scholarly journals Comparison of the Calculated Drought Return Periods Using Tri-variate and Bivariate Copula Functions Under Climate Change Condition

2021 ◽  
Author(s):  
Elaheh Motevali Bashi Naeini ◽  
Ali Mohammad Akhoond-Ali ◽  
Fereydoun Radmanesh ◽  
Jahangir Abedi Koupai ◽  
Shahrokh Soltaninia
Keyword(s):  
Climate Change ◽  
Return Periods ◽  
Copula Functions ◽  
Change Condition ◽  
Bivariate Copula

scholarly journals Comparison of the Calculated Drought Return Periods Using Tri-variate and Bivariate Copula Functions under Climate Change Condition

2021 ◽  
Author(s):  
Elahe Motevali Bashi Naeini ◽  
Ali Mohammad Akhondali ◽  
Fereydoun Radmanesh ◽  
Jahangir Abedi-Koupai ◽  
Shahrokh Soltaninia
Keyword(s):  
Climate Change ◽  
Decisive Role ◽  
Copula Function ◽  
Drought Indices ◽  
Return Periods ◽  
Copula Functions ◽  
Drought Duration ◽  
Drought Characteristics ◽  
Primary Water ◽  
Bivariate Copula

Concerning the various effects of climate change on intensifying extreme weather phenomena all around the world, studying its possible consequences in the following years has attracted the attention of researchers. As the drought characteristics identified by drought indices are highly significant in investigating the possible future drought, the Copula function is employed in many studies. In this study, the two- and three-variable Copula functions were employed for calculating the return period of drought events for the historical, the near future, and the far future periods. The results of considering the two- and three-variable Copula functions were separately compared with the results of the calculated Due to the high correlation between drought characteristics, bivariate and trivariate of Copula functions were applied to evaluate the return periods of the drought. The most severe historical drought was selected as the benchmark, and the drought zoning map for the GCM models was drawn. The results showed that severe droughts can be experienced, especially in the upper area of the basin where the primary water resource is located. Also, the nature of the drought duration plays a decisive role in the results of calculating the return periods of drought events.

scholarly journals Comparison of the Calculated Drought Return Periods Using Tri-variate and Bivariate Copula Functions under Climate Change Condition

2021 ◽  
Author(s):  
Elaheh Motevalibashi Naeini ◽  
Ali Mohammad Akhoond-Ali ◽  
Fereydoun Radmanesh ◽  
Jahangir Abedi Koupai ◽  
Shahrokh Soltaninia
Keyword(s):  
Climate Change ◽  
Decisive Role ◽  
Copula Function ◽  
Drought Indices ◽  
Return Periods ◽  
Copula Functions ◽  
Drought Duration ◽  
Drought Characteristics ◽  
Primary Water ◽  
Bivariate Copula

Abstract Concerning the various effects of climate change on intensifying extreme weather phenomena all around the world, studying its possible consequences in the following years has attracted the attention of researchers. As the drought characteristics identified by drought indices are highly significant in investigating the possible future drought, the Copula function is employed in many studies. In this study, the two- and three-variable Copula functions were employed for calculating the return period of drought events for the historical, the near future, and the far future periods. The results of considering the two- and three-variable Copula functions were separately compared with the results of the calculated Due to the high correlation between drought characteristics, bivariate and trivariate of Copula functions were applied to evaluate the return periods of the drought. The most severe historical drought was selected as the benchmark, and the drought zoning map for the GCM models was drawn. The results showed that severe droughts can be experienced, especially in the upper area of the basin where the primary water resource is located. Also, the nature of the drought duration plays a decisive role in the results of calculating the return periods of drought events.

scholarly journals Future behavior of wind wave extremes due to climate change

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hector Lobeto ◽  
Melisa Menendez ◽  
Iñigo J. Losada
Keyword(s):  
Climate Change ◽  
Wave Climate ◽  
Climate Change Scenarios ◽  
Return Periods ◽  
Extreme Wave ◽  
Future Behavior ◽  
Climate Simulations ◽  
Wave Conditions ◽  
Ne Pacific ◽  
Change In Mean

AbstractExtreme waves will undergo changes in the future when exposed to different climate change scenarios. These changes are evaluated through the analysis of significant wave height (Hs) return values and are also compared with annual mean Hs projections. Hourly time series are analyzed through a seven-member ensemble of wave climate simulations and changes are estimated in Hs for return periods from 5 to 100 years by the end of the century under RCP4.5 and RCP8.5 scenarios. Despite the underlying uncertainty that characterizes extremes, we obtain robust changes in extreme Hs over more than approximately 25% of the ocean surface. The results obtained conclude that increases cover wider areas and are larger in magnitude than decreases for higher return periods. The Southern Ocean is the region where the most robust increase in extreme Hs is projected, showing local increases of over 2 m regardless the analyzed return period under RCP8.5 scenario. On the contrary, the tropical north Pacific shows the most robust decrease in extreme Hs, with local decreases of over 1.5 m. Relevant divergences are found in several ocean regions between the projected behavior of mean and extreme wave conditions. For example, an increase in Hs return values and a decrease in annual mean Hs is found in the SE Indian, NW Atlantic and NE Pacific. Therefore, an extrapolation of the expected change in mean wave conditions to extremes in regions presenting such divergences should be adopted with caution, since it may lead to misinterpretation when used for the design of marine structures or in the evaluation of coastal flooding and erosion.

scholarly journals Flooding Conditions at Aveiro Port (Portugal) within the Framework of Projected Climate Change

2021 ◽  
Vol 9 (6) ◽  
pp. 595
Author(s):  
Américo Soares Ribeiro ◽  
Carina Lurdes Lopes ◽  
Magda Catarina Sousa ◽  
Moncho Gomez-Gesteira ◽  
João Miguel Dias
Keyword(s):  
Climate Change ◽  
Sea Level ◽  
Climate Change Impacts ◽  
Storm Surges ◽  
Historical Period ◽  
Return Periods ◽  
Wave Regime ◽  
Mean Sea Level ◽  
Sea Levels ◽  
Far Future

Ports constitute a significant influence in the economic activity in coastal areas through operations and infrastructures to facilitate land and maritime transport of cargo. Ports are located in a multi-dimensional environment facing ocean and river hazards. Higher warming scenarios indicate Europe’s ports will be exposed to higher risk due to the increase in extreme sea levels (ESL), a combination of the mean sea level, tide, and storm surge. Located on the west Iberia Peninsula, the Aveiro Port is located in a coastal lagoon exposed to ocean and river flows, contributing to higher flood risk. This study aims to assess the flood extent for Aveiro Port for historical (1979–2005), near future (2026–2045), and far future (2081–2099) periods scenarios considering different return periods (10, 25, and 100-year) for the flood drivers, through numerical simulations of the ESL, wave regime, and riverine flows simultaneously. Spatial maps considering the flood extent and calculated area show that most of the port infrastructures' resilience to flooding is found under the historical period, with some marginal floods. Under climate change impacts, the port flood extent gradually increases for higher return periods, where most of the terminals are at high risk of being flooded for the far-future period, whose contribution is primarily due to mean sea-level rise and storm surges.

Bias correction of extreme values of high resolution climate simulations for risk analysis.

2021 ◽  
Author(s):  
luis Augusto sanabria ◽  
Xuerong Qin ◽  
Jin Li ◽  
Robert Peter Cechet
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Extreme Values ◽  
The Body ◽  
Future Climate ◽  
Return Periods ◽  
Climate Conditions ◽  
Mitigation And Adaptation ◽  
Climate Simulations ◽  
The Impact

Abstract Most climatic models show that climate change affects natural perils' frequency and severity. Quantifying the impact of future climate conditions on natural hazard is essential for mitigation and adaptation planning. One crucial factor to consider when using climate simulations projections is the inherent systematic differences (bias) of the modelled data compared with observations. This bias can originate from the modelling process, the techniques used for downscaling of results, and the ensembles' intrinsic variability. Analysis of climate simulations has shown that the biases associated with these data types can be significant. Hence, it is often necessary to correct the bias before the data can be reliably used for further analysis. Natural perils are often associated with extreme climatic conditions. Analysing trends in the tail end of distributions are already complicated because noise is much more prominent than that in the mean climate. The bias of the simulations can introduce significant errors in practical applications. In this paper, we present a methodology for bias correction of climate simulated data. The technique corrects the bias in both the body and the tail of the distribution (extreme values). As an illustration, maps of the 50 and 100-year Return Period of climate simulated Forest Fire Danger Index (FFDI) in Australia are presented and compared against the corresponding observation-based maps. The results show that the algorithm can substantially improve the calculation of simulation-based Return Periods. Forthcoming work will focus on the impact of climate change on these Return Periods considering future climate conditions.

scholarly journals Effect of grazing period management on growth performances of camel in climate change condition

2019 ◽  
Author(s):  
Champak Bhakat
Keyword(s):  
Climate Change ◽  
Body Weight ◽  
Weight Gain ◽  
Body Weight Gain ◽  
The Body ◽  
Maximum Temperature ◽  
Change Condition ◽  
Average Maximum ◽  
Group 2 ◽  
Group 1

In order to decide the optimum time of grazing for camels during hot summer months, 10 growing camel calveswere divided into 2 equal groups. First group was sent for grazing during 10:00 h to 16:00 h daily and second groupallowed for grazing during thermo neutral period. The climatic variables were recorded daily (April 2012 to March2013). The average daily gain and total body weight gain in calves sent for grazing during relatively cool parts ofday (group 2) was significantly higher as compared to group 1 calves sent as per routine farm schedule. Theaverage intake of fodder and water from manger was higher in group 1 calves. The average DMI from manger forgroup 1 calves was higher as compared to group 2 calves. The comparative biometrics of camel calves in differentgrazing management practices revealed that body length, heart girth, height at wither, neck length were significantly(P<0.01) higher in group 2 calves as compared to group 1 calves. After 180 days of experimentation, humpcircumference vertical and hind leg length were significantly (P<0.05) increased in group 2 as compared to group1. Analysis of recorded data of climatic parameters revealed that average maximum temperature was higher duringJune 2012. The values of THI also were higher in monsoon and post monsoon months hence the practice of sendingcamel calves during relatively comfortable part of hot and hot humid months was successful in getting good growth.The relative humidity was significantly higher during morning as compared to evening period for all months. TheTHI was significantly lower during morning as compared to evening hours for all months in different climate forwhole year. Economic analysis reveals that the cost of feed per kg body weight gain was quite less in group 2 ascompared to group 1. So the practice of grazing of camel calves during cool hours of day remain profitable forfarmers by looking at the body weight gain and better body conformation in climate change condition.

scholarly journals Climate and hydrological variability: the catchment filtering role

2015 ◽  
Vol 19 (1) ◽  
pp. 379-387 ◽  
Author(s):  
I. Andrés-Doménech ◽  
R. García-Bartual ◽  
A. Montanari ◽  
J. B. Marco
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Peak Flow ◽  
Flood Frequency ◽  
Annual Maximum ◽  
Return Periods ◽  
Rainfall Runoff ◽  
Maximum Peak ◽  
Hydrological Variability ◽  
The Impact

Abstract. Measuring the impact of climate change on flood frequency is a complex and controversial task. Identifying hydrological changes is difficult given the factors, other than climate variability, which lead to significant variations in runoff series. The catchment filtering role is often overlooked and thus may hinder the correct identification of climate variability signatures on hydrological processes. Does climate variability necessarily imply hydrological variability? This research aims to analytically derive the flood frequency distribution based on realistic hypotheses about the rainfall process and the rainfall–runoff transformation. The annual maximum peak flow probability distribution is analytically derived to quantify the filtering effect of the rainfall–runoff process on climate change. A sensitivity analysis is performed according to typical semi-arid Mediterranean climatic and hydrological conditions, assuming a simple but common scheme for the rainfall–runoff transformation in small-size ungauged catchments, i.e. the CN-SCS model. Variability in annual maximum peak flows and its statistical significance are analysed when changes in the climatic input are introduced. Results show that depending on changes in the annual number of rainfall events, the catchment filtering role is particularly significant, especially when the event rainfall volume distribution is not strongly skewed. Results largely depend on the return period: for large return periods, peak flow variability is significantly affected by the climatic input, while for lower return periods, infiltration processes smooth out the impact of climate change.

scholarly journals Drought Risk Analysis in the Eastern Cape Province of South Africa: The Copula Lens

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1938 ◽  
Author(s):  
Christina M. Botai ◽  
Joel O. Botai ◽  
Abiodun M. Adeola ◽  
Jaco P. de Wit ◽  
Katlego P. Ncongwane ◽  
...  
Keyword(s):  
South Africa ◽  
Gaussian Copula ◽  
Dependence Structure ◽  
Drought Risk ◽  
Eastern Cape Province ◽  
Return Periods ◽  
Eastern Cape ◽  
Copula Functions ◽  
Drought Duration ◽  
Drought Duration And Severity

This research study was carried out to investigate the characteristics of drought based on the joint distribution of two dependent variables, the duration and severity, in the Eastern Cape Province, South Africa. The drought variables were computed from the Standardized Precipitation Index for 6- and 12-month accumulation period (hereafter SPI-6 and SPI-12) time series calculated from the monthly rainfall data spanning the last five decades. In this context, the characteristics of climatological drought duration and severity were based on multivariate copula analysis. Five copula functions (from the Archimedean and Elliptical families) were selected and fitted to the drought duration and severity series in order to assess the dependency measure of the two variables. In addition, Joe and Gaussian copula functions were considered and fitted to the drought duration and severity to assess the joint return periods for the dual and cooperative cases. The results indicate that the dependency measure of drought duration and severity are best described by Tawn copula families. The dependence structure results suggest that the study area exhibited low probability of drought duration and high probability of drought severity. Furthermore, the multivariate return period for the dual case is found to be always longer across all the selected univariate return periods. Based on multivariate analysis, the study area (particularly Buffalo City, OR Tambo and Alfred Zoo regions) is determined to have higher/lower risks in terms of the conjunctive/cooperative multivariate drought risk (copula) probability index. The results of the present study could contribute towards policy and decision making through e.g., formulation of the forward-looking contingent plans for sustainable management of water resources and the consequent applications in the preparedness for and adaptation to the drought risks in the water-linked sectors of the economy.

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