scholarly journals Application of a Disaggregation Method for the Generation of Climate Changed Intensity-Duration-Frequency Curves for Predicting Future Extreme Rainfall Impacts on Transportation Infrastructure

2019 ◽  
Vol 271 ◽  
pp. 04002 ◽  
Author(s):  
Cesar Do Lago ◽  
Eduardo Mendiondo ◽  
Francisco Olivera ◽  
Marcio Giocomoni
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Extreme Rainfall ◽  
Global Climate Models ◽  
Transportation Infrastructure ◽  
Rainfall Regime ◽  
Rainfall Time Series ◽  
The Future ◽  
Intensity Duration Frequency ◽  
Frequency Curves

Potential consequences of climate change are the increase in the magnitude and frequency of extreme rainfall storm events. In order to assess what are the potential impacts of climate change in the transportation infrastructure, new intensity-duration-frequency curves are needed. In this study, projected IDF curves were created based on three Global Climate Models (GCM) for the representative concentration pathways (RCP) 4.5 and 8.5. The selected GCMs are: ACCESS1-0, CSIRO-MK3-0-6 and GFDL-ESM2M. Projected IDFs for the near (2025-2049), mid (2050-2074) and far future (2075-2099) were created after disaggregating the project rainfall time series using the Bartlett-Lewis Rectangular Pulses Stochastic Model. The projected IDFs were compared with the IDF currently used and generated based on historical data. The results indicate that climate change is likely to decrease rainfall intensities in all the future horizons in the tested area of San Antonio, Texas. Further analysis is recommended, including the use of bias correction of those GCM models and use of a broader range of models that can better quantify uncertainty of the future rainfall regime.

scholarly journals Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part II: Climate Change Impact Assessment)

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1548
Author(s):  
Suresh Marahatta ◽  
Deepak Aryal ◽  
Laxmi Prasad Devkota ◽  
Utsav Bhattarai ◽  
Dibesh Shrestha
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Climate Models ◽  
Assessment Tool ◽  
Swat Model ◽  
Global Climate Models ◽  
Climate Data ◽  
The Future ◽  
The Impact ◽  
Mountainous River

This study aims at analysing the impact of climate change (CC) on the river hydrology of a complex mountainous river basin—the Budhigandaki River Basin (BRB)—using the Soil and Water Assessment Tool (SWAT) hydrological model that was calibrated and validated in Part I of this research. A relatively new approach of selecting global climate models (GCMs) for each of the two selected RCPs, 4.5 (stabilization scenario) and 8.5 (high emission scenario), representing four extreme cases (warm-wet, cold-wet, warm-dry, and cold-dry conditions), was applied. Future climate data was bias corrected using a quantile mapping method. The bias-corrected GCM data were forced into the SWAT model one at a time to simulate the future flows of BRB for three 30-year time windows: Immediate Future (2021–2050), Mid Future (2046–2075), and Far Future (2070–2099). The projected flows were compared with the corresponding monthly, seasonal, annual, and fractional differences of extreme flows of the simulated baseline period (1983–2012). The results showed that future long-term average annual flows are expected to increase in all climatic conditions for both RCPs compared to the baseline. The range of predicted changes in future monthly, seasonal, and annual flows shows high uncertainty. The comparative frequency analysis of the annual one-day-maximum and -minimum flows shows increased high flows and decreased low flows in the future. These results imply the necessity for design modifications in hydraulic structures as well as the preference of storage over run-of-river water resources development projects in the study basin from the perspective of climate resilience.

scholarly journals Estimation of the Future Probable Precipitation based on the Assumption of Non-Stationarity in Seoul

2020 ◽  
Vol 20 (1) ◽  
pp. 19-29
Author(s):  
Minsu Jeong ◽  
Taesam Lee ◽  
JooHeon Lee ◽  
Hyeonseok Choi ◽  
Sunkwon Yoon
Keyword(s):  
Climate Change ◽  
Markov Chain ◽  
Differential Evolution ◽  
Frequency Analysis ◽  
Climate Models ◽  
Time Series Data ◽  
Global Climate Models ◽  
Series Data ◽  
Hourly Rainfall ◽  
The Future

In this study, an estimation of the future probable rainfall in Seoul, Korea, was performed, using non-stationary frequency analysis according to climate change and it was compared with the current probable rainfall. Hourly rainfall data provided by the Korea Meteorological Administration with durations of 1, 2, 3, 6, 12, 24, and 48-h were used as input. For the future projection of precipitation, the RCP 8.5 scenario was selected with the same durations. Moreover, the future hourly rainfall was extracted from using the daily precipitation from 29 Global Climate Models (GCMs), based on the statistical temporal down-scaling method and their corresponding bias corrections. Subsequently, the annual maximum precipitation was extracted for each year. In this study, both stationary and non-stationary frequency analysis was applied based on the observed and predicted time series data sets. In particular, for the non-stationary frequency analysis, the Differential Evolution Markov Chain technique, which combines the Bayesian-based Differential Evolution and Markov chain Monte Carlo methods, was adopted. Finally, the current and future intensity-duration-frequency curves were derived from the optimal probability distribution, and each probable rainfall was estimated. The results of the 29-scenario are presented with quantile estimations. The non-stationary frequency analysis results for Seoul revealed rainfalls of 94.4 mm/h for 30 y, 101.7 mm/h for 50 y, and 111.5 mm/h for 100 y return periods. The average value of the 29-GCM model ensemble was estimated to be approximately 5 mm/h higher than that obtained from the stationary frequency analysis. Considering the changes in hydrological characteristics due to climate change in Seoul, the results of this study could be utilized to pro-actively respond to natural disasters due to such phenomena.

scholarly journals The Impacts of Climate Change on Maximum Daily Discharge in the Payab Jamash Watershed, Iran

2019 ◽  
Vol 11 (1) ◽  
pp. 1035-1045
Author(s):  
Farzad Parandin ◽  
Asadollah Khoorani ◽  
Ommolbanin Bazrafshan
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Climate Models ◽  
River Flow ◽  
Flow Simulation ◽  
Global Climate Models ◽  
Historical Period ◽  
Future Period ◽  
The Future ◽  
Daily Discharge

Abstract One of the most crucial consequences of climate change involves the alteration of the hydrologic cycle and river flow regime of watersheds. This study was an endeavor to investigate the contributions of climate change to maximum daily discharge (MDD). To this end, the MDD simulation was carried out through implementing the IHACRES precipitation-runoff model in the Payyab Jamash watershed for the 21st century (2016-2100). Subsequently, the observed precipitation and temperature data of the weather stations (1980-2011) as well as 4 multi-model outputs of Global Climate Models (GCMs) under the maximum and minimum Representative Concentration Pathways (RCPs) (2016-2100) were utilized. In order to downscale the output of GCMs, Bias Correction (BC) statistical method was applied. The projections for the 21st century indicated a reduction in Maximum Daily Precipitation (MDP) in comparison with the historic period in the study area. The average projected MDP for the future period was 9 mm/day and 5 mm/ day under 2.6 and 8.5 RCPs (4.6% and 2.6% decrease compared with the historical period), respectively. Moreover, the temperature increased in Jamash Watershed based on 2.6 and 8.5 RCPs by 1∘C and 2∘C(3.7% and 7.4% increase compared with the historical period), respectively. The findings of flow simulation for the future period indicated a decrease in MDD due to the diminished MDP in the study area. The amount of this decrease under RCP8.5 was not remarkable (0.75 m3/s), whereas its value for RCP2.6 was calculated as 40m3/s (respectively, 0.11% and 5.88% decrease compared with the historical period).

scholarly journals A Multi-Hazard Probabilistic Framework for Quantifying Bridge Failure Risk Considering Climate Change

2019 ◽  
Vol 271 ◽  
pp. 01006
Author(s):  
Omid khandel ◽  
Mohamed Soliman
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Flood Hazard ◽  
Global Climate Models ◽  
Occurrence Rate ◽  
Temperature Profiles ◽  
Probabilistic Framework ◽  
Failure Risk ◽  
The Future ◽  
The Impact

Climate change has recently been recognized as a significant factor that can drive changes to current design and life-cycle assessment practices of infrastructure systems. The instability in temperature profiles and precipitation patterns in recent decades indicate that the future flood hazard occurrence rate may not necessarily follow historical trends. In addition to the impact of climate change on flood hazard occurrence rate and the associated scour progression, it could also affect the corrosion propagation in structural components. This paper presents a probabilistic framework for quantifying the multi-hazard failure risk of bridges under gradual and sudden deterioration considering climate change. Downscaled climate data adopted from the global climate models are employed to predict the future streamflow and temperature profiles at a given location. These profiles are subsequently used to quantify future failure probability and risk under corrosion and flood hazard. The proposed framework is illustrated on an existing bridge located in Oklahoma.

scholarly journals Comparative study of conceptual versus distributed hydrologic modelling to evaluate the impact of climate change on future runoff in unregulated catchments

2019 ◽  
Vol 11 (2) ◽  
pp. 341-366 ◽  
Author(s):  
Hashim Isam Jameel Al-Safi ◽  
Hamideh Kazemi ◽  
P. Ranjan Sarukkalige
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Climate ◽  
Distributed Model ◽  
Runoff Reduction ◽  
The Future ◽  
The Impact

Abstract The application of two distinctively different hydrologic models, (conceptual-HBV) and (distributed-BTOPMC), was compared to simulate the future runoff across three unregulated catchments of the Australian Hydrologic Reference Stations (HRSs), namely Harvey catchment in WA, and Beardy and Goulburn catchments in NSW. These catchments have experienced significant runoff reduction during the last decades due to climate change and human activities. The Budyko-elasticity method was employed to assign the influences of human activities and climate change on runoff variations. After estimating the contribution of climate change in runoff reduction from the past runoff regime, the downscaled future climate signals from a multi-model ensemble of eight global climate models (GCMs) of the Coupled Model Inter-comparison Project phase-5 (CMIP5) under the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios were used to simulate the future daily runoff at the three HRSs for the mid-(2046–2065) and late-(2080–2099) 21st-century. Results show that the conceptual model performs better than the distributed model in capturing the observed streamflow across the three contributing catchments. The performance of the models was relatively compatible in the overall direction of future streamflow change, regardless of the magnitude, and incompatible regarding the change in the direction of high and low flows for both future climate scenarios. Both models predicted a decline in wet and dry season's streamflow across the three catchments.

scholarly journals Introducing Non-Stationarity Into the Development of Intensity-Duration-Frequency Curves under a Changing Climate

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1008
Author(s):  
Daniele Feitoza Silva ◽  
Slobodan P. Simonovic ◽  
Andre Schardong ◽  
Joel Avruch Goldenfum
Keyword(s):  
Return Period ◽  
Climate Models ◽  
Global Climate ◽  
Extreme Rainfall ◽  
Value Theory ◽  
Extreme Value ◽  
Global Climate Models ◽  
Water Infrastructure ◽  
Planning And Design ◽  
Intensity Duration Frequency

Intensity-duration-frequency (IDF) relationships are traditional tools in water infrastructure planning and design. IDFs are developed under a stationarity assumption which may not be realistic, neither in the present nor in the future, under a changing climatic condition. This paper introduces a framework for generating non-stationary IDFs under climate change, assuming that probability of occurrence of quantiles changes over time. Using Extreme Value Theory, eight trend combinations in Generalized Extreme Value (GEV) parameters using time as covariate are compared with a stationary GEV, to identify the best alternative. Additionally, a modified Equidistance Quantile Matching (EQMNS) method is implemented to develop IDFs for future conditions, introducing non-stationarity where justified, based on the Global Climate Models (GCM). The methodology is applied for Moncton and Shearwater gauges in Northeast Canada. From the results, it is observed that EQMNS is able to capture the trends in the present and to translate them to estimated future rainfall intensities. Comparison of present and future IDFs strongly suggest that return period can be reduced by more than 50 years in the estimates of future rainfall intensities (e.g., historical 100-yr return period extreme rainfall may have frequency smaller than 50-yr under future conditions), raising attention to emerging risks to water infrastructure systems.

Projections for Temperature, Precipitation, Wind, and Snow in the Baltic Sea Region until 2100

2018 ◽  
Author(s):  
Ole Bøssing Christensen ◽  
Erik Kjellström
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Baltic Sea ◽  
Climate Models ◽  
Global Climate Models ◽  
Anthropogenic Climate Change ◽  
The Baltic Sea ◽  
Baltic Sea Region ◽  
The Future ◽  
The Baltic

The ecosystems and the societies of the Baltic Sea region are quite sensitive to fluctuations in climate, and therefore it is expected that anthropogenic climate change will affect the region considerably. With numerical climate models, a large amount of projections of meteorological variables affected by anthropogenic climate change have been performed in the Baltic Sea region for periods reaching the end of this century.Existing global and regional climate model studies suggest that:• The future Baltic climate will get warmer, mostly so in winter. Changes increase with time or increasing emissions of greenhouse gases. There is a large spread between different models, but they all project warming. In the northern part of the region, temperature change will be higher than the global average warming.• Daily minimum temperatures will increase more than average temperature, particularly in winter.• Future average precipitation amounts will be larger than today. The relative increase is largest in winter. In summer, increases in the far north and decreases in the south are seen in most simulations. In the intermediate region, the sign of change is uncertain.• Precipitation extremes are expected to increase, though with a higher degree of uncertainty in magnitude compared to projected changes in temperature extremes.• Future changes in wind speed are highly dependent on changes in the large-scale circulation simulated by global climate models (GCMs). The results do not all agree, and it is not possible to assess whether there will be a general increase or decrease in wind speed in the future.• Only very small high-altitude mountain areas in a few simulations are projected to experience a reduction in winter snow amount of less than 50%. The southern half of the Baltic Sea region is projected to experience significant reductions in snow amount, with median reductions of around 75%.

Future distribution of cotton and wheat in Australia under potential climate change

2015 ◽  
Vol 154 (2) ◽  
pp. 175-185 ◽  
Author(s):  
F. SHABANI ◽  
B. KOTEY
Keyword(s):  
Climate Change ◽  
Triticum Aestivum ◽  
Climate Models ◽  
Emission Scenario ◽  
Climatic Factors ◽  
Global Climate ◽  
Global Climate Models ◽  
Cotton Production ◽  
The Future ◽  
Potential Climate Change

SUMMARYThe present study applies refined and improved scenarios for climate change to quantify the effects of potential alterations in climatic factors on localities for wheat and cotton production, which are two crops important to Australia's economy. The future distributions of Gossypium (cotton) and Triticum aestivum L. (wheat) were modelled using CLIMEX software with the A2 emission scenario generated by CSIRO-Mk3·0 and MIROC-H global climate models. The results were correlated to identify areas suitable for these economically important crops for the years 2030, 2050, 2070 and 2100 in Australia. The analysis shows that the areas where wheat and cotton can be grown in Australia will diminish from 2030 to 2050 and 2070 through to 2100. While cotton can be grown over extensive areas of the country until 2070, the area grown to wheat will decrease significantly over the period.

scholarly journals Disaggregation of future GCMs to generate IDF curves for the assessment of urban floods

2021 ◽  
Author(s):  
H. Tayşi ◽  
M. Özger
Keyword(s):  
Climate Change ◽  
Short Duration ◽  
Urban Areas ◽  
Climate Models ◽  
Global Climate ◽  
Drainage System ◽  
Global Climate Models ◽  
Urban Floods ◽  
Idf Curves ◽  
Intensity Duration Frequency

Abstract Urbanization and industrialization cause an increase in greenhouse gas emissions, which in turn causes changes in the atmosphere. Climate change is causing extreme rainfalls and these rainfalls are getting stronger day after day. Floods are threatening urban areas, and short-duration rainfall and outdated drainages are responsible for urban floods. Intensity–Duration–Frequency (IDF) curves are crucial for both drainage system design and assessment of flood risk. Once IDF curves are determined from historical data, they are assumed to be stationary. However, IDF curves must be non-stationary and time varying based on preparation for extreme events. This study generates future IDF curves with short-duration rainfalls under climate change. To represent future rainfall, an ensemble of four Global Climate Models generated under Representative Concentration Pathways (RCP) 4.5 and 8.5 were used in this study. A new approach to the HYETOS disaggregation model was applied to disaggregate daily future rainfall into sub-hourly using disaggregation parameters of hourly measured rainfalls. Hence, sub-hourly future rainfalls will be obtained capturing historical rainfall patterns instead of random rainfall characteristics. Finally, historical and future IDF curves were compared. The study concludes that increases in short-duration rainfalls will be highly intensified in both the near and distant futures with a high probability.

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