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A river acts both as a source and carrier of water for supporting and sustaining the biological diversity and integrity of the aquatic, wetland and riparian species and natural ecosystems. To accomplish these functions, it is necessary that river water meets some essential qualitative and quantitative parameters and the stream-flow exhibits the dynamics and hydrological attributes comparable to that of natural or unaltered river flows (hydrologic regime).
This hydrologic regime is the lifeline of freshwater
ecosystem and all diverse variety of aquatic & riparian species are
for long accustomed and adapted to the characteristic temporal, spatial
and hydrologic variation of water flow cycles attributable to the
natural or unaltered water flow. Unfortunately, this regime and its
naturally configured variation patterns get disturbed failing to absorb
the stresses induced by our ever-increasing demands and environmentally
irresponsive use of water. To evaluate the shifts in the pre and
post-reservoir hydrologic parameters, the effect of Wimbleball
Reservoir have been analyzed based on the long-term flow-patterns of
the downstream discharge of the reservoir. The analysis was conducted
by a very robust statistical model called the IHA model. Both long term
differences and RVA analysis show substantial impacts of man made
reservoir control on the biota of the Exe-catchment.
Introduction
Water bodies like rivers, streams, channels, etc. serve a dual function
being essential source points for our day-to-day water requirements as
well being its transporters or carriers by flowing in and channeling
water downstream to the river beds, catchments and agricultural fields
in the process supporting and sustaining the biological diversity and
integrity of the aquatic, wetland and riparian species and natural
ecosystems. Our earth is also called the ‘water planet’ as water forms
approximately 70% of its total surface (The Ground Water Foundation,
2003) but only a part of it is available for our use. This realization
has long back prompted us to take up some water management practices.
In the beginning, water management practices were very much focused on
issues like water quality and flood control measures and the overall
strategy was never so broad to include other aspects like water
quantity, stream flow management and restoration (BD, Richter, etal,
1997)2. However, issues pertaining to water quantity, flow,
restoration, etc. gradually started to get prominence in our policy
framework following a landmark order passed by the US Supreme Court
identifying the separation of water quality from water quantity and
flow as an artificial distinction and recommending incorporation of
both water quality and quantity objectives in a broader and
comprehensive water management policy framework (US-EPA, 2002)3. Water
quality, quantity & flow conditions are in way inseparable features
considering the fact that the amount of flow in a river effects many
issues of water quality and water quantity at the same time. Therefore,
the assessment on the wholesomeness of water in any system is
essentially dictated by the above conditions of quality, quantity and
flow characteristics. Going by this approach broadens the overall water
policy framework making this a comprehensive management initiative.
This shift in water management approach necessitated re-configuration
of the erstwhile single or limited objective driven practice of flood
& storm water control thereby embracing a comprehensive initiative
of total ecosystem management & restoration having multi-utility
potentials. This system is very important and effective because this
takes into account the sustainable use of water resources or ‘water
takings’ and their possible restoration (Dept. of Fisheries &
Oceans, Canada, 2002)4. Under the ambit of this, it is necessary that
river water meets some essential qualitative and quantitative
parameters and the stream-flow exhibits the dynamics and hydrological
attributes (hydrologic regime) comparable to that of natural or
unaltered river flow (Richter D. Brian & etal) 5. This hydrologic
regime or ‘natural flow regime’ is the lifeline of freshwater ecosystem
and all diverse variety of aquatic & riparian species are for long
accustomed and adapted to the characteristic temporal, spatial and
hydrologic variations of water flow cycles attributable to the natural
or unaltered water flow. Unfortunately, this regime and its naturally
configured variation patterns get disturbed (Allan David & Hinz
Leon, SNRE, 2004)6 failing to absorb the stresses induced by our
ever-increasing water takings demands and environmentally irresponsive
use of water. In fact, this is the point where human intervention or
controls and water integrity issues found themselves in a highly
confronting and conflicting platform. Increased water demands
compelling human actions like construction of water reservoirs, dams,
impoundments, etc. for storing and using water for domestic, energy and
hydropower, artificial parks and various other uses have started taking
their toll on river waters and water bodies substantially degrading the
quality, quantity and importantly squeezing the downstream water flows
(Benke, A. C. 1990). This flow reduction in rivers consequential to man
made flood and irrigation control practices like reservoirs and dams
are found to alter the natural hydrologic regime bringing in a series
of impairments to overall ecosystem and also opening up a new front in the field of river and hydrology studies.
This paper aims to assess the variations in the hydrological
parameters of a river system specifically attributable to impacts of
man-made interventions or controls like reservoirs. Primarily, the
research ambition is to identify and evaluate the degree of alterations
in the hydrologic profile by analyzing the long-term historical as well
recent water flow records representative of the pre-impact and
post-impact period of construction and commissioning of a typical
reservoir. An emerging computer tool called the ‘IHA’ (Indicators of
Hydrologic Alterations) has been applied to generate scenarios and
analyze the data. The records and data needs for this study have been
sourced from an existing gauging station in the Exe river of South-West
England strategically selected to represent the influence of the
‘Wimbleball Reservoir’.
Natural Flow Regime & Hydrologic Alterations – Ecological Significance
The concept of natural flow regime is based on the understanding
that aquatic and riparian organisms depend upon, or can tolerate a
range of flow conditions specific to each species (Poff etal, 1997)7.
For example, certain fish species moves into safer floodplain areas
during floods to feed and escape from attacks of other species
occupying the main water body thereby adapting a mechanism to survive
and carry on all by itself. This in a way indicates that if flooding
occurs at the right time of the year, and lasts for the right amount of
time, these fish populations will benefit from the flood event finally.
Again as a contrast to this case, other species may be adversely
affected by the same flood. With the development of the science of
hydrology, it has been confirmed with a good degree of confidence that
a hydrologic regime with all its natural and temporal variations (both
intra-annual and inter-annual) are needed to maintain and restore the
natural form and function of aquatic ecosystems. However, this
prerequisite is not in line with the traditional water management
practice which is functionally attuned to influence and dampen natural
fluctuations with the objective to provide steady and undisturbed
supply of water for different in-stream and out-of-stream activities
(Richter et al., 2003) . Moreover, for intervening and containing
extreme drought and flood events, the traditional water management
initiatives rather relied on moderating and limiting flow fluctuations.
Many studies indicate ‘natural flow regime’ as a determinant to
in-stream flow needs of a water body. For example, (Richter et al,
1996) and (Poff et al. 1997) generalized that natural flow conditions
may indicate and determine in-stream flow requirements. There exists a
correlation between stream-flow and other physicochemical
characteristics critical to ecological integrity of streams and rivers
(Poff etal., 1997). Precisely, flow can be associated to some direct as
well indirect or secondary impacts and as such flow characteristics can
be used as surrogates for other in-stream indicators and ecosystem
conditions and importantly the components of a flow regime as shown in
figure-1, are very much accessible to scientific inquiry (IFC, 2002,
Poff et al. 1997, Richter et al., 1996) .
Any disruption, fragmentation and dilution of this natural regime of
water-flow leads to ‘Hydrological alteration’ and in general, this can
be defined as any anthropogenic disruption in the magnitude or timing
of natural river flows (Biosciences, 50-9, 2000). The natural flow
regime of a river is dependent on various factors including rainfall,
temperature and evaporation when considered in a broader geographic
scale or macro-scale and is also influenced by the physical
characteristics of a catchment at the catchment level or micro-scale
(Resh et al, 1988) . As mentioned earlier, river flow regimes are also
affected directly and indirectly by human activities. Such human
interventions disrupting natural flow of a river through construction
and operation of reservoirs and dams have the potential of triggering a
series of undesirable consequences like extensive ecological
degradation, loss of biological diversity, water quality deterioration,
groundwater depletion, and also more frequent and intense flooding
(Poff et al, 1997). Reservoir are built to store water to compensate
for fluctuations in river flow, thereby providing a measure of human
control of water resources, or to raise the level of water upstream to
either increase hydraulic head or enable diversion of water into a
canal. The creation of storage and head allows reservoirs to generate
electricity, to supply water for agriculture, industries, and
municipalities, to mitigate flooding and to assist river navigation
(Resh et al. 1988).
The biological effects of hydrologic alterations are often difficult to
disentangle from those of other environmental perturbations in heavily
developed catchments as identified by Rosenberg et al. (Environmental
Reviews 5: 27–54, 1997) . The impacts of large-scale hydrological
alteration include habitat fragmentation within rivers (Dynesius and
Nilsson 1994) , downstream habitat changes, such as loss of
floodplains, riparian zones,and adjacent wetlands and deterioration and
loss of river deltas and ocean estuaries (Rosenberg et al. 1997)36,
deterioration of irrigated terrestrial environments and associated
surface waters (McCully 1996) . Hydrological alterations also bring in
other indirect or secondary impacts on the genetic, ecosystem and
global levels. They can cause genetic isolation through habitat
fragmentation (Pringle 1997) , changes in processes such as nutrient
cycling and primary productivity (Pringle 1997, Rosenberg et al. 1997),
etc.
With the realization of the importance of natural flow regime and the
possible dangers posed by human alterations, there emerged a relatively
new and promising water and ecology management paradigm. Many
researchers started seeing this as a very comprehensive and sound
management option and on many occasions stressed regarding the urgency
of protecting or restoring "natural" hydrologic regimes (Sparks 1992;
National Research Council, Doppelt et al. 1993; and Dynesius &
Nilsson 1994) . Effective ecosystem management of aquatic, riparian,
and wetland system requires that existing hydrologic regimes be
characterized using biologically-relevant hydrologic parameters, and
that the degree to which human-altered regimes differ from natural or
preferred conditions be related to the status and trends of the biota
(BD, Richter, etal, 1997). Ecosystem management efforts should be
considered experiments, testing the need to maintain or restore natural
hydrologic regime characteristics in order to sustain ecosystem
integrity. Only some limited studies have closely examined hydrologic
influences on ecosystem integrity and this is mainly because most of
the commonly used statistical tools are poorly suited for
characterizing hydrologic data into biologically relevant attributes
(BD, Richter, etal, 1997). Without such knowledge, ecosystem managers
will not be compelled to protect or restore natural hydrologic regime
characteristics. However, recently, there have been some significant
developments in the field of hydrological studies and importantly few
robust computer statistical tools and models like IHA & Range of
Variability Approach (RVA) using the (Indicators of Hydrologic
Alterations, BD, Richter, etal, 1997), Wetted Physical Habitat
Simulation System (PHABSIM Model, Jowett, 1997)35, Flow Incremental
Methodology (FIM), other Hydrologic Modelling Software like GAWSER,
Ontario Flow Assessment Techniques (OFAT), etc. are now know to exist
(Jowett, 1997).
The following sections attempt to evaluate and assess the possible
effects of hydrological alteration specifically induced by human
interventions or activities. A very useful computer model called the
IHA model (available at Freshwaters.com) has been used for generating
and evaluating the effects of flow variations. The ecological zone
considered for analysis in this paper is the ‘Exe river Estuary’ region
and the gauging station selected is 45001 - Exe at Thorverton.
The Indicators of Hydrologic Alteration (IHA) Method – Approaches & Application
The evaluation and assessment of the flow regime of the Exe-river
system and the variations it witnessed after the construction of the
‘Wimbleball Reservoir’ have been accomplished by the application of a
very detailed computer-modeling tool known as the IHA or ‘Indicators of
Hydrologic Assessment’ model. The software basically takes birth from
the concept of integrity and wholesomeness of the ‘natural flow regime’
and is configured and capable of determining the relative
transformations and variations in this natural flow regime subject to
any natural or artificial modifications or alterations (BD, Richter,
etal, 1997). At first, it requires defining and identifying a series of
biologically-relevant hydrologic attributes that characterize intra and
inter-annual variations in water conditions which are further processed
for a robust statistical variation analysis after isolating the
data-sets to represent two different periods resembling the pre-impact
and post-impact scenarios (Rosenberg, et al, 2002). The Nature
Conservancy is now the custodian of this statistical tool, which is
very useful for assessing the degree to which human activities have
changed flow regimes (US-EPA, 2002). Brian D. Richter and et al. from
the Nature Conservancy (Richter D. Brian, etal, 1996-97) have
identified four basic for this analysis and they are:
(i) Define the data series (e.g., stream-gauge or well records) for pre- and post-impact periods in the ecosystem of interest.
(ii) Calculate values of hydrologic attributes - Values for each of 32
ecologically-relevant hydrologic attributes are calculated for each
year in each data series, i.e., one set of values for the pre-impact
data series and one for the post-impact data series.
(iii) Compute inter-annual statistics - Compute measures of
central tendency and dispersion for the 32 attributes in each data
series, based on the values calculated in step 2. This produces a total
of 64 inter-annual statistics for each data series (32 measures of
central tendency and 32 measures of dispersion).
(iv) Calculate values of the Indicators of Hydrologic Alteration -
Compare the 64 inter-annual statistics between the pre- and post-impact
data series, and present each result as a percentage deviation of one
time period (the post-impact condition) relative to the other (the
pre-impact condition). The method equally can be used to compare the
state of one system to itself over time (e.g., pre- versus post-impact
as just described); or it can be used to compare the state of one
system to another (e.g., an altered system to a reference system), or
to compare current conditions to simulated results based on models of
future modification to a system.
The same computational strategies will work with any
regular-interval hydrologic data, such as monthly means; however, the
sensitivity of the IHA method for detecting hydrologic alteration is
increasingly compromised with time intervals longer than a day (Richter
D. Brian, etal, 1996-97). Detection of certain types of hydrologic
impacts, such as the rapid flow fluctuations associated with hydropower
generation at dams, may require even shorter (hourly) interval. They
have also suggested that ‘the basic data for estimating all attribute
values may preferably be daily mean water conditions (levels, heads,
flow rates). Hydrologic conditions in general can vary in four
dimensions within an ecosystem (three spatial dimensions and time).
However, the three spatial domains can be scaled down to one with the
assumption that only one spatial domain exists at any strategic
location over time in a river system. Restricting the domain to one
specific point within a hydrologic system (like any measuring point in
a river) makes it simple for us to identify specific water conditions
with one spatial and one temporal domain. These events may be specific
water conditions like heads, levels, rate of change, etc. (Richter D.
Brian, etal, 1996) whose temporal variations can be recorded and
assessed from that particular spatial point or from a single position.
Such temporal changes in water conditions are commonly portrayed as
plots of water condition against time, or hydrographs.
Here, we seek to study and analyze the variations in hydrologic
conditions using indicators and attributes, which should essentially be
biologically relevant as well as responsive to human influences or
modifications like reservoir and dam operations, ground water pumping,
agricultural activities, etc. at the same time (Richter D. Brian, etal,
1996,). Importantly, a variety of features or parameters of a
hydrologic regime can be used and functionally superimposed (Sensu
Southwood 1977, 1988; Poff & Ward 1990}40 to virtually represent
and finally characterize the "physical habitat templates" (Townsend
& Hildrew, 1994)43 or "environmental filters" (Sensu Keddy 1992)42
that shape the biotic composition of aquatic, wetland, and riparian
ecosystems. The IHA method is based on 32 biologically relevant
hydrologic attributes, which are divided into five major groups to
statistically characterize intra-annual hydrologic variation as shown
in Table-1. These 32 attributes are based upon the following five
fundamental characteristics of hydrologic regimes:
1. the magnitude of the water condition at any given time is a
measure of the availability or suitability of habitat, and defines such
habitat attributes as wetted area or habitat volume, or the position of
a water table relative to wetland or riparian plant rooting zones;
2. the timing of occurrence of particular water conditions can
determine whether certain life cycle requirements are met, or influence
the degree of stress or mortality associated with extreme water
conditions such as floods or droughts;
3. the frequency of occurrence of specific water conditions such as
droughts or floods may be tied to reproduction or mortality events for
various species, thereby influencing population dynamics;
4. the duration of time over which a specific water condition exists
may determine whether a particular life cycle phase can be completed,
or the degree to which stressful effects such as inundation or
desiccation can accumulate;
5. the rate of change in water conditions may be tied to the
stranding of certain organisms along the water's edge or in pounded
depressions, or the ability of plant roots to maintain contact with
phreatic water supplies.
A detailed representation of the hydrologic regime can be obtained
from these 32 parameters for the purpose of assessing hydrologic
alteration. Importantly, all the parameters having good ecological
relevance do not call for any parameter specific statistical analysis
and all of them can be processed by single and unique approach like the
IHA (Kozlowski 1984; Gustard 1984; Poff & Ward 1989)46. Also,
because certain stream-flow levels shape physical habitat conditions
within river channels, it is needed to identify some hydrologic
characteristics that might aid in detection of physical habitat
alterations. (Richter D. Brian, etal, 1997). Sixteen of the hydrologic
parameters focus on the magnitude, duration, timing, and frequency of
extreme events, because of the pervasive influence of extreme forces in
ecosystems (Gaines & Denny 1994)48 and geomorphology (Leopold
1994)49 and other 16 parameters measure the central tendency of either
the magnitude or rate of change of water conditions (Table-2). The
rationale underlying the five major groupings and the specific
parameters included within each are described below.
Table-2: Summary of various Hydrological Groups
Groups Descriptions Number of total Hydrologic Parameters
1 Magnitude of monthly water conditions 12
2 Magnitude & duration of annual extremes 10
3 Timing of annual extremes 02
4 Frequency & duration of high & low pulses 04
5 Rate & frequency of change in conditions 04
Group-1: Magnitude of Monthly Water Conditions
This group includes 12 parameters, each of which measures the
central tendency (mean) of the daily water conditions for a given
month. The monthly mean of the daily water conditions describes
"normal" daily conditions for the month, and thus provides a general
measure of habitat availability or suitability. The similarity of
monthly means within a year reflects conditions of relative hydrologic
constancy, whereas inter-annual variation (e.g., coefficient of
variation) in the mean water condition of a given Month provides an
expression of environmental contingency (Colwell 1974; Poff & Ward
1989). The terms "constancy" and "contingency" as used here refer to
the degree to which monthly means vary from month to month (constancy),
and the extent to which flows vary within any given month
(contingency).
Group-2: Magnitude and Duration of Annual Extreme Water Conditions
The 10 parameters in this group measure the magnitude of extreme
(minimum and maximum) annual water conditions of various duration,
ranging from daily to seasonal. The durations that we use follow
natural or human-imposed cycles, and include the 1-day, 3-day, 7-day
(weekly), 30-day (monthly), and 90-day (seasonal) extremes. For any
given year, the 1-day maximum (or minimum) is represented by the
highest (or lowest) single daily value occurring during the year; the
multi-day maximum (or minimum) is represented by the highest (or
lowest) multi-day average value occurring during the year. The mean
magnitudes of high and low water extremes of various duration provide
measures of environmental stress and disturbance during the year;
conversely, such extremes may be necessary precursors or triggers for
reproduction of certain species. The inter-annual variation (e.g.,
coefficient of variation) in the magnitudes of these extremes provides
another expression of contingency.
Group-3: Timing of Annual Extreme Water Conditions
This group includes 02 parameters one measuring the Julian date of
the 1-day annual minimum water condition, and the other measuring the
Julian date of the 1-day maximum water condition. The timing of the
highest and lowest water conditions within annual cycles provides
another measure of environmental disturbance or stress by describing
the seasonal nature of these stresses. Key life cycle phases (e.g.,
reproduction) may be intimately linked to the timing of annual
extremes, and thus human induced changes in timing may cause
reproductive failure, stress, or mortality. The inter-annual variation
in timing of extreme events reflects environmental contingency.
Group-4: Frequency and Duration of High and Low Pulses
This group has 04 parameters include two, which measure the number
of annual occurrences during which the magnitude of the water condition
exceeds an upper threshold or remains below a lower threshold,
respectively, and two, which measure the mean duration of such high and
low pulses. These measures of frequency and duration of high- and
low-water conditions together portray the pulsing behavior of
environmental variation within a year, and provide measures of the
shape of these environmental pulses. Hydrologic pulses are defined here
as those periods within a year in which the daily mean water condition
either rises above the 75th percentile (high pulse) or drops below the
25th percentile (low pulse) of all daily values for the pre-impact time
period.
Group-5: Rate and Frequency of Change in Water Conditions
The four parameters included in this group measure the number and
mean rate of both positive and negative changes in water conditions
from one day to the next. The
Rates and frequency of change in water conditions can be described in
terms of the abruptness and number of intra-annual cycles of
environmental variation, and provide a measure of the rate and
frequency of intra-annual environmental change.
Assessing Hydrologic Alteration
In assessing the impact of a perturbation on the hydrologic regime,
we want to determine whether the state of the perturbed system differs
significantly from what it would have been in the absence of the
perturbation. In particular, we want to test whether the central
tendency or degree of inter-annual variation of an attribute of
interest has been altered by the perturbation (Stewart-Oaten et al.
1986)55. The assessment of impacts to natural systems often poses
difficult statistical problems, however, because the perturbation of
interest cannot be replicated or randomly assigned to experimental
units (Carpenter 1989; Carpenter et al. 1989; Hurlbert 1984;
Stewart-Oaten et al. 1986)66. The lack of replication does not hinder
estimation of the magnitude of an effect, but limits inferences
regarding its causes. However, the IHA method is robust and can be
easily adapted to more sophisticated experimental designs.
A standard statistical comparison of the 32 IHA parameters between two
data series would include tests of the null hypothesis that the central
tendency or dispersion of each has not changed. However, this null
hypothesis is generally far less interesting in impact assessments than
questions about the sizes of detectable changes and their potential
biological importance. A standardized process for assessing hydrologic
impacts is included within the IHA software. The Range of Variability
Method (RVA) is another analysis frame in which to assess change in a
structured manner. This method of determining hydrologic alteration is
based on the theory that there is natural variability in stream-flow.
The RVA software would plot and determine whether an activity, such as
water taking, would alter the stream-low outside this normal
variability. Significant alteration would occur if the stream-low
regime were altered more than one standard deviation from the natural
variability, which may have ecological consequences.
Development of Pre- and Post-Impact scenarios
When adequate hydrologic records are available for both the
pre-impact and post-impact time periods, application of the IHA method
will be relatively straightforward using the statistical procedures
described above. When pre- or post-impact records are nonexistent,
include data gaps, or are inadequate in length, however, various data
reconstruction or estimation procedures will need to be employed.
Examples of such procedures include the hydrologic record extension
techniques described by Searcy (1960) and Alley & Burns (1983).
Hydrologic simulation modeling or water budgeting techniques can also
be used to synthesize hydrologic records for comparison using the IHA
method (Linsley et al. 1982)73.
Accounting for Climatic Differences
Climatic differences between the pre- and post-impact time periods
obviously have the potential to substantially influence the outcome of
the IHA analysis. Various statistical techniques can be used to test
for climatic differences in the hydrologic data to be compared. When
the IHA analysis is to be based upon actual hydrologic measurements
rather than estimates produced from models, a reference site or set of
sites uninfluenced by the human alterations being examined can be used
as climatic controls (Alley & Burns 1983). For example, a
stream-gauge may exist upstream of a reservoir thought to have impacted
a study site. Analyses can establish a statistical relationship between
stream-lows at the study site and at the upstream reference site using
synchronous pre-dam data sets for the two sites. This relationship can
then be used to estimate the stream-low conditions that would have
occurred at the study site during the post-impact time period in the
absence of the reservoir.
IHA Application- Description of Study Site
As mentioned earlier, the principal motive of this study is to
analyze and evaluate the impacts, if any, of human interventions like
reservoir operations on the overall sanctity and natural integrity,
i.e. the natural hydrologic regime of water bodies like rivers. Here
the operation of a well know reservoir in the south-west coast of
Britain called the ‘Wimbleball reservoir’ has been identified as the
human intervention point which is sufficiently used to store and supply
water to cater to human needs like hydropower, drinking water supply,
etc. (SW-Environment Agency, 2003)81 and eventually it ends up
regulating a river system in the process. The down-stream water body
and habitat, which is expected to come under the influence of the
alterations resulting from the Wimbleball reservoir operations,
considered here is the Exe-river estuary system. The main motivation
for selection of the above reservoir and the river system happens to be
the strategically located river monitoring system (gauge-station),
which falls in the influence zone. This station is designated as
‘No.45001-Exe at Thorverton’ having a grid reference of ‘21 (SS) 936
016’ (NRFA & Data Holdings, 2005)66. Figure-2 (enclosed) shows a
diagrammatic representation of the Exe-river catchments area along with
the positions of the river and reservoir. The national authority NRFA,
describes the monitoring station as “Velocity-area station with
cableway and flat V-Crump profile weir constructed in 1973 due to
unstable bed condition” (NRFA, 2005)66. There also exists minor culvert
flow through mill u/s of station included in rating. Notably, Low flows
are affected significantly by the operations of the Wimbleball
reservoir post-1979 and by exports to the Taw catchment. Station is
control point for operational releases from Wimbleball (NRFA & Data
Holdings, 2005)66. The headwaters drain Exmoor and the geology is
predominantly Devonian sandstones and Carboniferous Culm Measures, with
subordinate Permian sandstones in the east, Moorland, forestry and a
range of agriculture (NRFA & Data Holdings, 2005)66.
The Exe Estuary is partially an enclosed tidal area composed of both
aquatic (marine, brackish and freshwater) and terrestrial habitats. The
Estuary makes an important contribution to the diversity of British
estuaries by virtue of its unspoilt nature, international conservation
importance, recreational opportunities and high landscape value
(SW-Environment Agency, 2003) . This Estuary flows through an open
landscape with gently rolling hills on either side. It is shallower
than many estuaries in the south west of England, so the tide plays a
significant role, with large expanses of sandbanks and mudflats exposed
at low water. The waters, foreshore and low-lying land of the area
create a varied habitat, which supports a diverse range of flora and
fauna. The Estuary is particularly important for ornithological
interests, both in terms of the diversity of species represented and in
the large numbers of birds utilizing its resources. This importance is
reflected in the area's designations as a Wetland of International
Importance under the Ramsar Convention, a SPA and a SSSI
(SW-Environment Agency, 2003) .
According to the South West Water Company, the major water supplier in
the Exe-region, the demand for water has risen by approximately 30%
since 1976. In the mid-seventies each person used an average of 24
gallons (110 liters) a day. Today, that figure has risen to 35 gallons
(159 liters) (southwestwater.co.uk) . Even if this region is relatively
a wet part of England, the geology of the region sees most rainwater
draining away very quickly. About 90% of the water in this part is
sourced from surface waters in the form of rivers and reservoirs and
only about 10% water is derived from underground sources, that too in
the East Devon area (SW-Environment Agency, 2003) . This is the reason
why it was decided to consider only surface waters in this study.
Significantly, the region’s water storage capacity at present has
almost quadrupled compared to the requirements of the mid-seventies.
Therefore, it is evident that this region heavily depends on surface
waters and water abstractions here appear to be very substantial.
Data Processing for IHA Application
For this study, a strategic water monitoring station has been
identified over river Exe that captures flow data just down the
discharge point of the Wimbleball reservoir. Moreover, this particular
station is also very much desirable as this gives us a series of fairly
long-term river flow (mean daily flow) and condition data covering both
the pre and post periods of Wimbleball construction. The data sets used
in running the IHA software include long-term flow conditions (mean
daily flow) recorded at the gauge-station No.45001-Exe at Thorverton’.
The data for this station along with related information have been
taken from the NRFA and Data Holding’s on-line information and their
centralized data bank. IHA protocols recommend using at least a
20-year’s time series data set for better analysis and consistency in
results (Richter D. Brian, etal, 1997). In line with this requirement,
a fairly long-term time-series data set starting from 1956 to 2005 has
been considered in this study with a pre-impact period span of 24 years
(1956-1979) and a post-impact period span of 24 years (1980-2005).
Already mentioned earlier, the main aim of this study is to investigate
and see if there exist any changes or shifts in the river hydrologic
conditions during the post-Wimbleball construction period (Wimbleball
was commissioned during 1979) on account of reservoir related human
activities as compared to the period before Wimbleball construction
when no great human influence was observed to exist in the area. The
data set pertaining to different river flow parameters, which have been
used here may have serial correlations but this should not be a problem
in case of this analysis as the intention is to evaluate back-to-back
differences in magnitudes of the parameters under two sets of
time-periods. Thus, here it was preferred to carry out a simple
non-parametric statistical analysis for which the available data are
quite sufficient. Moreover, there is no need for any data log
transformation, which can be easily judged by having a look at the data
set. However, this being a very long chain of data, a separate check
for data consistency and unexpected outliers has been carried out here
by transposing the data into very powerful data-mining & analysis
tool called ‘Free-Fore’ (from Oakdale Engineering). The raw data used
here has been downloaded from the NRFA web database. The mean daily
flow values for all the years were downloaded as a .csv file which then
has been directly imported into the IHA database for starting the
statistical analysis. Then, for each of the 32 hydrologic parameters,
the differences between the pre- and post-impact time periods in both
the mean and coefficient of variation are presented, expressed as both
a magnitude of difference and a deviation percentage (Table-3). These
comparisons of means and coefficients of variation for each of the 32
parameters comprise the 64 different Indicators of Hydrologic
Alteration. Approximate confidence limits are also estimated for the
difference between means and CV, respectively (Table-3), using standard
formulae that are approximately valid when distributions are not Normal
or change (e.g., have unequal variances) between time periods (Snedecor
& Cochran 1967; Stewart-Oaten et al. 1992) .
Results & Analysis
The flow data for years 1956 to 2005 as obtained from the webpage of
NRFA have units in cms (cubic meters per second) and the same were
imported into the IHA model without any unit conversions. The impact of
the Wimbleball reservoir, if any, may only be expected to show shifts
in hydrological profile in and around the monitoring station, which is
strategically located to record river conditions just in the
down-stream of the Wimblebal discharge or regulation point. The period
of impact then shall begin with the year 1979, the year when the
reservoir was commissioned.
The IHA results for the Exe-river are given in Tables-(3-5) and
represented in Figures-(1 to 8). As revealed from the tables and
figures, the relative differences between means ranged from -53%
(annual 1-day maximum flow) to +135% (low pulse counts) for the
individual attributes, while the average absolute difference for the
five groups ranged from 11% (Group 1: monthly means) to 96% (Group 4:
frequency and duration of pulses). For individual attributes, the
relative difference in CV ranged from -60% (mean August flow) to +72%
(mean April flow); the range for the five groups was 26% (Group 4:
frequency and duration of pulses) to 41% (Group 3: timing of extreme
events).
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