scholarly journals Quantifying the Impact of Future Climate Change on Runoff in the Amur River Basin Using a Distributed Hydrological Model and CMIP6 GCM Projections

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1560
Author(s):  
Ke Wen ◽  
Bing Gao ◽  
Mingliang Li

The Amur River is one of the top ten longest rivers in the world, and its hydrological response to future climate change has been rarely investigated. In this study, the outputs of four GCMs in the Coupled Model Intercomparison Project Phase 6 (CMIP6) were corrected and downscaled to drive a distributed hydrological model. Then, the spatial variations of runoff changes under the future climate conditions in the Amur River Basin were quantified. The results suggest that runoffs will tend to increase in the future period (2021–2070) compared with the baseline period (1961–2010), particularly in August and September. Differences were also found among different GCMs and scenarios. The ensemble mean of the GCMs suggests that the basin-averaged annual precipitation will increase by 14.6% and 15.2% under the SSP2-4.5 and SSP5-8.5 scenarios, respectively. The increase in the annual runoff under the SSP2-4.5 scenario (22.5%) is projected to be larger than that under the SSP5-8.5 scenario (19.2%) at the lower reach of the main channel. Future climate changes also tend to enhance the flood peak and flood volume. The findings of this study bring new understandings of the hydrological response to future climate changes and are helpful for water resource management in Eurasia.

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Nabaz R. Khwarahm

Abstract Background The oak tree (Quercus aegilops) comprises ~ 70% of the oak forests in the Kurdistan Region of Iraq (KRI). Besides its ecological importance as the residence for various endemic and migratory species, Q. aegilops forest also has socio-economic values—for example, as fodder for livestock, building material, medicine, charcoal, and firewood. In the KRI, Q. aegilops has been degrading due to anthropogenic threats (e.g., shifting cultivation, land use/land cover changes, civil war, and inadequate forest management policy) and these threats could increase as climate changes. In the KRI and Iraq as a whole, information on current and potential future geographical distributions of Q. aegilops is minimal or not existent. The objectives of this study were to (i) predict the current and future habitat suitability distributions of the species in relation to environmental variables and future climate change scenarios (Representative Concentration Pathway (RCP) 2.6 2070 and RCP8.5 2070); and (ii) determine the most important environmental variables controlling the distribution of the species in the KRI. The objectives were achieved by using the MaxEnt (maximum entropy) algorithm, available records of Q. aegilops, and environmental variables. Results The model demonstrated that, under the RCP2.6 2070 and RCP8.5 2070 climate change scenarios, the distribution ranges of Q. aegilops would be reduced by 3.6% (1849.7 km2) and 3.16% (1627.1 km2), respectively. By contrast, the species ranges would expand by 1.5% (777.0 km2) and 1.7% (848.0 km2), respectively. The distribution of the species was mainly controlled by annual precipitation. Under future climate change scenarios, the centroid of the distribution would shift toward higher altitudes. Conclusions The results suggest (i) a significant suitable habitat range of the species will be lost in the KRI due to climate change by 2070 and (ii) the preference of the species for cooler areas (high altitude) with high annual precipitation. Conservation actions should focus on the mountainous areas (e.g., by establishment of national parks and protected areas) of the KRI as climate changes. These findings provide useful benchmarking guidance for the future investigation of the ecology of the oak forest, and the categorical current and potential habitat suitability maps can effectively be used to improve biodiversity conservation plans and management actions in the KRI and Iraq as a whole.


2021 ◽  
Author(s):  
Xiaohong Chen ◽  
Haoyu Jin ◽  
Pan Wu ◽  
Wenjun Xia ◽  
Ruida Zhong ◽  
...  

Abstract The source region of the Yangtze River (SRYR) is located in the hinterland of the Tibetan Plateau (TP). The natural environment is hash, and the hydrological and meteorological stations are less distributed, making the observed data are relatively scarce. In order to overcome the impact of lack of data, the China Meteorological Forcing Dataset (CMFD) was used to correct the meteorological data, to make the data more closer to the real distribution on the SRYR surface. This paper used the Soil and Water Assessment Tool (SWAT) to verify interpolation effect. Since the SRYR is an important water resource protection area, have a great significance to study the hydrological response under future climate change. The Back Propagation (BP) neural network algorithm was used to integrate data extracted from the six Global Climate Models (GCMs), and then the SWAT model was used to predict runoff changes in the future status. The results show that the CMFD data set has a high precision in the SRYR, and can be used for meteorological data correction. After the meteorological data correction, the Nash-Sutcliffe efficiency increased from 0.64 to 0.70. Under the future climate change, the runoff in the SRYR shows a decreasing trend, and the distribution of runoff during the year changes greatly. This reflects the amount of water resources in the SRYR will be decreased, which will brings challenges to water resources management in the SRYR.


Author(s):  
zhen wang ◽  
Meixue Yang ◽  
xuejia wang ◽  
lizhen cheng ◽  
guoning wan ◽  
...  

Climate changes may pose challenges to water management. Simulation and projection of climate-runoff processes through hydrological models are essential means to assess the impact of global climate change on runoff variations. This study focuses on the upper Taohe River Basin which is an important water sources for arid and semi-arid regions in Northwest China. In order to assess the impacts of environmental changes, outputs from a regional climate model and the SWAT hydrological model were used to analyze the future climate change scenarios to water resources quantitatively. The examined climate changes scenarios results showed that average annual temperature from 2020 to 2099 in this area exhibits a consistent warming trend with different warming rates, at rates of 0.10°C/10a, 0.20°C /10a and 0.54°C /10a under RCP2.6, RCP4.5 and RCP8.5(Representative Concentration Pathways, RCPs), The value of precipitation experiences different trends under different emission scenarios. Under the RCP2.6, average precipitation would decrease at a rate of 3.69 mm/10a, while under the RCP4.5 and RCP8.5, it would increase at rates of 4.97 mm/10a and 12.28 mm/10a, respectively. The calibration and validation results in three in-site observations (Luqu, Xiabagou and Minxian) in the upper Taohe River Basin showed that SWAT hydrological model is able to produce an acceptable simulation of runoff at monthly time-step. In response to future climate changes, projected runoff change would present different decreasing trends. Under RCP2.6, annual average runoff would experience a progress of fluctuating trend, with a rate of-0.6×108m3 by 5-year moving average method; Under the RCP4.5 and RCP8.5, annual average runoff would show steadily increasing trends, with rates of 0.23×108m3 and 0.16×108m3 by 5-year moving average method. The total runoff in the future would prone to drought and flood disasters. Overall, this research results would provide a scientific reference for reginal water resources management on the long term.


2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Fei Yuan ◽  
Mingwei Ma ◽  
Liliang Ren ◽  
Hongren Shen ◽  
Yue Li ◽  
...  

Quantitative evaluation of future climate change impacts on hydrological drought characteristics is one of important measures for implementing sustainable water resources management and effective disaster mitigation in drought-prone regions under the changing environment. In this study, a modeling system for projecting the potential future climate change impacts on hydrological droughts in the Weihe River basin (WRB) in North China is presented. This system consists of a large-scale hydrological model driven by climate outputs from three climate models (CMs) for future streamflow projections, a probabilistic model for univariate drought assessment, and a copula-based bivariate model for joint drought frequency analysis under historical and future climates. With the observed historical climate data as the inputs, the Variable Infiltration Capacity hydrological model projects an overall runoff reduction in the WRB under the Intergovernmental Panel on Climate Change A1B scenario. The univariate drought assessment found that although fewer hydrological drought events would occur under A1B scenario, drought duration and severity tend to increase remarkably. Moreover, the bivariate drought assessment reveals that future droughts in the same return period as the baseline droughts would become more serious. With these trends in the future, the hydrological drought situation in the WRB would be further deteriorated.


2010 ◽  
Vol 4 ◽  
pp. 25-29 ◽  
Author(s):  
Xieyao Ma ◽  
Takao Yoshikane ◽  
Masayuki Hara ◽  
Yasutaka Wakazuki ◽  
Hiroshi G Takahashi ◽  
...  

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