Preprints
https://doi.org/10.5194/hess-2021-528
https://doi.org/10.5194/hess-2021-528

  23 Dec 2021

23 Dec 2021

Review status: this preprint is currently under review for the journal HESS.

Attribution of climate change and human activities to streamflow variations with a posterior distribution of hydrological simulations

Xiongpeng Tang1,2,3, Guobin Fu4, Silong Zhang1, Chao Gao1, Guoqing Wang2,3, Zhenxin Bao2,3, Yanli Liu2,3, Cuishan Liu2,3, and Junliang Jin2,3 Xiongpeng Tang et al.
  • 1Beijing Normal University at Zhuhai, Zhuhai 519087, China
  • 2State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing 210098, China
  • 3Nanjing Hydraulic Research Institute, Nanjing 210029, China
  • 4CSIRO, Land and Water, Private Bag 5, Wembley, WA 6913, Australia

Abstract. Hydrological simulations are a main method of quantifying the contribution rate (CR) of climate change (CC) and human activities (HAs) to watershed streamflow changes. However, the uncertainty of hydrological simulations is rarely considered in current research. To fill this research gap, based on the Soil and Water Assessment Tool (SWAT) model, in this study, we propose a new framework to quantify the contribution rate of climate change and human activities based on the posterior histogram distribution of hydrological simulations. In our new quantitative framework, the uncertainty of hydrological simulations is first considered to avoid the phenomenon of "equifinality for different parameters", which is common in hydrological simulations. The Lancang River (LR) Basin in China, which has been greatly affected by human activities in the past two decades, is then selected as the study area. The global gridded monthly sectoral water use data set (GMSWU), coupled with the dead capacity data of the large reservoirs within the LR basin and the Budyko hypothesis framework, are used to compare the calculation result of the novel framework. The results show that (1) the annual streamflow at Yunjinghong station in the Lancang River Basin changed abruptly in 2005, which was mainly due to the construction of the Xiaowan hydropower station that started in October 2004. The annual streamflow and annual mean temperature time series from 1961 to 2015 in the LR Basin showed a significant decreasing and increasing trend at the α = 0.01 significance level, respectively. The annual precipitation showed an insignificant decreasing trend. (2) The results of quantitative analysis using the new framework showed that the reason for the decrease in the streamflow at Yunjinghong station was 42.6 % due to climate change, and the remaining 57.4 % was due to human activities, such as the construction of hydropower stations within the study area. (3) The comparison with the other two methods showed that the contribution rate of climate change calculated by the Budyko framework and the GMSWU data were 37.2 % and 42.5 %, respectively, and the errors of the calculations of the new framework proposed in this study were within 5 %. Therefore, the newly proposed framework, which considers the uncertainty of hydrological simulations, can accurately quantify the contribution rate of climate change and human activities to streamflow changes. (4) The quantitative results calculated by using the simulation results with the largest Nash-Sutcliffe efficiency coefficient (NSE) indicated that climate change was the dominant factor for streamflow reduction, which was in opposition to the calculation results of our new framework. In other words, our novel framework could effectively solve the calculation errors caused by the “equifinality for different parameters” of hydrological simulations. (5) The results of this case study also showed that the reduction in the streamflow in June and November was mainly caused by decreased precipitation and increased evapotranspiration, while the changes in the streamflow in other months were mainly due to human activities such as the regulation of the constructed reservoirs. In general, the novel quantitative framework that considers the uncertainty of hydrological simulations presented in this study has validated an efficient alternative for quantifying the contribution rate of climate change and human activities to streamflow changes.

Xiongpeng Tang et al.

Status: open (until 21 Feb 2022)

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Xiongpeng Tang et al.

Xiongpeng Tang et al.

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Short summary
In this study, we proposed a new framework that considered the uncertainties of model simulations to quantify the contribution rate of climate change and human activities to streamflow changes. Then, the Lancang River Basin was selected for the case study. The results of quantitative analysis using the new framework showed that the reason for the decrease in the streamflow at Yunjinghong station was mainly due to human activities.