.25% increase in “Eco
shower” uptake, average incremental
For every 10% increase in “Ban
compliance”, average incremental
saving in water was c. 0.65 million
litres

Model v1: Prospective
20
Census
2011
N households
Household
size
Age distribution
Work
status
Synthetic survey
Year Jan-Mar Apr-Jun Jul-Aug Sep-Oct
2016
2017
2018
2019
2020
2021
Drought Temporary use bans & efficiency measures
Severe Temporary use bans & efficiency measures

Prospective: With(out) drought
21
2016
2017
2018
2019
2020
2021
Without drought
Drought
efficiency measures
Severe
efficiency measures

Prospective: With(out) drought
22
Year Normal
consumptio
n
Adjusted
consumption
%
reduction
Normal
consumption
Adjusted
consumption
% reduction
2016 105.44 104.57 0.82% 105.44 104.42 0.96%
2017 105.07 102.70 2.25% 105.07 102.53 2.42%
2018 105.96 102.02 3.72% 105.96 99.60 6.00%
2019 105.57 100 5.28% 105.57 97.60 7.55%
2020 105.48 98.33 6.78% 105.48 97.31 7.74%
2021 105.54 96.87 8.22% 105.54 97.07 8.02%
Sum 633.07 604.48 4.51% 633.067 598.55 5.45%
Without drought With drought response
Total demand reduction is 28.59 and 34.52 million litres respectively (2016-2021)
2016
2017
2018
2019
2020
2021
Without drought
Drought
efficiency measures
Severe
efficiency measures
The hosepipe ban ‘effect’

Prospective: Sensitivity
23
2016
2017
2018
2019
2020
2021
Drought
efficiency measures
Severe
efficiency measures
For every 0.5% increase in “dual
flush” uptake, average incremental
For every 0.5% increase in “Eco
shower” uptake, average incremental
For every 10% increase in “Ban
compliance”, average incremental
saving in water was c. 9 million litres

Prospective: Robustness
24
Mean 4.55% (4.32 to 4.74%), Std.dev 0.10
Mean 5.43% (5.22 to 5.66%), Std.dev 0.09
2016
2017
2018
2019
2020
2021
Without drought
Drought
efficiency measures
Severe
efficiency measures
• Re-run model 100 times
Varies over a
narrow range

Contents
 The problem
 Model Framework
 Next Steps
25

Next Steps
26
 Adding:
– Practices
– Weather
– Interactions
 Linking to
– drought forecasts
1994 2012

Thank you!
 b.anderson@soton.ac.uk (@dataknut)
 Come and work on the project!
– “Research Fellow in Household Water Demand Modelling”
 jobs.soton.ac.uk/Vacancy.aspx?ref=782916AT
27

Modeling Water Demand During Droughts

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