The
relationship between Lamb weather types and long-term changes in flood
frequency, River Eden, UK
Abstract:
Research has found that both flood magnitude and
frequency in the UK
KEY WORDS historical floods;
trends; weather types; flood frequency; flood magnitude
1.
Introduction
Flood risk is becoming an
increasingly important issue in northwest Europe in general and in the UK England
Severe flood events have been reported for the
UK in the spring of 1998 (central England) (Horner and Walsh, 2000), autumn
2000 (Sussex and Yorkshire; Kelman, 2001; Marsh and Dale, 2002;), autumn 2004 (Boscastle;
Golding et al., 2005; Roseveare and
Trapmore, 2008), winter 2005 (Carlisle; Environment Agency, 2006), summer 2007
(central and northern England; Marsh and Hannaford, 2007; Marsh, 2008), autumn
2008 (northern England; Wilkinson et al.,
2010) and autumn 2009 (northwest England; Eden and Burt., 2010). It has been
suggested that recent decades have seen more frequent and higher-magnitude
river flow extremes (Wheater, 2006) and that we are now in a flood-rich period
(Macdonald, 2006; Lane, 2008).
The apparent increase in flood events, however,
needs to be evaluated to assess whether or not it represents a long-term trend
or simply shorter-term variability. Robson (2002)
analysed both local and UK river flood series and found that there was an
increasing trend over the past 30–50 years, emphasising that assumptions of
stationarity in flood frequency analyses need to be questioned (Milly et al., 2008). Furthermore, there seems
to be a pattern and clustering of the worst flood events rather than a random
occurrence (Wheater,
2006),
perhaps related to shorter-term climatic variability. Others have reached the
same conclusion with respect to smaller regional datasets. For example,
Scotland has seen an increased river flood frequency since 1988, with new
maximum discharges recorded for many rivers, especially in the west (Black,
1995; Black and Burns, 2002; Werritty, 2002).
In relation to Europe, Brazdil et al. (2006) notes the large number of
flood events throughout central Europe in the last two decades; Rhine/Meuse in
December 1993 and January 1995; Biescas (Pyrenees) in August 1996; Morova/Oder
in July 1997; and the Elbe in August 2002. However, although many studies have
investigated flood frequency (Kundzewicz and Robson, 2004; Lindstrom and
Bergstrom, 2004; Radziejewski and Kundzewicz, 2004; Kundzewicz et al., 2005; Svensson et al., 2005), finding statistically
significant general trends has been more difficult. This is likely to be a
consequence of the low frequency of extreme events, meaning that long records
are needed to have the required number of events to identify statistically
significant trends. There are examples of historical flood records that suggest
periods of greater flood occurrence than others. Barriendos et al. (2003) investigated the
stationarity assumption for flood records in France
and Spain Germany Europe experienced increased flooding frequencies in the
18th century, which has been hypothesized to have been caused by the Late
Maunder Minimum period. Macdonald (2006) found that this observation was not
present in the UK UK
These studies aside, there have been relatively
few assessments of both the extent and timescales of flood clustering, and even
fewer assessments of what might drive them. This paper explores the extent and
timescales of flood clustering for a 2400 km2 river catchment in northwest England , the River Eden at Carlisle ,
combining the shorter-term gauged record with longer-term historical data to
construct a flood record for the last 240 years. It then tests the first
hypothesis that the flood record can be divided into relatively flood-rich and
relatively flood-poor periods.
The link between weather systems and
hydrological flows, particularly extremes (floods and droughts) has been
investigated by a few studies. Higgs (1987) investigated the link between
weather types and floods for the River Severn at Bewdley, using a 101-year
record. Zonal (westerly) weather systems were found to be associated with the
highest-magnitude floods. Rumsby and Macklin (1994) studied the flooding frequency
and magnitude of the River Tyne, considering weather types as a controlling
factor. Major floods were found to be linked to meridional circulation
(easterly weather types), while more moderate floods occurred in periods when
zonal weather systems dominated (westerlies). A possible explanation for this
was through the high-amplitude waves associated with meridional circulations,
which are linked to situations when high pressure causes blocking of
depressions, leading to long-duration, high-intensity precipitation. A further
study by Rumsby and Macklin (1996) compared the western Severn catchment, with
the eastern Tyne catchment. The west of England is more susceptible to zonal
precipitation (westerlies), while the northeast of England
is in the rain shadow of the Pennines, so receives more precipitation from
meridional (easterly) weather systems which absorb moisture over the North Sea . Grew (unpublished) used daily weather system
classifications, unlike the previous studies which used monthly or annual
categories, for 130 peak over threshold (POT) series in Scotland Scotland Yorkshire . Westerly, cyclonic, cyclonic westerly
and southwesterly weather systems were found to have caused 79.7% of the floods
in the flood record since 1875.
Expanding the spatial scale to include the
weather types that cause floods in central Europe
has found that similar weather types are also regionally important. However, a
different weather type classification is used in Europe ,
the Grosswetterlagen (Baur, 1944), which has 30 classes under 3 main headings
of zonal (westerly), mixed and meridional (easterly). Kastner (1997) found that
only 5 of the 30 circulation types caused floods in Bavaria ,
while Petrow et al. (2007) found that
19 of the 30 caused floods in the Mulde catchment, Germany Gulf of Genoa , and therefore is characterized by a warm and
moist air mass, which leads to high precipitation in the Alps .
A continental-scale study of 488 catchments in Europe
by Prudhomme and Genevier (2010) found that the cyclonic westerly weather type
occurred more frequently before and during a flood event than the annual
average.
At a larger scale, the link between weather
types and atmospheric processes and circulations has been investigated. For the
UK UK UK Europe . Fowler and
Kilsby (2002) found a positive correlation between the NAO and the
precipitation quantities in the west of the UK UK
2.
Methodology
2.1. The Eden
catchment and flooding in the city of Carlisle
The Eden Eden Carlisle
2.2. Short-term gauged record
It was possible to obtain a recent gauged record
of river flows for the Sheepmount gauging station in Carlisle
(Figure 1) which opened in January 1967. Digital records begin in 1976 and the
station is still operating. Here, event frequency and magnitude trends are
analysed using POT and annual maxima (Amax) series respectively for two scales
of high-flow event. The number of events per hydrological year that exceeded
the Q1 value (347 m3s–1), which was calculated from the
digitized record for 1976–2007 was determined. This threshold was chosen to
represent the full range of high-flow events in the Eden
To provide information on a second scale of
event, the Q1 events were also separated into high flows (347 m3s–1
<Q <500 m3s–1) and extreme flood events (Q
>500 m3s–1). The extreme flood threshold was
determined using a previous study by Smith and Tobin (1979) of long-term
flooding in Carlisle . Smith and Tobin (1979)
calculated the return period of floods in the 1800–1970 period. The return
period of the 1968 flood was found to be 42.75 years using the historical
record, which is comparable to the 38.5 years calculated by the North-West
Water Authority (Smith and Tobin, 1979). The discharge of events recorded in
the British Chronology of Hydrological Events database and Smith and Tobin were
found at Warwick Bridge
Annual maxima series record the largest
instantaneous flood peak in each hydrological year (Svensson et al., 2005). The major advantage of
this approach is that data are easy to extract, but insignificant flows can be
included in the record, if a year was particularly flood poor. Thus, the peak
discharge of each POT event was also considered. Records were extended back to
1967 using the POT Hiflows database (www.environment-agency.gov.uk/hiflows).
2.3. Creating a longer-term
extreme high-flow record
Past research has shown the risks of concluding
the presence or absence of trends in short-term gauged records. There have been
several recommendations (Table I) as to the minimum required record length,
ranging from 10 to 50 years reflecting the problem that what can appear to be a
trend in a short-duration record may actually be shown to be fluctuation in a
longer data record (Robson, 2002; Kundzewicz and Robson, 2004; Dixon et al., 2006) and be associated with
spurious trends (e.g. Konrad and Booth, 2002). For instance, Hisdal et al. (2001), for a single station,
found significant positive and negative trends in annual flood maxima as a 30-year
moving window was applied to the record. Robson (2002) shows that shorter
record lengths are more susceptible to edge effects, when periods that have
several floods or few floods at the beginning and/or end of the record
influence the strength of the trend. Hannaford and Marsh’s (2007) benchmark
dataset for UK records had an average length of 33.7 years reflecting the fact
that much of the UK gauging station network was commissioned in the 1960s and
1970s (Lees, 1987).
Given the possibility that the 40-year record
(1967–2007) is too short to reliably detect trends in the dataset, a longer
timescale extreme flood record was constructed for the River Eden at Carlisle , using multiple sources of information. First,
the British Chronology of Hydrological Events (Black and Law, 2004) was used.
As of October 7th 2010, it listed 126 (some repeated) extreme flood records for
the River Eden. For copyright reasons, records generally cover the period
before 1931, although for the Eden
Second, newspaper reports from the Carlisle
Patriot, Carlisle Journal, Cumberland News, Evening News and Star, and the
Carlisle Directory were used to identify extreme flood occurrence. Some of the
records give specific details, such as a quotation, while others just list the
event and source. Third, extreme flood levels recorded on Eden
Bridge in Carlisle
by indentations with associated years indicate the peak flood water stage. Markings
are present for the 1822, 1856, 1868, 1925, 1952, and 1968 floods. The level of
the January 2005 extreme flood event was one metre higher than the highest
previous mark. Such marks need to be assessed for their originality, by
checking the age of the structure on which they are preserved (Brazdil et al., 2006). Eden Bridge
Finally, Smith and Tobin (1979) ranked 49 major
known extreme floods at Carlisle between 1800
and 1968 according to the approximate extent of flooding. Â This was an important source of information as
it allowed the threshold for extreme floods to be standardized between the
different sources and timescales of the floods. The British Chronology of
Hydrological Events only recorded floods up until 1931, while gauged data
starts in 1959 at Warwick
Bridge Warwick Bridge Warwick Bridge Carlisle showing the source of the information. The
reliability of the flood record increases with time due to better gauging and
recording of events. However, it is believed that the post-1800 record includes
most of the actual events. This is because multiple sources of information have
been used to derive the record.
2.4. Atmospheric drivers of
flood events
The weather in the UK UK UK
There are several advantages to using a weather-type
classification to investigate multivariate climatological factors: (1) The
classes are simple and easy to use; (2) The length of the record allows for
long term trends to be investigated; and (3) They are based on physical
linkages between the climate (large-scale processes) and weather patterns
(local scale). However, there are several limitations in the use of these
classifications (O’Hare and Sweeney, 1993). First, there is an issue regarding
the balance between number of classes and ease of use. The seven Lamb weather
types were thought to be too simplistic, so Jenkinson and Collinson (1977)
added another 20 classes. This allowed the UK UK UK
weather types these classifications are of the UK UK
The methodology used aims to identify links
between the objective lamb weather types and events of different magnitude
(>Q1 events (high flows) and extreme floods) for the gauged period and
consisted of the following steps. First, the objective Lamb Weather-Type
dataset was sourced (www.cru.uea.ac.uk/cru/data/lwt),
which starts in 1880 and continues to the present day. The weather type on the
day of each >Q1 event was extracted from the dataset, along with the weather
classification on the previous two days. As the Eden is quite a large catchment
(2400 km2), the number of days of precipitation that result in a
high flow or extreme flood events downstream may be more than just the day of
the event. Grew (unpublished) stated that the number of days of precipitation
is dependent upon the specific catchment characteristics, including area and
gradient. The relative time between the peak flow in the Upper Eden (Kirkby
Stephen) and the Lower Eden (Sheepmount), has
a maximum lag of 34.5 h, and a mean lag time of 12 h. The delay between
precipitation and a peak flow occurring will increase this response time
further. Longfield and Macklin (1999) devised a method using daily rainfall
records to assess the number of days responsible for flood generation. The
previous four days were included and each day given a weighting dependent upon
the amount of rainfall. The objective Lamb weather type on the day with the most
rainfall was taken as the dominant synoptic system that caused each event. However,
we focus on the sequencing of weather types. In this study, the weather types
on the previous two days as well the day of the event are assessed. First, each
day is looked at separately; and second, the sequence of days is investigated.
 Event-generating
weather types were then identified from this dataset, as the weather types that
occur most frequently on days, and this was undertaken for both >Q1 and
extreme flood events. The weather types that occur on >Q1 events were
compared with those associated with extreme flood events. Trends in the extreme
flood-generating weather types are then investigated over the historical
timescale by calculating the percentage of each hydrological year for the
extreme flood-generating weather types both individually and combined. The
average of the 1880–2007 period was calculated, then the average was subtracted
from each hydrological year. This means that positive values represented years
which had a greater-than-average proportion of the year with these extreme
flood-generating weather types, while negative values had less than the
average. The cumulative was then calculated for the deviations from the average
and can be plotted against time. This plot is a means of visualising the
sequencing of flood-generating weather types. A period when the deviation is
trending from negative to positive suggests a greater number of
flood-generating weather types. The longer the period of this trend, the
greater the length of the period when more flood-generating weather types have
been present than average. If we imagine a flood-generating weather type as one
that may, but that does not necessarily, produce a flood, then the longer a
positive trend, the more likely it might be expected to identify a flood in the
flood series.
3.
Results
3.1. Gauged records
Figure 2(a) shows that the late
1960s and 1970s were relatively poor in terms of >Q1 flow events, with fewer
than the average number of events per year every hydrological year except 1967–1968
and 1974–1975, which were the years with the most events in the entire record. Events
>Q1 occurred in every year except 1995–1996, a year of hydrological drought.
The Pearson’s product moment
correlation coefficient
of the number of >Q1 events over time for Sheepmount is
only 0.07, which is not statistically significant (p = 0.42). Of the 138 >Q1 events since 1967, 31% were classified
as extreme flood events. The largest number of extreme flood events in a hydrological
year is 4, and occurred in 1967–1968, 1981–1982, and 2003–2004. There are also
no statistically significant trends in either non-extreme >Q1 (r = 0.01 p = 0.93) or extreme flood (r
= 0.19 p = 0.22) events over the
gauged period at Sheepmount.
Figure 2(b) shows the annual maximum flood for
the River Eden at Carlisle (Sheepmount) and
indicates a wider range in the magnitude of the annual maximum flood. The most
extreme flood was in January 2005 with a magnitude of 1516 m3s–1,
with other notable extreme floods in 1968, 1981, 1985, and 1995. Annual maximum
flows which are below the extreme flood threshold we are using (500 m3s–1)
are highlighted in grey (34% of hydrological years). The lowest AMax magnitude
for Carlisle (Sheepmount) was 291 m3s–1
in 1995–1996, although years without extreme floods seem to have occurred in
the 1970s more than at present. A second, more robust approach used to assess
the frequency and magnitude of extreme floods considers the magnitude of the
events that exceed the >500 m3s–1 extreme flood
threshold (Figure 2(c)). However, there are also no statistically significant
trends in this record. In conclusion, the short-term records do not exhibit any
statistically significant trends in either high flow or extreme flood frequency
or magnitude for the River Eden at Carlisle . Â However, as Kundzewicz and Robson
(2004) notes that a failure to identify significant trend does not necessarily
mean that there is not one, especially given the relatively short duration of
the record used here.
3.2. Historical flood record
for Carlisle
Figure 3 shows the cumulative number of extreme
floods (>500 m3s–1) since 1770. The periods on Figure
3 where the gradient of the line is steep indicate flood rich periods. Times
when the line is flatter are flood poor. It appears that there are three flood-rich
periods over the past 240 years: (1) 1873–1904; (2) 1923–1933; and (3) 1994
onwards, each separated by periods which were relatively flood poor, which have
been classified visually. The years with the most extreme floods are 1877 and
1891, with 5 recorded in these years. The period before 1850 has very few
extreme floods, which may be due to the lack of evidence for them occurring,
rather than a lack of existence. However, it is assumed that the largest events
have been recorded. The magnitude of the largest events have been estimated by
the Environment Agency (2006). Bankfull discharge at the Sheepmount station is
1434 m3s–1, and only the 2005 event exceeded this
threshold. However, floodplain inundation occurred in all the events recorded
in the British Chronology of Hydrological Events database, which has an
approximate threshold of 500 m3s–1.
3.3. Weather types for instrumented period
floods
Using the Objective Lamb Weather Types, it was
found that 11 of the 25 weather types have caused extreme flood events in the
gauged periods (1976–2007 at Sheepmount), of which 5 (cyclonic = 27.3%, westerly
= 15.9%, southwesterly = 15.9%, cyclonic southwesterly = 6.8%, cyclonic westerly
= 15.9%) accounted for 81.8% of the extreme flood events (Figure 4). These
results are similar to the findings of Longfield and Macklin (1999) for the
Yorkshire Ouse Catchment, where four circulation types (W, C, CW and SW)
accounted for 79.7% of all events (and the same 5 weather types caused 82.6% of
flood events in the Ouse record). These particular weather types highlight the
importance of both cyclonic weather types and weather systems from a westerly
and southwesterly direction to both high flows and extreme floods occurring in Carlisle . Cyclonic weather systems are likely to cover a
greater spatial area and lead to a more coherent catchment response. Furthermore,
as they are not prescribed a direction, this means that they are often blocked
by other air masses, meaning they are stationary, resulting in a prolonged
rainfall event. Several studies have found that these weather systems are of
notable importance in accounting for precipitation in this region (Malby et al., 2007) and the UK
Figure 5(a) indicates that the common weather
types on the two preceding days are the same as the ones on the day of the
event itself for extreme events. However, the order of importance of the five
dominant weather types is different for the preceding days than the day of the
extreme flood itself. While cyclonic weather systems are the most common on the
day of the event, weather systems from a southwesterly (38% on previous day,
25% on two days before) and westerly (20.4% on the previous day, 25% on two
days before) direction are the most common on the two preceding days. Cyclonic
weather systems are less common on the days previous to an event occurring
(15.9% on previous day, 9.1% on two days before). Furthermore, cyclonic weather
systems from a westerly and southwesterly direction are also less common on the
days prior to an event.
The sequencing of the weather types may also be
important in causing extreme floods, as they control the antecedent conditions
of the catchment. This has been assessed in terms of whether or not the
previous two days and the day of the event were classified as an event-generating
weather type (C, W, SW, CW, and CSW). Table II shows that 47.7% of extreme
floods have had event-generating weather types on both the day of the event and
the previous two days, while a further 27.3% of extreme flood events occurred
on days with both the day of the event and the day before classified as an
event-generating weather type. Only one extreme flood since 1976 occurred when
none of the three days were classified as one of the extreme flood-generating weather
types. No extreme floods occur in sequences where just the day of the event is
an event-generating weather type (1 0 0).
None of these analyses takes account of the
proportion of the year associated with each weather type. Therefore, Figure 6
shows the percentage of the 1976–2007 period classified as each weather type. Anti-cyclonic
and cyclonic weather systems dominate, accounting for 20.7 and 13.8%,
respectively, for the whole period, and 21.1 and 13.0%, respectively, of the
last 40 years. Weather systems from a southwesterly and westerly direction also
have a high frequency individually, as well as for anti-cyclones and cyclones.
The likelihood of a particular weather system
causing an event can be determined by dividing the number of events occurring
on days of a particular weather type by the total number of days of the same
weather type over the same period. Figure 7 shows that the most likely weather
type to cause an extreme flood in Carlisle is the Cyclonic Westerly, with a
2.6% chance of an event occurring on a day with this weather system over the UK
3.4. Comparison of high flow and extreme flood
event-generating weather types
Figure 4 shows that 10 of the objective Lamb
weather types have occurred on days of high flows, and the same 5 weather types
account for 93.6% of the days when high flows occur (cyclonic = 34.0%, westerly
= 19.1%, southwesterly = 17.0%, cyclonic southwesterly = 12.8, cyclonic westerly
= 10.6%) A Chisquare test showed that the weather types that cause extreme
floods and smaller-magnitude high flows are statistically similar (p = 0.32). The weather types on the
preceding two days are also similar for both high flows and extreme flood
events (Figure 5(a) and (b)). This is significant because it means that weather
types cannot be used to distinguish between the magnitude of the event that
might occur: whether a high flow or an extreme flood. Furthermore, the
sequencing of weather types show no significant (Chi-square test p = 0.99) difference for events of
differing magnitude, with high flows and extreme floods showing similar
percentages for each sequence.
3.5. Weather types for the historical
period
The relationship between weather systems and
extreme flood frequency will now be investigated over a longer timescale. A few
previous studies have looked into how weather type frequency has changed over
approximately the last 100 years (Lamb, 1972; Jones and Kelly, 1982; Briffa,
1990; Sweeney and O’Hare, 1992; Fowler and Kilsby, 2002; Malby et al., 2007). Many of these
investigations reported a decrease in the number of westerly days since the
1950s, while cyclonic and anti-cyclonic weather systems have become more common
since the 1980s. The focus here is those weather types are found to produce
most of the extreme flood events in the recent gauged period.
Figure 8 shows the cumulative number of extreme
floods (>500 m3s–1) since 1880, superimposed upon the
cumulative deviation of flood-generating weather types. The periods in Figure 8
where the gradient of the line is steep indicate flood-rich periods. Times when
the line is flatter are flood poor. In relation to flood-generating weather
types, it is clear that there are a number of scales of variability. At the
largest scale, there are two periods of generally positive trend, with the
exception of short breaks in this trend: 1902–1938 and 1983–2007; before 1902
there was a dominant negative trend; and between 1938 and 1983 there were
shorter periods of negative and positive trend. Thus, Figure 8 shows that flood-generating
weather types are not randomly located in time but clustered into periods when
there are generally more than average and generally fewer than average. The
association between these weather type patterns and the cumulative flood record
is interesting. For both the periods of 1902–1938 (until 1931) and 1983–2007,
the cumulative flood records are weak positive exponentials suggesting that as
the duration of generally positive deviations becomes longer, and the number of
flood-generating weather events in the positive sequence becomes greater, so
there are more floods. This does not require a mechanism like land use change
or groundwater recharge (which for the Eden is important but not that much so –
the Base Flow Index is 0.498), but is a result of clustering of
flood-generating weather types, which in turn increases the probability that
one of these weather events becomes a flood, and so, leads to an increase in
the number of floods. Similar overall trends are shown in historical rainfall
records (e.g. for Lockwood Reservoir; Fowler et al., 2002). Of course, it is also possible that the objective
Lamb weather-type classification misses some climatic signals, such as
precipitation intensity or quantity, as it is only a broad categorical system.
Figure 9 shows how the proportions of individual
weather types per year change over time. Firstly, the cyclonic-westerly (Figure
9(a)) weather system does not vary significantly from the average, with only a
range of 4.9% (0.6–5.5%). Also periods with more cyclonic-westerly weather
systems do not correlate well with the periods of increased extreme flood
activity in the Eden
4.
Discussion
If the latter part (post-1965, the start of the
gauged record) of Figure 3 is analysed, then it could be concluded that there
is a unidirectional trend of increasing extreme flood frequency in Carlisle,
that starts with very few floods during the late 1960s, a rising number of
floods until the early 1990s, and a very rapid rise after that into the flood-rich
period from 1994 to 2007. However, when put into the historical period context,
it becomes clear that there is not a unidirectional trend and that the period
since 1994 has been flood rich, but so have other periods. Several other
studies have identified flood-rich and flood-poor periods in historical flood
records (Grew and Werritty, 1995; Werritty et
al., 2002; Macdonald, 2006; Macdonald et
al., 2006; McEwen, 2006). These examples, along with the River Eden,
indicate that there are flood clusters throughout the historical period. However,
a conclusion from Macdonald (2006) was that these flood-rich periods are not
nationally synchronous, which indicates that regional climatic variability and
catchment-specific characteristics are important in controlling flooding
frequency. Possible reasons why flooding may not be recorded as regionally
synchronous may be that; (1) There is an absence of extreme flood event
recording in the documentary evidence; or (2) There are different causal
mechanisms for extreme flood generation in different river catchments. However,
it has been found that high-magnitude floods can transcend catchment
boundaries, depending on the precise forcing mechanisms and antecedent
conditions. The 1771 floods occurred in both the Rivers Eden and Tyne (Macdonald (2006), and there were floods on both the
River Severn and River Trent in 1796. Furthermore, along with the flood event
on the River Eden in January 2005, the River Tyne also exhibited flooding
(Archer et al., 2007a, 2007b). The
storm event which caused this flooding extended from the 6th to 9th January
2005 and affected northern England ,
southern Scandinavia , Germany
The presence of flood-rich and flood-poor
periods throughout the historical period has implications for the concept of
stationarity. This assumption states that natural systems fluctuate within an
unchanging range of values. However, as Milly et al. (2008) stated it has been compromized by human disturbance,
natural climate change, and variability. They go on to say that the assumption
of stationarity is dead and cannot be revived. Through analysing historical
flood records, it could be concluded that stationarity in flood frequency has
never existed, as floods have tended to cluster within certain periods
separated by flood-poor periods. Therefore, the range of behaviour of the
system depends on the timescale over which it is analysed. If the post-1960
period is analysed without the context of the historical period, then it could
be concluded that the behaviour that we are seeing today is unprecedented. However,
if the whole period is analysed then it can be concluded that today’s flood
frequency is not out of the range of past flood occurrence, suggesting a more
stationary behaviour. However, the presence of flood clustering means that
there is a variable chance of a flood occurring in every year of the record.
This raises a problem for flood frequency studies, as using short records will
not capture flood variability (Bardossy and Pakosch, 2005), while using longer
time series does not reflect stationary conditions, invalidating the
assumptions of standard frequency analysis (Khaliq et al., 2006).
This study has highlighted the importance of
cyclonic and westerly weather types, along with previous studies (Longfield and
Macklin, 1999). However, a recent study by Macdonald et al. (2010) for Wales
found that the link between westerly (SW, W, NW) weather systems and flood
occurrence only is statistically significant for northern Wales Wales Wales Britain
In addition, weather types and their link
to flood risk have been investigated over longer timescales. Brazdil et al. (2006) states that knowledge of
synoptic patterns for recent flood events can help explain past flood event
occurrence. It is this assumption that this study has made, using the last 40
years to define extreme flood-generating weather types and then looking at
their frequency over the historical period. This study has established a
possible link between the proportion of the year defined as an extreme flood-generating
weather type and extreme flood frequency. However, this analysis assumes that
the weather types that cause extreme flooding has not changed over time. The
weather types that have caused floods during the last three decades (1978–1987;
1988–1997; and 1998–2007) have been analysed to assess this assumption. Figure
10 shows that the weather types that result in extreme floods have changed from
the first decade, when two forms of anticyclonic weather types caused extreme
floods (A, AS) to CSE and CS in the last decade. In terms of the high-flow
events, the importance of the cyclonic weather type has nearly doubled from the
1978–1987 to the 1998–2007 period. However, the dominant weather types (5
extreme flood-generating weather types) have not changed over the 30-year
gauged period. Furthermore, it has been shown that the weather types that cause
both high flows and extreme floods have not changed statistically over the
decades (ANOVA p = 0.816). Malby et al. (2007) found that for the Eden
catchment, southwesterly and
westerly weather systems contributed the most to the decadal precipitation
totals. Furthermore, winter rainfall delivered by these weather systems has
increased over the last 30 years. Specifically, the precipitation associated
with each westerly weather system has increased between the 1970s and the 1990s
for 5 rainfall gauging stations in the Eden catchment. The quantity of rainfall
supplied by southwesterly weather systems was highest in the 1980s. Jacobeit
et al. (2003) found that a broader
range of circulation modes are important if studies are extended back into
historical periods.
The periods of a greater proportion of the year
than average of the five extreme flood-generating weather types correlate with
the flood rich periods. Furthermore, they match the periods identified by Wilby
et al. (1997) as periods when the NAO
was in a strong positive phase. Jones et
al. (1997) found a strong correlation between the NAO index and westerly
weather systems, which is one of the extreme flood-generating weather types. Wedgbrow
(2002) found a lag between the changing NAO index and the change in UK weather.
This was hypothesized to be caused by either climatological memory effects,
such as seasonal patterns, or hydrological memory effects, for example,
groundwater levels or antecedent moisture levels. This study has also found a
lag between the increase in the proportion of the year classified as one of the
five extreme flood-generating weather types and the increase in flood
frequency. This would seem to be expected due to the ‘chain of causality’
(Lawler et al., 2003) whereby the
link between large-scale atmospheric forcings, such as the NAO, are spatially
scaled down to their catchment effects, through the weather types and the
amount of precipitation which occur.
5.
Conclusion
Various event frequency and
magnitude indices have been used to investigate trends in both high flows and
extreme floods. First, the gauged record at Sheepmount, Carlisle (1967–2007),
was used to define the threshold of a high-flow event, which was taken to be
the Q1 value of 347 m3s–1. Extreme floods were defined by
a threshold of 500 m3s–1, to allow compatibility with the
longer-term Smith and Tobin (1979) study. The gauged record showed that,
although the 1960s and 1970s seemed >Q1 event poor in comparison to more
recent decades, there were no statistically significant trends over time. This
was also the case when the non-extreme >Q1 and extreme records were
considered separately. The annual maximum series showed that two thirds of
years experienced an extreme flood. There were more annual maximum events which
were less than 500 m3s–1 (high flows only) during the
1970s than at present, although again these trends were not statistically
significant. Multiple sources of documentary and epigraphic evidence were used
to compile an extreme flood record from 1770 to 2007. This showed that extreme
flood events have clustered in time, and 3 flood-rich periods were defined as
1873–1904; 1923–1933, and 1994–2007.
The Lamb weather types that occurred on the days
of extreme flood days (1976–2007) were extracted, and it was found that 11 out
of the 25 weather types have caused extreme floods in the gauged period. Of
these, 5 have caused 81.8% of extreme floods. These were cyclonic, westerly, southwesterly,
cyclonic-westerly, and cyclonc wouthwesterly. It was shown that there was no
statistically significant difference in the weather types that occur on days
with either high flows or extreme floods. The same five weather types were more
likely to occur on the previous two days before extreme flood events. The
sequencing of weather types was also found to be important, with ~50% of
extreme floods and high flows occurring after sequences of 3 days of the 5
event-generating weather types. However, the sequencing of days was not
statistically significant in determining whether an extreme flood or high flow
occurred. This means that weather types cannot be used to distinguish between
the magnitude of the event which might occur: whether a high flow or an extreme
flood.
The proportion of each hydrological year of the
five extreme flood-generating weather types was calculated. It was found that
there are two periods when the proportion of the year is less than the average
for a sustained period; 1902–1938; and 1983–2007. These were shown to correlate
with the flood-rich periods, although a lag existed between the increase in the
extreme flood-generating weather types and flood frequency increasing. These
periods also match with Wilby et al.
(1997) periods of a strong positive NAO index. Thus, the analysis suggests that
systematic organisation of the North Atlantic climate system, which drives the
weather types experienced by the UK, may be manifest as periods of elevated and
reduced flood risk, an observation that has major implications for analyses
that assume that climatic drivers of flood risk can be either statistically
stationary or are following a simple trend.
Acknowledgements
Ian Pattison was funded by the Environment
Agency and United Utilities as part of the EU Interreg IVB project ALFA (http://www.alfa-project.eu)
and acknowledges additional support from Durham University and the Eden Rivers
Trust. Two anonymous reviewers and the editor (Glenn McGregor) provided
valuable and constructive comments on an earlier version of this manuscript.
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Figure 1.          Map of the Eden Catchment.
Figure 2. Gauged records from the Eden at
Sheepmount in Carlisle (a) POT; (b) AMax; (c) Magnitude of POT events.
Figure 3.          Cumulative
number of extreme floods as a function of time.
Figure 4.          Percentage of floods since 1978 which
have occurred on days of particular Lamb weather types.
Figure 5.          Percentage of floods which have
occurred on days and preceding days of particular Lamb weather types: (a) high
flows; (b) extreme flood events.
Figure 6.          Percentage of the year classified as
each Lamb weather type for the 1976–2007 period.
Figure 7.          Probability
that a day with a particular Lamb weather type will also have an >Q1 event
occurring.
Figure 8.          Plot
showing how the proportion of the year classified as the five extreme flood-generating
weather types and extreme flood frequency have changed over time (dashed line
represents the cumulative extreme flood record, solid line represents weather
types).
Figure 9. Plot showing how individual extreme
flood-generating weather types have changed over time: (a) CW; (b) CSW; (c) C; (d)
W; and (e) SWÂ (dashed line represents
the cumulative extreme flood record, solid line represents weather types).
Figure 10.        Percentage of floods since 1978 which
have occurred on days of particular Lamb weather types: (a) 1978–1987; (b) 1988–1997;
(c) 1998–2007.
Table I.           Summary of record length
requirements from the literature for identifying trends in flood records.
|
Reference
|
Record length needed to
identify trends
|
|
Interagency Advisory Committee on Water Data 1982
|
10 years
|
|
Richter et
al., 1997Â
|
20 years
|
|
Lettenmaier et
al., 1994; Lins and Slack, 1999; Douglas et al., 2000Â
|
at least 30 years
|
|
Gan et al., 1991; Huh et al.,
2005
|
at least 40-year records
|
|
Kundzewicz and Robson 2000, 2004
|
at least 50 years
|
Table II.        Percentage of events of each sequence
(day of event, day before, 2 days before) of event-generating weather types. 1
= event-generating weather type (C, W, SW, CW, CSW); 0 = day with another
weather type.
|
Sequence
|
% of extreme floods
|
% of high flows
|
% of all events
|
|
1
1 1
|
47.7
|
53.2
|
51.4
|
|
1
1 0
|
27.3
|
21.3
|
23.2
|
|
1
0 0
|
0.0
|
8.5
|
5.8
|
|
1
0 1
|
6.8
|
10.6
|
9.4
|
|
0
1 1
|
4.5
|
3.2
|
3.6
|
|
0
1 0
|
2.3
|
1.1
|
1.4
|
|
0
0 1
|
9.1
|
0.0
|
2.9
|
|
0
0 0
|
2.3
|
2.1
|
2.2
|
Â
Table
III. A complete record of the extreme floods in Carlisle showing the source of
the information.
|
|
BCHE
|
Newspapers
|
Epigraphic
|
Smith & Tobin
|
Warwick Bridge
|
Sheepmount
|
|
1771
|
Y
|
|
|
|
|
|
|
1773
|
Y
|
|
|
|
|
|
|
1781
|
Y
|
|
|
|
|
|
|
1783
|
Y
|
|
|
|
|
|
|
1794
|
Y
|
|
|
|
|
|
|
1794
|
|
Y
|
|
|
|
|
|
1803
|
Y
|
|
|
|
|
|
|
1804
|
Y
|
|
|
|
|
|
|
1808
|
Y
|
|
|
|
|
|
|
1809
|
Y
|
Y
|
|
Y
|
|
|
|
1809
|
Y
|
Y
|
|
Y
|
|
|
|
1815
|
Y
|
Y
|
|
Y
|
|
|
|
1815
|
Y
|
|
|
|
|
|
|
1818
|
|
Y
|
|
|
|
|
|
1821
|
|
Y
|
|
|
|
|
|
1822
|
Y
|
Y
|
Y
|
Y
|
|
|
|
1851
|
Y
|
Y
|
|
Y
|
|
|
|
1852
|
Y
|
|
|
Y
|
|
|
|
1856
|
Y
|
Y
|
Y
|
Y
|
|
|
|
1858
|
|
Y
|
|
|
|
|
|
1868
|
Y
|
|
Y
|
Y
|
|
|
|
1868
|
Y
|
|
|
|
|
|
|
1870
|
Y
|
|
|
|
|
|
|
1874
|
Y
|
|
|
|
|
|
|
1874
|
Y
|
|
|
|
|
|
|
1874
|
Y
|
|
|
Y
|
|
|
|
1875
|
Y
|
Y
|
|
|
|
|
|
1876
|
Y
|
|
|
|
|
|
|
1876
|
Y
|
|
|
|
|
|
|
1876
|
Y
|
|
|
|
|
|
|
1877
|
Y
|
|
|
|
|
|
|
1877
|
Y
|
|
|
|
|
|
|
1877
|
Y
|
|
|
|
|
|
|
1877
|
Y
|
|
|
|
|
|
|
1877
|
Y
|
|
|
|
|
|
|
1878
|
Y
|
|
|
|
|
|
|
1878
|
Y
|
|
|
|
|
|
|
1880
|
Y
|
|
|
|
|
|
|
1881
|
Y
|
|
|
|
|
|
|
1881
|
Y
|
|
|
|
|
|
|
1881
|
Y
|
|
|
|
|
|
|
1882
|
Y
|
|
|
|
|
|
|
1882
|
Y
|
|
|
|
|
|
|
1883
|
Y
|
|
|
|
|
|
|
1883
|
Y
|
|
|
|
|
|
|
1883
|
Y
|
|
|
|
|
|
|
1885
|
Y
|
|
|
|
|
|
|
1885
|
Y
|
|
|
|
|
|
|
1890
|
Y
|
|
|
|
|
|
|
1891
|
Y
|
|
|
Y
|
|
|
|
1891
|
Y
|
|
|
Y
|
|
|
|
1891
|
Y
|
|
|
Y
|
|
|
|
1891
|
Y
|
|
|
Y
|
|
|
|
1891
|
Y
|
|
|
Y
|
|
|
|
1892
|
Y
|
Y
|
|
Y
|
|
|
|
1894
|
Y
|
|
|
|
|
|
|
1895
|
Y
|
|
|
|
|
|
|
1896
|
Y
|
|
|
Y
|
|
|
|
1898
|
Y
|
|
|
Y
|
|
|
|
1899
|
Y
|
|
|
Y
|
|
|
|
1899
|
Y
|
|
|
|
|
|
|
1900
|
Y
|
|
|
|
|
|
|
1903
|
Y
|
|
|
Y
|
|
|
|
1903
|
Y
|
Y
|
|
Y
|
|
|
|
1903
|
Y
|
Y
|
|
|
|
|
|
1904
|
Y
|
|
|
|
|
|
|
1907
|
|
Y
|
|
|
|
|
|
1914
|
Y
|
|
|
Y
|
|
|
|
1914
|
Y
|
|
|
Y
|
|
|
|
1916
|
Y
|
|
|
Y
|
|
|
|
1918
|
Y
|
Y
|
|
Y
|
|
|
|
1921
|
Y
|
|
|
Y
|
|
|
|
1924
|
Y
|
|
|
Y
|
|
|
|
1924
|
Y
|
|
|
Y
|
|
|
|
1925
|
Y
|
Y
|
Y
|
Y
|
|
|
|
1926
|
Y
|
Y
|
|
Y
|
|
|
|
1926
|
Y
|
Y
|
|
Y
|
|
|
|
1927
|
Y
|
|
|
|
|
|
|
1928
|
Y
|
|
|
Y
|
|
|
|
1928
|
Y
|
|
|
Y
|
|
|
|
1929
|
Y
|
Y
|
|
Y
|
|
|
|
1929
|
Y
|
|
|
Y
|
|
|
|
1930
|
Y
|
|
|
Y
|
|
|
|
1931
|
Y
|
|
|
Y
|
|
|
|
1931
|
|
|
|
Y
|
|
|
|
1932
|
|
|
|
Y
|
|
|
|
1933
|
|
|
|
Y
|
|
|
|
1933
|
|
|
|
Y
|
|
|
|
1938
|
|
Y
|
|
|
|
|
|
1941
|
|
Y
|
|
Y
|
|
|
|
1945
|
|
Y
|
|
|
|
|
|
1947
|
|
Y
|
|
Y
|
|
|
|
1947
|
|
Y
|
|
|
|
|
|
1952
|
|
|
Y
|
|
|
|
|
1954
|
Y
|
|
|
Y
|
|
|
|
1954
|
|
Y
|
|
Y
|
|
|
|
1954
|
|
Y
|
|
Y
|
|
|
|
1954
|
|
Y
|
|
Y
|
|
|
|
1956
|
|
Y
|
|
|
|
|
|
1958
|
|
Y
|
|
|
|
|
|
1962
|
|
Y
|
|
|
Y
|
|
|
1964
|
|
Y
|
|
Y
|
Y
|
|
|
1965
|
|
|
|
|
Y
|
|
|
1966
|
|
Y
|
|
|
Y
|
|
|
1967
|
|
Y
|
|
|
Y
|
Y
|
|
1967
|
|
Y
|
|
|
Y
|
Y
|
|
1968
|
Y
|
Y
|
Y
|
Y
|
Y
|
Y
|
|
1972
|
|
Y
|
|
|
Y
|
Y
|
|
1979
|
|
|
|
|
Y
|
Y
|
|
1979
|
|
|
|
|
Y
|
Y
|
|
1982
|
|
Y
|
|
|
Y
|
Y
|
|
1985
|
|
|
|
|
Y
|
Y
|
|
1987
|
|
Y
|
|
|
Y
|
Y
|
|
1990
|
|
Y
|
|
|
Y
|
Y
|
|
1991
|
|
|
|
|
Y
|
Y
|
|
1991
|
|
|
|
|
Y
|
Y
|
|
1995
|
|
Y
|
|
|
Y
|
Y
|
|
1995
|
|
|
|
|
Y
|
Y
|
|
1997
|
|
Y
|
|
|
Y
|
Y
|
|
1997
|
|
|
|
|
Y
|
Y
|
|
1998
|
|
|
|
|
Y
|
Y
|
|
1999
|
|
|
|
|
Y
|
Y
|
|
1999
|
|
|
|
|
Y
|
Y
|
|
2000
|
|
|
|
|
Y
|
Y
|
|
2000
|
|
|
|
|
Y
|
Y
|
|
2000
|
|
|
|
|
Y
|
Y
|
|
2002
|
|
|
|
|
Y
|
Y
|
|
2002
|
|
|
|
|
Y
|
Y
|
|
2003
|
|
|
|
|
Y
|
Y
|
|
2004
|
|
|
|
|
Y
|
Y
|
|
2004
|
|
|
|
|
Y
|
Y
|
|
2004
|
|
|
|
|
Y
|
Y
|
|
2005
|
|
Y
|
|
|
Y
|
Y
|
|
2005
|
|
Y
|
|
|
Y
|
Y
|
|
2006
|
|
|
|
|
Y
|
Y
|
|
2006
|
|
|
|
|
Y
|
Y
|
|
2006
|
|
|
|
|
Y
|
Y
|
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