Use of a grid‐based hydrological model and regional climate model outputs to assess changing flood risk

Bell, V. A.; Kay, Alison L.; Jones, R. G.; Moore, Robert J.

doi:10.1002/joc.1539

Cited by 53 publications

(36 citation statements)

References 23 publications

(28 reference statements)

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“…The rationale behind using two model structures is that they provide an initial estimate of the uncertainty linked to the choice of a given model structure, following the approach of recent climate change impact studies (Kay et al, 2009;Wilby and Harris, 2006). PDM (Probability Distributed Model) has been developed and used for more than 20 years (Moore, 1985(Moore, , 2007, notably in climate change impact studies (Arnell et al, 1997;Prudhomme et al, 2003;Bell et al, 2007;Prudhomme and Davies, 2009a,b). This study made use of a version of PDM with 5 parameters described by Senbeta et al (1999) and implemented by Wood (2005), using a linear reservoir for routing the fast and slow pathways.…”

Section: Hydrological Modellingmentioning

confidence: 99%

Using UKCP09 probabilistic climate information for UK water resource planning

Christierson

Vidal²,

Wade

2012

Journal of Hydrology

103

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Water companies in the United Kingdom have considered climate change in their water resources plans for more than a decade through studies funded by UK Water Industry Research (UKWIR). This paper presents an initial assessment of the impact of the UK Climate Projections 2009 (UKCP09) on river flows at a national scale for the 2020s under the A1B scenario and the implications for water resource planning. A daily hydrological modelling framework based on two conceptual model structures and the Generalized Likelihood Uncertainty Estimation (GLUE) methodology has been applied to 70 catchments across the UK. A Latin Hypercube Sampling approach was adopted to handle the probabilistic nature of UKCP09. Results show a decrease in mean annual flow over most of the UK, with negative median values of all monthly changes except in winter over the western and northern mountainous areas. Furthermore the results indicate a high likelihood of a significant decline in summer flows. An analysis of variance shows that the main uncertainty in river flow changes comes from the spread in climate projections. Finally results are found to be consistent with a previous UKWIR assessment based on individual projections from 6 Global Climate Models (GCMs) under the A2 scenario. The reduction in summer low-flows, critical for water resources, appears however more limited with UKCP09. Although most expected changes are within natural variability, the drier conditions overall and the greater spread of results with respect to previous assessments indicates a need for testing the robustness of water resource plans.

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Section: Hydrological Modellingmentioning

confidence: 99%

Using UKCP09 probabilistic climate information for UK water resource planning

Christierson

Vidal²,

Wade

2012

Journal of Hydrology

103

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“…Kay et al, 2006;Bell et al, 2007;Cloke et al, 2010;Prudhomme et al, 2010;Chen et al, 2012). In using global climate Copyright c 2012 Royal Meteorological Society model (GCM) projections for assessing future flood impact, sources of uncertainty include: emission scenario; climate model structure and parametrization; climate projection downscaling and correction techniques; hydrological model structure and parametrization; and observations.…”

Section: Introductionmentioning

confidence: 99%

“…MOS removes much of the model error in the precipitation, making it more useful in impact studies, which is considered by many to allow confidence in the examination of future changes in flow regimes in catchments from Europe and the wider world (e.g. Bell et al, 2007, Fowler et al, 2007bLeander and Buishand, 2007;Akhtar et al, 2009;Linde et al, 2010;Marke et al, 2011;Rojas et al, 2011;Turco et al, 2011). However, MOS can potentially also remove much of the spread in the driving variables, which could disrupt signals of climate change.…”

Section: Introductionmentioning

confidence: 99%

Modelling climate impact on floods with ensemble climate projections

Cloke

Wetterhall

et al. 2012

Quart J Royal Meteoro Soc

108

104

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The evidence provided by modelled assessments of future climate impact on flooding is fundamental to water resources and flood risk decision making. Impact models usually rely on climate projections from global and regional climate models (GCM/RCMs). However, challenges in representing precipitation events at catchment-scale resolution mean that decisions must be made on how to appropriately pre-process the meteorological variables from GCM/RCMs. Here the impacts on projected high flows of differing ensemble approaches and application of Model Output Statistics to RCM precipitation are evaluated while assessing climate change impact on flood hazard in the Upper Severn catchment in the UK. Various ensemble projections are used together with the HBV hydrological model with direct forcing and also compared to a response surface technique. We consider an ensemble of single-model RCM projections from the current UK Climate Projections (UKCP09); multi-model ensemble RCM projections from the European Union's FP6 'ENSEMBLES' project; and a joint probability distribution of precipitation and temperature from a GCM-based perturbed physics ensemble.The ensemble distribution of results show that flood hazard in the Upper Severn is likely to increase compared to present conditions, but the study highlights the differences between the results from different ensemble methods and the strong assumptions made in using Model Output Statistics to produce the estimates of future river discharge. The results underline the challenges in using the current generation of RCMs for local climate impact studies on flooding.

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“…Bell et al 2007;Prudhomme et al 2003;Milly et al 2002;Lehner et al 2006;Hirabayashi et al 2008;Dankers and Feyen 2009;Dankers et al 2013). A key conclusion of such studies is that the projected effects of climate change on the flood hazard may be very substantial, but are very dependent on climate scenario.…”

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confidence: 99%

The impacts of climate change on river flood risk at the global scale

2014

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This paper presents an assessment of the implications of climate change for global river flood risk. It is based on the estimation of flood frequency relationships at a grid resolution of 0.5×0.5°, using a global hydrological model with climate scenarios derived from 21 climate models, together with projections of future population. Four indicators of the flood hazard are calculated; change in the magnitude and return period of flood peaks, flood-prone population and cropland exposed to substantial change in flood frequency, and a generalised measure of regional flood risk based on combining frequency curves with generic flood damage functions. Under one climate model, emissions and socioeconomic scenario (HadCM3 and SRES A1b), in 2050 the current 100-year flood would occur at least twice as frequently across 40 % of the globe, approximately 450 million flood-prone people and 430 thousand km 2 of flood-prone cropland would be exposed to a doubling of flood frequency, and global flood risk would increase by approximately 187 % over the risk in 2050 in the absence of climate change. There is strong regional variability (most adverse impacts would be in Asia), and considerable variability between climate models. In 2050, the range in increased exposure across 21 climate models under SRES A1b is 31-450 million people and 59 to 430 thousand km 2 of cropland, and the change in risk varies between −9 and +376 %. The paper presents impacts by region, and also presents relationships between change in global mean surface temperature and impacts on the global flood hazard. There are a number of caveats with the analysis; it is based on one global hydrological model only, the climate scenarios are constructed using pattern-scaling, and the precise impacts are sensitive to some of the assumptions in the definition and application.

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Use of a grid‐based hydrological model and regional climate model outputs to assess changing flood risk

Cited by 53 publications

References 23 publications

Using UKCP09 probabilistic climate information for UK water resource planning

Using UKCP09 probabilistic climate information for UK water resource planning

Modelling climate impact on floods with ensemble climate projections

The impacts of climate change on river flood risk at the global scale

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