Paul Rustomji

Modelling and testing spatially distributed sediment budgets to relate erosion processes to sediment yields

Identifying the erosion processes contributing to increased basin fine sediment yield is important for reducing downstream impacts on aquatic ecosystems. However, erosion rates are spatially variable, and much eroded sediment is stored within river basins and not delivered downstream. A spatially distributed sediment budget model is described that assesses the primary sources (hillslope soil erosion, gully and riverbank erosion) and sinks (floodplain and reservoir deposition) of fine sediment for each link in a river network. The model performance is evaluated in a 17,000-km^2 basin in south-east Australia using measured suspended sediment yields from eight catchments within the basin, each 100-700km^2 in area. Spatial variations within the basin in yield and area-specific yield were reliably predicted. Observed yields and area-specific yields varied by 17-fold and 15-fold respectively between the catchments, while predictions were generally within a factor of 2 of observations. Model efficiency at predicting variations in area-specific yield was good outside forested areas (0.58), and performance was weakly sensitive to parameter values. Yields from forested areas were under-predicted, and reducing the predicted influence of riparian vegetation on bank erosion improved model performance in those areas. The model provided more accurate and higher resolution predictions than catchment area interpolation of measured yields from neighbouring river basins. The model is suitable for guiding the targeting of remediation measures within river basins to reduce downstream sediment yields.

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

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 18C increase in global average surface air temperature. Using the best-performing RRM ensemble, approximately half the GCMES used 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 GCMES resulted in a difference of within 65% 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 GCMES projections. 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 GCMES and rainfall‐runoff modeling.