Impact assessment of multiple uncertainty sources on high flows under climate change

2015 ◽  
Vol 47 (1) ◽  
pp. 61-74 ◽  
Author(s):  
Ye Tian ◽  
Yue-Ping Xu ◽  
Martijn J. Booij ◽  
Long Cao
Keyword(s):  
Climate Change ◽  
Eastern China ◽  
Maximum Temperature ◽  
Annual Maximum ◽  
Emission Scenarios ◽  
Hydrologic Models ◽  
Future Period ◽  
Uncertainty Sources ◽  
Small Uncertainty ◽  
High Flows

This paper aims to investigate the uncertainty ranges of high flows under climate change in Jinhua River basin, eastern China. Four representative concentration pathways (RCPs), three global climate models (GCMs), 10 downscaling parameter sets and three hydrologic models are applied to simulate future discharges. Changes of annual maximum discharges are assessed for the baseline period (1961–1990) and future period (2011–2040). The uncertainties of annual maximum discharges are calculated for each uncertainty source and compared with different combinations of them. The minimum temperature will probably increase all year round in the future period and maximum temperature would increase in most cases. The changes of precipitation showed different directions by different models and emission scenarios. The annual maximum discharges would decrease for all RCPs. The order of uncertainty ranges of high flows due to different uncertainty sources from high to low is: hydrologic models, GCMs, parameter sets in the downscaling method and emission scenarios. It must be noted that the small uncertainty contribution from different emission scenarios is due to the study period when the differences in increase of radiative forcing and greenhouse gas concentration are less obvious between different RCPs compared to the second half of the 21st century.

scholarly journals Evaluating the climate change effects on temperature, precipitation and evapotranspiration in eastern Iran using CMPI5

2021 ◽  
Author(s):  
Guangli Fan ◽  
Amjad Sarabandi ◽  
Mostafa Yaghoobzadeh
Keyword(s):  
Climate Change ◽  
Climate Changes ◽  
Maximum Temperature ◽  
Emission Scenarios ◽  
Future Period ◽  
Climate Change Effects ◽  
Eastern Iran ◽  
Large Fluctuations ◽  
Rcp 8.5 ◽  
Maximum Temperatures

Abstract In this study, the trend of climate changes during a future period from 2020 to 2039 has been evaluated using the data of the Fifth Climate Change Report under two emission scenarios RCP 4.5 and RCP 8.5 for Neishabour plain, Iran. Eleven models such as CESM, EC EARTH, HADGEM, MPI, NORESM, CANESM, CSIROM, GFDLCM2, GISS E2, IPSL and MIROC ESM have been used to evaluate changes in minimum and maximum temperatures, precipitation, and evapotranspiration. The results showed that GFDLCM2, MPI and IPSL models were more accurate in terms of precipitation and GISS E2 and GFDLCM2 models were the suitable option for predicting the maximum and minimum temperatures and evapotranspiration. Considering the evaluated parameters, minimum temperature, maximum temperature and evapotranspiration had approximately the constant trends and were accompanied by a slight increase and decrease for the next two decades, but for the precipitation, large fluctuations were predicted for the next period. Moreover, in the study years for the four parameters in all simulated models, the RCP 8.5 scenario has estimated a higher amount than the RCP 4.5 scenario.

scholarly journals Prediction of extreme floods based on CMIP5 climate models: a case study in the Beijiang River basin, South China

2015 ◽  
Vol 19 (3) ◽  
pp. 1385-1399 ◽  
Author(s):  
C. H. Wu ◽  
G. R. Huang ◽  
H. J. Yu
Keyword(s):  
Climate Change ◽  
River Basin ◽  
South China ◽  
Climate Models ◽  
Annual Maximum ◽  
Emission Scenarios ◽  
Vic Model ◽  
Extreme Floods ◽  
Beijiang River ◽  
Increasing Trends

Abstract. The occurrence of climate warming is unequivocal, and is expected to be experienced through increases in the magnitude and frequency of extreme events, including flooding. This paper presents an analysis of the implications of climate change on the future flood hazard in the Beijiang River basin in South China, using a variable infiltration capacity (VIC) model. Uncertainty is considered by employing five global climate models (GCMs), three emission scenarios (representative concentration pathway (RCP) 2.6, RCP4.5, and RCP8.5), 10 downscaling simulations for each emission scenario, and two stages of future periods (2020–2050, 2050–2080). Credibility of the projected changes in floods is described using an uncertainty expression approach, as recommended by the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). The results suggest that the VIC model shows a good performance in simulating extreme floods, with a daily runoff Nash–Sutcliffe efficiency coefficient (NSE) of 0.91. The GCMs and emission scenarios are a large source of uncertainty in predictions of future floods over the study region, although the overall uncertainty range for changes in historical extreme precipitation and flood magnitudes are well represented by the five GCMs. During the periods 2020–2050 and 2050–2080, annual maximum 1-day discharges (AMX1d) and annual maximum 7-day flood volumes (AMX7fv) are expected to show very similar trends, with the largest possibility of increasing trends occurring under the RCP2.6 scenario, and the smallest possibility of increasing trends under the RCP4.5 scenario. The projected ranges of AMX1d and AMX7fv show relatively large variability under different future scenarios in the five GCMs, but most project an increase during the two future periods (relative to the baseline period 1970–2000).

scholarly journals Assessment of extreme flows and uncertainty under climate change: disentangling the uncertainty contribution of representative concentration pathways, global climate models and internal climate variability

2020 ◽  
Vol 24 (6) ◽  
pp. 3251-3269 ◽  
Author(s):  
Chao Gao ◽  
Martijn J. Booij ◽  
Yue-Ping Xu
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
River Basin ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Internal Climate Variability ◽  
Low Flows ◽  
Uncertainty Sources ◽  
High Flows

Abstract. Projections of streamflow, particularly of extreme flows under climate change, are essential for future water resources management and the development of adaptation strategies to floods and droughts. However, these projections are subject to uncertainties originating from different sources. In this study, we explored the possible changes in future streamflow, particularly for high and low flows, under climate change in the Qu River basin, eastern China. ANOVA (analysis of variance) was employed to quantify the contribution of different uncertainty sources from RCPs (representative concentration pathways), GCMs (global climate models) and internal climate variability, using an ensemble of 4 RCP scenarios, 9 GCMs and 1000 simulated realizations of each model–scenario combination by SDRM-MCREM (a stochastic daily rainfall model coupling a Markov chain model with a rainfall event model). The results show that annual mean flow and high flows are projected to increase and that low flows will probably decrease in 2041–2070 (2050s) and 2071–2100 (2080s) relative to the historical period of 1971–2000, suggesting a higher risk of floods and droughts in the future in the Qu River basin, especially for the late 21st century. Uncertainty in mean flows is mostly attributed to GCM uncertainty. For high flows and low flows, internal climate variability and GCM uncertainty are two major uncertainty sources for the 2050s and 2080s, while for the 2080s, the effect of RCP uncertainty becomes more pronounced, particularly for low flows. The findings in this study can help water managers to become more knowledgeable about and get a better understanding of streamflow projections and support decision making regarding adaptations to a changing climate under uncertainty in the Qu River basin.

scholarly journals Prediction of extreme floods based on CMIP5 climate models: a case study in the Beijiang River basin, South China

2014 ◽  
Vol 11 (8) ◽  
pp. 9643-9669 ◽  
Author(s):  
C. H. Wu ◽  
G. R. Huang ◽  
H. J. Yu
Keyword(s):  
Climate Change ◽  
River Basin ◽  
South China ◽  
Climate Models ◽  
Annual Maximum ◽  
Emission Scenarios ◽  
Vic Model ◽  
Extreme Floods ◽  
Beijiang River ◽  
Increasing Trends

Abstract. The occurrence of climate warming is unequivocal, and is expected to be experienced through increases in the magnitude and frequency of extreme events, including flooding. This paper presents an analysis of the implications of climate change on the future flood hazard in the Beijiang River basin in South China, using a Variable Infiltration Capacity (VIC) model. Uncertainty is considered by employing five Global Climate Models (GCMs), three emission scenarios (RCP2.6, RCP4.5, and RCP8.5), ten downscaling simulations for each emission scenario, and two stages of future periods (2020–2050, 2050–2080). Credibility of the projected changes in floods is described using an uncertainty expression approach, as recommended by the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). The results suggest that the VIC model shows a good performance in simulating extreme floods, with a daily runoff Nash and Sutcliffe efficiency coefficient (NSE) of 0.91. The GCMs and emission scenarios are a large source of uncertainty in predictions of future floods over the study region, although the overall uncertainty range for changes in historical extreme precipitation and flood magnitudes are well represented by the five GCMs. During the periods 2020–2050 and 2050–2080, annual maximum 1-day discharges (AMX1d) and annual maximum 7-day flood volumes (AMX7fv) are projected to show very similar trends, with the largest possibility of increasing trends occurring under the RCP2.6 scenario, and the smallest possibility of increasing trends under the RCP4.5 scenario. The projected ranges of AMX1d and AMX7fv show relatively large variability under different future scenarios in the five GCMs, but most project an increase during the two future periods (relative to the baseline period 1970–2000).

Assessing the spatio-temporal variation and uncertainty patterns of historical and future projected water resources in China

2013 ◽  
Vol 4 (3) ◽  
pp. 302-316
Author(s):  
Qiuan Zhu ◽  
Hong Jiang ◽  
Changhui Peng ◽  
Jinxun Liu ◽  
Xiuqin Fang ◽  
...  
Keyword(s):  
Climate Change ◽  
Temporal Variation ◽  
Spatial And Temporal Variation ◽  
Historical Period ◽  
Precipitation Pattern ◽  
Climate Change Scenarios ◽  
Emission Scenarios ◽  
Future Period ◽  
Dynamic Global Vegetation Model ◽  
The Future

The spatial and temporal variation and uncertainty of precipitation and runoff in China were compared and evaluated between historical and future periods under different climate change scenarios. The precipitation pattern is derived from observed and future projected precipitation data for historical and future periods, respectively. The runoff is derived from simulation results in historical and future periods using a dynamic global vegetation model (DGVM) forced with historical observed and global climate models (GCMs) future projected climate data, respectively. One GCM (CGCM3.1) under two emission scenarios (SRES A2 and SRES B1) was used for the future period simulations. The results indicated high uncertainties and variations in climate change effects on hydrological processes in China: precipitation and runoff showed a significant increasing trend in the future period but a decreasing trend in the historical period at the national level; the temporal variation and uncertainty of projected precipitation and runoff in the future period were predicted to be higher than those in the historical period; the levels of precipitation and runoff in the future period were higher than those in the historical period. The change in trends of precipitation and runoff are highly affected by different climate change scenarios. GCM structure and emission scenarios should be the major sources of uncertainty.

scholarly journals Spatio-Temporal Characteristics of Meteorological Drought Under Changing Climate in Semi-Arid Region of Northern Ethiopia

2020 ◽  
Author(s):  
Biniyam Yisehak ◽  
Henok Shiferaw ◽  
Haftu Abrha ◽  
Amdom Gebremedhin ◽  
Haftom Hagos ◽  
...  
Keyword(s):  
Climate Change ◽  
Meteorological Drought ◽  
Extreme Drought ◽  
Maximum Temperature ◽  
Northern Ethiopia ◽  
Emission Scenarios ◽  
Changing Climate ◽  
Spatial Coverage ◽  
Annual Minimum Temperature ◽  
Rcp 8.5

Abstract Background: Below-normal availability of water for a considerable period of time induces occurrence of drought. This paper investigates the characteristics of meteorological drought under changing climate. The meteorological drought was assessed using the Standardized Precipitation Index (SPI) and the Reconnaissance Drought Index (RDI). The climate change was also analyzed using delta based statistical downscaling approach of RCP 4.5 and RCP 8.5 in R software packages. Results: The result of climate change projections showed that the average annual minimum temperature will be increased by about 0.8-2.9°C. The mean annual maximum temperature will be also increased by 0.9-3.75 °C. The rainfall projection generally showed an increasing trend, it exhibited an average annual increase of 3.5-13.4 % over the study area. The drought projection showed that there would be extreme drought events in study area for the future (2018-2099). The SPI result indicates that drought will be occurred in the study area after 1-5 and 1-6 years under RCP 4.5 and 8.5 emission scenarios respectively and the RDI value also shows drought will occurred after 1-6 and 2-7 years under RCP 4.5 and RCP 8.5 emission scenarios respectively over the study area. Almost more than 72% of the current and future spatial coverage of drought in the study area will be affected by extreme drought, 22.3% severely and 5.57% also moderate drought.Conclusions: Therefore, the study helps to provide useful information for policy decision makers to implement different adaptation and mitigation measures of drought in the region.

scholarly journals A large-sample investigation into uncertain climate change impacts on high flows across Great Britain

2021 ◽  
Author(s):  
Rosanna Lane ◽  
Gemma Coxon ◽  
Jim Freer ◽  
Jan Seibert ◽  
Thorsten Wagener
Keyword(s):  
Climate Change ◽  
Great Britain ◽  
Climate Change Impacts ◽  
Heavy Precipitation ◽  
Hydrological Modelling ◽  
Climate Projections ◽  
Annual Maximum ◽  
Parameter Uncertainties ◽  
High Flows ◽  
The Impact

Abstract. Climate change may significantly increase flood risk across Great Britain (GB), but there are large uncertainties in both future climatic changes and how these propagate into changing river flows. Here, the impact of climate change on the magnitude and frequency of high flows is modelled for 346 larger (> 144 km2) catchments across GB using the latest UK Climate Projections (UKCP18) and the DECIPHeR hydrological modelling framework. This study provides the first spatially consistent GB projections including both climate ensembles and hydrological model parameter uncertainties. Generally, results indicated an increase in the magnitude and frequency of high flows (Q10, Q1 and annual maximum) along the west coast of GB in the future (2050–2075), with increases in annual maximum flows of up to 65 % for west Scotland. In contrast, median flows (Q50) were projected to decrease across GB. All flow projections contained large uncertainties, and while the RCMs were the largest source of uncertainty overall, hydrological modelling uncertainties were considerable in east and south-east England. Regional variation in flow projections were found to relate to i) differences in climatic change and ii) catchment conditions during the baseline period as characterised by the runoff coefficient (mean discharge divided by mean precipitation). Importantly, increased heavy-precipitation events (defined by an increase in 99th percentile precipitation) did not always result in increased flood flows for catchments with low runoff coefficients, highlighting the varying factors leading to changes in high flows. These results provide a national overview of climate change impacts on high flows across GB, which will inform climate change adaptation, while also highlighting the need to account for uncertainty sources when modelling climate change impact on high flows.

scholarly journals Assessment of extreme flows and uncertainty under climate change: disentangling the contribution of RCPs, GCMs and internal climate variability

2020 ◽  
Author(s):  
Chao Gao ◽  
Martijn J. Booij ◽  
Yue-Ping Xu
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
River Basin ◽  
Mean Flow ◽  
Extreme Flows ◽  
Internal Climate Variability ◽  
Low Flows ◽  
Uncertainty Sources ◽  
High Flows ◽  
Floods And Droughts

Abstract. Projections of streamflow, particularly of extreme flows under climate change are essential for future water resources management and development of adaptation strategies to floods and droughts. However, these projections are subject to uncertainties originating from different sources. In this study, we explore the possible changes in future streamflow, particularly for high and low flows, under climate change in the Qu River basin, East China. ANOVA (Analysis of Variance) is employed to quantify the contribution of different uncertainty sources from RCPs (Representative Concentration Pathways), GCMs (Global Climate Models) and internal climate variability, using an ensemble of four RCP scenarios, nine GCMs and 1,000 simulated realizations of each model-scenario combination by SDRM-MCREM (a stochastic daily rainfall model coupling a Markov chain model with a rainfall event model). The results show that annual mean flow and high flows are projected to increase and low flows will probably decrease in 2041–2070 (2050s) and 2071–2100 (2080s) relative to the historical period 1971–2000, suggesting a higher risk of floods and droughts in the future in the Qu River basin, especially for the late 21st century. Uncertainty in mean flows is mostly attributed to GCM uncertainty. For high flows and low flows, internal climate variability and GCM uncertainty are two major uncertainty sources for the 2050s and 2080s, while for the 2080s, the effect of RCP uncertainty is becoming more pronounced, particularly for low flows. The findings in this study can help water managers to get a better knowledge and understanding of streamflow projections and support decision making on adaptions to changing climate under uncertainty in the Qu River basin.

scholarly journals Estimating Extremes in Transient Climate Change Simulations

2005 ◽  
Vol 18 (8) ◽  
pp. 1156-1173 ◽  
Author(s):  
Viatcheslav V. Kharin ◽  
Francis W. Zwiers
Keyword(s):  
Climate Change ◽  
Extreme Value Distribution ◽  
Extreme Value ◽  
Value Distribution ◽  
Generalized Extreme Value Distribution ◽  
Precipitation Extremes ◽  
Maximum Temperature ◽  
Temperature Extremes ◽  
Emission Scenarios ◽  
Transient Climate Change

Abstract Changes in temperature and precipitation extremes are examined in transient climate change simulations performed with the second-generation coupled global climate model of the Canadian Centre for Climate Modelling and Analysis. Three-member ensembles were produced for the time period 1990–2100 using the IS92a, A2, and B2 emission scenarios of the Intergovernmental Panel on Climate Change. The return values of annual extremes are estimated from a fitted generalized extreme value distribution with time-dependent location and scale parameters by the method of maximum likelihood. The L-moment return value estimates are revisited and found to be somewhat biased in the context of transient climate change simulations. The climate response is of similar magnitude in the integrations with the IS92a and A2 emission scenarios but more modest for the B2 scenario. Changes in temperature extremes are largely associated with changes in the location of the distribution of annual extremes without substantial changes in its shape over most of the globe. Exceptions are regions where land and ocean surface properties change drastically, such as the regions that experience sea ice and snow cover retreat. Globally averaged changes in warm extremes are comparable to the corresponding changes in annual mean daily maximum temperature, while globally averaged cold extremes warm up faster than annual mean daily minimum temperature. There are considerable regional differences between the magnitudes of changes in temperature extremes and the corresponding annual means. Changes in precipitation extremes are due to changes in both the location and scale of the extreme value distribution and exceed substantially the corresponding changes in the annual mean precipitation. Generally speaking, the warmer model climate becomes wetter and hydrologically more variable. The probability of precipitation events that are considered extreme at the beginning of the simulations is increased by a factor of about 2 by the end of the twenty-first century.

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