scholarly journals Projecting Hydrological Responses to Climate Change Using CMIP6 Climate Scenarios for the Upper Huai River Basin, China

2021 ◽  
Vol 9 ◽  
Author(s):  
Guodong Bian ◽  
Jianyun Zhang ◽  
Jie Chen ◽  
Mingming Song ◽  
Ruimin He ◽  
...  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Return Period ◽  
Hydrological Model ◽  
Flood Frequency ◽  
Precipitation Series ◽  
Climate Scenarios ◽  
Huai River Basin ◽  
Huai River ◽  
Increasing Trend

The influence of climate change on the regional hydrological cycle has been an international scientific issue that has attracted more attention in recent decades due to its huge effects on drought and flood. It is essential to investigate the change of regional hydrological characteristics in the context of global warming for developing flood mitigation and water utilization strategies in the future. The purpose of this study is to carry out a comprehensive analysis of changes in future runoff and flood for the upper Huai River basin by combining future climate scenarios, hydrological model, and flood frequency analysis. The daily bias correction (DBC) statistical downscaling method is used to downscale the global climate model (GCM) outputs from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and to generate future daily temperature and precipitation series. The Xinanjiang (XAJ) hydrological model is driven to project changes in future seasonal runoff under SSP245 and SSP585 scenarios for two future periods: 2050s (2031–2060) and 2080s (2071–2100) based on model calibration and validation. Finally, the peaks over threshold (POT) method and generalized Pareto (GP) distribution are combined to evaluate the changes of flood frequency for the upper Huai River basin. The results show that 1) GCMs project that there has been an insignificant increasing trend in future precipitation series, while an obvious increasing trend is detected in future temperature series; 2) average monthly runoffs in low-flow season have seen decreasing trends under SSP245 and SSP585 scenarios during the 2050s, while there has been an obvious increasing trend of average monthly runoff in high-flow season during the 2080s; 3) there is a decreasing trend in design floods below the 50-year return period under two future scenarios during the 2050s, while there has been an significant increasing trend in design flood during the 2080s in most cases and the amplitude of increase becomes larger for a larger return period. The study suggests that future flood will probably occur more frequently and an urgent need to develop appropriate adaptation measures to increase social resilience to warming climate over the upper Huai River basin.

scholarly journals Variations of Drought Tendency, Frequency, and Characteristics and Their Responses to Climate Change under CMIP5 RCP Scenarios in Huai River Basin, China

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2174 ◽  
Author(s):  
Jingcai Wang ◽  
Hui Lin ◽  
Jinbai Huang ◽  
Chenjuan Jiang ◽  
Yangyang Xie ◽  
...  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Eastern China ◽  
Cmip5 Models ◽  
Drought Severity ◽  
Global Circulation Models ◽  
Huai River Basin ◽  
Huai River ◽  
The Future ◽  
The Impact

Huai River Basin (HRB) is an important food and industrial production area and a frequently drought-affected basin in eastern China. It is necessary to consider the future drought development for reducing the impact of drought disasters. Three global circulation models (GCMs) from Coupled Model Intercomparison Project phase 5 (CMIP5), such as CNRM-CM5 (CNR), HadGEM2-ES (Had) and MIROC5 (MIR), were used to assessment the future drought conditions under two Representative Concentration Pathways (RCPs) scenarios, namely, RCP4.5 and RCP8.5. The standardized precipitation evapotranspiration index (SPEI), statistical method, Mann-Kendall test, and run theory were carried out to study the variations of drought tendency, frequency, and characteristics and their responses to climate change. The research showed that the three CMIP5 models differ in describing the future seasonal and annual variations of precipitation and temperature in the basin and thus lead to the differences in describing drought trends, frequency, and drought characteristics, such as drought severity, drought duration, and drought intensity. However, the drought trend, frequency, and characteristics in the future are more serious than the history. The drought frequency and characteristics tend to be strengthened under the scenario of high concentration of RCP8.5, and the drought trend is larger than that of low concentration of RCP4.5. The lower precipitation and the higher temperature are the main factors affecting the occurrence of drought. All three CMIP5 models show that precipitation would increase in the future, but it could not offset the evapotranspiration loss caused by significant temperature rise. The serious risk of drought in the future is still higher. Considering the uncertainty of climate models for simulation and prediction, attention should be paid to distinguish the effects of different models in the future drought assessment.

Nonstationarity-based evaluation of flood frequency and flood risk in the Huai River basin, China

2018 ◽  
Vol 567 ◽  
pp. 393-404 ◽  
Author(s):  
Peng Sun ◽  
Qingzhi Wen ◽  
Qiang Zhang ◽  
Vijay P. Singh ◽  
Yuyan Sun ◽  
...  
Keyword(s):  
River Basin ◽  
Flood Risk ◽  
Flood Frequency ◽  
Huai River Basin ◽  
Huai River ◽  
The Huai River Basin

scholarly journals Trends of Hydroclimate Variables in the Upper Huai River Basin: Implications of Managing Water Resource for Climate Change Mitigation

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Abel Girma ◽  
Denghua Yan ◽  
Hao Wang ◽  
Xinshan Song ◽  
Tianlin Qin ◽  
...  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Trend Detection ◽  
Mean Annual Temperature ◽  
Study Region ◽  
Huai River Basin ◽  
Slope Test ◽  
Huai River ◽  
The Mean ◽  
Average Annual Precipitation

The present study attempted to investigate the trends of mean annual temperature, precipitation, and streamflow changes to determine their relationships in the upper Huai river basin. The Mann–Kendall (MK), Sen’s slope test estimator, and innovative trend detection (ф) (ITA) methods were used to detect the trends. According to the findings, average annual precipitation shows a descending trend (ф = −0.17) in most stations. An increasing trend was found only in Fuyang station (ф = 1.02). In all stations, the trends of mean annual temperature (ф = 0.36) were abruptly increased. During the past 57 years, the mean air temperature has considerably increased by 12°C/10a. The river streamflow showed a dramatic declining trend in all stations for the duration of the study period (1960–2016) (ф = −4.29). The climate variability in the study region affects the quantity of the streamflow. The river streamflow exhibits decreasing trends from 1965 onwards. The main possible reason for the declining stream flow in the study area is the declining amount of precipitation on some specific months due to the occurrence of climate change. The outcomes of this study could create awareness for the policymakers and members of the scientific community, informing them about the hydroclimatic evolutions across the study basin, and become an inordinate resource for advanced scientific research.

scholarly journals ESA CCI Soil Moisture Assimilation in SWAT for Improved Hydrological Simulation in Upper Huai River Basin

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Yongwei Liu ◽  
Wen Wang ◽  
Yuanbo Liu
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Hydrological Model ◽  
European Space Agency ◽  
Low Flow ◽  
Observation Error ◽  
Rainfall Runoff ◽  
Huai River Basin ◽  
Huai River ◽  
Streamflow Simulation

The assimilation of satellite soil moisture (SM) products with coarse resolution is promising in improving rainfall-runoff modeling, but it is largely impacted by the data assimilation (DA) strategy. This study performs the assimilation of a satellite soil moisture product from the European Space Agency (ESA) Climate Change Initiative (CCI) in a physically based semidistributed hydrological model (SWAT) in the upper Huai River basin in China, with the objective to improve its rainfall-runoff simulation. In this assimilation, the ensemble Kalman filter (EnKF) is adopted with full consideration of the model and observation error, the rescaling technique for satellite SM, and the regional applicability of the hydrological model. The results show that the ESA CCI SM assimilation generally improves the streamflow simulation of the study catchment. It is more effective for low-flow simulation, while for very high-flow/large-flood modeling, the DA performance shows uncertainty. The less-effective performance on large-flood simulation lies in the relatively low dependence of rainfall-runoff generation on the antecedent SM as during which the SM is nearly saturated and the runoff is largely dominated by precipitation. Besides, the efficiency of DA is deteriorated by the dense forest coverage and the complex topography conditions of the basin. Overall, the ESA CCI SM assimilation improves the streamflow simulation of the SWAT model in particular for low flow. This study provides an encouragement for the application of the ESA CCI SM in water management, especially over low-flow periods.

scholarly journals Improving the Distributed Hydrological Model Performance in Upper Huai River Basin: Using Streamflow Observations to Update the Basin States via the Ensemble Kalman Filter

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Yongwei Liu ◽  
Wen Wang ◽  
Yiming Hu ◽  
Wei Cui
Keyword(s):  
Kalman Filter ◽  
River Basin ◽  
Ensemble Kalman Filter ◽  
Hydrological Model ◽  
Model Performance ◽  
Real Data ◽  
Distributed Hydrological Model ◽  
Huai River Basin ◽  
Huai River

This study investigates the capability of improving the distributed hydrological model performance by assimilating the streamflow observations. Incorrectly estimated model states will lead to discrepancies between the observed and estimated streamflow. Consequently, streamflow observations can be used to update the model states, and the improved model states will eventually benefit the streamflow predictions. This study tests this concept in upper Huai River basin. We assimilate the streamflow observations sequentially into the Soil and Water Assessment Tool (SWAT) using the ensemble Kalman filter (EnKF) to update the model states. Both synthetic experiments and real data application are used to demonstrate the benefit of this data assimilation scheme. The experiment shows that assimilating the streamflow observations at interior sites significantly improves the streamflow predictions for the whole basin. Assimilating the catchment outlet streamflow improves the streamflow predictions near the catchment outlet. In real data case, the estimated streamflow at the catchment outlet is significantly improved by assimilating the in situ streamflow measurements at interior gauges. Assimilating the in situ catchment outlet streamflow also improves the streamflow prediction of one interior location on the main reach. This may demonstrate that updating model states using streamflow observations can constrain the flux estimates in distributed hydrological modeling.

scholarly journals Inconsistent variation of return periods of temperature extremum in China and its projection based on CMIP6 results

2021 ◽  
Vol 3 (12) ◽  
Author(s):  
Xueyuan Kuang ◽  
Danqing Huang ◽  
Ying Huang
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
High Temperature ◽  
Low Temperature ◽  
River Basin ◽  
Northeast China ◽  
Extreme Temperature ◽  
Huai River Basin ◽  
Huai River ◽  
Temperature Extremum

AbstractIncreasingly extreme temperature events under global warming can have considerable impacts on sectors such as industrial activities, health, and transportation, suggesting that risk for these kinds of events under climate change and its regional sensitivity should be reassessed. In this study, the observation and multi-model simulations from CMIP6 are comprehensively used to explore the regional differences of the extreme temperature response to climate change from the perspective of return period (RP). The Gumbel model of generalized extremum distribution is applied to estimate the RP for the annual extremum of temperature based on Gaussian distribution of daily temperature. The analysis on the observation in selected three sites indicates that the regional inconsistency of RP variation is not only existed in extreme high temperature (HTx) but also in low temperature (LTn) during the past several decades. The annual amplitude of temperature extremum in the Northeast China is enlarged with summer becoming hotter and winter becoming colder while the opposite situation is detected in Huang-Huai River Basin with cooler summer and relatively stable winter, and South China is characterized by hotter summer and slight warmer winter. From the spatial distribution of the HTx and LTn variations of fix RP, it is found that the Northeast China and Jiang-Huai River Basin is the most sensitive areas, respectively, in the response of extreme low temperature and high temperature to global warming. However, the regional inconsistency of the extreme temperature change is only observed under SSP1-2.6 scenario in the CMIP6 simulation but gradually disappeared from SSP2-4.5 to SSP5-8.5.

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