SECCIÓN 4ª. Tercerías

Following the literature review carried out in Chapter 2 a prospective (exploratory future trend) scenario type is selected for generating future supply scenarios for this study (see section 2.5.5). This form of scenario generation is based on the extrapolation and alteration of past data trends projected forward in time utilising plausible climate projections, combined with randomised variations in the timing and frequency of future drought periods, in order to produce a wide array of different scenarios that avoid directly copying historic patterns of events.

A reliable source of data for producing plausible scenarios of future hydrological time series and synthetic flows for a water resource zone in the UK is by using the UK climate projections (UKCP09) developed in 2009 by the UK Climate

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Impacts Programme (UKCIP). The UKCP09 projections are still the leading source of climate information for the UK and its regions, but are scheduled to be upgraded in 2018 to the UKCP18 projections (Defra, 2016b). The projections are created to help users with the process of adapting their systems to a changing climate (UKCIP, 2009). UKCP09 only provides changes in climate and therefore requires hydrological modelling to derive hydrological time series that represent a range of climate model projections. However this has subsequently been addressed by the ‘Future Flows Climate Programme’ (Prudhomme et al., 2012) which uses the UKCP09 regional climate model to generate climate change projections of river flows. In this study the application of using the Future Flows climate/hydrology scenarios to generate future river flow projections for the region’s major contributing rivers and reservoirs is tested. The Future Flows project utilises the latest projections from the UK Climate Impact Program (UKCIP), derived from the UKCP09 regional climate models (RCMs) from the Met office Hadley Centre. They provide 11 plausible realisations (all assumed equally likely) of the river flows at various river gauging stations across England, Wales and Scotland and account for the impact of climate change to 2100 under a Medium emission scenario (Figure 4.3).

The key advantage of the Future Flow scenarios is that they are transient flow projections, so they do not require additional rainfall-runoff modelling and so can be directly utilised to continuously simulate the supply-demand balance over a given planning horizon. Direct use of UKCP09 projects is not suitable for this study as the projections provide “snap shots” of climate change for predefined time horizons and therefore cannot be easily manipulated for transient analysis. Using transient projections allows a direct analysis of the timing of interventions over the planning horizon.

The limitation of the current Future Flow projections is their utilisation of only a medium global emission scenario and their formation from the SRES emission scenarios (IPCC, 2000), scenarios recently superseded by the improved Representative Concentration Pathways (RCPs) (Moss et al., 2010), However, once resampled multiple times (as outlined below), the Future Flow projections provide an adequate range of uncertainty for this specific metric evaluation. Resampling of the flow projections (as outlined below) eliminates any bias in the

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selection of adaptation strategies due to the timing and duration of future drought conditions exhibited (which are fixed in time without resampling), and enables a sufficient investigation into the role of climate variability on the region’s resources. The scenario generation process is not the focus of this study; however, it is recommended that water practitioners wishing to employ this methodology in practice should examine the widest range of plausible projections available.

In order to generate multiple future synthetic river flows and reservoir inflows for a region a Future Flows gauging site of closest proximity to the resource zone is selected. The specific time-series inflow/flow data required for each source of water, be it a reservoir or at a river abstraction point, is then translated using a monthly flow factoring method (Arnell and Reynard, 1996), which perturbs the historic flow data to match the flow changes projected at the gauging site. Flow factors describe the percentage change in monthly average flows over a 30 year historic period (1961-1990) with those of a 30 year future period at the gauging site (e.g. 2050s = 2041-2070). The limitation of a flow factor approach is that the historical sequencing of drought events is unchanged (Diaz-Nieto and Wilby, 2005), such that if a drought event occurs after 10 years historically it would appear in every climate change scenario after 10 years and force a similar pathway of adaptation strategies. In order to test the adaptation strategies against a range of different naturally varying scenarios, the historical flows are resampled (Ledbetter et al., 2012) using 3 month seasonal blocks (Dec-Feb, Mar-May, Jun-Aug and Sep-Nov) to create new realisations of historical climate. Each new flow projection is formed by resampling the past 100 years of flow records (1915-2014 inclusive), then selecting a 25 year period at random (Figure 4.2).

In order to then impose the transient climate change signal of the Future Flows scenarios within the resampled historical sequences a novel rolling flow factor method is devised to produce factors for each year in the future planning horizon. For example, to create flow factors for 2020 a future flow period from 2005-2034 is compared with the 1961-1990 baseline, for 2021 the future averaging period is advanced a single year to 2006-2035 and so on for each year in the planning/time horizon. The flow factors are then used to perturb the historic resampled river flow and reservoir inflow data at each source/site within

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the resource zone to ensure the system is modelling the same patterns of weather and climate change throughout the system at the same time (Figure 4.2).

Figure 4.2: Supply scenario generation process – resampling and rolling flow factor method to generate transient flow projections imposed with Future Flow

climate change signals

Figure 4.3: Future Flow climate/hydrology projections and example of three resampled flow sequences – conceptual drawing

Future Flow projections

Historic flow data – 100 years of data resampled

1915 2014 25 year segment selected at random 1961 1990 2005 2034 2020 1961 1990 2015 2044 2030

Repeated for each year of the future planning horizon

Monthly averages from 1961-1990 are compared with monthly averages for each future 30 year Future Flow time slice to calculate rolling flow factors. Avg Avg Avg Avg

Rolling Future Flow factors are then imposed on the resampled historic data segments. 2030

2020

Historic data Ensemble of 11 transient Future Flow projections

Present day Time Future horizon

Annual average river flow

Historic flow sequences are resampled then imposed with each transient Future Flow projection – example of three resampled flow scenarios

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Figure 4.3 gives a conceptual example of a historic river flow sequence and its 11 transient Future Flow projections. As detailed above, each flow scenario is formed by resampling the past 100 years of flow records (1915-2014 inclusive), then selecting a 25 year period at random before imposing each Future Flow transient climate change signal using the rolling flow factor method. Note in Figure 4.3 how the resampled flow scenarios maintain the downward trend of the given Future Flow projection but the stochastic resampling has re-ordered the drought periods to eliminate historic bias.

As the likelihoods of the different scenarios is not quantifiable the supply uncertainty is classified as “deep” (Walker et al., 2013b). The reliability of minor additional sources of water unique to the following case studies (Chapter 5), such as applicable minor groundwater sources or imported supplies from a neighbouring region, that are not projected to be significantly impacted upon by the regions climate change projections, will use their current daily/monthly contributing supply values as consistent inputs over the full planning horizon (Bristol Water, 2014; Southern Water, 2009).

Using transient sequences of flows is different to the standard engineering practice (the EBSD method) which assumes a single linear interpolation of supply availability from the baseline to the 2030s.