Use of soil data in a grid-based hydrological model to estimate spatial variation in changing flood risk across the UK

JOURNAL OF HYDROLOGY

卷:377

Article

Bell, V. A.¹  Kay, A. L.¹  Jones, R. G.²  Moore, R. J.¹  Reynard, N. S.¹ 

[1] Ctr Ecol & Hydrol, Wallingford OX10 8BB, Oxon, England

[2] Univ Reading, Reading Unit, Hadley Ctr, Met Off, Reading RG6 6BB, Berks, England

关键词: Rainfall-runoff model;    Regional Climate Model;    Flood frequency: climate change;   

DOI  :  10.1016/j.jhydrol.2009.08.031

来源: Elsevier

【 摘 要 】

A grid-based flow routing and runoff-production model, configured to employ as input either observed or Regional Climate Model (RCM) estimates of precipitation and potential evaporation (PE), has previously been used to assess how climate change may impact river flows across the UK. The slope-based Grid-to-Grid (G2G) model adequately simulated observed river flows under current climate conditions for high relief catchments, but was less successful when applied to lower-relief and/or groundwater-dominated areas. The model has now been enhanced to employ a soil dataset to configure the probability-distributed store controlling soil-moisture and runoff generation within each grid-cell. A comparison is made of the ability of both models to simulate gauged river flows across a range of British catchments using observations of rainfall and PE as input. Superior performance from the enhanced G2G formulation incorporating the soil dataset is demonstrated. Following the model assessment, the observed precipitation and PE data used as input to both hydrological models were replaced by REM estimates on a 25 km grid for a Current (1961-1990) and a Future (2071-2100) time-slice. Flood frequency curves derived from the flow simulations for the two time-slices are used to estimate, for the first time, maps of changes in flood magnitude for all river points on a I km grid across the UK. A high degree of spatial variability is seen in the estimated change in river flows, reflecting both projected climate change and the influences of landscape and climate variability. These maps also highlight large differences between the climate impact projections arising from the two models. The improved structure and performance of the soil-based G2G model adds confidence to its projections of flow changes being realistic consequences of the climate change scenario applied. A resampling method is used to identify regions where these projections may be considered robust. However, with the climate change scenario used representing only one plausible evolution of the future climate, no clear message can be drawn here about projected river flow changes. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.

【 授权许可】

Free