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.

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 Probabilistic hydrological drought index forecasting based on meteorological drought index using Archimedean copulas

2019 ◽  
Vol 50 (5) ◽  
pp. 1230-1250 ◽  
Author(s):  
Majid Dehghani ◽  
Bahram Saghafian ◽  
Mansoor Zargar
Keyword(s):  
Drought Index ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Hydrological Drought ◽  
Dependence Structure ◽  
Monthly Precipitation ◽  
Drought Condition ◽  
Copula Functions ◽  
Hydrological Droughts ◽  
Hydrological Drought Index

Abstract Hydrological drought forecasting is considered a key component in water resources risk management. As sustained meteorological drought may lead to hydrological drought over time, it is conceptually feasible to capitalize on the dependency between the meteorological and hydrological droughts while trying to forecast the latter. As such, copula functions are powerful tools to study the propagation of meteorological droughts into hydrological droughts. In this research, monthly precipitation and discharge time series were used to determine Standardized Precipitation Index (SPI) and Standardized Hydrological Drought Index (SHDI) at different time scales which quantify the state of meteorological and hydrological droughts, respectively. Five Archimedean copula functions were adopted to model the dependence structure between meteorological/hydrological drought indices. The Clayton copula was identified for further investigation based on the p-value. Next, the conditional probability and the matrix of forecasted class transitions were calculated. Results indicated that the next month's SHDI class forecasting is promising with less than 10% error. Moreover, extreme and severe meteorological drought classes lead to hydrological drought condition with a more than 70% probability. Other classes of meteorological drought/wet conditions lead to normal hydrological (drought) condition with less than 50% probability and to wet hydrological condition with over 20% probability.

scholarly journals Meteorological Drought Assessment in Sharjah, UAE Using Drought Indices

2022 ◽  
Vol 13 (1) ◽  
pp. 16-20
Author(s):  
Mhamd S. Oyounalsoud ◽  
◽  
Arwa Najah ◽  
Abdullah G. Yilmaz ◽  
Mohamed Abdallah ◽  
...  
Keyword(s):  
United Arab Emirates ◽  
Crop Production ◽  
Standardized Precipitation Index ◽  
Extended Period ◽  
Meteorological Drought ◽  
Distribution Functions ◽  
Drought Indices ◽  
Monthly Precipitation ◽  
Drought Assessment ◽  
The Standardized Precipitation Index

Drought is a natural disaster that significantly affects environmental and socio-economic conditions. It occurs when there is a period of below average precipitation in a region, and it results in water supply shortages affecting various sectors and life adversely. Droughts impact the ecosystems, crop production, and erode livelihoods. Monitoring drought is essential especially in the United Arab Emirates (UAE) due to the scarcity of rainfall for an extended period of time. In this study, drought is assessed in Sharjah UAE using monthly precipitation and average temperature data recorded for 35 years (1981-2015) at the Sharjah International Airport. The standardized precipitation Index (SPI), and the Reconnaissance Drought Index (RDI) are selected to predict future droughts in the region. SPI and RDI are fitted to the statistical distribution functions (gamma and lognormal) in an annual time scale and then, a trend analysis of index values is carried out using Mann-Kendal test. The correlation between SPI and RDI indices was found to be high where both showed high drought frequencies and a tendency to get drier over time, thus indicating the need of appropriate drought management and monitoring.

scholarly journals Risk assessment of meteorological drought in China under RCP scenarios from 2016 to 2050

2016 ◽  
Author(s):  
Kuo Li ◽  
Jie Pan
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Water Resources ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Mitigation Strategies ◽  
Sensitivity Index ◽  
Drought Risk ◽  
Emission Scenarios ◽  
The Impact

Abstract. Climate change has been a hotspot of scientific research in the world for decades, which caused serious effects of agriculture, water resources, ecosystem, environment, human health and so on. In China, drought accounts for almost 50 % of the total loss among all the meteorological disasters. In this article the interpolated and corrected precipitation of one GCM (HadGEM2-ES) output under four emission scenarios (RCP2.6, 4.5, 6.0, 8.5) were used to analyze the drought. The standardized precipitation index (SPI) calculated with these data was used to assess the climate change impact on droughts from meteorological perspectives. Based on five levels of SPI, an integrated index of drought hazard (IIDH) was established, which could explain the frequency and intensity of meteorological drought in different regions. According to yearbooks of different provinces, 15 factors have been chosen which could represent the impact of drought on human being, crops, water resources and economy. Exposure index, sensitivity index and adaptation index have been calculated in almost 2400 counties and vulnerability of drought has been evaluated. Based on hazard and vulnerability evaluation of drought, risk assessment of drought in China under the RCP2.6, 4.5, 6.0, 8.5 emission scenarios from 2016 to 2050 has been done. Results from such a comprehensive study over the whole country could be used not only to inform on potential impacts for specific sectors but also can be used to coordinate adaptation/mitigation strategies among different sectors/regions by the central government.

Multifractal Properties of Meteorological Drought at Different Time Scales in a Tropical Location

2020 ◽  
pp. 2150007
Author(s):  
Samuel Toluwalope Ogunjo
Keyword(s):  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Temporal Scale ◽  
Fluctuation Analysis ◽  
Monthly Precipitation ◽  
Scaling Exponent ◽  
Economic Activities ◽  
Temporal Scales ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Long Range Correlations

Tropical countries, like Nigeria, depend on rainfall for agriculture, power generation, transportation and other economic activities. Drought will hinder the performance of these activities, hence, it poses a significant threat to the economy. Understanding fluctuations and structures in droughts will help in forecasting, planning and mitigating its impact on livelihoods. In this study, the multifractal properties of drought at four temporal scales were investigated over different locations across Nigeria. Drought was computed using the standardized precipitation index from monthly precipitation data from 1980 to 2010. Using multifractal detrended fluctuation analysis, meteorological drought was found to have multifractal properties at 1-, 6-, 12- and 24-month temporal scale. The generalized Hurst exponent of drought at different time-scale showed dependence on scaling exponent. Long-range correlations were found to be main source of multifractality at all temporal scales. The multifractal strength increases with increasing temporal scale except for a few locations. The range of spectrum width were found to be 0.306–0.464 and 0.596–0.993 at 1- and 24-month temporal scale, respectively. No significant trend was found in the degree of multifractality across different climatic zones of Nigeria.

scholarly journals Finescale Evaluation of Drought in a Tropical Setting: Case Study in Sri Lanka

2009 ◽  
Vol 48 (1) ◽  
pp. 77-88 ◽  
Author(s):  
Bradfield Lyon ◽  
Lareef Zubair ◽  
Vidhura Ralapanawe ◽  
Zeenas Yahiya
Keyword(s):  
Sri Lanka ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Drought Indices ◽  
Drought Risk ◽  
Mitigation And Adaptation ◽  
Wide Range ◽  
Drought Relief ◽  
Drought Indicators ◽  
The Standardized Precipitation Index

Abstract In regions of climatic heterogeneity, finescale assessment of drought risk is needed for policy making and drought management, mitigation, and adaptation. The relationship between drought relief payments (a proxy for drought risk) and meteorological drought indicators is examined through a retrospective analysis for Sri Lanka (1960–2000) based on records of district-level drought relief payments and a dense network of 284 rainfall stations. The standardized precipitation index and a percent-of-annual-average index for rainfall accumulated over 3, 6, 9, and 12 months were used, gridded to a spatial resolution of 10 km. An encouraging correspondence was identified between the spatial distribution of meteorological drought occurrence and historical drought relief payments at the district scale. Time series of drought indices averaged roughly over the four main climatic zones of Sri Lanka showed statistically significant (p < 0.01) relationships with the occurrence of drought relief. The 9-month cumulative drought index provided the strongest relationships overall, although 6- and 12-month indicators provided generally similar results. Some cases of appreciable drought without corresponding relief payments could be attributed to fiscal pressures, as during the 1970s. Statistically significant relationships between drought indicators and relief payments point to the potential utility of meteorological drought assessments for disaster risk management. In addition, the study provides an empirical approach to testing which meteorological drought indicators bear a statistically significant relationship to drought relief across a wide range of tropical climates.

scholarly journals Modelling High Dimensional Paddy Production Data using Copulas

2021 ◽  
Vol 29 (1) ◽  
Author(s):  
Nuranisyha Mohd Roslan ◽  
Wendy Ling Shinyie ◽  
Sim Siew Ling
Keyword(s):  
Time Series ◽  
Marginal Distribution ◽  
Reference Group ◽  
Estimation Method ◽  
Information Criterion ◽  
Copula Function ◽  
Archimedean Copula ◽  
Copula Functions ◽  
Estimation Errors ◽  
Elliptical Copula

As the climate change is likely to be adversely affecting the yield of paddy production, thence it has brought a limelight of the probable challenges on human particularly regional food security issues. This paper aims to fit multivariate time series of paddy production variables using copula functions and predicts the next year event based on the data of five countries in southeast Asia. In particular, the most appropriate marginal distribution for each univariate time series was first identified using maximum likelihood parameter estimation method. Next, we performed multivariate copula fitting using two types of copula families, namely, elliptical copula family and Archimedean copula family. Elliptical copula family studied are normal and t copula, while Archimedean copula family considered are Joe, Clayton and Gumbel copulas. The performance of marginal distribution and copula fitting was examined using Akaike information criterion (AIC) values. Finally, we used the best fitted copula model to forecast the succeeding event. In order to assess the performance of copula function, we computed the forecast means and estimation errors of copula function with a generalized autoregressive conditional heteroskedasticity model as reference group. Based on the smallest AIC, the majority of the data favoured the Gumbel copula, which belongs to Archimedean copula family as well as extreme value copula family. Likewise, applying the historical data to forecast the future trends may assist all relevant stakeholders, for instance government, NGO agencies, and professional practitioners in making informed decisions without compromising the environmental as well as economical sustainability in the region.

scholarly journals Global and regional performances of SPI candidate distribution functions in observations and simulations

2020 ◽  
Author(s):  
Patrick Pieper ◽  
André Düsterhus ◽  
Johanna Baehr
Keyword(s):  
Time Series ◽  
Distribution Function ◽  
Weibull Distribution ◽  
Standardized Precipitation Index ◽  
Distribution Functions ◽  
Monthly Precipitation ◽  
Precipitation Data ◽  
Data Set ◽  
Exponentiated Weibull Distribution ◽  
Exponentiated Weibull

Abstract. The Standardized Precipitation Index (SPI) is a widely accepted drought index. Its calculation algorithm normalizes the index via a distribution function. Which distribution function to use is still disputed within literature. This study illuminates the long-standing dispute and proposes a solution which ensures the normality of the index for all common accumulation periods in observations and simulations. We compare the normality of SPI time-series derived with the gamma, Weibull, generalized gamma, and the exponentiated Weibull distribution. Our normality comparison evaluates actual against theoretical occurrence probabilities of SPI categories, and the quality of the fit of candidate distribution functions against their complexity with Akaike's Information Criterion. SPI time-series, spanning 1983–2013, are calculated from Global Precipitation Climatology Project's monthly precipitation data-set and seasonal precipitation hindcasts from the Max Planck Institute Earth System Model. We evaluate these SPI time-series over the global land area and for each continent individually during winter and summer. While focusing on an accumulation period of 3-months, we additionally test the drawn conclusions for other common accumulation periods (1-, 6-, 9-, and 12-months). Our results suggest to exercise caution when using the gamma distribution to calculate SPI; especially in simulations or their evaluation. Further, our analysis shows a distinctly improved normality for SPI time-series derived with the exponentiated Weibull distribution relative to other distributions. The use of the exponentiated Weibull distribution maximizes the normality of SPI time-series in observations and simulations both individual as well as concurrent. Its use further maximizes the normality of SPI time-series over each continent and for every investigated accumulation period. We, therefore, advocate to derive SPI with the exponentiated Weibull distribution, irrespective of the heritage of the precipitation data or the length of analyzed accumulation periods.

scholarly journals Meteorological Drought Monitoring in Northeastern China Using Multiple Indices

Water ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 72 ◽  
Author(s):  
Fengping Li ◽  
Hongyan Li ◽  
Wenxi Lu ◽  
Guangxin Zhang ◽  
Joo-Cheol Kim
Keyword(s):  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Monthly Precipitation ◽  
Precipitation Data ◽  
Z Score ◽  
Predictive Values ◽  
Daily Precipitation Data ◽  
Precipitation Changes

Drought monitoring is one of the significant issues of water resources assessment. Multiple drought indices (DIs), including Percent of Normal (PN), Standardized Precipitation Index (SPI), statistical Z-Score, and Effective Drought Index (EDI) at 18 different timesteps were employed to evaluate the drought condition in Wuyuer River Basin (WRB), Northeast China. Daily precipitation data of 50 years (1960–2010) from three meteorological stations were used in this study. We found DIs with intermediate time steps (7 to 18 months) to have the highest predictive values for identifying droughts. And DIs exhibited a better similarity in the 12-month timestep. Among all the DIs, EDI exhibited the best correlation with other DIs for various timesteps. When further comparing with historical droughts, Z-Score, SPI, and EDI were found more sensitive to multi-monthly cumulative precipitation changes (r2 > 0.55) with respect to monthly precipitation changes (r2 ≤ 0.10), while EDI was more preferable when only monthly precipitation data were available. These results indicated that various indices for different timesteps should be investigated in drought monitoring in WRB, especially the intermediate timesteps should be considered.

Drought indices supporting drought management in transboundary watersheds subject to climate alterations

Water Policy ◽  
2014 ◽  
Vol 17 (5) ◽  
pp. 865-886 ◽  
Author(s):  
Furat A. M. Al-Faraj ◽  
Miklas Scholz ◽  
Dimitris Tigkas ◽  
Martino Boni
Keyword(s):  
Climate Change ◽  
Management Practices ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Drought Indices ◽  
Management Approach ◽  
Drought Risk ◽  
Drought Management ◽  
Anthropogenic Pressures ◽  
Transboundary River Basin

There is growing concern in Iraq about the inefficiency of reactive drought management practices. Corresponding actions are largely characterized as emergency-based responses that treat the symptoms of drought rather than consider the vulnerability components associated with impacts. The Diyala watershed shared between Iraq and Iran has been used as an example transboundary river basin marked by ineffectiveness of drought management. The standardized precipitation index and the reconnaissance drought index were used to determine the historical meteorological drought episodes and analysis indicated climate change-induced alterations in the area. Spatiotemporal drought maps were drawn, which can be used for the identification of drought prone areas and assist with proactive planning. This paper discusses the underlying causes of the impairments of drought management policies, and the challenges and difficulties accompanying the governance of drought in Iraq. Given the influence of climate change and the upstream anthropogenic pressures, the time has come to adopt a gradual nation-wide transition step to drought risk planning incorporating a management approach at the transboundary scale. Moreover, the institutional and technical water vulnerability components associated with drought management should be considered in an integrated manner. The paper presents a generic technical template to support decision-makers in drought risk management.

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