Human impacts increasingly affect the global hydrological cycle and indeed dominate hydrological changes in some regions. Hydrologists have sought to identify the human-impact-induced hydrological variations via parameterizing anthropogenic water uses in global hydrological models (GHMs). The consequently increased model complexity is likely to introduce additional uncertainty among GHMs. Here, using four GHMs, between-model uncertainties are quantified in terms of the ratio of signal to noise (SNR) for average river flow during 1971–2000 simulated in two experiments, with representation of human impacts (VARSOC) and without (NOSOC). It is the first quantitative investigation of between-model uncertainty resulted from the inclusion of human impact parameterizations. Results show that the between-model uncertainties in terms of SNRs in the VARSOC annual flow are larger (about 2% for global and varied magnitude for different basins) than those in the NOSOC, which are particularly significant in most areas of Asia and northern areas to the Mediterranean Sea. The SNR differences are mostly negative (−20% to 5%, indicating higher uncertainty) for basin-averaged annual flow. The VARSOC high flow shows slightly lower uncertainties than NOSOC simulations, with SNR differences mostly ranging from −20% to 20%. The uncertainty differences between the two experiments are significantly related to the fraction of irrigation areas of basins. The large additional uncertainties in VARSOC simulations introduced by the inclusion of parameterizations of human impacts raise the urgent need of GHMs development regarding a better understanding of human impacts. Differences in the parameterizations of irrigation, reservoir regulation and water withdrawals are discussed towards potential directions of improvements for future GHM development. We also discuss the advantages of statistical approaches to reduce the between-model uncertainties, and the importance of calibration of GHMs for not only better performances of historical simulations but also more robust and confidential future projections of hydrological changes under a changing environment.
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, People’s Republic of China;Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, People’s Republic of China;University of Chinese Academy of Sciences, Beijing 100101, People’s Republic of China;Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, People’s Republic of China;Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, People’s Republic of China;University of Chinese Academy of Sciences, Beijing 100101, People’s Republic of China;Potsdam Institute for Climate Impact Research, 14412 Potsdam, Germany and Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany;School of Geography, University of Nottingham, Nottingham NG7 2RD, United Kingdom;National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki, 305-8506, Japan;International Institute for Applied Systems Analysis, Laxenburg, Austria;International Institute for Applied Systems Analysis, Laxenburg, Austria;NASA Goddard Institute for Space Studies, New York, United States of America;Center for Climate Systems Research, Columbia University, New York, United States of America;Department of Physical Geography, Utrecht University, Utrecht, The Netherlands
Recommended Citation:
Xingcai Liu,Qiuhong Tang,Huijuan Cui,et al. Multimodel uncertainty changes in simulated river flows induced by human impact parameterizations[J]. Environmental Research Letters,2017-01-01,12(2)