Jean-Michel Perraud

Estimating the Relative Uncertainties Sourced from GCMs and Hydrological Models in Modeling Climate Change Impact on Runoff

AbstractThis paper assesses the relative uncertainties from GCMs and from hydrological models in modeling climate change impact on runoff across southeast Australia. Five lumped conceptual daily rainfall–runoff models are used to model runoff using historical daily climate series and using future climate series obtained by empirically scaling the historical climate series informed by simulations from 15 GCMs. The majority of the GCMs project a drier future for this region, particularly in the southern parts, and this is amplified as a bigger reduction in the runoff. The results indicate that the uncertainty sourced from the GCMs is much larger than the uncertainty in the rainfall–runoff models. The variability in the climate change impact on runoff results for one rainfall–runoff model informed by 15 GCMs (an about 28%–35% difference between the minimum and maximum results for mean annual, mean seasonal, and high runoff) is considerably larger than the variability in the results between the five rainfall–...

Rainfall-runoff Modelling across Southeast Australia: Datasets, Models and Results

Abstract This study describes a daily rainfall, potential evaporation and streamflow data set compiled for the important water resources region of southeast Australia, and the application of six commonly used lumped conceptual rainfall-runoff models to estimate daily runoff across the region. The daily climate data set and the daily modelled runoff are available from 1895 to 2008 at 0.05° grid resolution across the region. The modelling exercise indicates that the rainfall-runoff models can generally be calibrated to reproduce the daily observed streamflow (for 232 catchments in the high runoff generation areas), and the regionalisation results indicate that the use of optimised parameter values from a gauged catchment nearby can model runoff reasonably well in the ungauged areas. There are differences between the six models, but they are relatively small when used to describe aggregated results across large regions.

Conceptual Rainfall–Runoff Model Performance with Different Spatial Rainfall Inputs

AbstractDifferent methods have been used to obtain the daily rainfall time series required to drive conceptual rainfall–runoff models, depending on data availability, time constraints, and modeling objectives. This paper investigates the implications of different rainfall inputs on the calibration and simulation of 4 rainfall–runoff models using data from 240 catchments across southeast Australia. The first modeling experiment compares results from using a single lumped daily rainfall series for each catchment obtained from three methods: single rainfall station, Thiessen average, and average of interpolated rainfall surface. The results indicate considerable improvements in the modeled daily runoff and mean annual runoff in the model calibration and model simulation over an independent test period with better spatial representation of rainfall. The second experiment compares modeling using a single lumped daily rainfall series and modeling in all grid cells within a catchment using different rainfall inp...

Application of a Macroscale Hydrologic Model to Estimate Streamflow across Southeast Australia

AbstractReliable predictions of water availability and streamflow characteristics, and the impact of climate and land use change on water availability, are central to water resources planning and management. This paper assesses the application of the widely used macroscale hydrologic model, the three-layer Variable Infiltration Capacity model (VIC-3L), to estimate daily streamflow in 191 unregulated catchments across southeast Australia and evaluates the regionalization of model parameters to predict streamflow in ungauged catchments. The parameter values in the VIC-3L model are estimated using three methods: default values, optimized values based on model calibration, and regionalized values based on spatial proximity method. The modeled streamflows from VIC-3L are assessed against the observed streamflows from the catchments. The authors discuss the model performance based on different parameter estimation methods and the effects of rainfall regimes on streamflow prediction. Also the implication of usin...

Bias in streamflow projections due to climate‐induced shifts in catchment response

Demand for quantitative assessments of likely climate change impact on runoff is increasing and conceptual rainfall-runoff models are essential tools for this task. However, the capacity of these models to extrapolate under changing climatic conditions is questionable. A number of studies have found that model predictive skill decreases with changed climatic conditions, especially when predicting drier climates. We found that model skill only declines under certain circumstances, in particular, when a catchments rainfall-runoff processes change due to changed climatic drivers. In catchments where the rainfall-runoff relationship changed significantly in response to prolonged dry conditions, runoff was consistently overestimated. In contrast, modeled runoff was unbiased in catchments where the rainfall-runoff relationship remained unchanged during the dry period. These conclusions were not model dependent. Our results suggest that current projections of runoff under climate change may provide overly optimistic assessments of future water availability in some regions expecting rainfall reductions.

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.