Estimating the Impact of Projected Climate Change on Runoff across the Tropical Savannas and Semiarid Rangelands of Northern Australia

• Published in: Journal of hydrometeorology 2012-04, Vol.13 (2), p.483-503
• Main Authors: Petheram, Cuan, Rustomji, Paul, McVicar, Tim R., Cai, WenJu, Chiew, Francis H. S., Vleeshouwer, Jamie, Van Niel, Thomas G., Li, LingTao, Cresswell, Richard G., Donohue, Randall J., Teng, Jin, Perraud, Jean-Michel
• Format: Article
• Language: English
• Subjects: Climate change; Climate models; Freshwater; Global climate models; Hydrological modeling; Modeling; Rain; Stormwater; Stream flow; Tropical climates; Watersheds
• ISSN: 1525-755X; 1525-7541
• DOI: 10.1175/JHM-D-11-062.1

The majority of the world’s population growth to 2050 is projected to occur in the tropics. Hence, there is a serious need for robust methods for undertaking water resource assessments to underpin the sustainable management of water in tropical regions. This paper describes the largest and most comprehensive assessment of the future impacts of runoff undertaken in a tropical region using conceptual rainfall–runoff models (RRMs). Five conceptual RRMs were calibrated using data from 115 streamflow gauging stations, and model parameters were regionalized using a combination of spatial proximity and catchment similarity. Future rainfall and evapotranspiration projections (denoted here as GCMES) were transformed to catchment-scale variables by empirically scaling (ES) the historical climate series, informed by 15 global climate models (GCMs), to reflect a 1°C increase in global average surface air temperature. Using the best-performing RRM ensemble, approximately half the GCMESused resulted in a spatially averaged increase in mean annual runoff (by up to 29%) and half resulted in a decrease (by up to 26%). However, ~70% of the GCMESresulted in a difference of within ±5% of the historical rainfall (1930–2007). The range in modeled impact on runoff, as estimated by five RRMs (for individual GCMES), was compared to the range in modeled runoff using 15 GCMES(for individual RRMs). For mid- to high runoff metrics, better predictions will come from improved GCMESprojections. A new finding of this study is that in the wet–dry tropics, for extremely large runoff events and low flows, improvements are needed in both GCMESand rainfall–runoff modeling.