A 439-year simulated daily discharge dataset (1861–2299) for the upper Yangtze River, China

<p>The outputs of four global climate models (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR and MIROC5), which were statistically downscaled and bias corrected, were used to drive four hydrological models (Hydrologiska Byråns, HBV; Soil and Water Assessment Tool, SWAT; Soil and Water Integrated Model,...

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Main Authors: C. Gao, B. Su, V. Krysanova, Q. Zha, C. Chen, G. Luo, X. Zeng, J. Huang, M. Xiong, L. Zhang, T. Jiang
Format: Article
Language:English
Published: Copernicus Publications 2020-02-01
Series:Earth System Science Data
Online Access:https://www.earth-syst-sci-data.net/12/387/2020/essd-12-387-2020.pdf
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language English
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author C. Gao
B. Su
V. Krysanova
Q. Zha
C. Chen
G. Luo
X. Zeng
J. Huang
M. Xiong
L. Zhang
T. Jiang
spellingShingle C. Gao
B. Su
V. Krysanova
Q. Zha
C. Chen
G. Luo
X. Zeng
J. Huang
M. Xiong
L. Zhang
T. Jiang
A 439-year simulated daily discharge dataset (1861–2299) for the upper Yangtze River, China
Earth System Science Data
author_facet C. Gao
B. Su
V. Krysanova
Q. Zha
C. Chen
G. Luo
X. Zeng
J. Huang
M. Xiong
L. Zhang
T. Jiang
author_sort C. Gao
title A 439-year simulated daily discharge dataset (1861–2299) for the upper Yangtze River, China
title_short A 439-year simulated daily discharge dataset (1861–2299) for the upper Yangtze River, China
title_full A 439-year simulated daily discharge dataset (1861–2299) for the upper Yangtze River, China
title_fullStr A 439-year simulated daily discharge dataset (1861–2299) for the upper Yangtze River, China
title_full_unstemmed A 439-year simulated daily discharge dataset (1861–2299) for the upper Yangtze River, China
title_sort 439-year simulated daily discharge dataset (1861–2299) for the upper yangtze river, china
publisher Copernicus Publications
series Earth System Science Data
issn 1866-3508
1866-3516
publishDate 2020-02-01
description <p>The outputs of four global climate models (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR and MIROC5), which were statistically downscaled and bias corrected, were used to drive four hydrological models (Hydrologiska Byråns, HBV; Soil and Water Assessment Tool, SWAT; Soil and Water Integrated Model, SWIM; and Variable Infiltration Capacity, VIC) to simulate the daily discharge at the Cuntan hydrological station in the upper Yangtze River from 1861 to 2299. As the performances of hydrological models in various climate conditions could be different, the models were first calibrated in the period from 1979 to 1990. Then, the models were validated in the comparatively wet period, 1967–1978, and in the comparatively dry period, 1991–2002. A multi-objective automatic calibration programme using a univariate search technique was applied to find the optimal parameter set for each of the four hydrological models. The Nash–Sutcliffe efficiency (NSE) of daily discharge and the weighted least-squares function (WLS) of extreme discharge events, represented by high flow (<span class="inline-formula"><i>Q</i><sub>10</sub></span>) and low flow (<span class="inline-formula"><i>Q</i><sub>90</sub></span>), were included in the objective functions of the parameterization process. In addition, the simulated evapotranspiration results were compared with the GLEAM evapotranspiration data for the upper Yangtze River basin. For evaluating the performances of the hydrological models, the NSE, modified Kling–Gupta efficiency (KGE), ratio of the root-mean-square error to the standard deviation of the measured data (RSR) and Pearson's correlation coefficient (<span class="inline-formula"><i>r</i></span>) were used. The four hydrological models reach satisfactory simulation results in both the calibration and validation periods. In this study, the daily discharge is simulated for the upper Yangtze River under the preindustrial control (piControl) scenario without anthropogenic climate change from 1861 to 2299 and for the historical period 1861–2005 and for 2006 to 2299 under the RCP2.6, RCP4.5, RCP6.0 and RCP8.5 scenarios. The long-term daily discharge dataset can be used in the international context and water management, e.g. in the framework of Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) by providing clues to what extent human-induced climate change could impact streamflow and streamflow trend in the future. The datasets are available at: <a href="https://doi.org/10.4121/uuid:8658b22a-8f98-4043-9f8f-d77684d58cbc">https://doi.org/10.4121/uuid:8658b22a-8f98-4043-9f8f-d77684d58cbc</a> (Gao et al., 2019).</p>
url https://www.earth-syst-sci-data.net/12/387/2020/essd-12-387-2020.pdf
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spelling doaj-3d70d184b22645fc93f56985664285c42020-11-25T03:05:26ZengCopernicus PublicationsEarth System Science Data1866-35081866-35162020-02-011238740210.5194/essd-12-387-2020A 439-year simulated daily discharge dataset (1861–2299) for the upper Yangtze River, ChinaC. Gao0B. Su1V. Krysanova2Q. Zha3C. Chen4G. Luo5X. Zeng6J. Huang7M. Xiong8L. Zhang9T. Jiang10Department of Geography & Spatial Information Techniques, Ningbo University, Ningbo 315211, ChinaNational Climate Centre, China Meteorological Administration, Beijing 100081, ChinaPotsdam Institute for Climate Impact Research, Potsdam, GermanyDepartment of Geography & Spatial Information Techniques, Ningbo University, Ningbo 315211, ChinaDepartment of Geography & Spatial Information Techniques, Ningbo University, Ningbo 315211, ChinaDepartment of Geography & Spatial Information Techniques, Ningbo University, Ningbo 315211, ChinaSchool of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaBureau of Hydrology, Changjiang River Water Resources Commission, Wuhan 430010, ChinaState Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Institute for Disaster Risk Management, School of Geographical Science, Nanjing University of Information Science & Technology, Nanjing 210044, China<p>The outputs of four global climate models (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR and MIROC5), which were statistically downscaled and bias corrected, were used to drive four hydrological models (Hydrologiska Byråns, HBV; Soil and Water Assessment Tool, SWAT; Soil and Water Integrated Model, SWIM; and Variable Infiltration Capacity, VIC) to simulate the daily discharge at the Cuntan hydrological station in the upper Yangtze River from 1861 to 2299. As the performances of hydrological models in various climate conditions could be different, the models were first calibrated in the period from 1979 to 1990. Then, the models were validated in the comparatively wet period, 1967–1978, and in the comparatively dry period, 1991–2002. A multi-objective automatic calibration programme using a univariate search technique was applied to find the optimal parameter set for each of the four hydrological models. The Nash–Sutcliffe efficiency (NSE) of daily discharge and the weighted least-squares function (WLS) of extreme discharge events, represented by high flow (<span class="inline-formula"><i>Q</i><sub>10</sub></span>) and low flow (<span class="inline-formula"><i>Q</i><sub>90</sub></span>), were included in the objective functions of the parameterization process. In addition, the simulated evapotranspiration results were compared with the GLEAM evapotranspiration data for the upper Yangtze River basin. For evaluating the performances of the hydrological models, the NSE, modified Kling–Gupta efficiency (KGE), ratio of the root-mean-square error to the standard deviation of the measured data (RSR) and Pearson's correlation coefficient (<span class="inline-formula"><i>r</i></span>) were used. The four hydrological models reach satisfactory simulation results in both the calibration and validation periods. In this study, the daily discharge is simulated for the upper Yangtze River under the preindustrial control (piControl) scenario without anthropogenic climate change from 1861 to 2299 and for the historical period 1861–2005 and for 2006 to 2299 under the RCP2.6, RCP4.5, RCP6.0 and RCP8.5 scenarios. The long-term daily discharge dataset can be used in the international context and water management, e.g. in the framework of Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) by providing clues to what extent human-induced climate change could impact streamflow and streamflow trend in the future. The datasets are available at: <a href="https://doi.org/10.4121/uuid:8658b22a-8f98-4043-9f8f-d77684d58cbc">https://doi.org/10.4121/uuid:8658b22a-8f98-4043-9f8f-d77684d58cbc</a> (Gao et al., 2019).</p>https://www.earth-syst-sci-data.net/12/387/2020/essd-12-387-2020.pdf