Who Benefits and Who Loses From Flood Risk Reduction

Environment and Planning C: Government and Policy 2012, volume 30, pages 448–466

doi:10.1068/c10208

Who benefi ts and who loses from fl ood risk reduction?

Edmund C Penning-Rowsell, Joanna Pardoe

Middlesex University, The Burroughs, London NW4 4BT, England;e-mail: [email protected]; [email protected] 7 December 2010; in revised form 9 October 2011

Abstract. The distributional eff ects of investment for the reduction of fl ood risk are

explored, with the UK as an example. Using three case studies, we initially investigate

the ‘gainers’ and the ‘losers’ from three contrasting engineering-oriented fl ood alleviation

and land drainage schemes, the results of which appear to show that property owners

at risk of fl ooding were the gainers and the general fl ood-free taxpayer was the loser.

An analysis of fl ood damages, however, shows that those losing work from repairing or

replacing fl ood damaged goods are a primary loser group as risk is reduced. Investigating

insurance cover for fl ooding (near-universal in the UK) also shows that the principal

real gainers appear to be insurance companies and their shareholders, since premiums

generally do not appear to fall as risk is reduced. The implication of these novel results are

evaluated both for the UK and, briefl y, for elsewhere in the world.

Keywords: fl oods, risk reduction, losers, gainers, insurance, recovery, case studies

IntroductionHazard reduction policy makers in many countries have generally taken as the criterion for their success the aggregate benefi cial effect of their policies on the population, property, and environments affected. Research over many decades has tended to follow suit, with an emphasis on the overall effectiveness of intervention measures (eg, Burby, 2000; Clark 1998; Cutter, 1996; Faisal et al, 1999; Platt, 1986; Schanze, 2006; Smith, 1981; Thorne et al, 2007; Werrity, 2006). The intervention strategies adopted have long been questioned, especially by geographers, both in the UK (eg, Parker, 2000; Penning-Rowsell et al, 1986; Smith and Tobin, 1979; Smith and Ward, 1998) and particularly in the USA (eg, Hewitt, 1997; Kates, 1962; Kates and Burton, 1986; White, 1973), but this questioning has focused mainly on a persistent critique of engineering-dominated approaches rather than on any systematic consideration of distributional effects.

This has meant that the issue of for whom these policy and practices are effective or effi cient—and therefore who gains and who loses—has rarely been raised and even more infrequently researched. The differential impact of hazard events themselves has often been noted as adversely affecting the poor more than the affl uent (Walker et al, 2003; 2004; Winchester, 1992); the aftermath of hurricane Katrina and the 2004 Indian Ocean tsunami have repeated these messages. However, with some notable exceptions (Scanlon, 1988; Ward, 2007), very little attention has been given to the distributional effects of hazard reduction measures, because economic analysis has driven decision making (MAFF, 1999) and economists generally ignore such effects (Green, 2003). For those implementing the necessary measures the question of who gains and who loses has also been of secondary interest (if considered at all) compared with effi cient risk reduction for society as a whole, perhaps because the source of their funding for most traditional engineering interventions has been national taxation rather than local benefi ciaries.

The situation is beginning to change, at least in the UK. First, the UK government has shifted its fl ood risk management (FRM) investment criteria towards a broader range

Who benefi ts and who loses from fl ood risk reduction? 449

of ‘outcome measures’ and a consideration of ‘payment for outcomes’, thereby including a ‘people’ dimension to complement the economic analysis (Defra, 2006a; 2007; 2010a; Johnson and Penning-Rowsell, 2010). They have also introduced, second, a system of differential social weights (Defra, 2004a). Third, UK FRM policy makers have become somewhat concerned about the ‘fairness’ of outcomes, not just their effi ciency (Defra, 2005; Johnson and Penning-Rowsell, 2010; Johnson et al, 2007). These are all useful initiatives in beginning to ask who gains from this investment, but there is little evidence that this has so far affected either the decisions that are made or what happens ‘on the ground’.

In pursuing these themes of the consequences and fairness of FRM, and with the UK as a case example, we investigate the distribution of the tangible economic impacts of FRM measures (Penning-Rowell et al, 2005). It is recognised that a multicriteria approach would be preferable, but these tangible economic impacts still dominate decision making and therefore outcomes (Environment Agency, 2010). We also focus on structural FRM options, because tackling the distributional consequences of both structural and nonstructural (‘nonengineering’) measures such as warning systems, building regulations (Johnson et al, 2004), or spatial planning (Pardoe et al, 2011) would introduce excessive complexity at this stage of this research’s development, and also because these engineering options also still remain dominant (Harries and Penning-Rowsell, 2011). But one such nonstructural measure is considered here—fl ood insurance—and we highlight this because it crucially affects the pattern and distribution of hazard impacts (ABI, 2002; 2008; Lamond, 2008).

The context: changing risk and policy arrangements Flood risk managers and their decisions obviously sit within a complex context affected by risk perceptions, policy directions, and expenditure trends. Regarding risk, fl ooding in the UK is no longer seen by a wide range of government and nongovernmental bodies as a trivial problem (Evans et al, 2004; Pitt, 2008). Large parts of England and Wales are judged offi cially to be at risk of fl ooding from rivers and the sea [approximately 11% of their land area (NAO, 2007)], and major fl oods in 1998, 2000, and 2007 have provided some corroborating evidence. In England, alone, some 2.1 million properties are considered to be in areas subject to some fl ood risk, affecting 4.3 million people (8.7% of the population) (Environment Agency, 2009). These totals exclude substantial areas at risk from fl ooding from inadequate sewerage in urban areas (Pitt, 2008) or from groundwater.

Owing to climatic and societal changes, risk also appears to be rising (Evans et al, 2004), and the policy response has recently been signifi cant. First, real increases in funding for investment for a wide range of FRM activities have been delivered. High levels are committed for the future, albeit somewhat lower than currently is the case, all ultimately paid for by national taxpayers routed through central government grants to the Environment Agency (EA) and local authorities. The sums involved are now not inconsiderable (fi gure 1).

In parallel, second, the government in England’s Making Space for Water (MSFW) (Defra, 2004b; 2005) and the Pitt Review (Pitt, 2008) have set out a revised policy agenda, a decade or more after the last initiative (Environment Agency, 1993). MSFW proposes to manage this risk with a portfolio of approaches which refl ect both national and local priorities, and “to deliver the greatest environmental, social and economic benefi t, consistent with the Government’s sustainable development principles” (Defra, 2005, page 15). The focus is on a more determined and integrated approach to risk management, with risk defi ned as the product of the probability and the consequences of fl ooding. A key point here is that this new emphasis on the latter component of risk naturally raises the question of “consequences for whom?”

450 E C Penning-Rowsell, J Pardoe

One area where these consequences for those at risk or experiencing fl ooding are now also treated differently is in fl ood insurance: here, too, there has been policy change. To ensure insurance cover remains widely available, the government agreed a ‘Statement of Principles’ (SOP) with the Association of British Insurers (ABI) that sets out the insurers’ commitment to maintain fl ood cover for the majority of domestic and small business properties in exchange for complementary commitments to the recently elevated levels of government investment in FRM (ABI, 2002; 2008). The SOP has distributional consequences in that, for example, it treats those at ‘signifi cant risk’ differently from others, and insurers are not obliged to insure new houses built in fl ood risk areas at all. The statement is up for replacement in 2013, and the outcome is as yet unknown, but the insurance industry is seeking moves towards a less-regulated regime that is likely to differentiate to an even greater extent between its various customers.

Other distributional effects are also being actively explored by government. HM Treasury’s (2003) Green Book urges that distributional impacts are explicitly stated and quantifi ed during investment appraisals. These principles have been embodied in Defra’s (2004a) supplementary appraisal guidance and the recent EA equivalent (Environment Agency, 2010). Disaggregated approaches to assessing FRM benefi ts have been trialled to identify more clearly who are the benefi ciaries from individual decisions (Defra, 2006b). Finally, social justice issues (Johnson et al, 2007; NERA, 2007) are also of growing concern, driven in part by worries that the economics-led investment appraisal regime leads to greater investment where communities are richest.

However, despite these far-reaching contextual changes, there remains no systematic information on the gainers and losers from this investment or the policy imperatives that drive it. Moves towards a ‘localism’ agenda after the UK General Election in 2010 will inevitably raise this issue, as will the proposed new system of payment for outcomes whereby investment contributions provided by local benefi ciaries will determine to some degree what those outcomes will be (Defra, 2010b). But the research base here is threadbare, and the growth in our understanding of the distributional consequences of modern FRM has been far outpaced by the rapidly changing context.

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Other public investment (local levy, contributions, Internal Drainage Board income, funding from the Department of Communities and Local Government for coastal maintenance)

Figure 1. Total central and local government expenditure on fl ood risk management (England) at 2008/09 prices (from Environment Agency, 2009).


Analytical framework At its simplest, the conceptual framework for the research reported here is one that sought to catalogue and map distributional effects by illuminating the links between the funding of FRM investment—and those who contribute to this funding—with those who directly or indirectly benefi t from that investment. To assist with this, we also seek to identify and evaluate the ‘conduits’ for the deployment of that investment—the institutions involved—and the measures that they and others use to create the risk reduction that underpins the generation of the benefi ts for the benefi ciaries. We have done this by, fi rst, examining three case studies and then, second, broadening our analysis to a wider national scene by examining both the nature of fl ood damages and the insurance arrangements that seek to compensate those affl icted by fl oods for the damage that they incur.

This analytical framework led to a number of questions that drove the information gathering in this research, including about the characteristics of the FRM policy or activity that we are examining, the likely impacts of these measures, and who are the funders of these measures. We were then concerned with who are the gainers and losers from these measures, the value of these gains and losses, and hence the distributional effects on the relevant different interest groups. Given the complexity here, we have also needed to identify the gaps in our knowledge and data that limit this analysis and thereby gauge how robust might be the results.

Owing mainly to data defi ciencies, not all these questions can be fully answered here, and nor can the core arguments about distributional effects be exhaustively explored, and in this respect the research reported here was exploratory. However, the fundamental question of who benefi ts (and loses) from FRM expenditure has not been posed in these terms before in the UK, or elsewhere, so an exploratory approach appears justifi ed.

Three contrasting case studies The case studies were not chosen to be ‘representative’ of typical FRM effort around the country, and as such should not be taken to illustrate national distributional patterns.

Following Yin’s (2009) multiple case exploratory methodology, they instead focused on contrasting risk situations to tease out a range of results: a south coast location subject to both fl ooding and erosion (West Bay, Dorset), a northern England city with a fl uvial fl ood risk (Carlisle), and a north country area where investment had aimed primarily to provide enhanced fl ood protection and drainage to agricultural land (the Lyth Valley, Westmorland) (HR Wallingford, 2008).

Methods Within the overall analytical framework the case studies used a mixture of methods, depending on the nature of the schemes that had been implemented, the data that were available, and whether key ‘actors’ were still in offi ce or in the locality. Thus farms and farmers were our concern in the Lyth valley; the harbour users and others at West Bay; and the institutions that responded to the fl ooding in Carlisle. Whilst the approaches were different, the focus was identical: the effect of the interventions and those affected.

The research also relied heavily on documentary evidence such as EA reports, including Project Appraisal Reports (PARs), and information from EA staff—for example, about current arrangements for maintenance expenditure. But fi eldwork was used in all cases to catalogue the impacts of the FRM expenditure on the ground, because in this fi eld much of ‘the devil is in the detail’. We conducted many interviews with key ‘actors’ (eg, the Harbourmaster and the caravan park owner at West Bay, and several local authority staff in Carlisle).

We also interviewed those who may have benefi ted indirectly from the investments, such as estate agents, property developers, and the consultants involved at West Bay. In all,


we undertook six detailed site investigations and conducted more than thirty-fi ve in-depth semistructured interviews and meetings (twenty face-to-face and ten telephone interviews for West Bay; six meetings in Carlisle; and two detailed fi eld surveys and associated meetings related to the Lyth Valley). The different sample sizes refl ect the different degrees of diversity in the target populations.

Carlisle, Cumbria Serious fl ooding in Carlisle in January 2005 affected approximately 1844 properties (including the fi re station, courts, and the Civic Centre). The impacts included 2 deaths from drowning, 70 serious injuries, 1925 homes and businesses fl ooded—some to 2 m in depth—at least 3000 people homeless for up to 12 months, 40 000 addresses temporarily without power, and 3000 jobs put at risk (Cabinet Offi ce, 2010).

Two engineering schemes have been promoted to alleviate this fl ooding, both a combination of bank raising and channel improvements. The fi rst, for the Eden and Petteril rivers, is largely protecting residential properties to a 1-in-200-year standard (the 2005 fl ood being estimated as a 1:170-year event). The second, for the Caldew catchment and Carlisle, is protecting housing and industrial estates to the same standard. Neither scheme ranked high in terms of national priority scoring (Environment Agency, 2008) but were planned and implemented as a result of media and political pressure on the EA following the 2005 fl ood.

Funding and cost The funding for the two schemes is from national and local taxpayers channelled through Defra and EA’s Grant in Aid scheme. The cost of the Eden and Petteril scheme was £13.4 million with minor contributions (~£65 000) by Carlisle City Council and Toby Inns (a restaurant and pub business) (Environment Agency, North West, 2005). Construction (77%), consultants (12%), and EA salaries (3%) made up most of the costs. The cost breakdown was anticipated in the PAR to be: labour 30%, plant 18%, and materials 52%. Total costs included 1.3% for environmental enhancement and 7% for land purchase and compensation. The owners and occupiers of some 1490 residential and 45 commercial properties benefi t from the scheme, amounting to an average damage saving of nearly £36 000 per property.

For the Caldew and City Centre project the costs for the preferred scheme are £38 million (Environment Agency, 2006). Construction (58%), consultants (9%), and salaries (3%) make up the majority of these costs. The owners or occupiers of some 2330 properties (a mix of commercial and residential) are assumed to benefi t from the improvement work, at over £75 000 per property (direct losses only). This fi gure is large because of the number of large nonresidential properties (NRPs) protected, including McVities/United Biscuits, employing 1000 people, which was fl ooded and thereby closed in 2005, thus putting the future of the factory at risk. Well over half of the potential future damages are attributable to only nineteen properties, less than 4% of the total number at risk. Of these, four are computer centres (27% of total NRP damages to be avoided), eleven are offi ces (19%), and four are ‘superstores’ (10%). Small numbers of private business enterprises are therefore major benefi ciaries of the scheme, as are their employees.

Impacts on property prices, and regeneration potentialAnalysis of the 2005 event showed little or no evidence of falls in residential property prices after the fl ood; the general trend since was upwards until the recession of 2007–12 (HR Wallingford, 2008). Interviews with estate agents verifi ed that the fl ooding did not depress the housing market, so the two schemes appear unlikely to have the opposite effect and lead to increased house values.

However, the 2005 fl ood was a major catalyst for plans for the redevelopment of Carlisle. The Carlisle Renaissance project is critically dependent on the implementation of the new


fl ood alleviation works and seeks to redevelop the heart of the city in what is one of England’s most deprived regions (Carlisle Renaissance, 2009; Carroll et al, no date). Most of the investment is targeted at generating over 2600 jobs and delivering over 70 000 m2 of new offi ce, commercial, retail, and residential space, thus benefi tting all the town’s population and others besides. Both the core Carlisle Renaissance developments are within the fl ood plain, which by 2011 will have had the 200-year return period standard of protection.

Gaps in our knowledge The actual outcomes from FRM investment are often uncertain (Chatterton et al, 2012); Carlisle is no exception. Much of the information here on fl ood risk reduction benefi ts (eg, future damages to be avoided) is drawn from prescheme PARs and inevitably suffers, therefore, from being forecasts rather than known impacts [eg, as researched by Chatterton et al (2010)]. A fuller and clearer picture of who actually benefi ts from the Carlisle FRM investment will emerge only with time, including the wider benefi ts should the Renaissance initiative have its intended effects. Much of the initiative’s lower cost expenditure has survived, although by 2010 the University of Cumbria had withdrawn plans to locate its headquarters and a major new campus here in “a priority area for regeneration in Carlisle” (Carlisle Renaissance, 2009, page 10).

West Bay, DorsetFollowing a major storm and fl ood in 1974 causing widespread damage and the evacuation of local people and holidaymakers, the West Bay Coastal Defence and Harbour Improvement Scheme was completed in 2004, designed to address a range of issues: safeguarding the West Bay frontage against coastal erosion; fl ood protection for households, commercial properties, and a large caravan park; improving the harbour; and enhancing the amenities of West Bay. The engineering structures were designed to reduce the probability of fl ooding and the consequential damage and to provide safer access to the harbour in storm conditions by replacing a narrow entrance built in the 19th century.

Funding sources Within the fragmented governance arrangements that are typical of coastal situations in the UK (McFadden et al, 2006) the EA is responsible for coastal fl ood defence on the East Beach and for fl uvial fl ood defence on the River Brit. The local authority, West Dorset District Council (WDDC), is the Harbour Authority and is also responsible for coastal protection (erosion mitigation) and fl ood defence on the West Beach.

The cost of the scheme was £20.3 million (table 1), met through multiple funding sources (table 2). Defra’s Fishing Harbour Grant covered 50% of the harbour improvement costs, and the WDDC’s funding drew partly on council tax revenue (ie, from local residents and businesses) and partly from national taxpayers since local authorities then recouped most of this type of expenditure from central government (see CLG 2008).

Costs and benefi ciariesThe benefi ciaries we investigated were the residents and commercial property owners the scheme sought to protect. We also investigated the ‘conduits’ such as consultants, contractors, and others carrying out the work, those benefi ting from possible local economic regeneration, harbour users in the form of commercial fi shing and leisure boat owners, amenity users of West Bay including tourists and related businesses, and relevant members of the insurance industry.

The contractors were the main direct benefi ciaries from the funding, but much of their income was passed on to others such as their employees and suppliers (table 1).The benefi ciaries in terms of risk reduction included 550 households and 55 commercial properties, but ‘peace of mind’ and reduced worry (‘intangible’ benefi ts) were considered to be signifi cant for many residents, caravan


owners, and businesses we surveyed. The three local Bridport estate agents we interviewed considered that the scheme had not had a noticeable effect on either house prices or sales.

Indirect effects and gaps in knowledgeThe Harbour Improvement Scheme has radically improved the appearance of the area and could potentially have benefi ted local landowners and developers by encouraging development here; the EA would be less likely to object given the increased standard of fl ood protection.

The picture, however, is unclear. Two major developments indeed occurred after the initiation of the scheme, within the previously high fl ood risk zone. But attributing at least one of these developments to the scheme was shown to be incorrect, as our interviews established that outline planning permission had been given to an earlier application and the developers had shown an interest in the site prior to the harbour improvements.

Intended benefi ts also failed to live up to expectations. For example, with the safer harbour entrance it was assumed that fi shing would be more active, employing fi fteen full-time commercial boats. But by 2008 the fl eet had dwindled to about ten to twelve vessels of which only fi ve or six were considered by the Harbour Master to be full-time boats. The WDDC had

Table 2. West Bay scheme: sources of funding.

Contributor % January 2006 (£)

Defra fi shing harbour grant 3 609 580Defra coast protection grant 14 2 840 644Defra fl ood defence grant 33 6 630 200WDDC capital budget 3 609 580WDDC revenue budget 34 6 930 927Environment Agency 13 2 698 408

Total 100 20 319 339

Notes: Defra = Department for Environment, Food and Rural Affairs; WDDC = West Dorset District Council.

Table 1. West Bay cost breakdown.

Category Subheading Total amounts (£ million)

WDDC staff fees 0.45Consultants’ fees 1.04Legal fees 0.07Compensation/supplies 0.30Beach CCTV 0.07Contractors plant and equipment 1.35

design fees 0.70materials 5.68labour 1.52site overheads 3.06subcontractors (concrete, electrical, etc) 4.58fee percentage (off-site overheads and profi t) 1.56cost overrun penalty −0.07

Contractors: total 18.40

Notes: WDDC = West Dorset District Council.


anticipated an increase in harbour revenue, but after the scheme was implemented the annual income had increased only from about £49 000 to about £67 500.

The local economy appears to have been enhanced, via commercial tourism, but this has probably more to do with the World Heritage Site status granted in 2001 to the regional coastline, with West Bay promoted as the ‘gateway’ to the Jurassic Coast. Employment was temporarily created for contractors and subcontractors for the scheme, but most of these contractors operate nationally, the direct labour cost fraction is quite small (table 1), and a gap in our knowledge remains concerning the source of this labour and hence how these potential benefi ts were felt in the local labour market.

The Lyth Valley, Cumbria The ‘land drainage’ system of schemesThe Lyth Valley Flood Risk Management System is in a predominantly rural area at the northern end of Morecambe Bay, south of Kendall. Some 30% of the system is within designated sites of both European (eg, Special Areas of Conservation; Special Protection Areas) and international environmental importance (eg, Ramsar sites).

The River Kent Estuary is tidal and has embanked defences and tidal gates that were all improved between 1979 and 1989. This provided fl ood protection for the valley, and the defence design criterion was to provide a 1% (100-year) annual probability threshold of overtopping. Within the system there are 20 km of fl uvial raised defences, 11 km of raised tidal defences, a network of artifi cial drainage channels, fi ve pumping stations, and three tidal gate structures. The scheme was designed to improve drainage and reduce fl ooding to 1853 ha of pasture, based on a 1: 25-year fl uvial fl ood protection standard.

This type of ‘land drainage’ activity during the 1970s and early 1980s refl ected the overriding FRM policy of the time under the Land Drainage Act 1930 (Tunstall et al, 2004). This was to provide improved main river and arterial drainage systems primarily to assist farming in the search of national food self-suffi ciency (Penning-Rowsell and Chatterton, 1977; Purseglove, 1988). Benefi ts to rural settlements were often incidental, and those to the environment through managing water levels to promote enhanced biodiversity were largely ignored (Penning-Rowsell et al, 1986). The Lyth Valley therefore still bears the hallmarks of the previous policy imperative, but more than 20 years later some costly maintenance is still required to maintain the standard of fl ood defences, preserve channel conveyance, and continue with the associated pumping regimes.

Costs and benefi tsThe ultimate funders of these measures were and still are, again, the national taxpayers. The annual maintenance activity is all resourced from the EA’s Grant in Aid programme. Discounted costs over 50 years were £6.258 million with, after 2007/08, an additional maintenance budget in excess of £200 000 per year.

Agricultural intensifi cation to a mixture of intensive and extensive arable production and intensive grazing were assumed when determining the benefi ts of the scheme,(1) as with many similar investments (Penning-Rowsell et al, 1986). In reality, our fi eld surveys showed that there has been little take-up of such agricultural intensifi cation as a result of the drainage works and that the allocation of Agricultural Land Classifi cation (ALC) Grade 3 to nearly 99% of the drained area (2279 ha) appears to be overoptimistic. Field inspections suggest that the poorer ALC Grade 4 is more appropriate, and, assuming this, the annual agricultural benefi ts from the scheme would reduce substantially to only £22 800 (HR Wallingford, 2008); even the farmers who the scheme is seeking to assist have for some reason not benefi ted from the anticipated

(1) EA archive Files 28, 28/1, and 28/2 at the Agency’s Penrith offi ce at Ghyll Mount, Penrith, Cumbria.


income growth. A comparison with the estimated £200 000 annual maintenance cost is striking: the scheme would not be promoted now, but the necessary maintenance continues.

Wider impactsAlthough fundamentally for agricultural improvement, the defence raising has provided fl ood protection to the valley’s isolated properties (forty-two residential and eighteen nonresidential), primarily in the village of Sampool. All the properties are within the EA’s Flood Zone 3 (<1% fl uvial; <0.5% tidal annual fl ood probability), and without the tidal defences all but one property would be at signifi cant risk from fl ooding. The annual benefi ts of the fl ood risk reduction average some £15 285 per house and £12 510 per NRP. The discounted total (£831 000) again compares unfavourably with the £6.258 million capital costs.

In terms of wider benefi ts, the A590 is the only viable road between the M6 motorway and the town of Barrow in Furness, so there are considerable advantages in keeping it fl ood free. A major gas supply pipe and water main cross the southern part of the valley and would probably not be harmed by fl ooding, but the magnitude of any infrastructure benefi ts from the scheme remain one of our knowledge gaps, although they are likely to be small in relation to its full cost.

Summary of case-study fi ndings Three signifi cant fi ndings emerge from these case studies, none of which is surprising but each of which is important when we look at the wider picture below. First, not all the anticipated benefi ts of FRM investment are realised. In each case there are contextual reasons for these shortfalls: no economic growth—or even decline—in fi shing or farming in West Bay and the Lyth valley, respectively, and a truncated regeneration initiative for Carlisle. Whatever the reason, the benefi ciaries are likely to be less numerous and varied than was forecast by the schemes’ promoters.

Second, most benefi ts that are realised appear to be direct fl ood damages avoided, as intended. The aggregate distribution (fi gure 2) shows that the main benefi ciaries appear to be individual householders and the owners or users of commercial property, through risk reduction resulting in signifi cantly less future fl ood damage, although, as the fi gures given above show, the benefi ts per property affected vary widely (from £12 510 to over £75 000).

Third, fi nancial transfers are similar, refl ecting commercial and governance arrangements, despite signifi cant changes in many of the FRM institutions and policies between the 1970s scheme in the Lyth Valley and the recent investment in Carlisle. In both West Bay and Carlisle the contractors were the principal initial benefi ciaries in terms of direct payment received (and staff employed), and this is likely to have been the case for the Lyth drainage scheme. In all three cases the overwhelming majority of the funding has come from national taxation, routed through Defra, the EA, or local authorities (or their predecessors in case of the Lyth Valley), rather than from the direct benefi ciaries themselves. This makes the general fl ood-risk-free taxpayer a major ‘loser’ in each case, and within the generally ‘progressive’ tax regime in the UK (where, for example, the richest 1% of the population pay 25% of all income tax) the more affl uent in the country carry the largest absolute burden here.

But other taxation arrangements complicate the picture and modify the extent of ‘gain’ and ‘loss’. Construction costs include a range of taxation elements such as fuel duty, value-added tax (VAT), and income tax and national insurance payments by employers and employees; all such costs revert to the government in one way or another, thereby reducing the real (net) cost to HM Treasury—and hence the ‘loss’ to the taxpayer—of their FRM investment.

On the other hand, without this investment the costs of the repair or replacement of property damaged by fl ooding also include taxation elements, most obviously again the VAT paid by those fl ood victims or their insurance companies seeking to restore their assets to their


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Notes: Defra = Department for Environment, Food and Rural Affairs; WDDC = West Dorset District Council.

Figure 2. Summary of the benefi ciaries and funders in the three case studies. The logarithmic scale is used to show more clearly the different proportions within the two groups, given widely different absolute values.

prefl ood state. Thus this ‘gain’ in avoiding these costs with risk-reducing FRM investment is also a loss to HM Treasury and the general taxpayer of the taxes that these costs would incur, so the Treasury ‘loses’ £200 million for every £1 billion of fl ood losses avoided (at the 2012 VAT rate of 20%). These matters are pursued somewhat further below, but more research would be needed to tease out the magnitude of all these effects.

Benefi ciaries and losers: the wider picture The second summary conclusion from the case studies above was that fl ood damage avoided was the main gain from the FRM investment, illustrated by the data given in fi gure 2. This is fully in line with EA and government FRM policy, past and present. It is therefore instructive—again pursuing the theme of gainers and losers—to examine in more detail the wider picture regarding fl ood damage and its mitigation. This is done, fi rst, by examining the nature of this damage and, second, by evaluating the distributional effects of insurance arrangements on this situation.

Who loses income from reduced fl ood repairs and replacements?At fi rst sight, fl oods create only what we term losses, but that is far from the case. Many individuals and organisations gain from fl ooding, in that it gives them opportunities to repair property, replace damaged items, and gain income from assisting with the processes of recovery. These activities give those involved in this work a livelihood, and thus the fl ood victim’s loss can be someone else’s gain. This gain is counted as part of national gross domestic product, just as a shopkeeper selling chocolate or a farmer growing wheat are counted. Any


reduction in fl ood losses lessens the total volume and value of this work and hence reduces the number of those who can profi tably be engaged in this employment or the annual income that they each thereby derive. These are therefore losers from FRM investment; for more detail here see Penning-Rowsell and Pardoe (2012).

Floods in England and Wales are typically shallow, having average depths of perhaps 0.30–0.50 m inside the properties affected. There are exceptions, where depths are much greater, but they are not common. Figures 3 and 4 show the potential fl ood damages to the average residential property and NRP, at these fl ood depths, using the best UK data on fl ood damages (from Penning-Rowsell et al, 2010). To pursue the wider picture of impacts, and who is involved, the data have been broken down by the Standard Industrial Classifi cation (SIC) of the economic activities of those repairing the damage or replacing the items that cannot be salvaged and hence repaired (Offi ce for National Statistics, 2009a).

Figures 3 and 4 show that in the domestic sector, where 203 inventory and 77 building fabric damage items have been analysed, damage is dominated by just fi ve elements: building (re)construction; clean-up; replacing furniture and replacing two types of electrical appliances. These SIC industrial sectors tend to be dominated by local small-scale traders with relatively low wage rates, such that the mean annual wages of employees in these fi rst fi ve SICs, covering 76% of total losses, have wage rates that are a full 15% below the national average (Offi ce for National Statistics, 2009b).

In the NRP sector the data are less precise, as potential fl ood losses are recorded in only fi ve categories (stock; moveable equipment; building structure; services; fi xtures and fi ttings) for the thirty-four NRP types (eg, high street shops; plant hire companies) for which we have reliable fl ood damage data. Here the average damage at 0.50 m shown in fi gure 4(2) therefore spans these many different types of property, but losses are dominated by the costs of repair or replacement of (a) plumbing, heating, and air conditioning, (b) construction of commercial buildings, (c) offi ce furniture, and (d) ‘other machinery’ (together comprising some 83% of the total). Again, these are not high wage sectors of the UK economy (and few elements would be imported from abroad), averaging only 13% higher than the national average wage rates, and with the fi rst 29% of employee costs [(a) above] at exactly that national average.

What fi gure 3 also shows is that for every residential property taken out of fl ood risk, in relation to each fl ood that it would have experienced, those involved in clean-up operations lose income to the extent of nearly £10 000 (using the 0.30 m fl ood depth data). The furniture manufacturers and retailers lose over £5500 from the loss of sales that they would have made to replace the furniture damaged or needing repair after the fl ood: 15% of the total. Indeed, because that fl ood loss of £5500 is an economic loss, based on depreciated values (Penning-Rowsell et al, 2005), the loss of sales is likely to be double that per property fl ooded as fl ood victims replace their partly used assets with new purchases at the prevailing retail prices.

These fi gures per property are small. But consider the situation with the average FRM investment, where the ratio of benefi ts to costs is generally now over 8.0 : 1 (Environment Agency, 2008). With an annual capital scheme spend of around £570 million by the EA, a total of £4560 million of potential fl ood damage is presumably being averted, on average, each year. If we assume, not unreasonably, that 50% of these damages avoided are to residential properties (eg, Environment Agency, 2007), then losses to furniture manufacturers from this fl ood risk reduction—as an example—is 15% of that amount, or £342 million per annum. This is a considerable sum, to be added to the loss of their income from not supplying NRPs with their new furniture following fl oods, given that this is also the third largest item revealed in that analysis (fi gure 4). And employees making domestic furniture (SIC 47599) earn only 70.6%

(2) Data are not available for the 0.3 m depth in NRPs.


Wholesale of furniture, carpets, and lighting equipment, £10 055, 8%

Wholesale of offi ce furniture, £14 933, 12%

Wholesale of other machinery and equipment, £13 676, 11%

Plumbing, heating, and air conditioning installation, £36 497, 29%

Construction of commercial buildings, £26 957, 22%

Other, £21 999, 18%

Figure 4. Nonresidential property fl ood damage components at 0.5 m fl ood depth: ‘losers’ from fl ood risk reduction (by Standard Industrial Classifi cation sector).

Other, £13 955, 21%Audio

and video equipment, £1570, 2%

Electrical, plumbing, and other, £3725, 6%

Electrical household appliances, £3952, 6%

Construction of domestic buildings, £27 118, 41%

Cleaning services £8001, 12%

Furniture, lighting, and other household articles, £7725, 12%

Figure 3. Residential property damage components at 0.3 m fl ood depth: ‘losers’ from fl ood risk reduction (by Standard Industrial Classifi cation sector).

of the national average wage (Offi ce for National Statistics, 2009b). But we must remember, of course, that implementing fl ood risk reduction schemes creates employment, and for low wage earners (in construction, transport, etc), so that gain needs to be balanced against these losses. However, the 8.0 : 1 benefi t : cost ratio means that employment gains from this construction


effort are only approximately one eighth of the income losses from the reduction in fl ood damage.

But there are sustainability and moral issues here. Sustainability criteria mean we should try to avoid the waste caused when damaging fl oods mean prematurely replacing our televisions or carpets. And while fl oods clearly bring gains to some in UK society (and even to exporters to the UK), this does not mean we should seek not to reduce fl ood risk, any more than we should seek not to reduce road accidents because they give employment to ambulance drivers. But if economic effects are the only ones we count when making FRM investment decisions—and this is still more or less the situation now in the UK (Johnson and Penning-Rowsell, 2010)—then this issue becomes the more real; the result here is a clear signal that perhaps not all gains and losses from FRM should be judged as morally equal even if they are economically equivalent. In the end we have to make the judgment that we would rather as a society—if we have that option—to employ fewer ambulance drivers.

Flood damage and insurance: other distributional issues The analysis in fi gure 2 is therefore shown to be oversimplistic in one important respect. Clearly, the analysis of fl ood damages, above, demonstrates that plumbers, heating engineers, and clean-up operatives (amongst others) are the real ‘losers’ from FRM investment (as well as the general risk-free taxpayer) because their repair and replacement functions—and incomes—are thereby reduced.

But to obtain a fuller picture, we also need to consider the effects of insurance arrangements, because they redistribute gains and losses. In this respect householders and businesses are not necessarily the fi nal benefi ciary of FRM investment if their losses from the fl oods thereby averted would have been recovered through insurance arrangements. Such insurance is uniquely common in the UK, where private companies sell cover to property owners and competitive market pressures appear largely to determine premiums (Arnell, 2000; Lamond et al, 2009). On the basis of the government’s Household Expenditure Survey and evidence from its own members, the ABI (2009) estimate that the take-up of insurance in the UK is such that 93% of all homeowners have home buildings insurance cover (where this insurance is a standard condition of a UK mortgage), although this falls to 85% of the poorest 10% of households purchasing their own property. Some 75% of all households have home contents insurance, although half of the poorest 10% of households do not have this protection.

Notwithstanding these differences, by far the majority of householders are insured against fl ood losses, within ‘bundled’ policies combining fl ood, theft, fi re, and storm cover (Green and Penning-Rowsell, 2004; Priest et al, 2005). This does not mean that all fl ood losses are covered, because many of those insured are underinsured; and, of course, none of the so-called ‘intangible’ losses from fl oods (Tapsell et al, 2002) are covered at all. But under a series of agreements between the insurance industry and government stretching back to the 1960s (Arnell, 2000) insurers have obligations to provide continuity of cover for most households and small businesses in exchange for government continuing to invest in risk reduction measures (ABI, 2008).

To examine this question of fl ood damage avoided very broadly, in this context, we can assume that if there is investment on FRM in a community (and nationally), then fl ood losses there should decline. If there is no such decline in fl ood losses, then the investment will not have been worthwhile. If there is this decline in fl ood losses, then insured claims should be fewer (and/or lower). This, in turn, should be refl ected in lower premiums—or changes to other arrangements such as reduced excesses (ie, ‘deductibles’)—paid by those whose risk of fl ooding has been reduced. If there is no such change in premium arrangements, then the relevant insurance company will retain its full premium income but have lower costs (ie, lower claims payouts). This should result in the insurance company making larger profi ts for its shareholders.


Almost the only research in this area has been undertaken by Priest (2003) and Lamond (2008). Priest showed, in 2003 and for a small sample, that insurance premium rates were broadly constant across different risk categories. Lamond (2008) was able to demonstrate from her research, for the sample of 198 respondents she surveyed, that the variation in insurance premium rates for low, moderate, and signifi cant risk areas is not signifi cant (table 3): there is no signifi cant difference in the average premium charged for fl ood insurance whether properties are at risk or not, or even fl ooded or not.

The variability around the average premium is greater for those at risk or who have been fl ooded (table 3), probably refl ecting the diffi culty these householders have in getting insurance at all. People who moved into their properties since 2000 showed a degree more of a risk-based pattern of insurance cover, but the differences in premiums between risk categories were not large. Lamond (2008) thereby concluded that the average premium paid by those who are able to obtain insurance is not determined by the risk of fl ood or fl ood history.(3) For new residents—those not resident there during the 2000 fl oods—there is an effect from EA risk category, but, on average, it is less than double the premium paid by those outside the fl oodplain (ie, £3.7/£1000 insured compared with £1.9/£1000).

There is also some anecdotal evidence about much higher insurance excesses in areas that have recently been fl ooded (Pitt, 2008, page 155). However, Lamond’s (2008) survey shows that, whilst some were as high as £2500, most were only about £50. There were very few high excesses, although some reported being asked to accept them but then found a better contract elsewhere: a classic way in which insurance companies use their price structures to deter some potential customers in order to reduce the numbers of high-risk properties within their portfolios.

The evidence that is available—sparse though it is—therefore suggests that insurance premiums do not decline when FRM investment reduces risk. Recent discussions with insurance brokers and insurers confi rm that fl ood insurance premiums are not fundamentally risk related.(4) If that is the case, then insurers and their shareholders are the main benefi ciaries of this fl ood hazard reduction (and the low-to-middle-income wage earners discussed above in relation to repairers of the damage are the main direct losers).

But, again, there are complications. Insured householders gain from fl ooding insofar as insurers pay out more than economic values through their near-ubiquitous new-for-old policies,

(3) This was confi rmed in 2010/11 in discussions with those participating in HM Treasury coordinated deliberations about the future after 2013 of the SOP.(4) ‘Fighting fl ood risk together’ conference, ABI, November 2010.

Table 3. Median insurance rate by Environment Agency risk category (£ per £1000 insured) (source: Lamond, 2008).

Total Resident Not resident in 2000

Flooded Resident notfl ooded

Outside the fl ood plain 2.2 2.5 1.9 na 2.5Low fl ood risk 2.6 2.5 2.6 3.2 2.4Moderate fl ood risk 2.5 2.4 3.7 2.5 2.3Signifi cant fl ood risk 2.5 2.3 2.3 2.4 2.3Total (all) 2.5 2.5 2.5 2.5 2.4Kruskal–Wallis test 0.101 0.451 0.006** 0.557 0.353

** Signifi cant difference.Note: na = nonapplicable.


although the insured pay for this betterment through enhanced annual premiums, so this effect is likely to be small. Many people are underinsured, and not all damage is compensated, so these householders lose during fl oods—and gain from FRM investment—but their premiums presumably are lower to refl ect this underinsurance; the effect may well be neutral. Household cover also attracts the Insurance Premium tax, at 6% from January 2011 (previously 5%). This means that insurance companies do not accrue to themselves all the costs of FRM investment: a small amount of insurance premium income from those in fl ood risk areas whose risk is reduced with FRM investment is returned to the government rather than remain with the insurers.

But there is another possibility vis-à-vis insurance and insurers when FRM investment reduces risk. Perhaps the effect is to reduce all premiums to lower levels than they would need to be if fl ooding were more widespread (without that investment) and claim totals were therefore higher; then the burden of insurance claims would have to be refl ected in higher premiums to retain target levels of profi tability or the return on insurance companies’ capital. If investment reduces all premiums to lower levels in this way, then all policy holders are the benefi ciaries of investment-led fl ood risk reductions, just as all taxpayers (even those without fl ood risk) pay for that investment to deliver these reductions.

If that were to be the case, then insurance premiums should have refl ected this and declined as investment reduced risk. However, this is as yet largely unknowable, giving the bundling of UK fl ood insurance with other peril categories such as fi re, theft, subsidence, and storm damage. To accept this possibility that the effect is to reduce all premiums therefore needs unambiguous evidence from further research—and far greater transparency regarding insurers’ risks, claims, income, and profi tability—something that insurers have been unwilling to agree to in the past. Without this evidence, and with the research results reported here suggesting that premiums are unrelated to risk, then the balance of our conclusion remains that insurers and their shareholders are the principal benefi ciaries of fl ood hazard reduction.

Conclusions The research reported here commenced with three case studies, but their results and the conclusions drawn led to the need for a wider and more fundamental analysis of the distributional effects of fl ood damage and fl ood risk reduction (summarised in table 4). That analysis shows that the effect of this risk reduction is not always what it seems. This has highlighted three key aspects of who benefi ts—and who loses—from the kind of state investment in fl ood mitigation that is near-universal in the UK and common throughout the world.

First, our three case studies show that fl ood damage and loss avoided is the main benefi t of interventions to reduce fl ood risk, as one would expect, and that some other types of benefi ts are exaggerated—in our cases—in the process of predicting in project investment Table 4. Gainers and losers from hazard reduction through fl ood risk mitigating investment: summary for the UK.

Gainers from risk-reducing investment

Neutral Losers from risk-reducing investment

Direct The uninsuredThe underinsuredThose who would otherwise incur intangible (ie, uninsurable) losses

The fully insured Flood-risk-free general taxpayers (circa £570 mper annum)

Indirect Insurance companies and their shareholdersHM Treasury and hence taxpayers: value-added tax (VAT) etc levied on the construction of fl ood risk management works

Those who obtain income from fl ood loss repair and replacementHM Treasury and hence taxpayers (VAT loss on the above)


appraisals who the benefi ciaries might be. The conclusion here is that the numbers and variety of these benefi ciaries are less than was anticipated.

Second, our investigations of these fl ood damages show that there is at least a prima facie case that those losing most from investment in FRM—as well as the risk-free taxpayers—are low-wage manual workers, through the loss (with fewer damaging fl oods) of the fl ood repair and replacement activity that they largely undertake.

Third, the exploration of insurance effects has suggested strongly that insurers and their shareholders are the main benefi ciaries of investment in hazard reduction, given that insurance premiums appear not to decline with the reduced risks and fl ood damage that this investment brings. Those gaining from this investment are therefore relatively high-income insurance shareholders, through insurance companies seeing lower costs while maintaining their income.

This leads to the conclusion that the distribution of gainers and losers is unusually regressive, and that if this set of results is what Defra and the government intends for FRM in the UK, it is surprising. If it is not what they intend, then their FRM policy and its implementation needs a radical overhaul.

There are, then, three signifi cant implications. First, the general taxation-funded EA and Defra capital investment on FRM in the UK should in future target only the prevention of losses that are not insured, and thus focus on the uninsured or underinsured parts of the population and on those losses that are not measured in monetary terms and therefore cannot be insured (table 4). Resilience and similar property-level or community-level measures should be promoted (and funded) by Defra and EA for residential and commercial properties only where there is a guarantee from those insuring those properties that cover is provided and that insurance premiums will be reduced proportionately. In terms of recurrent expenditure, fl ood warning systems should not purposefully target saving damages, where they are insured, but target minimising loss of life and other intangible impacts. This approach will not be easy to achieve, but a concerted move in these directions is certainly warranted and not impossible.

Second, if those without risk or at very low risk are to be treated fairly [whilst recognising the many facets of that concept (Johnson et al, 2007)], the insurance premiums for those genuinely at risk should rise to refl ect the true cost of that insurance, with a move to actuarially or risk-based premium rates. If premiums do not rise in this way, then those without risk and those already protected will continue to subsidise those at risk. It may be the case that they are not unhappy to do so, for altruistic reasons (and this needs further research), but this subsidy may well discourage any individual risk-reducing actions that those at risk might take, and also give the strong impression to those protected that their government’s expenditure in this area was not worthwhile because their costs of insuring against future fl oods remains stubbornly the same.

Finally, there are implications for elsewhere in the world. Wherever there are fl ood risk reduction programmes that are based on funds from general taxation—rather than the benefi ciaries paying the costs—analysts and governments need to investigate whether the distribution of gainers and losers is transparent, fair, and effi cient. Also, wherever there are insurance arrangements to compensate the victims of fl oods for the losses that they incur, questions need to be asked as to whether the insurers who provide that cover gain unfairly when governments invest taxpayers’ money to reduce the risks that their customers face.

Acknowledgements. We would like to acknowledge Nigel Walmsley, John Chatterton, and Sylvia Tunstall for their contributions to the case studies reported here and Sally Priest and Dennis Parker for comments on early drafts. The information from interviewees is also acknowledged, as are comments from Phil Rothwell (Environment Agency), Paul Davies (Financial Times), and two anonymous referees.


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Who Benefits and Who Loses From Flood Risk Reduction

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