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  1. National Taiwan Ocean University Research Hub

An Integrated Study on the Multiobjective and Sustainable Management of Shihmen Reservoir

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Project title
An Integrated Study on the Multiobjective and Sustainable Management of Shihmen Reservoir
Code/計畫編號
MOST104-2119-M009-002
Translated Name/計畫中文名
石門水庫多目標與永續營運整合研究-石門水庫多目標與永續營運整合研究
 
Funding Organization/主管機關
National Science and Technology Center for Disaster Reduction
 
Co-Investigator(s)/共同執行人
張良正(計畫主持人)
游保杉
 
Department/Unit
Department of Civil Engineering,NYCU
Website
https://www.grb.gov.tw/search/planDetail?id=11271397
Year
2015
 
Start date/計畫起
01-01-2015
Expected Completion/計畫迄
31-12-2015
 
Co-Investigator(s)
Kwan-Tun Lee
Bugetid/研究經費
3342千元
 
ResearchField/研究領域
土木水利工程
 

Description

Abstract
臺灣因地理位置特殊,雖年雨量充沛,但是旱澇現象分明,水庫在水資源調配上扮演重要角色。然而頻繁颱風暴雨造成集水區崩塌,使水庫嚴重淤積,大幅降低庫容與減少壽命,水庫如何有效排淤以維持永續經營乃是重要課題。其中石門水庫為北部地區最重要且供水負擔最重的水庫,故本研究以其為標的,兼顧防洪、排淤與供水等多目標操作,在水源供應與水庫永續經營同時考量下,求其最佳的聯合操作規則。 本研究涵蓋多個領域,子計畫一結合遺傳演算法與不同機器學習法進行雨量預報模式發展,以提供子計畫二和子計畫三模擬分析所需;子計畫二利用集水區之土壤特性資料與土壤沖蝕物理機制,建立分佈式土壤沖蝕模式。並配合邊坡穩定分析及土壤深度推估,建立崩塌土砂生成模式。最後,結合土壤沖蝕模式與崩塌土砂生成模式之成果,建立庫區泥砂動態模擬模式,以提供子計畫三中水庫防洪減淤操作時所需資訊。子計畫三同時考量事件型的防洪操作及非事件型的水資源調配,基於滿足安全、排渾及水資源供應等條件下,建立防洪排淤最佳操作規則。 本年度已完成1至6小時雨量預報模式、石門水庫集水區土壤沖蝕模式、崩塌土砂生成模式、庫區泥砂動態模擬模式及常態水資源調配模式之建立與分析,後續將持續透過三個子計畫的整合,探討石門水庫集水區之土砂產生與運移情況,對於石門水庫永續利用之衝擊,以及如何透過調配操作,達到防洪減淤之效用,除研發新技術外,亦兼顧實務應用。 Due to special geographical location of Taiwan, abundant annual precipitation is unevenly distributed in time making frequent drought and flood events. Hence, reservoirs are necessary and important hydraulic measures in Taiwan. However, high frequency storm events cause serious landslides in reservoir watersheds resulting sedimentation problems, and reduced storage space and life of the reservoirs. Therefore, sediment desilting for sustainable reservoir operation is a critical issue. The Shihmen Reservoir has the highest water supply loading in north Taiwan, and is the studied reservoir in this research. Under the consideration of fulfill water demand and sustainable reservoir management, a multi-objectives problem consists of flood control、sediment desilting and water supply is formulated. Optimal joint operations are then computed. This study covers multiple academic research areas including rainfall forecast and runoff simulation, sediment yield and transport in watershed and reservoir, and reservoir operation for flood mitigation and water supply. Project I combines Genetic Algorism and other machine learning skills to deal with precipitation prediction. Project II studies on the estimation of sediment yield and transport in the watershed and reservoir. Focusing on estimating the volume of sediment yield and simulating its physical movement during a storm event; Project III mainly focuses on multi-objective operation of the reservoir. The operation simultaneously considers the event-type flood mitigation and desilting operation and non-event type water supply management. The joint operation is optimized among the different objectives. 1 to 6 hours Precipitation Prediction Model, Soil Erosion model, Landslide model, Reservoir Sediment Transport model, and Water allocation model have been developed in this years. The optimal flood control and sediment sluicing operation and model combination will be discuss in next two years. The study contains both novel technology development and practical application. After technology transfer, the result of this study can be directly applied to real-world management for sustainable reservoir operation.
 
Keyword(s)
多目標水庫
防洪操作
泥沙傳輸
水庫排淤
水庫永續營運
Multi-objective reservoir
flood mitigation
flood control
sediment transport
reservoir desilting
sustainable reservoir management
 
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