Multivariate Assessment of Low-Flow Hazards via Copulas: The Case Study of the Çoruh Basin (Turkey)

Tosunoğlu, Fatih; Salvadori, Gianfausto; Yılmaz, Muhammet

doi:10.3390/w12102848

Cited by 3 publications

(2 citation statements)

References 39 publications

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“…where 𝐸(𝐷𝐼𝑇) is the expected value of DIT and 𝑇 𝑈>𝑢 is the return period of drought, which is determined by 𝑢. E(DIT) was calculated as the ratio of the total duration to the total number of droughts. It is also possible to extend the return period to the bivariate case by characterizing events with a coincidence or conditional probability [27], [28], i.e…”

Section: Joint Return Periodmentioning

confidence: 99%

Copula in Wildfire Analysis: A Systematic Literature Review

Najib¹,

Nurdiati²,

Sopaheluwakan

2021

InPrime:Ind.Jour.Pure.Applied.Math

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Copula model is a method that can be implemented in various study fields, including analyzing wildfires. The copula distribution function gives a simple way to define joint distribution between two or more random variables. This study aims to review the application of copula in the analysis of wildfires using a Systematic Literature Review (SLR) and provide insight into research opportunities related to the application in Indonesia. The results show there are very few articles using the copula model in the analysis of wildfires. However, the increasing number of article citations each year shows the importance of such article research and has contributed to wildfire analysis development. In that article, 50% of studies applied the copula model to direct wildfire analysis (using fire data) in Canada, Portugal, and the US. Meanwhile, the other 50% use the copula model for indirect wildfire analysis (not using fire data) in Canada and the European region. The outcome of the presented review will provide the latest research positions and future research opportunities on the application of copula in the analysis of wildfires in Indonesia.Keywords: copula; wildfire; systematic literature review. AbstrakModel copula merupakan metode yang dapat diimplementasikan pada berbagai bidang penelitian, salah satunya pada analisis kebakaran hutan. Fungsi sebaran copula memberikan cara yang mudah untuk mendefinisikan sebaran peluang bersama antara dua peubah acak atau lebih. Tujuan penelitian ini mengulas penerapan model copula tersebut pada analisis kebakaran hutan dalam studi literatur menggunakan Systematic Literature Review (SLR) serta memberikan peluang riset ke depan terkait implementasinya pada analisis kebakaran hutan di Indonesia. Hasil penelitian menunjukkan bahwa model copula pada analisis kebakaran hutan masih sangat sedikit. Namun, peningkatan jumlah sitasi artikel tiap tahun menunjukkan pentingnya penelitian tersebut dan memiliki kontribusi pada perkembangan analisis kebakaran hutan. Pada artikel tersebut, sebanyak 50% penelitian menerapkan model copula pada analisis kebakaran secara langsung (menggunakan data kebakaran) di Kanada, Portugal, dan Amerika. Sementara, sebanyak 50% lainnya menerapkan model copula pada analisis kebakaran secara tak langsung (tidak menggunakan data kebakaran), yaitu di Kanada dan kawasan Eropa. Hasil tinjauan memberikan posisi riset terkini serta usulan riset ke depan mengenai penerapan model copula untuk analisis kebakaran hutan dan lahan di Indonesia.Kata kunci: copula; kebakaran hutan; studi literatur sistematik.

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Section: Joint Return Periodmentioning

confidence: 99%

Copula in Wildfire Analysis: A Systematic Literature Review

Najib¹,

Nurdiati²,

Sopaheluwakan

2021

InPrime:Ind.Jour.Pure.Applied.Math

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“…Assessment of low-flow is an important aspect for water quality management, reservoir storage design, determining minimum release policy and safe surface water withdrawals (Tosunoglu et al, 2020). Numbers of indices viz., mean annual runoff, mean daily flow, median flow, Annual Minimum d-day Average Flow (AMdAF), absolute minimum flow are widely used to characterize the low-flow.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Generalized Extreme Value, Log Normal and Weibull Distributions for Assessment of Low-Flow

Vivekanandan¹

2021

JCEU

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Assessment of low-flow is an important aspect for water quality management, reservoir storage design, determining minimum release policy and safe surface water withdrawals. For which, the annual minimum d-day average flow is generally adopted procedure for characterizing the low-flow in a stream, which can be obtained by averaging the flow using moving average method for ‘d’ consecutive days viz., 7-, 10-, 14- and 30- days. This paper presents a study on comparison of three probability distributions such as Generalized Extreme Value, 2-parameter Log Normal (LN2) and Weibull adopted in estimation of low-flow for river Cauvery at Kollegal gauging site. The parameters are determined by three methods viz., method of moments, maximum likelihood method and L-Moments (LMO), and are used for estimation of low-flow. The adequacy of fitting probability distributions adopted in low-flow frequency analysis is evaluated by quantitative assessment through Goodness-of-Fit (viz., Chi-Square and Kolmogorov-Smirnov) and diagnostic (viz., correlation coefficient and root mean squared error) tests, and qualitative assessment using the fitted curves of the estimated low-flow. The results of quantitative and qualitative assessments indicate that LN2 (LMO) is better suited amongst three distributions adopted in estimation of 7-, 10-, 14- and 30- day low-flows for river Cauvery at Kollegal site.

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Copula-based bivariate drought severity and duration frequency analysis considering spatial–temporal variability in the Ceyhan Basin, Turkey

Eşit

Yüce

2022

Theor Appl Climatol

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In recent times, copula families have been mostly employed in bivariate drought duration and severity.Archimedean copulas are mainly used conveniently among various potential families for hydrologic design and water resource management. In this study, drought events are de ned by standard precipitation index (SPI 1-, 3-and 6-time series) series for 24-gauge stations in Ceyhan Basin Turkey, when the value fell below zero. Both duration and severity are tested their dependence with Mann-Kendall and Spearman Rho trend test at 0.05 signi cant level. The different marginal distribution function is tted to duration and severity data. Weibull and Lognormal distribution for drought duration, Weibull and Gamma distribution for drought severity are found more appropriate, respectively. The best t copula is found to construct a joint distribution function. However, disregarding tail dependencies can cause high uncertainty in extreme quantile predictions, resulting in incorrect hydrological design ndings. Hence, the in uence of upper tail dependencies is tested to select the most appropriate copula function. After acquiring the best t copula, the joint return periods are modeled for each station. Finally, considering drought risk categories (light, moderate, severe and extreme drought), spatial distributions of drought riskreturn period are constructed. Apart from using univariate frequency analysis, bivariate frequency analysis is performed to model the joint return period based on copula theory that is great of importance for hydrology design and water resource management.

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Multivariate Assessment of Low-Flow Hazards via Copulas: The Case Study of the Çoruh Basin (Turkey)

Cited by 3 publications

References 39 publications

Copula in Wildfire Analysis: A Systematic Literature Review

Copula in Wildfire Analysis: A Systematic Literature Review

Comparison of Generalized Extreme Value, Log Normal and Weibull Distributions for Assessment of Low-Flow

Copula-based bivariate drought severity and duration frequency analysis considering spatial–temporal variability in the Ceyhan Basin, Turkey

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