Keywords
runoff projections, climate change, scenario construction, rainfall
Start Date
1-7-2008 12:00 AM
Abstract
Runoff characteristics are inextricably linked with climate, particularly the spatial and temporal patterns of precipitation and evapotranspiration. The need for demonstrably objective climate change scenarios consistent with what is realistic under global warming predicted conditions is increasingly growing. Global climate models (GCMs) are the best tools available for simulating global and regional climate for predicting future climate. However, GCMs provide information at a resolution that is too coarse to give results that can be directly used in hydrological studies. This paper quantifies three simple methods of rainfall scenarios construction informed by GCMs for their potential use in providing desirable future rainfall scenarios for modelling runoff projections. Runoff simulations from daily rainfall time series obtained using three simple methods (constant scaling, daily scaling and daily translation) to transform GCM outputs to catchment-scale rainfall over South-East Australia for 1981- 2000 and 2046-2065 periods are used. In the constant scaling and daily scaling methods, the historical observed daily rainfall is scaled by the changes indicated by the GCM. In the constant scaling method, the entire daily rainfall series (in seasons) is scaled by the same factor. In daily scaling, the different daily rainfall amounts are scaled differently. In daily translation, a relationship between GCM simulation of the present rainfall and the observed catchment-scale rainfall is established, and used to convert the future GCM daily rainfall time series to catchment-scale rainfall series. In summary, the constant scaling method can be used in most applications to transform climate outputs from GCMs to drive hydrological models. However, where more detailed analyses of runoff distribution is required, the daily scaling and daily translation methods are potentially better, particularly if the GCMs used have skill in modelling extreme rainfall and daily rainfall series.
Runoff projection sensitivity to rainfall scenario methodology
Runoff characteristics are inextricably linked with climate, particularly the spatial and temporal patterns of precipitation and evapotranspiration. The need for demonstrably objective climate change scenarios consistent with what is realistic under global warming predicted conditions is increasingly growing. Global climate models (GCMs) are the best tools available for simulating global and regional climate for predicting future climate. However, GCMs provide information at a resolution that is too coarse to give results that can be directly used in hydrological studies. This paper quantifies three simple methods of rainfall scenarios construction informed by GCMs for their potential use in providing desirable future rainfall scenarios for modelling runoff projections. Runoff simulations from daily rainfall time series obtained using three simple methods (constant scaling, daily scaling and daily translation) to transform GCM outputs to catchment-scale rainfall over South-East Australia for 1981- 2000 and 2046-2065 periods are used. In the constant scaling and daily scaling methods, the historical observed daily rainfall is scaled by the changes indicated by the GCM. In the constant scaling method, the entire daily rainfall series (in seasons) is scaled by the same factor. In daily scaling, the different daily rainfall amounts are scaled differently. In daily translation, a relationship between GCM simulation of the present rainfall and the observed catchment-scale rainfall is established, and used to convert the future GCM daily rainfall time series to catchment-scale rainfall series. In summary, the constant scaling method can be used in most applications to transform climate outputs from GCMs to drive hydrological models. However, where more detailed analyses of runoff distribution is required, the daily scaling and daily translation methods are potentially better, particularly if the GCMs used have skill in modelling extreme rainfall and daily rainfall series.
