Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM) III: scenario analysis

An ensemble of 10 hydrological models was applied to the same set of land use change scenarios. There was general agreement about the direction of changes in the mean annual discharge and 90% discharge percentile predicted by the ensemble members, although a considerable range in the magnitude of predictions for the scenarios and catchments under consideration was obvious. Differences in the magnitude of the increase were attributed to the different mean annual actual evapotranspiration rates for each land use type. The ensemble of model runs was further analyzed with deterministic and probabilistic ensemble methods. The deterministic ensemble method based on a trimmed mean resulted in a single somewhat more reliable scenario prediction. The probabilistic reliability ensemble averaging (REA) method allowed a quantification of the model structure uncertainty in the scenario predictions. It was concluded that the use of a model ensemble has greatly increased our confidence in the reliability of the model predictions.

[1]  Dong-Jun Seo,et al.  Towards the characterization of streamflow simulation uncertainty through multimodel ensembles , 2004 .

[2]  S. Sorooshian,et al.  Multimodel Combination Techniques for Analysis of Hydrological Simulations: Application to Distributed Model Intercomparison Project Results , 2006 .

[3]  Richard L. Smith,et al.  Regional probabilities of precipitation change: A Bayesian analysis of multimodel simulations , 2004 .

[4]  Anthony J. Jakeman,et al.  Assessing the impact of land use change on hydrology by ensemble modelling(LUCHEM) II: ensemble combinations and predictions , 2009 .

[5]  T. Palmer,et al.  A Probability and Decision-Model Analysis of a Multimodel Ensemble of Climate Change Simulations , 2001 .

[6]  Johan Alexander Huisman,et al.  Monte Carlo assessment of uncertainty in the simulated hydrological response to land use change , 2006 .

[7]  F. Giorgi,et al.  Probability of regional climate change based on the Reliability Ensemble Averaging (REA) method , 2003 .

[8]  Renate Hagedorn,et al.  The rationale behind the success of multi-model ensembles in seasonal forecasting-II , 2005 .

[9]  Anthony J. Jakeman,et al.  Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM) I: Model intercomparison with current land use , 2009 .

[10]  Vazken Andréassian,et al.  Waters and forests: from historical controversy to scientific debate [review article] , 2004 .

[11]  Lu Zhang,et al.  Response of mean annual evapotranspiration to vegetation changes at catchment scale , 2001 .

[12]  K. Beven,et al.  On constraining the predictions of a distributed model: The incorporation of fuzzy estimates of saturated areas into the calibration process , 1998 .

[13]  J. Hewlett,et al.  A REVIEW OF CATCHMENT EXPERIMENTS TO DETERMINE THE EFFECT OF VEGETATION CHANGES ON WATER YIELD AND EVAPOTRANSPIRATION , 1982 .

[14]  A. Bronstert,et al.  Land-use impacts on storm-runoff generation: scenarios of land-use change and simulation of hydrological response in a meso-scale catchment in SW-Germany , 2002 .

[15]  S. Uhlenbrook,et al.  Quantifying the impact of land-use changes at the event and seasonal time scale using a process-oriented catchment model , 2004 .

[16]  Johan Alexander Huisman,et al.  Sensitivity of simulated hydrological fluxes towards changes in soil properties in response to land use change , 2004 .

[17]  John Ewen,et al.  Validation of catchment models for predicting land-use and climate change impacts. 3. Blind validation for internal and outlet responses , 2004 .

[18]  John Ewen,et al.  Validation of catchment models for predicting land-use and climate change impacts. 1. Method , 1996 .

[19]  Kevin Bishop,et al.  A TEST OF TOPMODEL'S ABILITY TO PREDICT SPATIALLY DISTRIBUTED GROUNDWATER LEVELS , 1997 .

[20]  Nicola Fohrer,et al.  Assessment of the effects of land use patterns on hydrologic landscape functions: development of sustainable land use concepts for low mountain range areas , 2005 .

[21]  P G Whitehead,et al.  Steady state and dynamic modelling of nitrogen in the River Kennet: impacts of land use change since the 1930s. , 2002, The Science of the total environment.

[22]  B. Weinmann,et al.  Simulating the effects of decoupled transfer payments using the land use model ProLand Simulation der Effekte entkoppelter Transferzahlungen mit dem Landnutzungsmodell ProLand , 2006 .

[23]  J. Houghton,et al.  Climate change 2001 : the scientific basis , 2001 .

[24]  Richard L. Smith,et al.  Quantifying Uncertainty in Projections of Regional Climate Change: A Bayesian Approach to the Analysis of Multimodel Ensembles , 2005 .

[25]  Andrew W. Western,et al.  A review of paired catchment studies for determining changes in water yield resulting from alterations in vegetation , 2005 .

[26]  Johan Alexander Huisman,et al.  Assessing the impact of land use change on hydrology by ensemble modelling (LUCHEM) IV: Model sensitivity to data aggregation and spatial (re-)distribution , 2009 .

[27]  Johan Alexander Huisman,et al.  Analysing the effects of soil properties changes associated with land use changes on the simulated water balance: A comparison of three hydrological catchment models for scenario analysis , 2007 .

[28]  B. Bhaduri,et al.  Assessing Watershed-Scale, Long-Term Hydrologic Impacts of Land-Use Change Using a GIS-NPS Model , 2000, Environmental management.

[29]  M. Noguer,et al.  Climate change 2001: The scientific basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change , 2002 .

[30]  F. Giorgi,et al.  Calculation of average, uncertainty range, and reliability of regional climate changes from AOGCM simulations via the reliability ensemble averaging (REA) method , 2002 .

[31]  Zong-ci Zhao,et al.  Climate change 2001, the scientific basis, chap. 8: model evaluation. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change IPCC , 2001 .

[32]  John D. Stednick,et al.  MONITORING THE EFFECTS OF TIMBER HARVEST ON ANNUAL WATER YIELD , 1996 .