DETAILS OF PROJECT PROPOSERS
Title of Project or
Research Theme
Project sponsor(s)
Real Time Abstraction Management
Organisation
Name
Severn Trent Water Ltd
Bernadette Ryan
Academic supervisor
University
Name
Sheffield
Dr James Shucksmith
DETAILS OF THE PROJECT
Project Description
Background / rationale
A number of long terms trends suggest that UK water resources will come under considerable
strain due to the impacts of climate change and population growth. Abstraction from river
systems is a major source of water supply in the UK, however increasing water demand and
increasing periods of low river flows will put pressure on abstraction sources, with potentially
significant associated environmental impacts.
Current licencing practice is based on a system of fixed consents, with no allowance for
prevailing river conditions. However a recent EA report (http://www.environmentagency.gov.uk/research/planning/135501.aspx) makes the case for a significant reform of
abstraction policies in the UK, specifically calling for a more flexible approach to abstraction.
There is therefore potential to move to ‘Real Time (RT) Abstraction’ where abstracted volumes
would vary to account for flow and quality conditions in the surface waters, projected demand,
and current storage as monitored and modelled in real time. Being able to maximise the
volume of abstracted water, (e.g. increasing abstraction from rivers at time of high river flow)
would optimise the use of potential water resources, system storage and potentially water
delivery. It has been suggested (STW Ltd) that currently up to 40ML/d of raw water is ‘missed’
in river abstraction due to infrequent flow data availability.
The real time management should also consider the associated water quality implications and
impacts, not only in terms of their physical and chemical (BOD, ammonia, pesticides etc)
parameters but also of microbiological parameters, especially linked to serviceability targets
e.g coliforms. This will a) minimise use of low quality, contaminated water in the water supply
system (lowering treatment costs) and b) minimise the impacts of abstraction on the river
environment. This project aims specifically to address these issues and here it is proposed to
link the research to the NERC funded Cloud to Coast C2C project,
http://www.sheffield.ac.uk/c2c, that is currently attempting to model the fate and transport of
faecal indicator organisms from where the rainfall falls in upland, rural and urban catchments
to coastal waters.
Enabling and establishing real time abstraction management will require a number of key
research questions to be investigated in relation to measurement techniques and
communications strategies, optimum data collection (quantity and quality) and management
(no. of sensors and their location), quantitative and qualitative modelling approaches, full cost
benefit analysis, interpretation of outputs to knowledge, prediction of uncertainty and a
decision framework for optimum near real time management.
1
Research challenge / questions
Enabling advanced abstraction management within a particular water resource catchment will
require near real time hydraulic and quality data from specific points in the river system, an
understanding of the likely source apportionment at catchment scale, the groundwater source
and abstraction potential, the water demand forecast and the current storage. This project will
focus on surface water abstraction in two catchments aiming to maximise the capture of raw
water resource from rivers in order to minimise use of groundwaters at times when surface
water is available. Modelling capabilities need to couple the near real time data to forecast
conditions at the abstraction points with a view to the maximum abstraction from ‘clean’
sources and the minimum use of ‘dirty’ water. This understanding will require coupling to
projected demand, storage and quality.
The main challenges will be
1) the development of reliable cost effective enabling hardware for real time monitoring
at sites (and determination of the optimum sites), together with challenges associated
with enabling the necessary telemetry and communications. (Our previous research
has highlighted that instruments are now available that can communicate with phones
and laptops and hence data may be accessed remotely)
2) the development of appropriate river modelling tools to utilise real time data in order
to predict river levels and river flow quality, including coliforms and pesticides, with an
assessment of the suitability of abstraction points for the potential delivery of water.
This should include open assessment of prediction uncertainty so that confidence in
predictions is demonstrated. (Here close collaboration will be made with the existing
C2C research programme, especially for the modelling of coliforms)
3) to refine the methodology to ensure that data is gathered at appropriate temporal
and spatial scales so as to give confidence in modelling tools as well as maximising the
benefits associated with increased abstraction volumes relative to technology and
management costs.
4) To deliver a cost benefit analysis of the proposed solutions for the chosen catchments
5) to develop a decision framework to operate the abstraction strategy based on near
real time data and model outputs.
6) to ensure the transferability of techniques to a full range of catchments with different
characteristics.
Methodology
1. Draw up a list of potential catchments that may be used within the study based on a
series of selection criteria (to be developed but certainly to include an understanding
of the catchment characteristics, river available storage and treatment options,
historical data, existing STW monitoring, current data management strategy,
quantitative and qualitative modelling capability and form of decision making)
2. Select catchments for detailed review and refine selection to 2 catchments
3. Assess cost effective technology for measuring flows, and relaying this information to
the works/ pumps.
4. Define monitoring strategy needed to successfully complete the project at each of the
2 catchments and install (this will be primarily existing but potentially with additional
data on quality – here work will build on expertise gained in project NEPTUNE at UoS)
5. Investigate appropriate modelling techniques capable of utilising data to generate RT
hydraulic and quality predictions within test catchments (here strong collaboration
with C2C).
6. Develop the model to describe the river flow and quality in response to time series
rainfall inputs. Calibrate the model.
2
7. Use the models to quantify uncertainty in model predictions and demonstrate how
uncertainty is related to modelling assumptions, lead time of prediction and resolution
of available datasets. Refine modelling tool and data gathering strategies to
appropriate complexity/level as required and to provide confidence in model outputs.
8. Use model in 2 ways:
 Establish optimum mode of operation to deliver RT abstraction data and decision
making
 Establish optimum use of abstracted water for serviceability requirements,
especially coliforms and pesticides.
9. Establish an holistic cost benefit framework to be used to maximise the quantity and
quality of raw water abstraction and highlight the relative benefits of a decision
strategy (what if scenarios) in near real time. (Note – climate and other scenarios will
be here assessed).
10. Test the framework to identify strategies to overcome periods of strain/poor quality,
11. Evaluate cost/benefits of the RT abstraction strategy, and show how relative costs and
benefits are related to resolution of data collection and catchment characteristics.
12. Develop strategies and a roadmap for implementation at other sites.
Adherence to abstraction licence conditions is imperative throughout, though an evaluation
of the potential effectiveness of a variable abstraction licence should be considered.
Anticipated outcomes & benefits for the sponsoring organisation and other stakeholders
Immediate benefits include optimisation of use of surface water resources in terms of quantity
and quality.
This will improve water security, reduce demand on other sources (e.g. groundwater), reduce
treatment costs (by abstracted better quality water) and reduce the environmental impacts of
abstraction (by minimising abstraction when river flows are low).
The use of near real time information will allow river abstraction volumes to be optimised and
balanced against quality and storage availability. Specifically by determining the optimum
use of water resources and mitigating of low flows via abstraction restraint as well as the
optimum use of resources to meet serviceability targets by controlling demand and water
quality e.g. coliforms, pesticides etc.
This would be supported by a full cost benefit analysis.
In addition, the development of a model to predict river flows and quality at abstraction
points will provide STW with a better understanding of the behaviour of complex river and
catchment systems. This can then be used for scenario analysis, hence potentially providing
significant longer terms benefits in relation to mitigating the potential impacts caused by
climate change, population growth and changing water quality standards.
Scientific contribution of the project together with any other innovative aspects.
The main scientific aspects of this proposal lie in furthering scientific understanding of
catchment behaviour and the by the use of high quality real time flow and quality datasets
over long time series. This includes the hydraulic performance of catchments and well as the
transport and fate of coliforms, pesticides and other water quality parameters. The
development and testing of flow and quality modelling tools will help develop a scientific
understanding of the uncertainty of various modelling approaches and explore how
uncertainty is related to the temporal and spatial scales of the measurement and model
complexity. Following the development of the modelling tools, a scenario analysis will be
undertaken using the latest understanding of likely parameter change (population, climate
etc) using STW data. This will allow a detailed study on the predicted impacts of climate
3
change and population change on water resources and the implications for water security in
the UK.
In addition other innovative aspects include the optimisation of quantity, quality and storage
for UK water supply, development of a detailed understanding of the implications of
abstraction on river environment and the developments of a methodology for the use,
deployment and sampling frequency for low cost flow and quality monitoring equipment in
surface waters.
Business or management element that is to be tackled in the research.
During periods of low levels of surface water availability, groundwater resources are used
more intensely to fill the gap to ensure that supply is maintained to customers. However,
internal research suggests that up to 40ML/d of water is being missed during periods of high
availability of surface water, due to limitations with monitoring and recording river flows. This
project seeks to identify the extent of this issue in 2 catchments and to establish a cost
effective methodology of real time data capture to ensure we maximise abstracted volumes
and can therefore minimise the draw on groundwater sources during dry periods.
This project will take into account the quality of the river water at times of high flow, in order
to assess the suitability of this excess of water for abstraction. This decision would necessarily
take into account the storage capacity of the treatment works and the works capability to
treat the abstracted water to meet drinking water quality standards.
A full cost- benefit analysis will provide managers with the additional information required to
establish the benefits of targeting the excess water available.
Predictions of the possible implementation of this methodology at other catchments will be
beneficial. Similarly, the potential to predict abstractable volumes in catchments would be
beneficial in terms of resource planning and investment strategy.
4