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http://dx.doi.org/10.3741/JKWRA.2016.49.7.607

Probabilistic prediction of reservoir storage considering the uncertainty of dam inflow  

Kwon, Minsung (Graduate School of Water Resources, Sungkyunkwan Univ.)
Park, Dong-Hyeok (Dept. of Civil and Environmental Engineering, Hanyang Univ.)
Jun, Kyung Soo (Graduate School of Water Resources, Sungkyunkwan Univ.)
Kim, Tae-Woong (Dept. of Civil and Environmental Engineering, Hanyang Univ.)
Publication Information
Journal of Korea Water Resources Association / v.49, no.7, 2016 , pp. 607-614 More about this Journal
Abstract
The well-timed water management is required to reduce drought damages. It is also necessary to induce residents in drought-affected areas to save water. Information on future storage is important in managing water resources based on the current and future states of drought. This study employed a kernel function to develop a probabilistic model for predicting dam storage considering inflow uncertainty. This study also investigated the application of the proposed probabilistic model during the extreme drought. This model can predict a probability of temporal variation of storage. Moreover, the model can be used to make a long-term plan since it can identify a temporal change of storage and estimate a required reserving volume of water to achieve the target storage.
Keywords
Drought; Probabilistic Prediction; Uncertainty; Water Management;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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