scholarly journals Drought Occurrence Probability Analysis Using Multivariate Standardized Drought Index and Copula Function Under Climate Change

2021 ◽  
Author(s):  
Kimia Naderi ◽  
mahnoosh moghaddasi ◽  
Ashkan Shokri
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Return Period ◽  
Drought Index ◽  
Historical Period ◽  
The Future ◽  
Joint Return ◽  
Joint Return Period ◽  
Drought Occurrence ◽  
Standardized Drought Index

Abstract This study aims to investigate the effect of climate change on the probability of drought occurrence in central Iran. To this end, a new drought index called Multivariate Standardized Drought Index (MSDI) was developed, which is composed of the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Soil Moisture Index (SSI). The required data included precipitation, temperature (from CRU TS), and soil moisture (from the ESA CCA SM product) on a monthly time scale for the 1980–2016 period. Moreover, future climate data were downloaded from CMIP6 models under the latest SSPs-RCPs emission scenarios (SSP1-2.6 and SSP5-8.5) for the 2020–2056 period. Based on the NRMSE, Sn, and NS evaluation criteria, the Galambos and Clayton functions were selected to derive copula-based joint distribution functions in both periods. The results showed that more severe droughts and longer will occur in the future compared to the historical period and in particular under the SSP5-8.5 scenario. From the derived joint return period, a drought event with defined severity or duration will happen in a shorter return period as compared with the historical period. In other words, joint return period indicated a higher probability of drought occurrence in the future period. Moreover, the joint return period analysis revealed that the return period of mild droughts will remain the same, while it decresed over extreme droughts in the future.

scholarly journals Time-varying copula and design life level-based nonstationary risk analysis of extreme rainfall events

2019 ◽  
Author(s):  
Pengcheng Xu ◽  
Dong Wang ◽  
Vijay P. Singh ◽  
Yuankun Wang ◽  
Jichun Wu ◽  
...  
Keyword(s):  
Climate Change ◽  
Risk Analysis ◽  
Return Period ◽  
Extreme Rainfall ◽  
Time Dependent ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Design Life ◽  
Joint Return ◽  
Joint Return Period

Abstract. Due to global climate change and urbanization, more attention has been paid to decipher the nonstationary multivariate risk analysis from the perspective of probability distribution establishment. Because of the climate change, the exceedance probability belonging to a certain extreme rainfall event would not be time invariant any more, which impedes the widely-used return period method for the usual hydrological and hydraulic engineering practice, hence calling for a time dependent method. In this study, a multivariate nonstationary risk analysis of annual extreme rainfall events, extracted from daily precipitation data observed at six meteorological stations in Haihe River basin, China, was done in three phases: (1) Several statistical tests, such as Ljung-Box test, and univariate and multivariate Mann-Kendall and Pettist tests were applied to both the marginal distributions and the dependence structures to decipher different forms of nonstationarity; (2) Time-dependent Archimedean and elliptical copulas combined with the Generalized Extreme Value (GEV) distribution were adopted to model the distribution structure from marginal and dependence angles; (3) A design life level-based (DLL-based) risk analysis associated with Kendall's joint return period (JRPken)and AND's joint return period (JRPand) methods was done to compare stationary and nonstationary models. Results showed DLL-based risk analysis through the JRPken method exhibited more sensitivity to the nonstationarity of marginal and bivariate distribution models than that through the JRPand method.

scholarly journals JOINT RETURN PERIOD ESTIMATION OF DAILY MAXIMUM AND MINIMUM TEMPERATURES USING COPULA METHOD

2021 ◽  
Vol 66 (2) ◽  
pp. 175-190
Author(s):  
M. A. M. Abraj ◽  
A. P. Hewaarachchi
Keyword(s):  
Return Period ◽  
Daily Maximum ◽  
Copula Method ◽  
Period Estimation ◽  
Joint Return ◽  
Joint Return Period

scholarly journals Joint return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation

2012 ◽  
Vol 9 (5) ◽  
pp. 6781-6828 ◽  
Author(s):  
S. Vandenberghe ◽  
M. J. van den Berg ◽  
B. Gräler ◽  
A. Petroselli ◽  
S. Grimaldi ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Three Dimensional ◽  
Distribution Functions ◽  
Return Periods ◽  
Design Variables ◽  
Joint Return ◽  
Design Values ◽  
Multivariate Frequency Analysis ◽  
Joint Return Period

Abstract. Most of the hydrological and hydraulic studies refer to the notion of a return period to quantify design variables. When dealing with multiple design variables, the well-known univariate statistical analysis is no longer satisfactory and several issues challenge the practitioner. How should one incorporate the dependence between variables? How should the joint return period be defined and applied? In this study, an overview of the state-of-the-art for defining joint return periods is given. The construction of multivariate distribution functions is done through the use of copulas, given their practicality in multivariate frequency analysis and their ability to model numerous types of dependence structures in a flexible way. A case study focusing on the selection of design hydrograph characteristics is presented and the design values of a three-dimensional phenomenon composed of peak discharge, volume and duration are derived. Joint return period methods based on regression analysis, bivariate conditional distributions, bivariate joint distributions, and Kendal distribution functions are investigated and compared highlighting theoretical and practical issues of multivariate frequency analysis. Also an ensemble-based method is introduced. For a given design return period, the method chosen clearly affects the calculated design event. Eventually, light is shed on the practical implications of a chosen method.

scholarly journals Estimations of statistical dependence as joint return period modulator of compound events. Part I: storm surge and wave height

2017 ◽  
Author(s):  
Thomas I. Petroliagkis
Keyword(s):  
Storm Surge ◽  
Wave Height ◽  
Return Period ◽  
Flood Hazard ◽  
Joint Probability ◽  
Irish Sea ◽  
Statistical Dependence ◽  
Joint Return ◽  
Compound Events ◽  
Joint Return Period

Abstract. The possibility of utilising statistical dependence methods in coastal flood hazard calculations is investigated, since flood risk is rarely a function of just one source variable but usually two or more. Source variables in most cases are not independent as they may be driven by the same weather event, so their dependence, which is capable of modulating their joint return period, has to be estimated before the calculation of their joint probability. Dependence and correlation may differ substantially from one another since dependence is focused heavily on tail (extreme) percentiles. The statistical analysis between surge and wave is performed over 32 river ending points along European coasts. Two sets of almost 35-year hindcasts of storm surge and wave height were adapted and results are presented by means of analytical tables and maps referring to both correlation and statistical dependence values. Further, the top 80 compound events were defined for each river ending point. Their frequency of occurrence was found to be distinctly higher during the cold months while their main low-level flow characteristics appear to be mainly in harmony with the transient nature of storms and their tracks. Overall, significantly strong values of positive correlations and dependencies were found over the Irish Sea, English Channel, south coasts of the North Sea, Norwegian Sea and Baltic Sea, with compound events taking place in a zero-lag mode. For the rest, mostly positive moderate dependence values were estimated even if a considerable number of them had correlations of almost zero or even negative value.

scholarly journals Appropriateness of Potential Evapotranspiration Models for Climate Change Impact Analysis in Yarlung Zangbo River Basin, China

Atmosphere ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 453 ◽  
Author(s):  
Pan ◽  
Xu ◽  
Xuan ◽  
Gu ◽  
Bai
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Climate Change Impact ◽  
Impact Analysis ◽  
Potential Evapotranspiration ◽  
Global Climate Models ◽  
Historical Period ◽  
Yarlung Zangbo River ◽  
The Future ◽  
Change Impact

Evapotranspiration (ET) is an important element in the water and energy cycle. Potential evapotranspiration (PET) is an important measurement of ET. Its accuracy has significant influence on agricultural water management, irrigation planning, and hydrological modelling. However, whether current PET models are applicable under climate change or not, is still a question. In this study, five frequently used PET models were chosen, including one combination model (the FAO Penman-Monteith model, FAO-PM), two temperature-based models (the Blaney-Criddle and the Hargreaves models) and two radiation-based models (the Makkink and the Priestley-Taylor models), to estimate their appropriateness in the historical and future periods under climate change impact on the Yarlung Zangbo river basin, China. Bias correction methods were not only applied to the temperature output of Global Climate Models (GCMs), but also for radiation, humidity, and wind speed. It was demonstrated that the results from the Blaney-Criddle and Makkink models provided better agreement with the PET obtained by the FAO-PM model in the historical period. In the future period, monthly PET estimated by all five models show positive trends. The changes of PET under RCP8.5 are much higher than under RCP2.6. The radiation-based models show better appropriateness than the temperature-based models in the future, as the root mean square error (RMSE) value of the former models is almost half of the latter models. The radiation-based models are recommended for use to estimate PET under climate change in the Yarlung Zangbo river basin.

scholarly journals Multi-factor joint return period of rainstorms and its agricultural risk analysis in Liaoning Province, China

2019 ◽  
Vol 10 (1) ◽  
pp. 1988-2008 ◽  
Author(s):  
Yu Feng ◽  
Ying Li ◽  
Zhiru Zhang ◽  
Shiyu Gong ◽  
Meijiao Liu ◽  
...  
Keyword(s):  
Risk Analysis ◽  
Return Period ◽  
Liaoning Province ◽  
Agricultural Risk ◽  
Joint Return ◽  
Joint Return Period

scholarly journals Assessment of spatiotemporal characteristics of agro-meteorological drought events based on comparing Standardized Soil Moisture Index, Standardized Precipitation Index and Multivariate Standardized Drought Index

2020 ◽  
Vol 11 (S1) ◽  
pp. 1-17 ◽  
Author(s):  
Muhammad Imran Khan ◽  
Xingye Zhu ◽  
Muhammad Arshad ◽  
Muhammad Zaman ◽  
Yasir Niaz ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Drought Indices ◽  
Moisture Index ◽  
Drought Characteristics ◽  
Soil Moisture Index ◽  
The Impact ◽  
Standardized Drought Index

Abstract Drought indices that compute drought events by their statistical properties are essential stratagems for the estimation of the impact of drought events on a region. This research presents a quantitative investigation of drought events by analyzing drought characteristics, considering agro-meteorological aspects in the Heilongjiang Province of China during 1980 to 2015. To examine these aspects, the Standardized Soil Moisture Index (SSI), Standardized Precipitation Index (SPI), and Multivariate Standardized Drought Index (MSDI) were used to evaluate the drought characteristics. The results showed that almost half of the extreme and exceptional drought events occurred during 1990–92 and 2004–05. The spatiotemporal analysis of drought characteristics assisted in the estimation of the annual drought frequency (ADF, 1.20–2.70), long-term mean drought duration (MDD, 5–11 months), mean drought severity (MDS, −0.9 to −2.9), and mild conditions of mean drought intensity (MDI, −0.2 to −0.80) over the study area. The results obtained by MSDI reveal the drought onset and termination based on the combination of SPI and SSI, with onset being dominated by SPI and drought persistence being more similar to SSI behavior. The results of this study provide valuable information and can prove to be a reference framework to guide agricultural production in the region.

Assessment of overtopping reliability and benefits of a flood detention dam

2008 ◽  
Vol 35 (10) ◽  
pp. 1177-1182 ◽  
Author(s):  
A. Melih Yanmaz ◽  
M. Engin Gunindi
Keyword(s):  
Return Period ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Site Specific ◽  
Joint Return ◽  
Dam Site ◽  
Bivariate Gamma Distribution ◽  
Project Characteristics ◽  
Joint Return Period

There is a growing tendency to assess safety levels of existing dams and to design new dams using probabilistic approaches according to project characteristics and site-specific conditions. This study is a probabilistic assessment of the overtopping reliability of a dam, which will be designed for flood detention purpose, and will compute the benefits that can be gained as a result of the implementation of this dam. In a case study, a bivariate flood frequency analysis was carried out using a five-parameter bivariate gamma distribution. A family of joint return period curves relating the runoff peak discharges to the runoff volumes at the dam site was derived. A number of hydrographs were also obtained under a joint return period of 100 years to observe the variation of overtopping tendency. The maximum reservoir elevation and overtopping reliability were determined by performing a probabilistic reservoir routing based on Monte Carlo simulations.

Quantitative multi-hazard risk assessment with vulnerability surface and hazard joint return period

2014 ◽  
Vol 29 (1) ◽  
pp. 35-44 ◽  
Author(s):  
Xiaodong Ming ◽  
Wei Xu ◽  
Ying Li ◽  
Juan Du ◽  
Baoyin Liu ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Return Period ◽  
Hazard Risk ◽  
Joint Return ◽  
Joint Return Period ◽  
Hazard Risk Assessment

scholarly journals Terrestrial ecosystems response to future changes in climate and atmospheric CO<sub>2</sub> concentration

2014 ◽  
Vol 11 (3) ◽  
pp. 3581-3614 ◽  
Author(s):  
V. K. Arora ◽  
G. J. Boer
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
High Latitude ◽  
Atmospheric Co2 ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Terrestrial Carbon ◽  
Simulated Precipitation ◽  
Atmospheric Carbon ◽  
Amazonian Region

Abstract. The response of the terrestrial carbon cycle to future changes in climate and atmospheric CO2 is assessed by analyzing simulations, for the 2006–2100 period, made with the second generation Canadian Earth system model (CanESM2) for the RCP 2.6, RCP 4.5 and RCP 8.5 climate change scenarios. Our interest is in the extent to which global terrestrial carbon pools and sinks, in particular those of the Amazonian region, are vulnerable to the adverse effects of climate change. CanESM2 results indicate that land remains an overall sink of atmospheric carbon for the 2006–2100 period. The net carbon uptake by land in response to changes in climate and atmospheric CO2 is close to 20, 80 and 140 Pg C for the RCP 2.6, 4.5 and 8.5 scenarios, respectively. The latitudinal structure of future atmosphere–land CO2 flux remains similar to that observed for the historical period with northern mid- to high-latitude regions gaining carbon from the atmosphere while the tropics remain either carbon neutral or a modest source of atmospheric carbon depending on scenario. These changes occur in conjunction with simulated precipitation and soil moisture increases over northern mid- and high-latitude land regions and precipitation and soil moisture decreases over the South American continent in all scenarios. Compared to other regions of the globe, which are either carbon sinks or near neutral, the Amazonian region is simulated to be a net source of carbon during the 21st century. Moreover, and unexpectedly, the rate of carbon loss to the atmosphere from the Amazonian region is largely independent of the differences between the three scenarios considered.

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