scholarly journals Run Theory and Copula-Based Drought Risk Analysis for Songnen Grassland in Northeastern China

2019 ◽  
Vol 11 (21) ◽  
pp. 6032 ◽  
Author(s):  
Wu ◽  
Zhang ◽  
Bao ◽  
Guo
Keyword(s):  
Risk Analysis ◽  
Goodness Of Fit ◽  
Distribution Functions ◽  
Drought Severity ◽  
Dependence Structure ◽  
Drought Risk ◽  
Drought Event ◽  
Return Periods ◽  
Copula Functions ◽  
Run Theory

Droughts are among the more costly natural hazards, and drought risk analysis has become urgent for the proper planning and management of water resources in grassland ecosystems. We chose Songnen grassland as a case study, used a standardized precipitation evapotranspiration index (SPEI) to model drought characteristics, employed run theory to define the drought event, and chose copula functions to construct the joint distribution for drought variables. We applied two kinds of return periods to conduct a drought risk assessment. After evaluating and comparing several distribution functions, drought severity (DS) was best described by the generalized extreme value (GEV) distribution, whereas drought duration (DD) was best fitted by gamma distribution. The root mean square error (RMSE) and Akaike Information Criterion (AIC) goodness-of-fit measures to evaluate their performance, the best-performing copula is Frank copula to model the joint dependence structure for each drought variables. The results of the secondary return periods indicate that a higher risk of droughts occurs in Keshan county, Longjiang county, Qiqiha’er city, Taonan city, and Baicheng city. Furthermore, a relatively lower risk of drought was found in Bei’an city, Mingquan county, Qinggang county, and qian’an county, and also in the Changling county and Shuangliao city. According to the calculation of the secondary return periods, which considered all possible scenarios in our study, we found that the secondary return period may be the best indicator for evaluating grassland ecosystem drought risk management.

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.

scholarly journals Bivariate Hydrologic Risk Assessment of Flood Episodes using the Notation of Failure Probability

2020 ◽  
Vol 6 (10) ◽  
pp. 2002-2023
Author(s):  
Shahid Latif ◽  
Firuza Mustafa
Keyword(s):  
Failure Probability ◽  
Goodness Of Fit ◽  
Peak Flow ◽  
Gaussian Copula ◽  
Dependence Structure ◽  
Distribution Analysis ◽  
Return Periods ◽  
Goodness Of Fit Test ◽  
Flood Peak ◽  
Flood Volume

Floods are becoming the most severe and challenging hydrologic issue at the Kelantan River basin in Malaysia. Flood episodes are usually thoroughly characterized by flood peak discharge flow, volume and duration series. This study incorporated the copula-based methodology in deriving the joint distribution analysis of the annual flood characteristics and the failure probability for assessing the bivariate hydrologic risk. Both the Archimedean and Gaussian copula family were introduced and tested as possible candidate functions. The copula dependence parameters are estimated using the method-of-moment estimation procedure. The Gaussian copula was recognized as the best-fitted distribution for capturing the dependence structure of the flood peak-volume and peak-duration pairs based on goodness-of-fit test statistics and was further employed to derive the joint return periods. The bivariate hydrologic risks of flood peak flow and volume pair, and flood peak flow and duration pair in different return periods (i.e., 5, 10, 20, 50 and 100 years) were estimated and revealed that the risk statistics incrementally increase in the service lifetime and, at the same instant, incrementally decrease in return periods. In addition, we found that ignoring the mutual dependency can underestimate the failure probabilities where the univariate events produced a lower failure probability than the bivariate events. Similarly, the variations in bivariate hydrologic risk with the changes of flood peak in the different synthetic flood volume and duration series (i.e., 5, 10, 20, 50 and 100 years return periods) under different service lifetimes are demonstrated. Investigation revealed that the value of bivariate hydrologic risk statistics incrementally increases over the project lifetime (i.e., 30, 50, and 100 years) service time, and at the same time, it incrementally decreases in the return period of flood volume and duration. Overall, this study could provide a basis for making an appropriate flood defence plan and long-lasting infrastructure designs. Doi: 10.28991/cej-2020-03091599 Full Text: PDF

scholarly journals ANALISIS RISIKO KEKERINGAN DI KABUPATEN BANTUL PROVINSI D.I. YOGYAKARTA

2021 ◽  
Vol 18 (2) ◽  
pp. 143
Author(s):  
Annisa Mu'awanah Sukmawati ◽  
Puji Utomo
Keyword(s):  
Risk Analysis ◽  
Rural Areas ◽  
Hazard Analysis ◽  
Drought Risk ◽  
Drought Event ◽  
Quantitative Research Methods ◽  
Risk Areas ◽  
High Level ◽  
The Impact ◽  
Very High

Bantul Regency is a district in Yogyakarta Province which has geographic, geological, hydrological, and demographic characteristics that are likely to cause drought. Drought event in Bantul Regency may have significant impacts on various aspects in line with the characteristics of drought impacts which are complex and cross-sectoral. This study addresses to analyze the level of risk of drought with observation units in 75 villages in the Bantul Regency. The risk analysis was carried out by comparing the time period of the 10 years, i.e. 2008 and 2018 to observe the shift of risk areas of drought in Bantul Regency. The research was conducted using quantitative research methods with quantitative descriptive and mapping analysis. The analysis steps are drought hazard analysis, vulnerability analysis, and drought risk analysis. The analysis shows that during the last 10 years, Kabupaten Bantul has been experiencing an increasing number of villages classified as high risk of drought, both in urban and rural areas. In 2008 there were 15 villages (20%) and increased to 21 villages (28%) in 2018 that were classified as very very high level. Meanwhile, in 2008 there were 30 villages (40%) in 2008 and increased to 32 villages (42.7%) in 2018 that were classified as very high level. It caused by the increasing probability of drought as well as vulnerability. The analysis results can be used as input for stakeholders to take mitigation and anticipation actions to reduce the impact of drought based on the spatial characteristics of the risk areas.

Flash Drought Characteristics by Different Severities in Humid Subtropical Basins: A Case Study in the Gan River Basin, China

2021 ◽  
pp. 1-44
Author(s):  
Yuqing Zhang ◽  
Qinglong You ◽  
Guangxiong Mao ◽  
Changchun Chen ◽  
Xin Li ◽  
...  
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Vapour Pressure Deficit ◽  
Severity Index ◽  
Drought Severity ◽  
Rapid Decline ◽  
Drought Risk ◽  
Drought Event ◽  
Drought Period ◽  
Drought Intensity

AbstractIt is essential to assess flash drought risk based on a reliable flash drought intensity (severity) index incorporating comprehensive information of the rapid decline (“flash”) in soil moisture towards drought conditions and soil moisture thresholds belonging to the “drought” category. In this study, we used the Gan River Basin as an example to define a flash drought intensity index that can be calculated for individual time steps (pentads) during a flash drought period over a given grid (or station). The severity of a complete flash drought event is the sum of the intensity values during the flash drought. We explored the spatial and temporal characteristics of flash droughts with different grades based on their respective severities. The results show that decreases in total cloud cover, precipitation, and relative humidity, as well as increases in 500 hPa geopotential height, convective inhibition, temperature, vapour pressure deficit, and wind speed can create favorable conditions for the occurrence of flash droughts. Although flash droughts are relatively frequent in the central and southern parts of the basin, the severity is relatively high in the northern part of the basin due to longer duration. Flash drought severity shows a slightly downward trend due to decreases in frequency, duration, and intensity from 1961 to 2018. Extreme and exceptional flash droughts decrease significantly while moderate and severe flash droughts trend slightly upward. Flash drought severity appears to be more affected by the interaction between duration and intensity as the grade increases from mild to severe. The frequency and duration of flash droughts are higher in July to October. The southern part of the basin is more prone to moderate and severe flash droughts, while the northern parts of the basin are more vulnerable to extreme and exceptional flash droughts due to longer durations and greater severities than other parts. Moderate, severe, extreme, and exceptional flash droughts occurred approximately every 3-6, 5-15, 10-50, and 30-200 year intervals, respectively, based on the copula analysis.

scholarly journals Drought Risk Analysis Using Stochastic Rainfall Generation Model and Copula Functions

2013 ◽  
Vol 46 (4) ◽  
pp. 425-437 ◽  
Author(s):  
Ji Young Yoo ◽  
Ji Yae Shin ◽  
Dongkyun Kim ◽  
Tae-Woong Kim
Keyword(s):  
Risk Analysis ◽  
Drought Risk ◽  
Generation Model ◽  
Copula Functions

scholarly journals Modelling the statistical dependence of rainfall event variables through copula functions

2011 ◽  
Vol 15 (6) ◽  
pp. 1959-1977 ◽  
Author(s):  
M. Balistrocchi ◽  
B. Bacchi
Keyword(s):  
Goodness Of Fit ◽  
Joint Probability ◽  
Weibull Model ◽  
Rainfall Event ◽  
Probabilistic Methods ◽  
Statistical Dependence ◽  
Dependence Structure ◽  
Copula Functions ◽  
Distribution Fitting ◽  
Independent Events

Abstract. In many hydrological models, such as those derived by analytical probabilistic methods, the precipitation stochastic process is represented by means of individual storm random variables which are supposed to be independent of each other. However, several proposals were advanced to develop joint probability distributions able to account for the observed statistical dependence. The traditional technique of the multivariate statistics is nevertheless affected by several drawbacks, whose most evident issue is the unavoidable subordination of the dependence structure assessment to the marginal distribution fitting. Conversely, the copula approach can overcome this limitation, by dividing the problem in two distinct parts. Furthermore, goodness-of-fit tests were recently made available and a significant improvement in the function selection reliability has been achieved. Herein the dependence structure of the rainfall event volume, the wet weather duration and the interevent time is assessed and verified by test statistics with respect to three long time series recorded in different Italian climates. Paired analyses revealed a non negligible dependence between volume and duration, while the interevent period proved to be substantially independent of the other variables. A unique copula model seems to be suitable for representing this dependence structure, despite the sensitivity demonstrated by its parameter towards the threshold utilized in the procedure for extracting the independent events. The joint probability function was finally developed by adopting a Weibull model for the marginal distributions.

scholarly journals A Bayesian copula-based spatio-temporal method for multivariate drought risk analysis: A case study of the Balkhash Lake Basin

2021 ◽  
Author(s):  
Xin Yang ◽  
Yongping Li
Keyword(s):  
Risk Analysis ◽  
Temporal Analysis ◽  
Lake Basin ◽  
Drought Risk ◽  
Severe Drought ◽  
Drought Event ◽  
Spatio Temporal ◽  
Guarantee Rate ◽  
East West

In this study, a Bayesian copula spatio-temporal drought risk analysis (BCSDA) method is developed through coupling Bayesian copula and spatio-temporal analysis into a general framework. BCSDA can effectively identify drought characteristics and reveal the temporal and spatial variation, as well as analyze drought risk at different guaranteed rates based on the influence of multivariate interaction. Then, BCSDA is applied to the Balkhash Lake Basin (a typical arid watershed in Central Asia) for analyzing drought risk during 1901-2017. Major findings are: (i) Balkhash Lake Basin suffered 53 drought events in 1901-2017, and the most severe drought event occurred in October 1973 to January 1977, which lasted for 40 months and developed into an extreme drought during April 1975 to June 1976, affecting 335,800 square kilometers of the study basin; (ii) most of the drought events developed in the direction of east-west, and Lli River delta and the alluvial plain were the most severe of drought (47.2%), followed by the plateau desert area (28.3%) and the arid grassland in north of Balkhash Lake (24.5%); (iii) drought shows significant seasonality which usually began in spring and summer (64.2%) and ended in summer and autumn (66.0%); (iv) in Balkhash Lake Basin, multivariate characteristics (duration, severity and area) would significantly affect drought risk; (v) the range of drought risk would be [1.9%, 18.1%], [3.7%, 33.1%], [8.7%, 46.0%], [16.0%, 55.1%] and [27.6%, 59.8%] when guarantee rate is 0.99, 0.98, 0.95, 0.90 and 0.80.

ESTIMATION OF THE FLOOD MAXIMUM VOLUMES FOR VARIOUS DURATIONS OF THE RIVER RUNOFF AND THEIR MUTUAL DEPENDANCES: A CASE STUDY ON HRON RIVER IN SLOVAKIA

2020 ◽  
Author(s):  
Veronika Bačová Mitková ◽  
◽  
Dana Halmová ◽  
Keyword(s):  
Probability Distribution ◽  
Extreme Values ◽  
Random Variable ◽  
Distribution Functions ◽  
Mathematical Tool ◽  
Return Periods ◽  
Copula Functions ◽  
Time Duration ◽  
Positive Dependence ◽  
Log Normal

This work deals with the determination of the annual maximum discharge volumes on the Hron River for the runoff time duration t = 2, 5, 10, and 20 days. The series of 84 years (1931–2015) mean daily discharges of the Hron River at Banská Bystrica station was used as input data to calculate the maximum annual volumes of runoff of the Hron River. Subsequently, the theoretical curves of exceedance of the maximal discharge volumes were determined by the LogPearson distribution of the Type III. This type of probability distribution is used to estimate maximum (extreme) values across a range of natural processes. The results of the estimated T-year volumes by using PL III distribution were compared to other types of theoretical distribution functions used in hydrological extreme analyses in Slovakia (Gamma, Log-normal, etc.). The second part of our work was focused on the bivariate modelling of the relationship between T-year maximum volumes with different duration and peak discharges. In the case of modelling without evaluating this mutual dependence of the flood wave characteristics, they may be overestimated (in the case of the negative dependence) or underestimated (in the case of the positive dependence). The Archimedean class of copula functions was used as mathematical tool for the dependence modelling. The LP III distribution was used as marginal probability distribution function. Subsequently joint and conditional return periods of the T-year maximum annual flows and T-year maximum volumes with different time duration were calculated. The first one defines joint return periods as: the return periods using one random variable equaling or exceeding a certain magnitude and/or using another random variable equaling or exceeding another certain magnitude. The second one is conditional return periods for one random variable, given that another random variable equals or exceeds a specific magnitude.

scholarly journals Bivariate Assessment of Drought Return Periods and Frequency in Brazilian Northeast Using Joint Distribution by Copula Method

Geosciences ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 135 ◽  
Author(s):  
Rodrigo Lins da Rocha Júnior ◽  
Fabrício Daniel dos Santos Silva ◽  
Rafaela Lisboa Costa ◽  
Heliofábio Barros Gomes ◽  
David Duarte Cavalcante Pinto ◽  
...  
Keyword(s):  
Return Period ◽  
Probability Distributions ◽  
Standardized Precipitation Index ◽  
Bivariate Distribution ◽  
Drought Risk ◽  
Drought Event ◽  
Monthly Precipitation ◽  
Copula Functions ◽  
Spatially Distributed ◽  
The Standardized Precipitation Index

The Northeast region of Brazil (NRB) is the most populous semiarid area in the world and is extremely susceptible to droughts. The severity and duration of these droughts depend on several factors, and they do not necessarily follow the same behavior. The aim of this work is to evaluate the frequency of droughts in the NRB and calculate the return period of each drought event using the copula technique, which integrates the duration and severity of the drought in the NRB in a joint bivariate distribution. Monthly precipitation data from 96 meteorological stations spatially distributed in the NRB, ranging from 1961 to 2017, are used. The copula technique is applied to the Standardized Precipitation Index (SPI) on the three-month time scale, testing three families of Archimedean copula functions (Gumbel–Hougaard, Clayton and Frank) to reveal which model is best suited for the data. Averagely, the most frequent droughts observed in the NRB are concentrated in the northern sector of the region, with an observed duration varying from three and a half to five and a half months. However, the eastern NRB experiences the most severe droughts, lasting for 14 to 24 months. The probability distributions that perform better in modeling the series of severity and duration of droughts are exponential, normal and lognormal. The observed severity and duration values show that, for average values, the return period across the region is approximately 24 months. Still in this regard, the southernmost tip of the NRB stands out for having a return period of over 35 months. Regarding maximum observed values of severity and duration, the NRB eastern strip has the longest return period (>60 months), mainly in the southeastern portion where a return period above 90 months was observed. The northern NRB shows the shortest return period (~45 months), indicating that it is the NRB sector with the highest frequency of intense droughts. These results provide useful information for drought risk management in the NRB.

scholarly journals Bivariate Frequency of Meteorological Drought in the Upper Minjiang River Based on Copula Function

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2056
Author(s):  
Fangling Qin ◽  
Tianqi Ao ◽  
Ting Chen
Keyword(s):  
Marginal Distribution ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Copula Function ◽  
Distribution Functions ◽  
Joint Probability Distribution ◽  
Drought Risk ◽  
Monthly Precipitation ◽  
Copula Functions ◽  
Minjiang River

Based on the Standardized Precipitation Index (SPI) and copula function, this study analyzed the meteorological drought in the upper Minjiang River basin. The Tyson polygon method is used to divide the research area into four regions based on four meteorological stations. The monthly precipitation data of four meteorological stations from 1966 to 2016 were used for the calculation of SPI. The change trend of SPI1, SPI3 and SPI12 showed the historical dry-wet evolution phenomenon of short-term humidification and long-term aridification in the study area. The major drought events in each region are counted based on SPI3. The results show that the drought lasted the longest in Maoxian region, the occurrence of minor drought events was more frequent than the other regions. Nine distribution functions are used to fit the marginal distribution of drought duration (D), severity (S) and peak (P) estimated based on SPI3, the best marginal distribution is obtained by chi-square test. Five copula functions are used to create a bivariate joint probability distribution, the best copula function is selected through AIC, the univariate and bivariate return periods were calculated. The results of this paper will help the study area to assess the drought risk.

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