Coincidence probability analysis of hydrologic low-flow under the changing environment in the Wei River Basin

Yang, Jie; Wang, Yimin; Yao, Jun; Chang, Jianxia; Xu, Guo-Xin; Wang, Xin; Hu, Hui

doi:10.1007/s11069-020-04051-3

Cited by 4 publications

(2 citation statements)

References 31 publications

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“…This method can describe the dependency structure between variables with different marginals and model their tail dependencies (Caraka et al, 2016). Copula has been widely used to address uncertainties in coincidence probability (Yang et al, 2020), conditional probability (H. W. Li et al, 2021), and joint return period analysis (Naeini et al, 2021). However, according to a systematic literature review, the copula is still limited to being applied in forest fire analysis (Najib et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Joint Distribution and Coincidence Probability of the Number of Dry Days and the Total Amount of Precipitation in Southern Sumatra Fire-Prone Area

NURDIATI¹,

NAJIB²,

THALIB³

2022

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El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) can affect the increase in rainfall intensity and the number of dry days, also known as dry spells that can cause drought and increase the potential for forest fires. This study examines the effect of ENSO and IOD conditions on the joint distribution of the number of dry days and total precipitation in a fire-prone area in southern Sumatra, Indonesia. The joint distribution is constructed using rotated copulas from several families, including Gaussian, student's t, Clayton, Gumbel, Frank, Joe, Galambos, BB1, BB6, BB7, and BB8. Fire-prone areas are defined using k-mean clustering, while the copula parameters are estimated using the inference of function for margins (IFM) method. Based on the peak of joint probability density functions (PDFs), ENSO and IOD conditions had a significant effect in the dry season but had no significant effect in the rainy season. The peak of joint PDFs is getting to the dry-dry conditions when the ENSO and IOD indexes increase in the dry season. However, based on coincidence probability, ENSO conditions still influence the joint distribution between the number of dry days and total precipitation during the rainy season but not with IOD conditions. The lower the ENSO index, the higher the probability of wet conditions co-occurring in the number of dry days and total precipitation. Meanwhile, ENSO and IOD conditions significantly affect the coincidence probability between the number of dry days and total precipitation. Moderate-Strong El Niño has the most considerable coincidence probability of 68.5%, followed by Positive IOD with 62.6%. The two conditions had similar effects on the joint distribution of the number of dry days and total precipitation. Moreover, the association between the number of dry days and the total precipitation was stronger in the dry season than in the rainy season.

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Section: Introductionmentioning

confidence: 99%

Joint Distribution and Coincidence Probability of the Number of Dry Days and the Total Amount of Precipitation in Southern Sumatra Fire-Prone Area

NURDIATI¹,

NAJIB²,

THALIB³

2022

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“…They can result in significant financial losses, the destruction of infrastructure, and the loss of human life, and as such are serious natural hazards (Brocca et al 2011;Li et al 2012;Stein et al 2020). In the context of global climate change, extreme meteorological and hydrological events are becoming more frequent, and the risk of basin-wide flooding is increasing (Wang et al 2019;Su 2020;Try et al 2020;Yang et al 2020). Therefore, more attention to basin-wide flooding mitigation is needed.…”

Section: Introductionmentioning

confidence: 99%

Flood hydrograph coincidence analysis of the upper Yangtze River and Dongting Lake, China

Chao

Wang

et al. 2021

Nat Hazards

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In hydrological research, flood events can be analyzed by flood hydrograph coincidence. Existing flood hydrograph coincidence research mostly focuses on the analysis of the coincidence risk probability of the annual maximum flood event using the 15-day maximum annual flood volume; the actual duration of the flood hydrograph is neglected. The duration of the flood hydrograph is a key variable in (1) determining whether flood hydrograph coincidence occurs, and (2) accurately calculating the flood hydrograph coincidence risk probability. This paper creatively proposes a novel method to analyze the flood hydrograph coincidence risk probability by establishing a five-dimensional joint distribution of flood volumes, durations and interval time for two hydrologic stations. More specifically, using the annual maximum flood of the upper Yangtze River and input from Dongting Lake as an example, the Pearson Type III and the mixed von Mises distributions were used to establish the marginal distribution of flood volumes, flood duration and interval time. Subsequently, the five-dimensional joint distribution based on vine copula was established to analyze the flood hydrograph coincidence risk probability. The results were verified by comparison with a historical flood sequence. The flood hydrograph coincidence volume-risk probability curve was also obtained, providing theoretical support for flood control safety and risk management in the middle and lower Yangtze River. This study also demonstrates the significant beneficial role of regulation by the Three Gorges Water Conservancy Project in mitigating flood risk of the Yangtze River.

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Development of Low Flow Duration-Frequency Curves by Hybrid Frequency Analysis

Orta

Aksoy

2022

Water Resour Manage

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Coincidence probability analysis of hydrologic low-flow under the changing environment in the Wei River Basin

Cited by 4 publications

References 31 publications

Joint Distribution and Coincidence Probability of the Number of Dry Days and the Total Amount of Precipitation in Southern Sumatra Fire-Prone Area

Joint Distribution and Coincidence Probability of the Number of Dry Days and the Total Amount of Precipitation in Southern Sumatra Fire-Prone Area

Flood hydrograph coincidence analysis of the upper Yangtze River and Dongting Lake, China

Development of Low Flow Duration-Frequency Curves by Hybrid Frequency Analysis

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