SID 5 Research Project Final Report

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SID 5
Research Project Final Report
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SID 5 (Rev. 3/06)
Project identification
1.
Defra Project code
2.
Project title
WU0108
The relationship between water availability and quality in
the context of agricultural practices in England and
Wales
3.
Contractor
organisation(s)
ADAS UK Ltd
54. Total Defra project costs
(agreed fixed price)
5. Project:
Page 1 of 29
£
61,538
start date.................
01 April 2007
end date..................
31/10/2007
6. It is Defra’s intention to publish this form.
Please confirm your agreement to do so. ...................................................................................YES
NO
(a) When preparing SID 5s contractors should bear in mind that Defra intends that they be made public. They
should be written in a clear and concise manner and represent a full account of the research project
which someone not closely associated with the project can follow.
Defra recognises that in a small minority of cases there may be information, such as intellectual property
or commercially confidential data, used in or generated by the research project, which should not be
disclosed. In these cases, such information should be detailed in a separate annex (not to be published)
so that the SID 5 can be placed in the public domain. Where it is impossible to complete the Final Report
without including references to any sensitive or confidential data, the information should be included and
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Executive Summary
7.
The executive summary must not exceed 2 sides in total of A4 and should be understandable to the
intelligent non-scientist. It should cover the main objectives, methods and findings of the research, together
with any other significant events and options for new work.
Changes in the quantity or availability of ground or surface water may arise due to anthroprogenic
changes such as abstraction, transfer and impoundment, as well as by natural variability in the rainfall and
water balance. Changes in average water quantity, and in the variation within and between years, are
predicted to occur over the coming decades due to climate changes. Agriculture places a significant
demand on regional water resources, for the irrigation of crops, washing and watering of livestock, and the
preparation of produce.
These agricultural effects on water quantity or availability, both annually and seasonally, have the potential
to impact on water quality, by influencing chemical effects (e.g. reduced dilution of point source inputs of
pollutants, or changing the kinetics of in-river processes by changing reach residence times) or by
influencing physical effects (e.g. reduced volume of useable habitat for plants and animals). The
combined chemical and physical effects can alter the ecology of a river reach, and potentially prevent a
reach from achieving the ‘good chemical and ecological status’ required by the Water Framework
Directive.
The aim of this project was, therefore, to review the relationship between water availability and water
quality in the context of agricultural practices, so as to provide Defra (and other stakeholders) with a better
understanding and a robust basis for decision making.
The specific analyses carried out by this project were:
•
•
•
•
Summarising the existing standards for good water status that may be impacted by changes in
water availability, with reference to the Water Framework Directive;
Summarising and mapping data on the agricultural demand for water, and quantifying the
agricultural impact on water availability, with special attention to seasonal and inter-annual effects;
Providing quantitative evidence of the impact of reduced water availability (due to agriculture) on
chemical and ecological status, under present land use and climate; and
Investigating the potential impact of climate change on water availability and quality.
The results of these analyses were placed in the context of the Water Framework Directive (WFD) and
provided an assessment of the regional pattern of impact across England and Wales. A full report is
available as Annexe I to this summary report.
This project assessed the quantity of water available for abstraction from surface waters for the current
SID 5 (Rev. 3/06)
Page 2 of 29
(baseline) climate, as well as estimating effects under future climate scenarios. We have been able to
place these in the context of the agricultural demand for water. A model was developed for the simulation
of time series of flow for the whole of England and Wales. The model is responsive to catchment
characteristics of land use and hydrogeology and it showed a good performance over a range of different
catchments, without the need for site-specific calibration to observed data.
The evaluation of agricultural demands in the context of available water showed that demands from
agriculture are significant in the summer period and in certain areas of the country, mainly concentrated in
East Anglia. Also, agriculture is presumably the most important abstractor in headwaters, as other
abstractors usually abstract from major rivers.
In many of the areas in which abstraction of summer surface water is classified as unsustainable by the
EA, agricultural demands are not significant. Abstraction of summer surface water is currently considered
unsustainable in all of the Southern Region and parts of East Anglia, but in most parts of the Southern
Region agricultural demands are less than 3 mm. This is because the crops requiring large amounts of
irrigation are not grown to a big extent in this region.
In East Anglia, where irrigation demands are significant, summer surface water abstractions are classified
as unsustainable in smaller parts, and no additional water is available in any part of East Anglia. With
decreasing summer flows under future climate conditions, less water will be available for abstractions,
while demands are expected to increase.
In terms of water quality, reassessment of standards under the WFD has created closer linkages between
chemical, nutrient and hydromporphological status and ecology. Thus, if agricultural water demand
impacts on dissolved oxygen, BOD, ammonia or P levels and/or flow, then this could have potential
impacts on the ecological status. We have concluded that changes to water quality due to dilution effects
are:
• chiefly related to point sources (sewage treatment works) rather than diffuse agricultural sources;
• are is most likely in the east;
• are most likely in the summer months.
In terms of climate change impacts on water availability, and the demand for irrigation water in summer,
we concluded that:
• Climate change is likely to increase demand for irrigation water during summer, and increase the
frequency of occurrence of extreme demand years and of low flows;
• annual variations are as great as or greater than expected changes in mean value within the next
few decades However the change in mean value, and in frequency of demand exceeding
availability, will impact on water resource planning and irrigation abstraction licensing.
This analysis did not take explicit account of other potential effects of climate change. Greater risk of
summer drought, with higher temperatures, could increase irrigation demand:
• by extension of Irrigation to a wider range of crops;
• by introduction of new crops requiring irrigation;
• by extension of irrigation into areas where irrigated crops are currently rare – i.e. towards the
west.
The extension of irrigated crops towards areas where they currently do not occur could have adverse
impact on rivers which are currently of relatively good ecological quality:
• by reduction of summer flows;
• by quality changes as discussed above;
• more directly, by the fact that some of these crops carry with them an increased risk of sediment
or other pollutant transfer.
The results form a basis of information for input to river basin planning, and for taking account of impacts
of climate change, in a uniform way. They should be made available to river basin planning teams. The
results suggest that conflict between supply and demand is greatest during summer, and in the east; and
that this conflict will become greater rather than less. This suggests that, in future, irrigation may only be
viable with winter storage to allow abstraction of water while flows are high. Further assessment of the
impacts of climate change should take account of likely changes in land use, and in crops for which
irrigation may become economic. As a result of climate change and consequent land management
change, and the difficulties of irrigation in eastern areas, it is possible that irrigation will increase in more
sensitive western catchments. The risk of this, and the ecological implications, should be investigated.
SID 5 (Rev. 3/06)
Page 3 of 29
Project Report to Defra
8.
As a guide this report should be no longer than 20 sides of A4. This report is to provide Defra with
details of the outputs of the research project for internal purposes; to meet the terms of the contract; and
to allow Defra to publish details of the outputs to meet Environmental Information Regulation or
Freedom of Information obligations. This short report to Defra does not preclude contractors from also
seeking to publish a full, formal scientific report/paper in an appropriate scientific or other
journal/publication. Indeed, Defra actively encourages such publications as part of the contract terms.
The report to Defra should include:
the scientific objectives as set out in the contract;
the extent to which the objectives set out in the contract have been met;
details of methods used and the results obtained, including statistical analysis (if appropriate);
a discussion of the results and their reliability;
the main implications of the findings;
possible future work; and
any action resulting from the research (e.g. IP, Knowledge Transfer).
1.
INTRODUCTION
Changes in the quantity or availability of ground or surface water may arise due to anthroprogenic changes such
as abstraction, transfer and impoundment, as well as by natural variability in the rainfall and water balance. The
water quantity available for use by agriculture is further affected by restrictions placed on abstraction, which are
constantly under review.
Changes in average water quantity, and in the variation within and between years, are predicted to occur over the
coming decades due to climate changes. These could compound low flow problems in summer months
especially in southern and eastern regions (Downing et al., 2003). While effects on mean annual water quantity
are uncertain and variable, there is consensus that summer rainfall will decrease, causing reduction in summer
flows and delay in the start of recharge in autumn.
Agriculture places a significant demand on regional water resources, for the irrigation of crops, washing and
watering of livestock, and the preparation of produce. The annual average volume of water used for irrigation in
6
3
England is c. 125×10 m (Weatherhead & Danert, 2002) and for the drinking and wash requirements of livestock
6
3
is c. 120×10 m (Smith, pers. comm.). The majority of water for drinking and washing is supplied by the mains
and therefore simply adds to the public water supply demand. The dominant source of water for irrigation is
abstraction from surface and ground waters, accounting for 95% of irrigation water in 2001 (Weatherhead &
-1
Danert, 2002). In the main irrigating regions of Anglia and the Midlands (EA regions), approximately 130 ML day
-1
were abstracted from surface waters, and 100 ML day from groundwater sources (Defra, 2005). The majority of
the water for irrigation is abstracted during summer (i.e. few users have sufficient storage to carry them through
the whole season). Abstractions, therefore, have the potential to significantly decrease natural river flows, and
especially low flows in summer months when the demand is greatest. Long-term changes in land use patterns, in
response to economic and climate change, may also impact on seasonal river flows by changing the balance of
rainfall and crop evapotranspiration through crop type and cover (Hulme et al., 1993).
These agricultural effects on water quantity or availability, both annually and seasonally, have the potential to
impact on water quality, by:
•
Influencing chemical effects ~ Including a) reduced dilution of point source inputs of pollutants, and b)
changing the kinetics of in-river processes by changing reach residence times;
•
Influencing physical effects ~ Including a) reduced volume of useable habitat for plants and animals, through
changes in flow depth and velocity, and b) changes in water temperatures.
The combined chemical and physical effects can alter the ecology of a river reach, and potentially prevent a reach
from achieving the ‘good chemical and ecological status’ required by the Water Framework Directive (WFD;
2000/60/EC).
The aim of this project was, therefore, to review the relationship between water availability and water quality in the
context of agricultural practices, so as to provide Defra (and other stakeholders) with a better understanding and
a robust basis for decision making.
SID 5 (Rev. 3/06)
Page 4 of 29
By ‘water availability’, we have interpreted this to mean water available for use in agricultural production (crop,
livestock and amenity plant production systems). However, this always has to be set against the quantity of water
within a catchment (surface and groundwater systems) and how agriculture interacts with the catchment water
resources.
1.1.
Objectives
1. To summarise existing standards for good water status that may be impacted by changes in water availability,
with reference to the Water Framework Directive;
2. To summarise and map data on the agricultural demand for water, and to quantify the agricultural impact on
water availability, with special attention to seasonal and inter-annual effects;
3. To quantify the impact of reduced water availability (due to agriculture) on chemical and ecological status,
under present land use and climate;
4. To investigate the potential impact of climate change on water availability and quality;
5. To use these data to review the regional pattern of impact across England and Wales, with special attention
to differences between types of pollutants.
6. To set these finding in the context of the Water Framework Directive and achieving its objectives.
2.
APPROACHES
The specific analyses carried out by this project were:
•
Summarising the existing standards for good water status that may be impacted by changes in water
availability, with reference to the Water Framework Directive;
•
Summarising and mapping data on the agricultural demand for water, and quantifying the agricultural
impact on water availability, with special attention to seasonal and inter-annual effects;
•
Providing quantitative evidence of the impact of reduced water availability (due to agriculture) on
chemical and ecological status, under present land use and climate; and
•
Investigating the potential impact of climate change on water availability and quality.
The results of these analyses were placed in the context of the Water Framework Directive (WFD; 2000/60/EC)
and provided an assessment of the regional pattern of impact across England and Wales.
A full report is available as Annexe I to this summary report.
3.
RESULTS AND DISCUSSION
3.1.
Potential impacts of reduced water availability
There are many potential impacts of reduced water quantity in catchments, and these must be taken into account
in determining both quantity and timing of any abstractions. In addition to the impacts directly on the river
systems and particular reaches affected by abstraction, there can be knock–on effects felt in lakes and other
water bodies fed by river suffering low flow events. Reduced flow through lakes and reservoirs can increase the
risk of algal blooms. River margin habitats may suffer if river levels or river water quality change. Restrictions on
abstractions are often driven by the need to maintain such habitats. Potential impacts include:
•
Habitat change and river morphology - changes in the natural fluctuations in flow will affect species
composition. Greatest concern has focused on low flows in summer, but changes in the pattern of flow
regimes could also have important impacts.
•
Increased temperature and reduced dissolved oxygen - low water levels and low flow rates result in river
water temperatures approaching ambient. Under the high temperatures typical of summer, and especially of
drought periods, this can result in water temperatures that kill or reduce the viability of fish, and other
organisms. At elevated temperatures, levels of dissolved oxygen (and other gases) fall.
•
Sedimentation - The deposition and accumulation of fine-grained sediment on river channel beds is
increasingly recognised as an important environmental problem. Increased sediment deposition overall could
occur where the frequency and extent of high flows, with their natural scouring effect, is reduced, especially
where this is coupled with lower flows in summer. Depletion of groundwater reserves could have this impact
on groundwater-fed streams, causing reduced flow throughout the year. Stagnation during extreme low flows
SID 5 (Rev. 3/06)
Page 5 of 29
can result in evaporation with total deposition of all suspended matter, leaving a layer of very fine sediment
which blocks air access to river beds.
•
Impacts on estuaries and tidal reaches - Large increases in salinity and other characteristics may occur in
near-estuarine reaches during periods of very low flow, when estuarine influence reaches further up the river
than normal, with adverse effects on salt intolerant plant and animal species.
•
Concentration of pollutants - reduction in river flow, coupled with maintained inputs of pollutants, will result in
increased concentrations of pollutants.
•
Sewage Treatment Works - The main issue is that input of sewage-derived pollutants is fairly constant
throughout the year, whereas the flow of water (and associated pollutants) derived from the land is
generally reduced in summer. Upstream abstractions could limit the quantity of relatively clean water
available for dilution of a downstream input of sewage. This risk is greatest in summer, when diffuse
inputs and flow from land are at a minimum.
•
Diffuse agricultural pollution - Diffuse pollution from agriculture occurs mainly during the high flow period
of winter. In general, concentrations of pollutants derived from agriculture are less likely to be affected by
abstraction of water than are pollutants derived from sewage, since agricultural pollutant inputs are
‘diffuse’ across the landscape, and the abstracted water removes them pro-rata. In livestock farming
areas, there can be a problem of intermittent ‘diffuse-point’ source pollution from direct discharge of yard
and parlour washings. Such pollution, although more extensive during winter, could occur at any time of
year and its impacts will be aggravated by low stream flow volumes.
•
In-stream transformations - during periods of low flow, residence times are extended. Increased residence
times allow greater equilibration with bed sediments, which may allow a decrease in concentration of
pollutants such as phosphorus if they exceed that of the bed sediments. Increased residence time also
allows opportunities for death and decay of FIOs and decay of agrochemicals in situ. High flows can,
however, mobilise sediment and associated phosphorus retained during low flows, through resuspension.
•
River plant communities - limited dilution or increases in sewage discharges can lead to increases in
inorganic nutrient concentrations, in particular P and possibly N, to which phytoplankton, macrophytes and
phytobenthos are highly responsive. Nutrient enrichment can lead to an increase in biomass in stream to the
exclusion of nutrient-sensitive slow growing species, thus changing the in-river species composition. The
initial nutrient concentration in the water column governs the effect of the nutrient enrichment, which may
have no impact if the nutrient is not limited. Regarding algal blooms, unless the residence time of the water in
the river is greater than the generation time of phytoplankton, which is of the order of several days, significant
biomass quantities cannot be achieved. The main risk of algal blooms is therefore in reservoirs, canals and
very slow moving rivers (Deflandre & Jarvie, 2004).
•
Impacts on invertebrates - invertebrates are frequently used as indicators of river health as they exhibit rapid
responses to a wide range of environmental factors. The invertebrate community is particularly affected by
oxygen concentrations as most are unable to regulate their oxygen uptake.
•
Impacts on fish - low flows and their corresponding impacts on river velocities and water depths affect
different fish species in different ways, the result of which can be changes in species assemblages in a given
river reach. For salmon, low flow conditions associated with droughts, coupled with increased water
temperature and reductions in dissolved oxygen have serious impacts on fish mortality resulting in gaps in the
age structure of communities. Only a few days of conditions that do not meet ideal requirements can result in
fish losses. Low flows at critical times can also affect migration; and spawning.
•
Abstracted water quality – reduction in summer flows could result in elevated concentrations of FIOs in
summer. These could pose a danger where the water is used for irrigation of fruit or vegetable crops to be
eaten raw and unprocessed. Increases in P concentrations in summer, due to flow reduction, could increase
the risk of algal blooms and the extended residence times at low flows would increase this risk still further.
Clearly, there are many impacts of water quantity availability on the hydrology, physics, chemistry and ecology of
rivers. Abstractions are licensed to ensure that given environmental standards are maintained in rivers defined in
terms of discharge rates that are related to other ecological measures. Standards for rivers therefore exist for the
UK driven by the EU legislation of the Nitrates Directive, Fisheries Directive, Habitats Directive, Bathing Waters
Directive, Shellfish Waters and Shellfish Hygiene Directives. However, the Water Framework Directive
(200/60/EC) currently places a greater onus on Member States to examine the links between ecological condition,
hydromorphology and flow, and to define a new raft of standards and methods to assess and monitor quality.
SID 5 (Rev. 3/06)
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3.2.
Summary of existing standards (Objective 1)
The aim was to summarise existing standards for good water status that may be impacted by changes in water
availability, with reference to the Water Framework Directive.
It is proposed that the current management and assessment methods used for water resources (e.g. CAMS) and
water quality (e.g. General Quality Assessment, GQA) in the UK will in time be replaced by a new set of methods
to determine whether Good Status is being achieved under the WFD. The new approach will be broader, due to
the need to consider the water environment as a whole by considering water quality, quantity (e.g. river flow) and
physical habitat (e.g. channel form and depth) alongside ecological indicators (e.g. populations of fish,
macroinvertebrates, and macrophytes) and by covering rivers, lakes, estuaries, coastal waters and groundwater.
Under the WFD, ecological quality is judged on the basis of the degree to which the observed conditions deviate
from those that would be expected in the absence of significant anthropogenic influence (Carvalho et al., 2002)
and, as such, ‘good’ and other status classes are assigned to each water body. The current and proposed
classification methods and standards for the WFD for both water quality and water quantity are set out below.
The focus is on rivers, because abstraction from groundwaters will have little impact on groundwater chemistry,
and any ecological impacts will be chiefly impact on surface waters.
Specific pollutants are substances (metals, solvents and some pesticides) discharged into the water environment
in ‘significant quantities’ and are known to harm ecology. To achieve Good Ecological Status under the WFD, the
UK is responsible for developing Environmental Quality Standards (EQSs) for Specific Pollutants.
Priority
Substances and Priority hazardous substances are of concern in reaching the ‘Good Chemical Status’
classification under the WFD. These substances are especially toxic. The standards for these substances are
being set by the European Commission directly (www.wfduk.org). Specific pollutants and priority substances are
not considered in any further detail within the scope of this project.
Current Water Quality Standards - Environment Agency GQA standards
The Environment Agency uses the General Quality Assessment (GQA) Scheme to consistently assess the state
of water quality of rivers and canals throughout England and Wales and to assess changes in state over time.
More than 7000 sampling sites in England and Wales are assessed for their chemical and biological status,
nutrient levels and aesthetic water quality.
Chemical, biological, nutrient and aesthetic parameters are monitored across this network (Table 1). The results
are compared to predetermined standards and a GQA grade is assigned for that parameter.
Table 1. Summary of the GQA.
Parameter
Determinands
GQA scoring system
Chemical
Dissolved oxygen, Biological oxygen demand &
ammonium
Score A-F, based on worst of the 3
chemical indicators (A=best)
Nutrient
Phosphorus and nitrate
Score 1-6 for each (1= lowest)
Biological
Calculation of an Ecological Quality Index based on
populations of macroinvertebrates
Score A-F (A=best)
Aesthetics
Litter, odour, colour and presence of oil on surface
Score a-f (a=best)
Environment Agency Flow Rules
The Environment Agency also manages abstractions in England and Wales. Key indicators have been the Q95
index, which is the flow that is equalled or exceeded 95% of the time, or indices of rarer events such as the mean
annual minimum flow. The Q95 has often been treated as a hands-off flow, by which no abstraction is permitted
when the flow is below this level. Whilst these approaches are not specifically chosen with ecological
considerations in mind, there are cases where more generic relationships have been identified to protect specific
elements of the river system. Water Framework and Habitats Directives, amongst others, have recently moved
the focus towards habitat protection and more complex abstraction and flow management. This is described
later.
The Catchment Abstraction Management Strategies (CAMS) process (Environment Agency, 2002) was
developed by the Environment Agency to ensure that the needs of the abstractor are met, as well as
safeguarding the environment. The CAMS process sets environment flow objectives in a consistent way across
England and Wales using the default framework of the Resource Assessment Management (RAM) framework
coupled with input from catchment stakeholder groups. The CAMS process is repeated every six years. The
CAMS is being applied across England and Wales to determine ecological sensitivity of water resources as a
forward look to the implementation of the WFD.
SID 5 (Rev. 3/06)
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To assess a river’s sensitivity to a reduction in flow, four elements of the ecosystem are assessed: 1) Physical
characterisation; 2) Fisheries; 3) Macrophytes; 4) Macro-invertebrates. Each element is given a score of 1 to 5,
with 5 being the most sensitive to change and 1 the least. The scores for each element are then combined to
categorise the river into one of 5 Environmental Weighting Bands, where band A is the most sensitive and band E
is the least. In turn, the RAM framework specifies allowable abstractions at different points in a flow duration
curve for natural flows for each weighting band. The percentage of natural Q95 that can be abstracted for each
band is given in Table 2.
Table 2. Percentage of natural Q95 that can be abstracted from each band on the RAM framework.
Environmental weighting band
% of Q95 that can be abstracted
A
B
C
D
E
Others
0-5
5-10
10-15
15-25
25-30
Special Treatment
This method focuses on producing an ecologically acceptable flow duration curve and is most appropriate when
the river ecosystem is controlled by broad characteristics of dry season/wet season or winter/summer flows
(Dyson et al., 2003). A more detailed habitat modelling approach, which aims to directly relate the changes in flow
regime to responses of target species, is recommended when more accurate environmental flows need to be
defined. PHABSIM is one such method and is outlined below. Importantly, in the WFD context, the CAMS
approach does, however, incorporate a ‘ground-truth’ review that considers whether the current condition of the
ecology is consistent with that expected from a comparison of actual and allowable abstraction.
Proposed Methods and Standards under the WFD
In 2004, the UK Technical Advisory Group on the Water Framework Directive (UKTAG) initiated a review
designed to lead to standards that would support Good Ecological Status under the WFD. The review covered
rivers, lakes, estuaries and coastal waters and both water quality and quantity standards and a framework to
support decisions about the morphology of water bodies (UKTAG, 2006). Part of the objective is to develop
standards which are readily assessed (e.g. relating to chemistry and flow) to support achievement of the
biological objectives. This process will be a continuing one as experience and evidence develop, and a review is
envisaged by 2012. The review built upon or augmented existing methods and standards where possible. Many
of these will eventually be subsumed within the WFD framework. This UKTAG work has been supported by close
working with other EU member states (‘intercalibration’).
Surface waters have been grouped of the basis on natural characteristics which are likely to affect their typical
ecological communities (altitude, location, geology and size). Environment standards will be type-specific where
appropriate.
Ecological status
The Water Framework Directive has as its default objectives:
• prevent deterioration of the status of all surface water and groundwater bodies;
• protect, enhance and restore all bodies of surface water and groundwater with the aim of achieving Good
Status for surface water and groundwater by 2015.
The WFD Annex V, Section 1.2 lists general definitions for rivers, lakes, transitional waters and coastal waters for
Good status/potential as follows:
“General Conditions”: Temperature, oxygen balance, pH , acid neutralising capacity, transparency and salinity, do
not reach levels outside the range established so as to ensure the functioning of the type specific ecosystem and
the achievement of the values specified above for the biological quality elements.
“Nutrient concentrations”: Do not exceed the levels established so as to ensure the functioning of the ecosystem
and the achievement of the values specified above for the biological quality elements.
Chemical standards
Chemical standards have been reviewed in the light of ecological information on their impact, where available,
and scientific expert judgement where not (UKTAG, 2006). The data were derived by identifying, on sites with
th
Good status, the 90 percentile value of the parameter. Some are as means, others as percentiles.
SID 5 (Rev. 3/06)
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The river typology classifies by altitude (encompassing gradient) and alkalinity (Table 3). The complexity of the
classification varies with the parameter. The critical chemical standards identified for rivers are similar to those
monitored under the GQA: Dissolved Oxygen, BOD, Ammonia, pH and Phosphorus (orthophosphate) – see
th
th
Tables 4-6. The standard for pH (5 and 95 percentile) should be >=6 to <= 9 for high or good ecological status.
Table 3. River Typology for oxygen status and ammonia (UKTAG 2006).
Site Altitude
Under 80
metres
Over 80
metres
-1
Alkalinity (as mg L CaCO3)
< 10
10 to 50
Type 1
Type 2
50 to 100
100 to 200
Type 3
Type 5
Type 4
Type 6
> 200
Type 7
Table 4. Standards for oxygen status and ammonia in rivers according to ecological status (good or high).
Type
Upland and low alkalinity
(Types 1,2,4,6)
Lowland and high alkalinity
(Types 3,5,7)
DO
(% saturation).
High
Good
80
75
70
60
BOD
-1
th
(mg L , 90 percentile)
High
Good
3
4
4
Total ammonia
-1
th
(mg L , 90 percentile)
High
Good
0.2
0.3
5
0.3
0.6
The typology for nutrients is slightly different from that for oxygen status and ammonia. The UKTAG consider that
evidence in relation to Type 3n (lowland calcareous rivers) may not be reliable, and that rivers classed as good
status may actually be impacted. Standards for Type 3n are therefore the same as for Type 4n.
Table 5. River Typology for nutrients (nitrate, P) in rivers (UKTAG 2006).
Site Altitude
Under 80 metres
Over 80 metres
-1
Annual mean alkalinity (as mg L CaCO3)
< 50
>50
Type 1n
Type 3n
Type 2n
Type 4n
-1
Table 6. Standards for phosphorus in rivers (UKTAG 2006) (soluble reactive P, ug L , annual mean).
Type
1n
2n
3n, 4n
High
30
20
50
Good
50
40
120
Standards for P were set in relation to diatoms. The revised standards cause a slight increase in failures
associated with ammonia, and a slight decrease in failures related to BOD, dissolved oxygen and P. Nitrates
standards are currently set by the Nitrates Directive (Defra, 2007) and have not been changed for rivers.
Water quantity standards
The Water Framework Directive requires hydromorphology, including flow and water level, to be protected for its
own sake at sites of High Status. Elsewhere, the criterion is determined in relation to ecological objectives.
Criteria will be assessed separately for Heavily Modified Water Bodies (e.g. hydropower schemes), where the
objective is to achieve good ecological potential but it is recognised that there are limits to what can be achieved
at reasonable cost.
An expert consensus approach then defined the proposed regulatory standards and thresholds for flow alteration
that would ensure Good Ecological Status (GES) in water bodies, for each river water body type as defined in the
new typology. Since all parts of the flow regime have been recognised as having some ecological importance,
there has been a move away from low flow measures towards environmental flows in relation to the natural flow
characteristics, and various attempts to define environmental river flow requirements have been reviewed by
Acreman & Dunbar (2004).
The river typology developed for flow conditions (Table 7) differs from that currently used under the Environment
Agency’s Resource Assessment and Management Framework (RAM) as a component of the CAMS process.
However the standards developed are broadly in line with current criteria. Much will still rest on interpretation in
the light of local conditions and competing demands on the water resource.
SID 5 (Rev. 3/06)
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Table 7. Typology for water resources standards for rivers (UKTAG 2006).
Type
A
B
C
D
Gradient
(m per km)
Altitude (m)
Description
A1
0.8+/- 0.4
36 +/- 25
A2*
Slightly
steeper
1.7 +/- 0.8
low altitude
55 +/38
Predominantly clay.
South East England,
East Anglia and
Cheshire plain
Chalk catchments;
predominantly gravel
beds; base-rich
Hard limestone and
sandstone; lowmedium altitude; lowmedium slope;
typically mesotrophic
with gravel-boulder or
pebble-cobble) bed
B1
4.1 +/-9.9
93 +/- 69
B2
Shallower
than B1
2.7 +/- 10.7
71 +/- 58
Non-calcareous
shales, hard limestone
and sandstone;
medium altitude;
medium slope;
oligomeso-trophic with
pebble, cobble and/or
boulder bed
C1
5.4 +/- 6.5
101 +/-84
C2
Steeper than
C1
7.3 +/- 10.8
130 +/- 90
Granites and other
hard rocks; low and
high altitudes; gentle
to steep slopes; ultraoligo
Oligo-trophic, with
cobble, boulder,
bedrock, and/or pebble
bed
D1
Medium
gradient
11.3+/- 15.6
low altitude
93+/- 92
D2
High gradient
25.5 +/- 33
High
Altitude 178
± 131
Clay and/or Chalk;
low altitude; low slope
Eutrophic; silt-gravel
bed
Hard sandstone,
Calcareous shales;
Predominantly South
and South West
England and South
West Wales
Predominantly North
West and East Scotland
Hard limestone; more
silt and sand than C2;
mesotrophic
Non-calcareous shales;
pebblebedrock;
Oligomeso-trophic
Oligotrophic, substrate
finer than D2 (including
silt and sand); more
slow flow areas than D2
Stream order 1 and 2
bed rock and boulder;
ultra-oligo trophic
torrential
* To reflect the different sensitivities of the headwaters of chalk streams to the downstream
reaches, type A2 was split into two – A2 (headwaters) and A2 (downstream)
These river types are defined by the physical characteristics of catchments that control the magnitude of average
and low flows. In order to define the river types for England and Wales for this project, the physical
characteristics can be derived from summary statistics held in the MAGPIE DSS database. This typology,
presented in Figure 1, provided the basis of our investigations of the impact of river low flows presented later in
this report.
Figure 1. Rivers in England and Wales classified using the UKTAG Typology.
SID 5 (Rev. 3/06)
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The standards for high flow status relate directly to those set by the WFD. Thus for high ecological status, at low
flows occurring 5% of the time over a 10-year period, the permitted abstraction is set as a maximum of 5% of
natural flow, and even at normal to high flows no more than 10% may be abstracted. However, for good status or
below the standards are set in terms of ecological criteria.
The standards for good status are more complex. Class A2 is further divided into upstream and downstream
classes. The flow regime is partitioned into percentiles, and the permitted percentage perturbation of flow (by
assumption, normally a flow reduction) is greater at average to high flows, than at low flows. The standards are
generally set to be tighter during summer than winter. They are designed in the light of the need to protect
macrophytes in spring and early summer, and macro-invertebrates and fish in late summer to early autumn.
‘Hands off’ flows are expected to continue to be operated by the Environment Agency as required, and the rules
may be over-ridden during special conditions such as drought orders. Where flows are enhanced, for example by
sewage discharge or pumped transfers between rivers, the resulting flow prior to abstraction is considered the
‘natural’ flow.
It will be seen that during low flow periods in summer, flow reductions envisaged in lowland rivers are typically 7.5
to 15% of natural flow (Table 8). However, these restrictions are not applied on a daily basis – it would be
possible in principle to take a large amount of water, exceeding these limits, on some days and less or none on
others. Additional restrictions may therefore be needed to protect sensitive ecosystems at critical times.
Standards for Moderate and Poor status have not been set, but it is envisaged that they may involve an additional
abstraction of about 15% of natural flow.
Table 8. Water resources standards for rivers and Good Status (UKTAG, 2006).
Types
A1
A2
(downstream),
B1, B2, C1, D1
A2 (headwaters),
C2, D2
Salmonid
spawning and
nursery areas
(not Chalk rivers)
Season
Flow > QN60
Flow >
Flow >
QN70
QN95
(% change allowed from the natural flow)
Flow <
QN95
April –Oct
30
25
20
15
Nov –March
35
30
25
20
April –Oct
25
20
15
10
Nov –March
30
25
20
15
April –Oct
20
15
10
7.5
Nov –March
25
20
15
10
April –Oct
25
20
15
10
Nov –March
20
15
flow >
QN80
10
Flow <
QN80
7.5
Detailed approaches to setting flow regimes
The standards under development by UKTAG provide a framework, but more detailed assessment will be
required for many rivers. Possible more detailed approaches include:
• Dundee Hydrological Regime Assessment Method (DHRAM).
• Physical Habitat Simulation (PHABSIM)
• Lotic Invertebrate Index for Flow Evaluation (LIFE)
More detail on these is presented in Annexe I.
Conclusions
The introduction of the WFD has placed more of a focus on managing water for maintaining/improving ecological
condition of the water. UKTAG have been developing standards that can be used to measure ecological impact
and these standards will continue to develop and be used in the implementation of the WFD.
For water quality, it is perhaps not surprisingly that the list of chemical and nutrient parameters is similar to that
monitored under the GQA:
• Chemical: dissolved oxygen, BOD, pH, ammonia
• Nutrient: phosphorus
SID 5 (Rev. 3/06)
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Other EU Directives (to be subsumed into the WFD) also provide various standards, most notably the:
• Bathing Water Directive – FIOs
• Nitrates Directive – nitrate
• Bathing Waters Directive - as well as DO, BOD, pH and ammonia, includes zinc and chlorine
• Shellfish Waters Directive – pH, temperature, colour, suspended solids, salinity, DO, hydrocarbons,
metals, organohalogens, FIOs and saxitoxin
For water quantity, UKTAG have developed a framework for permitted flow reductions. For rivers of high
ecological status the standards are fairly inflexible. For good status, the framework is more complex, but
decisions are based on river typology, season and flow rate. Basically, during low flow periods in summer, flow
reductions envisaged in lowland rivers are typically 7.5 to 15% of natural flow. However, these restrictions are not
applied on a daily basis – it would be possible in principle to take a large amount of water, exceeding these limits,
on some days and less or none on others. Additional restrictions may therefore be needed to protect sensitive
ecosystems at critical times. Although this framework provides useful guidance, it may be necessary to
undertake a more detailed analysis at the local level.
Thus, in summary, although much of the emphasis on water standards has moved to ecological drivers, most of
the parameters required in practice have already been monitored under the GQA. The WFD has driven the
development of a more stringent framework for linking ecology both to chemical/nutrient parameters and
hydromorphology. This provides a more robust framework for interpretation.
Consequently, our report has focused on:
• Understanding the links between flow and changes in chemical/nutrient quality
• The potential impacts of agricultural abstraction on flow, particularly in the summer
3.3.
Agricultural water demand (Objective 2)
The aim was to summarise and map data on the agricultural demand for water, and to quantify the agricultural
impact on water availability, with special attention to seasonal and inter-annual variation.
Agricultural water demand
Agriculture places a significant demand on regional water resources, for the irrigation of crops, washing and
watering of livestock, and the preparation of produce. The annual average volume of water used for irrigation in
6
3
England is c. 125×10 m (Weatherhead & Danert, 2002) and for the drinking and wash requirements of livestock
6
3
is c. 156×10 m (King et al., 2006).
The majority of abstractions from surface and ground waters in England and Wales are for the public water supply
(45%) and electricity supply (30%), with agriculture accounting for only c. 1% of total actual abstractions (EA,
2005). The dominant source of irrigation water is abstraction, with surface waters accounting for 58%, and
groundwater accounting for 36% of irrigation water in 2001 (Weatherhead & Danert, 2002). Water for drinking and
wash requirements of livestock are normally obtained from the mains supply. In the main irrigating regions of
-1
Anglia and the Midlands (EA regions), approximately 130 ML day are abstracted from surface waters, and 100
-1
ML day from groundwater sources (Defra, 2005). The usage of water for irrigation is obviously concentrated in
the drier parts of the country and peaks during the summer months, and so demand is usually greatest at those
times and in those regions where water availability is low. The overall impact of agricultural water demand may
therefore be significantly greater than the contribution to the national abstraction budget implies.
Crop irrigation
Irrigation water is assumed, in water resource calculations, to be entirely consumed. In contrast, water taken for
many other purposes (washing, household uses) is largely returned to surface waters, via water recovery/sewage
treatment works.
The irrigation demand occurs almost entirely during summer (apart from a small usage for frost protection of fruit).
It therefore places pressure on water supplies when rivers are at their lowest. The relative importance of irrigation
as a consumer of water is increased by this. Temporal elasticity can be improved by on-farm water storage.
Although 40% of root and fruit farmers who use irrigation have reservoirs, 80% of those using water abstract only
during summer, indicating that most of the storage capacity is insufficient to cover the whole summer; 11%
abstract only during winter, and the remainder abstract throughout the year. Weatherhead et al. (1997) reported
an increase in the total number of on-farm reservoirs and a doubling in the total storage capacity in the 5 years
from 1990-95. However, 90% of the water used in 1995 still came from summer abstraction. In the 2005 survey,
42% of holdings now have reservoir storage capacity, and 30% of the water used came from stored sources (50%
of their capacity).
SID 5 (Rev. 3/06)
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Irrigation demand obviously varies with the weather. It is both highly seasonal (concentrated in the summer) and
more variable from year to year than other agricultural water uses. The financial justification for installing an
irrigation system rests in the drier years when yields of un-irrigated crops are low, and prices high. Economics
dictate that sufficient equipment is installed to deal with these dry periods. During such periods, applications can
exceed 25 mm per week on each irrigated field and the equipment will be in daily use, moving round the irrigated
area on the farm in a 3-5 day cycle. During such periods, any interruption in water supply risks loss of yield on
part of the farm. The reported actual abstraction data show that average abstraction for irrigation is only 39% of
the total licensed volume (Defra, 2000). The license needs to be issued to cover the design driest year.
Of the irrigated field crops, more than half of abstracted water is used for potatoes, and the next biggest use of
irrigation is for field vegetables (Weatherhead & Danert, 2002). These crops are both high value, and yield and
quality are highly responsive to irrigation water (Bailey, 1990). At present, irrigation installation is most commonly
economically based on these crops, and other crops are irrigated opportunistically in years and at times when the
potato and vegetable crops on the farm do not require irrigation – for example, early and late in the season.
The national irrigation area is increasing slowly, at about 0.6 to 0.8% per annum based on current survey trends.
The volume of water used is predicted to increase more steeply, with greater emphasis on the most profitable
crops and greater average volumes applied. The national predicted growth rate in actual volumetric demand for a
‘design’ dry year was estimated to be about 1.5% from 2001 to 2021 (Weatherhead et al., 1997). In addition to
this trend, which was calculated after correction for weather patterns, climate change must be taken into account.
Warmer and drier summers will tend to increase irrigation demand on those crops currently irrigated.
Livestock requirements
The water requirements for livestock drinking water and washing were reviewed by Thompson et al. (2006). The
3
total estimated annual water use for livestock is 156 million m . The cattle sector is the major consumer, with a
3
3
3
total requirement of c. 82 million m , followed by sheep, at 17 million m , poultry at 12 million m and pigs at c. 8
3
million m for England and Wales. The predominant use of water is for drinking, and usage is concentrated in, but
not confined to, the wetter parts of the country where most cattle are raised. Expressed as a percentage of total
water, drinking water requirements ranged from 79% for dairy cattle, 87-99% for different categories of pigs,
>99% for sheep and 96-99% for poultry, respectively. The main source of water for livestock is mains water,
although 21% of water used for dairy stock (7% of total used for livestock) is from other sources (King et al.,
2006). The contribution of livestock water demand is therefore only 8% of total direct agricultural abstractions
from surface waters nationally.
National Context
The reported quantity of water distributed via the water companies of England and Wales averaged 15,300 ML
-1
6
3
day during 2001-2006, or about 5600 ×10 m per year (OFWAT, 2006). Agriculture accounted for about 2.6%
of this distributed water, mainly for livestock use.
Direct abstractions for irrigation and other agricultural uses accounted for only c. 1% of total licensed abstraction
volume, and 0.6% of total actual abstraction in 2004. They represented a volume equivalent to 2% of the
abstraction for public water supply. However, irrigation water places greater pressure on water supplies than
indicated by the annual volumes used because irrigation requirement is often maximal at periods of minimal
supply, i.e. is temporally inelastic; and is normally abstracted directly from river or groundwater, making it spatially
inflexible.
Irrigation demand is at present localised in space and time. During hot dry weather, irrigation demand may
exceed 25 mm per week on irrigated land. During summer, river flows are commonly as low as 10% to 20% of
the annual average. For a river with an annual runoff of 200 mm (typical of much of arable England), a flow of
10% of the mean is equivalent to 0.4 mm per week. It can readily be seen that irrigation of even 1% of the
catchment land area would, at periods of low flow, use more than half the flow – well in excess of allowable
abstraction. In contrast, public water supplies are drawn from multiple sources, and have systems of storage and
transfer to help maintain supplies during drought conditions.
Mapping Agricultural Water Demand
The general approach to mapping agricultural water demand was to integrate existing coefficients of water use
per unit crop area and livestock place (Thompson et al., 2006; Weatherhead & Danert, 2002) with agricultural
census data for the year 2000 held in MAGPIE (a Geographic Information System; Lord & Anthony, 2000). Water
2
demand was calculated at a spatial resolution of 1 by 1 km and summarised for each of the Water Framework
Directive river catchments defined by the Environment Agency. Irrigation water demand was flat profiled during
the summer months (June to August) based on actual abstraction records (King et al., 2006), whilst water
demand for livestock requirements was spread evenly throughout the year. It is likely that a flat profile of water
demand would be observed for the pig and poultry sector, with production dominated by mostly year-round
SID 5 (Rev. 3/06)
Page 13 of 29
housing systems, but for sheep and cattle peak demands for drinking water are expected during the summer
months.
Irrigation Demand Coefficients - Crop water use coefficients by crop category and region were calculated using
the irrigation survey and census data. The Irrigation Survey 2001 (Weatherhead & Danert, 2002) provides the
irrigation usage for field crops (i.e. not protected crops and nursery crops). The data collected is the area of
irrigated crops and amount used for various crop categories. Thereby, an average volume of water used per unit
area of irrigated crop can be calculated. The volume of water used per unit area of all cropping was then
estimated by combining this data with the total crop areas reported by the agricultural census (Data shown in
Annexe I: Table 4.2). As irrigation water demand is dependent on summer weather, the survey data always also
reflect the weather conditions of that particular year; for example in 2001 irrigation water demand was
comparatively small. Using a methodology developed by Weatherhead et al. (1994), Downing et al. (2003)
estimated the potential irrigation water use if 2001 had been a ‘design dry year’, defined as a dry year with an
irrigation need exceeded in 1 out of 5 years. This information was used to calculate crop water use coefficients for
the irrigation demand in a design dry year (Data shown in Annexe I: Table 4.3).
Livestock requirement coefficient - For livestock consumption, estimates of the typical water use per head of
livestock were taken from the recent Defra report “Water Use in Agriculture: Establishing a baseline” (King et al.,
2006). This report used data available from recent studies and surveys, as well as guidelines on “typical stock
requirements”, which are available as part of “Best Practice”, published by the Environment Agency. These data
were summarised to give coefficients of drinking and wash water requirement per head of livestock according to
the Defra livestock census categories (Data shown in Annexe I: Table 4.5). Some animal categories had to be
considered together as not all categories identified within the Defra census fit neatly within the groups readily
recognised within commercial production for which data on water requirements had been derived. Thus, beef
store cattle and growers as dairy replacements were considered together. Similarly maiden gilts and “barren sows
fattened for slaughter” are growing pigs and were considered together with finishing pigs in terms of drinking
water, and with dry sows for wash water since they are likely to be relatively few in number and kept on straw
rather than a slurry system.
Figures 2-4 map the total annual water use of livestock and irrigation, expressed as mm water over the whole
contributing catchment. The irrigation demand is based on records of actual water use in 2001, whilst the
livestock water use is an annual average derived from usage coefficients. Water demand is averaged over the
total contributing catchment area (from the mouth of the catchment to the headwater), but mapped against the
most downstream subcatchment. The demand that is shown at the mouth of a catchment is actually the averaged
demand over the total contributing catchment area. This contributing area may be as great as 1000 km² for major
rivers. This approach is used for all maps in this report.
It is unsurprising that the highest values for agricultural water demand are located within East Anglia, where water
is mainly used for crop irrigation (Fig. 3). The maximum annual demand is equivalent to 5-10% of the annual
average runoff from the river catchments, and is expected to contribute significantly to the demand on available
resources in this region. The demand for livestock is greatest in the intensive grassland areas of Wales and the
west of England, but the overall demand is generally less than 1% of the annual average catchment runoff (Fig.
2). Overall water demand for irrigation is increased by c. 40% in a design dry year (Fig. 4).
Figure 2. Map of calculated average annual agricultural
water use for livestock, expressed as a depth of water
(mm) over the total river catchment area.
SID 5 (Rev. 3/06)
Figure 3. Map of calculated average annual
agricultural water use for irrigation in 2001, expressed
as a depth of water (mm) over the total river catchment
area.
Page 14 of 29
Figure 4. Map of calculated average annual agricultural water
use for irrigation in a design ‘dry year’, expressed as a depth of
water (mm) over the total river catchment area.
Conclusions
The aim was to summarise and map data on the agricultural demand for water, and to quantify the agricultural
impact on water availability, with special attention to seasonal and inter-annual variation.
The reported total water usage by agriculture (for livestock and for irrigation) is quite small – approximately 1% of
total abstractions, with the following breakdown (on average):
Irrigation of crops
Watering/washing of livestock
Glasshouse/nursery stock
3
125 million m
3
156 million m
3
<20 million m
However, when considering the effects of agricultural water demand on water resources, there are several factors
to consider:
•
•
•
Seasonality – whereas, the watering requirements of livestock production will be reasonably uniform through
the year, irrigation requirements are highly seasonal with (obviously) most applied in the summer. This is at a
period when river flows will also be at their lowest, thus maximising any impacts of water abstraction. There
is no scope for shifting time of applications. Irrigation must be applied at critical growth stages and soil
moisture deficits, which generally fall in the May-August period. Thus, although livestock requirements are
greater in total, the highly seasonal nature of irrigation means that the potential impact is much greater.
Spatial variation – by combining agricultural statistics with livestock and crop irrigation coefficients, we have
been able to identify areas of the country with the greatest water demand. Not surprisingly, this is in the east
for irrigation and the west for livestock production. This spatial distribution, like the temporal, compounds the
potential impacts of irrigation abstraction. The livestock water requirements generally occur in the wetter
regions and so only constitute a water requirement of about 1% of a catchment’s total water run-off. In
contrast, irrigation requirements in the east can require 5-10% of a catchment’s total run-off (most of it in
summer when flows are at their lowest).
Inter-annual effects – Environment Agency data show that the livestock water requirements are generally
similar between years, whereas irrigation requirements can vary considerably, depending on summer
weather. Annual demand can vary by a factor of two; and, of course, demand is much greater in a dry year
when river flows will also be low. Our spatial analysis showed that irrigation requirements in a design dry
year increased irrigation demand by 40%, increasing the pressure on water resources in the east, but also in
the main irrigation areas of the midlands.
Thus, in summary, the irrigation requirements for high value crops (particularly in the drier east) has the potential
to greatly impact on the water resources of these catchments and, in particular, to impact on low flows.
Further analysis to quantify these effects was undertaken when considering the impacts of climate change. The
model constructed for this purpose also provided baseline (current day) calculations based on a long-term
weather dataset. The resulting modelled baseline flows and ‘available water’ for surface waters across England
and Wales were compared with agricultural demand. Available water was defined as the water that was available
for abstraction after taking account of permitted levels of abstraction from surface water for complying with good
SID 5 (Rev. 3/06)
Page 15 of 29
ecological status as defined by UKTAG (2006). The quantity of water currently abstracted for other purposes such
as public water supply was not taken into account. That is, all users would be in competition for this ‘available
water’.
Simulations based on the long-term weather dataset clearly demonstrated the spatial variability across England
and Wales with flows of 60 mm in East Anglia ranging up to 3000 mm in parts of Wales and north east England –
with variation (unsurprisingly) matching rainfall distribution. In terms of available water, the average across
England and Wales was 100 mm for the year, again with large variability (<30 mm in 20% of East Anglia).
However, it is the availability of summer flow (June- August) that is of great importance when considering
irrigation requirements, as described above. The average available water was 7 mm (range 1-100 mm).
The simulations confirmed also that, based on annual totals of available water, there is no conflict between
available water and agricultural demand. However, for the summer months from June to August, there are a
number of catchments, where the agricultural demand is greater than the summer available water. These
catchments are mainly located in East Anglia, where the summer demand for irrigation exceeds the summer
available water in c. 30% of the area. This area is extended in a year with a dry summer (defined as a year with a
summer flow which is exceeded in 80% of the years), when the irrigation demand exceeds the available water in
c. 60% of East Anglia. In the areas where the demand is in excess of the available water, the demand averages
260% of the available water in an average year and 440% in a dry year.
These conclusions are necessarily preliminary. Two assumptions which would lead to an over-estimation of the
problem are:
•
•
It was assumed that all of the water was abstracted from surface waters, whereas it is only 60% that comes
from this source.
It was assumed that all water was abstracted in the summer months for irrigation, whereas about 10% is
supplied from on-farm reservoirs (and this proportion is increasing) that are filled during winter.
There was some indication from the test catchments that the model may slightly underestimate flow. Conversely,
the monthly time step of the calculation is equivalent to assuming some degree of storage and flexibility in timing
of abstraction, which is not currently the case on all farms. Therefore, there will be years when total summer flow
is sufficient to meet demand, despite inadequate flow having occurred during part of the summer. In addition,
conflicts between summer flow and demand are likely to become more acute, due to a combination of climate
change; and tightening of ecological standards for river flow and water quality.
Despite these caveats, the approach highlights the challenges in some parts of the country in supplying sufficient
water to meet agricultural requirements at key times of the year without disrupting flow regimes with potential
impacts on the ecological status of some waters.
It should also be considered that there are other abstraction pressures on waters and agriculture is a relatively
small component. Abstraction for public water supply and industry is far greater in volume than for agriculture;
but in the long-term their relative impact is moderated by the fact that most of the water is recycled and returned
to the system.
3.4.
Impacts of reduced water availability (Objective 3)
The aim was to quantify the impact of reduced water availability (due to agriculture) on chemical and ecological
status, under present land use and climate.
Ground and surface water abstractions reduce river flows. Reduced flow is associated with reduced dilution of
point source inputs of pollutants (mainly sewage, but including industrial and urban discharges). The key
indicators of this form of pollution are increased concentrations of P and BOD at low flows. A given volume of
abstraction will have a greater proportional impact at summer low flows. Irrigation abstractions from rivers will be
concentrated within the summer period, as described earlier. Irrigation abstractions from groundwater will also be
predominantly during summer, but will have a more general impact via reduction in the groundwater levels, which
will affect flows throughout the year. Water for other agricultural uses including livestock is required all year round,
and is largely taken from the mains. It is, therefore, a more general load on the total water supply of an area, and
may not be attributable directly to a specific reach or catchment.
The objective of this analysis was to present empirical evidence of the relationship between river low flows as
affected by abstraction and water quality. The direct impact of agricultural abstractions on river water quality by
the reduced dilution of pollutant loadings was expected to be difficult to detect empirically as abstractions are
limited to c. 20% of the natural flow. The natural variability in water quality sample results due to variations in
timing with respect to flow conditions and the size of the pollutant load was expected to be greater than the
magnitude of the dilution effect. We therefore conducted an analysis of the general impact of changes in river flow
per se on water quality, from which we could extrapolate the impact of agricultural abstractions. The analysis
SID 5 (Rev. 3/06)
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made use of data from the Environment Agency General Quality Assessment monitoring network. Analyses were
made of regional and annual variations in water quality data and river flow based on data summarised for
chemical and phosphate status reports. A more detailed analysis of daily variations in quality in relation to sitespecific flow measurements was possible for the smaller number of sites in the Harmonised Monitoring Scheme,
which represents generally larger rivers discharging to the sea, with a relatively high point source contribution.
Regional relationships between annual flow and water quality
Strong negative relationships (i.e. poorer quality at lower flows) were established between river flow and
2
2
chemistry classification for the East of England (r 80%) and London (r 48%) regions and a weak negative
2
relationship for the South East (r 25%). These relationships existed for both annual total flows and the summer
flows.
These relationships were observed for regions with relatively low river flows and known high effluent discharges
due to a concentration of people and industry. In wetter regions, the relationship was more variable with no
2
2
relationship in the South West region (r 7%), and a strong negative relationship in the North West (r 44%) that
was possibly due to improvements in effluent treatment rather than variations in flow. In Wales, there was an
2
unexpected positive relationship (r 36%), i.e. poorer quality at higher flows. This might be associated with the
increased importance of diffuse agricultural pollution during high runoff years in this more rural region.
These analyses confirmed the general relationship between flow quantity and water quality. The results are
consistent with the concept that, in areas where water quality is dominated by sewage effluent inputs, dilution is
an important determinant of quality, and low flows are associated with poorer quality.
Seasonality of water quantity and quality
River monitoring sites were classified by region, and average values of the determinants of interest and
normalised flow were calculated for each calendar month. Regional and national averages of flow and water
chemistry were calculated from site mean data, in order to avoid giving undue weighting to sites with more
measurements within the periods of interest.
Lowest flows occurred on average during July and August, These are the prime months for irrigation. Lowest
flows were later, during August /September, in Southern Region and Thames. Both these regions have a high
proportion of groundwater-fed rivers. Groundwater contributions will maintain flows in early summer, declining
during later summer. Lowest mean monthly flows were about 40% of average overall, with relatively little
variation between regions despite the wide range of climate and other factors.
On average, greatest concentrations of orthophosphate (OP) occur in July to September (Fig. 5). These are the
months of lowest flow. The concentrations during the summer were on average twice the smallest
concentrations, which occurred during January. This broad pattern, that OP concentrations are greatest when
flows are smallest, is consistent across all regions. In Southern and Thames region, the maximum concentrations
occur somewhat later (September) compared to other regions, which is consistent with the later minimum in
flows. These patterns are characteristic of waters where the phosphorus concentrations are dominated by
sewage inputs (Jarvie et al., 2006).
Mean OP concentrations are greatest in the Midlands, Anglian and Thames regions, which are areas of relatively
low flow and high population density. They are least in the South West and Wales. However, even in these
regions, the HMS data show a tendency for increased concentrations of OP during summer. Many of the HMS
were deliberately sited downstream of sewage works, and the majority are on major rivers. The incidence of
sewage contamination is therefore relatively high.
1
1.5
0.75
1
0.5
0.5
OP, mg/l P
Normalised flow
2
Normalised
flow
OP, mg/l P
0.25
0
0
0
3
6
9
12
Month
Figure 5. Seasonality of flow and OP concentration: England and Wales HMS sites.
SID 5 (Rev. 3/06)
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5.2.2
Variation between years
The analysis was repeated to examine the year-to-year variation in flows and concentrations overall. Variation in
(normalised) flow during July to August was significantly correlated with July-August mean orthophosphate
2
concentrations (r = 0.37), as shown in Figure 6.
Orthophosphate
1.40
R2 = 0.37
1.20
1.00
0.80
0.60
0.40
0.20
0.00
0.00
0.20
0.40
0.60
0.80
1.00
Me a n Norma lise d Flow
Figure 6. Relationship between mean July-August OP concentrations in different
years and July-August normalised mean daily flow.
In addition to OP, concentrations of the following during July and August were also negatively correlated with
July-August mean daily flow:
2
• chloride (r = 0.39)
2
• conductivity (r = 0.50) and
2
• boron (r = 0.21).
All of these relationships indicate dilution behaviour typical of pollutants derived from sewage. For other sewagerelated pollutants, the relationships were less obvious, but there were trends to greater values at low flow and
during summer for both nitrite and copper. BOD and oxygen saturation behaved inconsistently in relation to flow.
Detailed analysis of data for individual sites indicated a greater risk of very high values at low flows, but the range
of values was also wider so that mean concentrations did not behave consistently. The variable patterns for BOD
may also reflect the fact that it is also contributed by diffuse sources especially at high flows. It should perhaps
be noted that summers with low flow tended to have greater temperatures also.
In contrast to OP and other sewage-related pollutants, concentrations of pollutants derived mainly from diffuse
sources did not increase during summer, and were not greater in years of low summer flows. In general, these
pollutants showed reduced concentrations during summer and at low flows:
• suspended sediment and turbidity;
• nitrate
Predictive relationships between OP and flow
In order to obtain a generalised predictive relationship between OP concentrations and flow during the period
when flows are most likely to be low, all HMS sample sites with values for both OP and flow during June to
September inclusive were combined. After initial exploratory analysis, detailed regressions were confined to sites
with more than 100 measurements for this summer period.
The analysis above indicates that OP concentrations should be proportional to the inverse of the flow, and
approximately proportional to the quantity of OP added by point sources, where these are important. It has been
shown earlier that sites with elevated OP concentrations generally are dominated by point sources, and show an
increase in concentration at low flow.
The theoretical analysis indicates that, where point sources dominate OP concentrations, concentrations will be
proportional to the inverse of flow rate. At moderate to low flows, where diffuse sources become relatively
insignificant, both the concentration at any given flow rate, and the rate of change of concentration with inverse of
normalised flow rate, will be linearly related to the OP contributed by point sources.
For this reason, both flows and OP concentrations were converted to normalised values, by expressing them
relative to the temporal mean flow or concentration for all data from that site. Normalised flows between 0.1 and
1 were converted to their inverse, and assigned a flow class in the range 1 to 10 at intervals of 1 unit. For each
SID 5 (Rev. 3/06)
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site, the regression of normalised OP on the inverse of the normalised flow was calculated. The gradient of this
regression was found to be linearly related to mean OP concentration, as would be expected from the theoretical
analysis.
For sites where the regression explained more than 25% of the variance in concentration, the relationship
between the coefficients of the regression and mean OP concentration was investigated further.
A relationship was derived by expressing all OP concentrations relative to the site temporal mean OP
concentration, and averaging by flow class:
Cr = (Mean OP) * ( 0.72 + 0.16 / Fr)
2
r = 0.95
Where:
-1
Measured total instantaneous OP concentration in the river = Cr mg L P
Measured total instantaneous flow in the river = Fr normalised flow units
This relationship did not hold for high flows (values of Fr greater than 1), since it predicts OP concentrations
somewhat greater than expected from diffuse sources at infinite flow. This is partly because the assumed
linearity ignores the dynamics of the contribution from diffuse sources. However, it allows us to predict the
relationships to be expected at low flows.
As a check on the above relationship, the relationship for the mean of all sites with more than 100 samples taken
during June – September was investigated. Samples were classified by flow class, to make comparison between
sites simpler. Sites where the correlation coefficient between flow and concentration was smaller than 0.5 were
omitted. For the remaining 81 sites, those with few measurements at flows less than 20% of mean flow were
classified as ‘groundwater fed’ (28 sites), and only data above 20% flow were used, since the few samples at low
flow were too variable to give meaningful trends. For other sites all data above 10% flow were used. There was
a consistent difference in behaviour between these two groups of sites, but further sub classification did not yield
further differentiation. The resulting relationships were:
Groundwater-dominated sites:
Cr
= (Mean OP) * (0.74 + 0.24/Fr)
All other sites:
Cr
= (Mean OP) * (0.89 + 0.12 / Fr)
Within each group, the coefficient of variation of normalised OP at a given normalised flow averaged 31%,
-1
compared with 145% for the OP concentrations expressed as measured (mg L P). In other words, classification
in this way reduced variability compared to the very wide range of actual OP concentrations. The regressions
obtained from these averaged data were very similar to those obtained by averaging the coefficients from
individual sites (Fig. 7):
2
Groundwater-dominated sites:
Cr
= (Mean OP) * (0.79 + 0.20/Fr)
r = 0.96
All other sites:
Cr
= (Mean OP) * (0.71 + 0.14 / Fr)
r = 0.98
2
OP / (Mean OP)
2.5
2.0
1.5
1.0
Groundwater-fed
0.5
Other
0.0
0
5
10
1/normalised flow
Figure 7. Relationship between inverse of normalised flow, and OP concentration
relative to mean OP, for June to September. Averaged data by flow class for sites with
> 100 data points.
The flow on the groundwater dominated sites was less variable, and extremely low flows (less than about 20% of
mean) were rare.
SID 5 (Rev. 3/06)
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Conclusions
The objective was to quantify the impact of reduced water availability (due to agriculture) on water quality under
present land use and climate. The underlying approach was to correlate quality measurements with river flow, to
inform the assessment of the likely effects of reduced flow due to water abstraction for agricultural use.
Reduction in flow due to abstraction of water will affect concentrations of pollutants either by reducing the quantity
of water available for dilution of a downstream pollution source; or by changing in-river processes. Diffuse water
pollution occurs mainly in the winter (when flows are at their highest). Point source pollution occurs all year, and
at specific locations. We could therefore hypothesise that effects of water abstraction due to dilution effects will
be greatest in the summer, and that effects will mainly be restricted to water quality parameters associated with
point source inputs. By analysing GQA and HMS data, we were able to demonstrate:
•
The importance of point sources – the inverse relationship between flow and water quality parameters (i.e.
reduced flow = increased concentration) was demonstrable for pollutants associated with sewage inputs (e.g.
orthophosphate, chloride, boron). Concentrations of pollutants derived mainly from diffuse sources (e.g.
nitrate, sediment) did not increase during summer, and were not greater in years of low summer flow. In
general, these pollutants showed decreased concentrations during these periods.
•
Regional effects – the inverse relationship between flow and water quality parameters was stronger in regions
with predominantly low rainfall and high populations (e.g. London, South East and East) and poorer in wetter
areas of low population (e.g. South West, Wales). This again supports the assertion that effects are
dominantly due to sewage related pollutants.
•
Groundwater-fed rivers – Flows tended to be at their lowest in July and August, apart from in Thames and
Southern regions, where it was August and September. These latter regions have a greater proportion of
groundwater-fed rivers where the groundwater sustains the surface water flows longer through the summer.
We were also able to demonstrate different quantitative relationships between OP concentrations and flow for
surface fed rivers compared with those that were predominantly groundwater-fed (see below).
To summarise, flows are least in the summer months (which coincides with the period of irrigation demand).
However, the effects of reduced flows (and, by inference, effects of any practices that abstract water at these
times) vary regionally and very with type of pollutant. Effects appear to be restricted to sewage pollutants (and,
again, by inference, any other pint pollutant source that feeds water systems during the summer months). Effects
are greatest in summer and in the driest parts of the country – which are also the areas and times with the
greatest irrigation demand.
We have been able to develop quantitative relationships which provide an indication of the likely effects of
reduced flow on water quality. A decrease in summer average river flow of 20% was estimated to result in an
increase in the average chemistry classification of between 0.10 and 0.20 grade points. As the scale of the
th
chemistry classification thresholds is approximately linear, this corresponds to an increase in the 90 percentile
-1
th
BOD concentrations of 0.2 to 0.4 mg L and a decrease in the 10 percentile dissolved oxygen concentration of 1
to 2% across all rivers in a region.
For orthophosphate, at average flow, concentration would be about 0.9 times the mean concentration; at half
average flow, about 1.08 times the mean; and at 0.1 times normalised flow, concentrations will be about 2.5 times
the mean. For surface water sites halving flow from 0.2 to 0.1 times mean flow, a change typical of summer low
flows, would cause an increase in OP concentration from about 1.4 to 2.1 times mean OP concentration, an
increase of about 50%.
The flow on the groundwater dominated sites was less variable, and extremely low flows (less than about 20% of
mean) were rare. On groundwater-dominated stream sites, halving of flow from 0.5 to 0.25 of average flow would
increase OP concentrations from about 1.2 times the mean to 1.6 times the mean OP value, an increase of about
one third.
Equivalent relationships would be expected for other pollutants derived from point sources. While clear
relationships were apparent for chloride and conductivity, data for other pollutants was more variable, and the
regression equations explained less of the variance. However, as indicated both by the analysis for OP above
and by theoretical analysis, abstraction of water during summer would increase the risk of excessively elevated
concentrations of these pollutants.
3.5.
Climate change effects (Objective 4)
The objective was to provide a model based quantification of the surface water available for abstraction within the
limits of good ecological status, and the proportion of this that is accounted for by current agricultural demand
SID 5 (Rev. 3/06)
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under present day and future climate scenarios. The general approach was to first develop a catchment scale
water balance and river routing model to simulate daily river flows. Permitted levels of abstraction for good
ecological status were then applied to the simulated river flows to calculate the maximum available water in the
summer months and across the year, and were compared to mapped agricultural demand.
Simulation of Natural river flow
This project was dependent on the simulation of daily river flows for each of the 7,800 river catchments defined by
the EA as part of the WFD catchment characterisation phase. In common with other studies, this required an
approach to model application without calibration of parameters for individual catchments. Model parameters
were derived from summary indices of present day catchment hydro-geological characteristics. The general
approach was to use a daily soil moisture balance model to estimate effective rainfall, which was then partitioned
into quick and slow response pathways and routed to give the catchment outflow on a daily basis. The
parameters of this model were determined from present day calibration procedures and then held constant under
changing rainfall and temperature time series for climate change scenarios.
The catchment routing model was based on versions of the ‘Probability Distributed Model’ (PDM; Moore, 1985)
and the ‘Identification of unit Hydrographs And Component flows from Rainfall, Evaporation and Streamflow’
model (IHACRES; Sefton & Boorman, 1997) in which daily time series of effective rainfall for a catchment unit are
partitioned into two parallel reservoirs representing quick and slow flow. Effective rainfall was simulated using a
modified form of the Daily Soil Moisture Accounting (DSMA) model described by Holmes et al. (2002). The
DSMA model was calibrated with PETG data produced by the MORECS model (Hough et al., 1996). Complete
details of the modelling approach are provided in Annexe I.
Model validation
Prior to application of the effective rainfall and river routing models to all catchments, they were applied to a
number of validation catchments for which spatially averaged rainfall, temperature and observed river flows were
available. Catchments classified as natural, i.e. the influence of abstractions or discharges is a maximum of 10%,
were selected, which resulted in a dataset of 23 catchments. The fractional extents of soils of each LAND-HOST
2
class within each catchment were derived by intersecting soils and land cover data on a regular 1 by 1 km grid
with the catchment boundaries. The land cover data were derived from the Land Cover Map of Great Britain
(Fuller et al., 2002) and the MAGPIE database (Lord & Anthony, 2000).
Model performance was assessed by evaluation of the bias in the annual average river flow and the NashSutcliffe criterion (Nash & Sutcliffe, 1970) which is sensitive to errors in the timing and magnitude of flow peaks.
Simulated and measured annual average river flows were well correlated but were frequently under-estimated
(average bias of 15%) although the original DSMA model had an average bias of only 2% (Fig. 8). Other model
formulations such as IHACRES introduce a non-linear rainfall runoff model to correct this bias on a catchment by
catchment basis. We did not correct the bias in this study as it was not clear whether the bias occurred in the
estimation of the PETG or critical RC values for the selected catchments, or whether the bias was simply a result
of a relatively short validation period.
2000
Simulated flow (mm)
1500
1000
500
0
0
500
1000
1500
2000
Observed flow (mm)
Figure 8. Comparison of modelled and observed annual average river flows for
selected river catchments using data for the period 1980-90.
Values of the Nash-Sutcliffe criterion less than zero indicate a model that is less efficient than simply using the
average observed flow as a predictor of the daily flow, whilst a value of one indicates a perfect model. The NashSutcliffe criterion for the daily flow simulations were generally in the range 0.30 to 0.91, with three outlier and very
poor simulations of -0.7,0.06 and 0.17 for the Dun (39028), Tillingbourne (39029) and Foston Beck (26003)
SID 5 (Rev. 3/06)
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catchments. The criterion for the monthly simulations relevant to this study are generally higher and, excluding
the three outliers, in the range of 0.53 to 0.95 indicating an overall good model fit to the validation data that is
comparable to criterion in the range 0.45 to 0.83 reported by Arnell & Reynard (1996) also for a climate change
impact study.
The model performed well for flashy and groundwater dominated catchments, and for catchments with various
levels of flow (more detail in Annexe I). The model was able to reproduce the year to year variation in observed
river flows for catchments with both high (e.g. 60006) and low annual rainfall (e.g. 25005). This gave us some
confidence that the model simulated the variation in annual AET correctly, in response to changes in available
water, so that the model could be expected to be capable of simulating the impacts of long-term changes in
rainfall as predicted for future climate.
Climate scenarios
Daily baseline and climate change scenarios on a 5 km grid across England and Wales for 2020s (2010-2039)
and 2050 (2040-2069) low and high emission scenarios were generated from the Met. Office 1961-90 monthly
data and the UKCIP02 monthly data by ADAS using the LARS-WG stochastic weather generator (Semenov &
Barrow, 1997). The standard procedure when employing climate change scenarios is to use the low and high
emission scenarios, as this was considered adequate to frame the extent of the problem.
Definition of ‘available water’ for abstraction
Standards for permitted levels of abstraction from surface water complying with good ecological status were
defined by UKTAG (2006) and were summarised earlier. Following these rules, permitted abstraction is between
7.5% and 35% of the daily flow and depends on the river type (for a map of the river types see Fig. 1), season,
and flow level. These rules were here applied to the simulated flow time series to estimate the surface water
which is available for abstraction following these standards. Note that the definition is total available water, and
takes no account of competing demands on this water, for example for public water supply.
Results
The simulated values of annual natural flow in England and Wales vary between 60 mm in the driest parts of East
Anglia to nearly 3000 mm in Wales and the Northeast of England (Fig. 9), with the spatial variation closely
following the variation of rainfall.
Under future climate projections, annual flows decrease on average over England and Wales by between 2% to
5% for the 2020s low to the 2050s high emission scenario (Fig. 10). These changes in annual amounts appear
relatively small and are because of the interactions between potential and actual evaporo-transpiration (PET and
AET) and drier summers/wetter winters. The higher temperatures in the 2020s and 2050s result in higher PET
but, due to reduced water availability especially in summer, AET remains nearly constant or decreases slightly.
1000
Base
LO2020
900
HI2020
800
LO2050
HI2050
700
mm
600
500
400
300
200
100
0
rain
Figure 9. Average annual simulated runoff for
1961-1990 baseline scenario for England and
Wales.
pet
aet
her
Figure 10. Simulated annual water balance for 1961-1990
baseline and climate scenarios for the 2020s and 2050s,
averaged over England and Wales.
The national average change masks greater regional spatial variation. For example, in the 2050s high emission
scenario a small increase in runoff is predicted of up to 15% in a narrow band on the East and South coast. More
generally there is a 5 to 10% reduction in runoff. The spatial variation in the change in runoff (Fig. 11) is broadly
similar to the change in rainfall and further differentiated by the spatial distribution of changes in AET. In the
wettest parts of the country – e.g. mid Wales and the Northeast - AET increases, but it decreases in the drier
parts of the country. This is caused by the decrease in annual precipitation and a more pronounced seasonality;
AET is more limited in the drier summers, but does not increase as much in wetter winters as PET levels in winter
SID 5 (Rev. 3/06)
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are generally low. The reduction in summer rainfall also results in a larger decrease in river flows during the
irrigation season from June to August with an average decrease for the 2050s high scenario over England and
Wales by around 27% (Fig. 12). The greatest percentage reductions in summer flow occur in catchments with
flashy river regimes. The smallest reductions occur in catchments dominated by baseflow, in which summer flows
are partially maintained by the increased winter rainfall, which enters the groundwater store and is released in the
summer months.
Figure 11. Percentage change in yearly runoff for the
2050s high emission scenario.
Figure 12. Percentage change in summer flow (Jun –
Aug) for the 2050s high emission scenario.
The range of changes in monthly flow is comparable to other studies (Arnell, 2004; Young & Reynard 2004;
Walsh & Kilsby 2007). However, there can be great differences between different hydrological models, (e.g. 20%
and more), in addition to uncertainties related to the climate projections (Prudhomme et al., 2005).
The average yearly available water in the 1961-1990 baseline scenario was just under 100 mm on average over
England and Wales but there was a large spatial variation and in c. 20% of East Anglia the yearly available water
is less than 30 mm. In relation to abstraction for irrigation, it is not only the average yearly available water but, in
particular, water available during the irrigation season between June and August and the variation between wet
and dry years which are of concern. Averaged over England and Wales, the summer available water, defined as
the water available between June to August inclusive, was around 7 mm (c. 7% of the yearly available water, Fig.
13) and varied between 1 to 100 mm.
100
8
average year
dry year
80
Summer available water (mm)
Yearly available water (mm)
7
60
40
20
6
5
4
3
2
1
0
0
Base LO2020 HI2020 LO2050 HI2050
Base
LO2020
HI2020
LO2050
HI2050
Figure 13. Yearly and summer (June - August) available water in an average year, and the yearly and summer
available water exceeded in 80% of the years, averaged over England and Wales for the 1961-1990 baseline
scenario and for the 2020s and 2050s low and high emission scenarios.
For the future scenarios, the average annual available water is only predicted to decrease by 1% for the 2020s
low emission scenario to 4% for the 2050s high emission scenario, suggesting that for the annual available water
the variation between years is more relevant than the long-term changes in future climate. Summer available
water in an average year averaged over England and Wales decreases by 8% to 28% for the 2020s low to the
2050s high emission scenario. The changes, however, show considerable spatial variation (Figs 14 and 15) in
England and Wales and the greatest percentage changes occur in the Western part of the country, where
agricultural water demands are currently relatively low. The reduction in summer available water in a dry year is 7
to 18%.
SID 5 (Rev. 3/06)
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Figure 14. Percentage change of the yearly available
water for 2050 high emission scenario compared to the
1961-1990 baseline scenario in England and Wales.
Figure 15. Percentage change of the summer available
water for 2050 high emission scenario compared to the
1961-1990 baseline scenario in England and Wales.
Compared to the average yearly available water, the agricultural demand is relatively small so that virtually
nowhere in England and Wales does the agricultural demand exceed the average yearly available water.
However, for the summer months from June to August, there are a number of catchments, where the agricultural
demand is greater than the summer available water. These catchments are mainly located in East Anglia, where
the summer demand exceeds the summer available water in c. 30% of the area (Fig. 16). This area is extended in
a year with a dry summer (defined as a year with a summer flow which is exceeded in 80% of the years), when
the agricultural demand exceeds the available water in c. 60% of East Anglia (Fig. 17). In the areas where the
demand is in excess of the available water, the demand averages 260% of the available water in an average year
and 440% in a dry year.
Figure 16. Average summer (Jun - Aug) available
water minus 2001 agricultural summer demand.
Figure 17. Summer (Jun - Aug) available water
exceeded in 80% of the years minus summer agricultural
demand for 2001 if a dry year.
Assuming present day demands, the area where summer agricultural demands in an average year in the 2050s
high emission scenario exceed summer available water from surface waters increases to 7% of England and
Wales and 32% of East Anglia, this is an increase of around 20% compared to the baseline. In a dry summer,
agricultural demands exceed summer available water in 19% of England and Wales and 68% of East Anglia, an
increase of around 10% compared to the baseline (Fig. 18 and Table 9).
SID 5 (Rev. 3/06)
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Table 9. Percentage of area where the irrigation demand exceeds the available surface water during the summer
months for an average year and a ‘dry year’ for the 1961-90 baseline scenario and the 2050s high emission
scenario for England and Wales and for the EA Anglian Region.
Baseline scenario
Average summer
Dry summer
England & Wales
East Anglia
6
26
HI2050s scenario
Average summer
Dry summer
18
62
7
32
England and Wales
East Anglia
10000
Demand as percentage of available water
10000
Demand as percentage of available water
19
68
baseline average summer
baseline dry summer
1000
2050s high average
summer
2050s high dry summer
100
10
1
1000
100
baseline average summer
10
baseline dry summer
2050s high average
summer
2050s high dry summer
1
0.1
0.1
0
20
40
60
80
100
0
20
40
60
80
100
Percentage area
Percentage area
Figure 18. Summer demand as percentage of available water for an average year and a ‘dry year’ for the 196190 baseline scenario and the 2050s high emission scenario for England and Wales and for the EA Anglian
Region.
Conclusions
The developed model was adequate at simulating flow in a range of catchments, which allowed us to take this
forward to simulate baseline flows (see earlier) and also the effects of selected climate change scenarios. Under
future climate projections, it was calculated that annual flows would decrease on average over England and
Wales by between 2% to 5% for the 2020s low to the 2050s high emission scenarios, respectively. These
changes in annual amounts appear relatively small and are because of the interactions between potential and
actual evaporo-transpiration (PET and AET) and drier summers/wetter winters. The higher temperatures in the
2020s and 2050s result in higher PET but, due to reduced water availability especially in summer, AET remains
nearly constant or decreases slightly.
The reduction in summer rainfall however results in a larger decrease in river flows during the irrigation season
from June to August with an average decrease for the 2050s high scenario over England and Wales by around
27%.
The simulations also show that the greatest percentage reductions in summer flow occur in catchments with
flashy river regimes. The smallest reductions occur in catchments dominated by baseflow, in which summer flows
are partially maintained by the increased winter rainfall, which enters the groundwater store and is released in the
summer months.
We know from water use statistics that agriculture uses only about 1% of abstracted water and it is therefore not
surprising that, when considering annual water availability and agricultural demand, there are no conflicts
demonstrated by the model simulations. As described earlier, it is the summer months that are critical for
6
3
irrigation requirement and this is when most of the 125 x 10 m is applied (plus livestock/nursery requirements).
Repeating this analysis of comparing available water and agricultural demand for the summer months only,
shows that (for baseline climate conditions), about 30% of East Anglia (and about 7% of England and Wales) is
affected. The area where demand is greater than availability increases to about 60% (East Anglia) or 20%
(England and Wales) in a dry year (defined as a year with 80% of average flow). The difference in area affected
between a wet and a dry year is much greater than the difference between baseline and the 2050 high scenario.
We can conclude, therefore, that the short-term annual variations in weather have a greater influence than longterm trends.
SID 5 (Rev. 3/06)
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In terms of water resource planning, however, the climatic changes are important, in that irrigation systems and
abstraction licensing must be designed to function in the ‘design dry year’ rather than an average year. The
economic benefit of the system is realised largely in the driest years.
It is important to note that the simulations take no account of increased irrigation demand due to climate change.
However, it is possible that the irrigation demands will increase. Irrigation demand in a dry year is predicted to
increase by around 20% in the 2020s and 30% in the 2050s (Downing et al., 2003). These increases vary
spatially and are greatest in the South and East and less in the West and North. The change in demand therefore
further worsens the situation in East Anglia. An increase in the demand of 30% would mean that in a dry summer
the area where summer agricultural demands exceed the available water increases to 24% of England and Wales
and 73% of East Anglia.
Finally, irrigation demand overall may increase under climate change, due to a combination of:
• Extension of irrigation to a wider range of crops, due to the increased frequency or severity of drought.
For example, maize is a major irrigated crop in many countries.
• Introduction of new crops which may require irrigation.
3.6.
Regional impacts (Objective 5)
The aim was to review the regional pattern of impact across England and Wales, with special attention to
differences between types of pollutants. The spatial analysis and modelling has demonstrated that:
•
On an annual basis, there is little conflict between water available in a catchment and that required for
agriculture. However, there is more pressure in the East than the West.
•
Water quality/chemistry – the impacts of reduced flow are most clearly demonstrable where there is a
significant input of sewage treatment (i.e. areas of high population) and low flows (i.e. drier areas).
Therefore, effects are greatest in the east and south east. Low flows could, of course, directly affect other
parameters, such as oxygen status, in all areas.
•
Although water demand for livestock is greater than for irrigation (in total):
o
o
•
Livestock are predominantly in the wetter west
Irrigation is restricted to the June-August period and is mainly required in the east
If we focus on this summer period, when flows will be at their lowest anyway:
o
o
The greatest pressure on water resources is in the east, with large proportions of East Anglia
showing a shortfall between irrigation demand and calculated available water.
There is an increase in the concentration of sewage-derived pollutants, but not nitrate and sediment
(more associated with diffuse pollution.
•
There is evidence that groundwater-fed rivers (predominantly in the south and south-east) reach their lowest
flows in August/September, somewhat later than surface water-fed rivers (July/August). This means that at
least part of the main irrigation demand commonly occurs before the lowest flows. Climate change also has
less impact on summer flows in groundwater-fed rivers because the increased winter rainfall is able to
replenish the reserves that sustain flow.
•
Overall, our predictions show that the total effect of climate change would be in the range of a 2-5% reduction
in run-off. Effects would be greatest in the wetter regions because summer AET will be closer to PET
whereas in the east PET is limited by the reduced summer rainfall under climate change. Nevertheless,
climate change will increase the pressure on water resources in the east. It is interesting to note that we
have demonstrated greater variation in run-off between years than we are predicting in change between the
average baseline and future climate change.
4.
CONCLUSIONS
4.1. Consequences for the Water Framework Directive (Objective 6)
This project has tried to assess the quantity of water available for abstraction from surface waters for the current
(baseline) climate, as well as estimating effects under future climate scenarios. We have been able to place these
in the context of the agricultural demand for water.
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A model was developed for the simulation of time series of flow for the whole of England and Wales. The model is
responsive to catchment characteristics of land use and hydrogeology and it showed a good performance over a
range of different catchments, without the need for site-specific calibration to observed data.
The evaluation of agricultural demands in the context of available water showed that demands from agriculture
are significant in the summer period and in certain areas of the country, mainly concentrated in East Anglia. Also,
agriculture is presumably the most important abstractor in headwaters, as other abstractors usually abstract from
major rivers.
In many of the areas in which abstraction of summer surface water is classified as unsustainable by the EA,
agricultural demands are not significant. Abstraction of summer surface water is currently considered
unsustainable in all of the Southern Region and parts of East Anglia (Fig. 19), but in most parts of the Southern
Region agricultural demands are less than 3 mm. This is because the crops requiring high amounts of irrigation
are not grown to a big extent in this region.
In East Anglia, where irrigation demands are significant, summer surface water abstractions are classified as
unsustainable in smaller parts, and no additional water is available in any part of East Anglia. With decreasing
summer flows under future climate conditions, less water will be available for abstractions, while demands are
expected to increase.
Figure 19. Areas of unsustainable surface water abstraction as defined by the Environment Agency (2001) for
summer surface water abstractions (1) and winter surface water abstractions (2).
In terms of water quality, reassessment of standards under the WFD has created closer linkages between
chemical, nutrient and hydromporphological status and ecology. Thus, if agricultural water demand impacts on
dissolved oxygen, BOD, ammonia or P levels and/or flow, then this could have potential impacts on the ecological
status. We have concluded that changes to water quality due to dilution effects are:
• chiefly related to point sources (sewage treatment works) rather than diffuse agricultural sources;
• are is most likely in the east;
• are most likely in the summer months.
In terms of climate change impacts on water availability, and the demand for irrigation water in summer, we
concluded that:
• Climate change is likely to increase demand for irrigation water during summer, and increase the
frequency of occurrence of extreme demand years and of low flows;
• annual variations are as great as or greater than expected changes in mean value within the next few
decades However the change in mean value, and in frequency of demand exceeding availability, will
impact on water resource planning and irrigation abstraction licensing.
This analysis did not take explicit account of other potential effects of climate change. Greater risk of summer
drought, with higher temperatures, could increase irrigation demand:
• by extension of Irrigation to a wider range of crops;
• by introduction of new crops requiring irrigation;
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•
by extension of irrigation into areas where irrigated crops are currently rare – i.e. towards the west.
The extension of irrigated crops towards areas where they currently do not occur could have adverse impact on
rivers which are currently of relatively good ecological quality:
• by reduction of summer flows;
• by quality changes as discussed above;
• more directly, by the fact that some of these crops carry with them an increased risk of sediment or other
pollutant transfer.
4.2 Recommendations
The results form a basis of information for input to river basin planning, and for taking account of impacts of
climate change, in a uniform way. They should be made available to river basin planning teams.
The results suggest that conflict between supply and demand is greatest during summer, and in the east; and that
this conflict will become greater rather than less. This suggests that, in future, irrigation may only be viable with
winter storage to allow abstraction of water while flows are high.
Further assessment of the impacts of climate change should take account of likely changes in land use, and in
crops for which irrigation may become economic.
As a result of climate change and consequent land management change, and the difficulties of irrigation in
eastern areas, it is possible that irrigation will increase in more sensitive western catchments. This may be a
result of changed cropping (greater areas of responsive crops grown in the west) and/or a need to irrigate crops
in the west due to the changed climate. The risk of this, and the ecological implications, should be investigated.
References to published material
9.
This section should be used to record links (hypertext links where possible) or references to other
published material generated by, or relating to this project.
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