Skip to main content
Article thumbnail
Location of Repository

A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

By Simon Gosling, R. G. Taylor, Nigel Arnell and M. C. Todd

Abstract

We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and development conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangu (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs typically simulate water resources impacts based on a more explicit representation of catchment water resources than that available from the GHM, and the CHMs include river routing. Simulations of average annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline (1961-1990) and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in global mean temperature from the HadCM3 climate model and (2)a prescribed increase in global-mean temperature of 2oC for seven GCMs to explore response to climate model and structural uncertainty.\ud We find that differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM, and they are generally larger for indicators of high and low flow. However, they are relatively small in comparison to the range of projections across the seven GCMs. Hence, for the six catchments and seven GCMs we considered, climate model structural uncertainty is greater than the uncertainty associated with the type of hydrological model applied. Moreover, shifts in the seasonal cycle of runoff with climate change are presented similarly by both hydrological models, although for some catchments the monthly timing of high and low flows differs.This implies that for studies that seek to quantify and assess the role of climate model uncertainty on catchment-scale runoff, it may be equally as feasible to apply a GHM as it is to apply a CHM, especially when climate modelling uncertainty across the range of available GCMs is as large as it currently is. Whilst the GHM is able to represent the broad climate change signal that is represented by the CHMs, we find, however, that for some catchments there are differences between GHMs and CHMs in mean annual runoff due to differences in potential evaporation estimation methods, in the representation of the seasonality of runoff, and in the magnitude of changes in extreme monthly runoff, all of which have implications for future water management issues

Publisher: Copernicus
Year: 2011
OAI identifier: oai:centaur.reading.ac.uk:19938

Suggested articles

Citations

  1. (2009). Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM). I: Model intercomparison with current land use,
  2. (2008). Assessment of exploitable groundwater resources of Denmark by use of ensemble resource indicators and a numerical groundwater – surface water model,
  3. (2009). Associations between elevated atmospheric temperature and human mortality: a critical review of the literature,
  4. Climate change and global water resources: SRES emissions and socioeconomic scenarios,
  5. (2008). Climate Change and Water,
  6. (2010). Climate change impacts – throwing the dice?
  7. Climate change impacts on river flows in Britain: the UKCIP02 scenarios.
  8. (2009). Comparison of uncertainty sources for climate change impacts: flood frequency in England,
  9. (1996). Distributed Hydrological Modeling,
  10. Effects of IPCC SRES∗ emissions scenarios on river runoff: a global perspective,
  11. (2009). Ensemble yield simulations: crop and climate uncertainties, sensitivity to temperature and genotypic adaptation to climate change,
  12. (2006). Estimating the sensitivity of mean annual runoff to climate change using selected hydrological models,
  13. (2010). Evaluation of global warming impacts for different levels of stabilisation as a step toward determination of the long-term stabilisation target,
  14. (2003). Global estimates of water withdrawals and availability under current and future “business-as usual” conditions,
  15. (2010). Global Hydrology Modelling and Uncertainty: Running Multiple Ensembles with a campus grid,
  16. (1998). Global land cover classification at 8 km spatial resolution: the use of training data derived from Landsat imagery in decision tree classifiers.,
  17. (2011). Gosling et al.: Comparing global and catchment-scale hydrological models 293
  18. (2009). Influence of global climate model selection on runoff impact assessment,
  19. (2006). Intercomparison of lumped versus distributed hydrologic model ensemble simulations on operational forecast scales,
  20. (2007). Multi-method global sensitivity analysis (MMGSA) for modelling floodplain hydrological processes,
  21. (2011). Multi-Model Estimate of the Global Water Balance: Setup
  22. (2010). Non-linear runoff generation model in small Alpine catchments,
  23. (2008). Performance metrics for climate models,
  24. (2001). Rainfall-Runoff Modelling:
  25. (2006). Regional calibration of the Pitman model for the Okavango River,
  26. Relative effects of multi-decadal climatic variability and changes in the mean and variability of climate due to global warming: future streamflows in
  27. (2007). resources and their management. Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by:
  28. (2009). S.: Effects of precipitation uncertainty on discharge calculations for main river basins,
  29. (2003). Scaling: An Examination of the Accuracy of the Technique for Describing Future Climates,
  30. (1994). Simulation of streamflow in a macroscale watershed using general circulation model data,
  31. (2011). The implications of climate policy for the impacts of climate change on global water resources, Global Environ. Change, in press,
  32. (2010). The relationship between climate forcing and hydrological response
  33. (2009). The role of hydrological model complexity and uncertainty in climate change impact assessment,
  34. (1995). The SLURP model, in: Computer Models of Watershed Hydrology, edited by:
  35. (2007). TheWCRP CMIP3 multimodel dataset: A new era in climate change research,
  36. (2001). Toward Improved Streamflow Forecasts: Value of Semidistributed Modeling,
  37. (2010). Uncertainty in climate change projections of discharge for the Mekong River Basin,
  38. (2009). Uncertainty in the estimation of potential evapotranspiration under climate change,
  39. (2010). Uncertainty in water resources availability in the Okavango River Basin as a result of climate change,
  40. (1999). W.: A simple water balance model for the simulation of streamflow over a large geographic domain,

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.