Global evaluation of simulated high- and low-flows from 23 macro-scale models

Macro-scale hydrological/land surface models are important tools for assessing historical and predicting future characteristics of extreme hydrological events, yet quantitative understandings of how these large-scale models perform in simulating extreme hydrological characteristics remain limited. Here we evaluate simulated high- and low-flows from 23 macro-scale models within three modeling experiments (i.e., 14 climate models from CMIP6, 6 global hydrological models from ISIMIP2a and 3 land surface models from GLDAS) against observation in 633 unimpaired catchments globally over 1971-2010. Our findings reveal limitations in simulating extreme flow characteristics by these models. Specifically, we find that (i) most models overestimate high-flow magnitudes (bias range: +15% to +70%) and underestimate low-flow magnitudes (bias range: -80% to -20%); (ii) interannual variability in high- and low-flows is reasonably reproduced by ISIMIP2a and GLDAS models but poorly reproduced by CMIP6 models; (iii) no model consistently replicates the observed trend direction in high- and low-flows in over two-thirds of the catchments, and most models overestimate high-flow trends and underestimate low-flow trends; and (iv) CMIP6 and GLDAS models show timing biases, with early high-flows and late low-flows, while ISIMIP2a models exhibit the opposite pattern. Furthermore, all models performed better in more humid environments and non-cold regions, with model structure and parameterization contributing more to uncertainties than climatic forcings. Overall, our results demonstrate that extreme flow characteristics simulated from current state-of-the-art macro-scale models still contain large uncertainties and provide important guidance regarding the robustness of assessing extreme hydrometeorological events based on these modeling outputs.