Probabilistic Event Based Rainfall-Runoff Modeling Using Copula Functions

Abdollahi, Sajjad; Akhoond‐Ali, Ali Mohammad; Mirabbasi, Rasoul; Adamowski, Jan

doi:10.1007/s11269-019-02339-z

Cited by 30 publications

(11 citation statements)

References 26 publications

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“…The introduction of the copula function caused a technological innovation in the field of hydrology, which could solve the multivariate frequency problem [32][33][34].…”

Section: Joint Distribution Model Of Adjacent Monthly Incoming Runoffmentioning

confidence: 99%

Study on the Optimal Operation of a Hydropower Plant Group Based on the Stochastic Dynamic Programming with Consideration for Runoff Uncertainty

Zhang

Chang

et al. 2022

Water

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Hydropower plant operation reorganizes the temporal and spatial distribution of water resources to promote the comprehensive utilization of water resources in the basin. However, a lot of uncertainties were brought to light concerning cascade hydropower plant operation with the introduction of the stochastic process of incoming runoff. Therefore, it is of guiding significance for the practice operation to investigate the stochastic operation of cascade hydropower plants while considering runoff uncertainty. The runoff simulation model was constructed by taking the cascade hydropower plants in the lower reaches of the Lancang River as the research object, and combining their data with the copula joint function and Gibbs method, and a Markov chain was adopted to construct the transfer matrix of runoff between adjacent months. With consideration for the uncertainty of inflow runoff, the stochastic optimal operation model of cascade hydropower plants was constructed and solved by the SDP algorithm. The results showed that 71.12% of the simulated monthly inflow of 5000 groups in the Nuozhadu hydropower plant drop into the reasonable range. Due to the insufficiency of measured runoff, there were too many 0 values in the derived transfer probability, but after the simulated runoff series were introduced, the results significantly improved. Taking the transfer probability matrix of simulated runoff as the input of the stochastic optimal operation model of the cascade hydropower plants, the operation diagram containing the future-period incoming water information was obtained, which could directly provide a reference for the optimal operation of the Nuozhadu hydropower plant. In addition, taking the incoming runoff process in a normal year as the standard, the annual mean power generation based on stochastic dynamic programming was similar to that based on dynamic programming (respectively 305.97 × 108kW⋅h and 306.91 × 108kW⋅h), which proved that the operation diagram constructed in this study was reasonable.

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“…The introduction of the copula function caused a technological innovation in the field of hydrology, which could solve the multivariate frequency problem [32][33][34].…”

Section: Joint Distribution Model Of Adjacent Monthly Incoming Runoffmentioning

confidence: 99%

Study on the Optimal Operation of a Hydropower Plant Group Based on the Stochastic Dynamic Programming with Consideration for Runoff Uncertainty

Zhang

Chang

et al. 2022

Water

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“…Correlation between interevent time and rainfall depth and between interevent time and rainfall duration is weak and can be neglected, while correlation between rainfall depth and duration is significant. Despite in last decades, copula functions were introduced in the hydrologic research for broadening the multivariate inference capability and overcome the correlation among rainfall variables (Abdollahi et al, 2019), in this paper they were neglected to simplify the derivation of final expressions. The overflow threshold 𝑣̅ in equations ( 8) and ( 9) was assumed equal to zero, as well as the minimum water content 𝑤 ̅ in equations ( 10) and ( 11).…”

Section: Applicationmentioning

confidence: 99%

Probabilistic Modelling of Sustainable Urban Drainage Systems

Raimondi

Chiano

Marchioni

et al. 2022

Preprint

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Sustainable Urban Drainage Systems (SuDS) gatherer effective strategies and control systems for stormwater management especially in highly urbanized areas characterized by large impervious surfaces that increase runoff peak flow and volume. The main goal is to restore the natural water balance by increasing infiltration, evapotranspiration and promoting rainwater reuse. This paper proposes an analytical probabilistic approach for the modelling SuDS applicable to different structures and goals. Developed equations allow to estimate the probability of overflow and the probability of pre-filling at the end of dry periods, to evaluate the efficiency of the storage in rainwater management and its ability to empty between consecutive events. A great advantage of the proposed method is that it allows to consider a chain of rainfall events; this aspect is particularly important for control systems SuDS characterized by low outflow rates which storage capacity is often not completely available at the end of a dry period because pre-filled by previous events. Suggested formulas were tested to two cases studies in Milan and Genoa, Italy.

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“…Interevent time results only weakly correlated to the other two variables, while the correlation between rainfall depth and duration is not negligible. However, to overcome the correlation with rainfall variables, copula functions have been recently introduced in the hydrologic research in order to broaden the multivariate inference capability (Abdollahi et al 2019); for simplicity they have not been considered in this work. The runoff probability has been estimated by varying the maximum retention capacity w max ; it has been calculated summing up the maximum retention capacity of the three layers composing the green roof (vegetation layer, growing medium and drainage layer): w max = w v,max + w g,max + w d,max .…”

Section: Applicationmentioning

confidence: 99%

Performance of Green Roofs for Rainwater Control

Raimondi

2020

Water Resour Manage

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Green roofs can be an effective tool for sustainable urban drainage, since they reduce and retain runoff by delaying its peak. Most studies analysing the retention capacity of green roofs are usually referred to a specific place and roof condition and do not consider the possibility that the roof could be partially pre-filled from previous rainfalls at the beginning of the given event. The aim of this paper is to develop an analytical probabilistic approach to evaluate green roof performance for stormwater control in terms of runoff that could be applied for different sites and climate conditions. To this end, the possibility that the green roof retention capacity could not be completely available owing to pre-filling from previous rainfall events has been considered and equations for an optimum green roof design, relating the runoff average return interval to the water retention capacity, have been proposed. The influence of parameters affecting the runoff process has been examined in depth and a case study to test the goodness of fit of the resulting equations has been developed.

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Probabilistic Event Based Rainfall-Runoff Modeling Using Copula Functions

Cited by 30 publications

References 26 publications

Study on the Optimal Operation of a Hydropower Plant Group Based on the Stochastic Dynamic Programming with Consideration for Runoff Uncertainty

Study on the Optimal Operation of a Hydropower Plant Group Based on the Stochastic Dynamic Programming with Consideration for Runoff Uncertainty

Probabilistic Modelling of Sustainable Urban Drainage Systems

Performance of Green Roofs for Rainwater Control

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