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

Gao, Chao; Su, Buda; Krysanova, Valentina; Zha, Qianyu; Luo, Gang; Zeng, Xiangyong; Huang, Jinlong; Xiong, Ming; Zhang, Liping; Jiang, Tong

doi:10.5194/essd-12-387-2020

Cited by 9 publications

(10 citation statements)

References 33 publications

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“…Although there are differences in rainfall under the BCC_CSM_1, BNU_ESM, CCSM4, CSIRO_MK3_6_0, GFDL_ESM2G, IPSL_CM5A_MR, MRI_CGCM3, and NorESM1_M climate models, extreme rainfall is constantly increasing under the once every 100, 50, 20 and 10 years. Based on the analysis of CMIP5, previous studies in the Yangtze River Basin also showed the temperature and rainfall are increasing in this area, which is consistent with the article's conclusions from the NEX-GDDP dataset [59][60][61]. This shows that climate has a significant effect on runoff in the small-scale Tiaoxi basin.…”

Section: Climate Change Trend In Nex-gddpsupporting

confidence: 86%

Future Flood Risk Assessment under the Effects of Land Use and Climate Change in the Tiaoxi Basin

Yang

2020

Sensors

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Global warming and land-use change affects runoff in the regional basin. Affected by different factors, such as abundant rainfall and increased impervious surface, the Taihu basin becomes more vulnerable to floods. As a result, a future flood risk analysis is of great significance. This paper simulated the land-use expansion and analyzed the surface change from 2020 to 2050 using the neural network Cellular Automata Markov (CA-Markov) model. Moreover, the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP) dataset was corrected for deviation and used to analyze the climate trend. Second, the verified SWAT model was applied to simulate future runoff and to analyze the future flood risk. The results show that (1) land use is dominated by cultivated land and forests. In the future, the area of cultivated land will decrease and construction land will expand to 1.5 times its present size. (2) The average annual precipitation and temperature will increase by 1.2% and 1.5 degrees from 2020 to 2050, respectively. During the verified period, the NSE and r-square values of the SWAT model are greater than 0.7. (3) Compared with the historical extreme runoff, the extreme runoff in the return period will increase 10%~25% under the eight climate models in 2050. In general, the flood risk will increase further under the climate scenarios.

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Section: Climate Change Trend In Nex-gddpsupporting

confidence: 86%

Future Flood Risk Assessment under the Effects of Land Use and Climate Change in the Tiaoxi Basin

Yang

2020

Sensors

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“…There are also large modeling efforts on river discharge and an overview of these models is given in Gao et al. (2020). However, multi‐yearly data sets for salt intrusion length are rare.…”

Section: Data and Modelmentioning

confidence: 99%

Explaining the Statistical Properties of Salt Intrusion in Estuaries Using a Stochastic Dynamical Modeling Approach

Dijkstra

Biemond

Lee

et al. 2023

Water Resources Research

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Determining the statistical properties of salt intrusion in estuaries on sub‐tidal time scales is a substantial challenge in environmental modeling. To study these properties, we here extend an idealized deterministic salt intrusion model to a stochastic one by including a stochastic model of the river discharge. In the river discharge model, two types of stochastic forcing are used: one independent (additive noise) and one dependent (multiplicative noise) on the river discharge state. Each type of forcing results in a non‐Gaussian response in the salt intrusion length, which we consider here as the distance of the 2 psu isohaline contour to the estuary mouth. The salt intrusion model including both types of stochastic forcing in the river discharge provides a satisfactory explanation of the multi‐year statistics of observed salt intrusion lengths in the San Francisco Bay estuary, in particular for the skewness of its probability density function.

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“…The years 1971-1980 were considered for calibration and years 1981-1990 were used to validate the models. An automated calibration technique named univariate search technique was used to calibrate the parameters of the four HMs, which has been widely used in previous studies [35,36]. Model simulations were evaluated by the Nash-Sutcliffe efficiency (NSE), the percent bias (PBIAS, %) and the coefficient of determination (R 2 ).…”

Section: Hydrological Models and Model Calibrationmentioning

confidence: 99%

“…The flow chart for the hydrological modelling process was shown in Figure S1. A complete description of these four HMs and the calibration procedure can be found in our previous paper [36].…”

Section: Hydrological Models and Model Calibrationmentioning

confidence: 99%

“…UYRB, the study area in this study, is a large scale basin with drainage area approximately 8.6 × 105 km 2 . Therefore, this study did not consider the LULCC here following other previous studies [25,30,36]. We assumed constant land use/land cover throughout the 21st century, as we modeled the upper and more remote regions of the YRB only.…”

Section: Hydrological Models and Model Calibrationmentioning

confidence: 99%

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Using Integrated Hydrological Models to Assess the Impacts of Climate Change on Discharges and Extreme Flood Events in the Upper Yangtze River Basin

Luo

Cai

et al. 2021

Water

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Amongst the impacts of climate change, those arising from extreme hydrological events are expected to cause the greatest impacts. To assess the changes in temperature and precipitation and their impacts on the discharge in the upper Yangtze Basin from pre-industrial to the end of 21st century, four hydrological models were integrated with four global climate models. Results indicated that mean discharge was simulated to increase slightly for all hydrological models forced by all global climate models during 1771–1800 and 1871–1900 relative to the 1971–2000 reference period, whereas the change directions in mean discharge were not consistent among the four global climate models during 2070–2099, with increases from HadGEM2-ES and MIROC5, and decreases from GFDL-ESM2M and IPSL-CM5A-LR. Additionally, our results indicated that decreases in precipitation may always result in the decrease in mean discharge, but increases in precipitation did not always lead to increases in discharge due to high temperature rise. The changes in extreme flood events with different return intervals were also explored. These extreme events were projected to become more intense and frequent in the future, which could have potential devastating impacts on the society and ecosystem in this region.

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

Cited by 9 publications

References 33 publications

Future Flood Risk Assessment under the Effects of Land Use and Climate Change in the Tiaoxi Basin

Future Flood Risk Assessment under the Effects of Land Use and Climate Change in the Tiaoxi Basin

Explaining the Statistical Properties of Salt Intrusion in Estuaries Using a Stochastic Dynamical Modeling Approach

Using Integrated Hydrological Models to Assess the Impacts of Climate Change on Discharges and Extreme Flood Events in the Upper Yangtze River Basin

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