Global Evaluation of Simulated High and Low Flows from 23 Macroscale Models

Author:

Guo Hui12,Hou Ying1,Yang Yuting1,McVicar Tim R.3

Affiliation:

1. a State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing, China

2. b North China University of Water Resources and Electric Power, Zhengzhou, China

3. c CSIRO Environment, Black Mountain, Canberra, Australian Capital Territory, Australia

Abstract

Abstract Macroscale 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 macroscale 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: from +15% to +70%) and underestimate low-flow magnitudes (bias range: from −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 noncold 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 macroscale models still contain large uncertainties and provide important guidance regarding the robustness of assessing extreme hydrometeorological events based on these modeling outputs. Significance Statement Macroscale hydrological and land surface models represent crucial tools for assessing historical trends and making predictions about future hydrological changes. Nevertheless, our current understanding of the quantitative performance of these large-scale models in simulating extreme hydrological characteristics remains limited. Here, we evaluate simulated high and low flows from 23 state-of-the-art macroscale models against observation in 633 unimpaired catchments globally over 1971–2010. Our results reveal important limitations in the extreme flow characteristics simulated from these models and provide important guidance regarding the robustness of assessing extreme hydrometeorological events based on these modeling outputs. The model evaluation performed herein serves as a pivotal, offering valuable insights to inform the development of the next generation of macroscale hydrological and land surface models.

Funder

Ministry of Science and Technology of the People''s Republic of China

National Natural Science Foundation of China

Publisher

American Meteorological Society

Reference96 articles.

1. Trends in global and basin-scale runoff over the late twentieth century: Methodological issues and sources of uncertainty;Alkama, R.,2011

2. Global maps of streamflow characteristics based on observations from several thousand catchments;Beck, H. E.,2015

3. Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling;Beck, H. E.,2017a

4. Global evaluation of runoff from 10 state-of-the-art hydrological models;Beck, H. E.,2017b

5. The influence of climate model uncertainty on fluvial flood hazard estimation;Beevers, L.,2020

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