Real-time prediction of the peak suspended sediment concentration and sediment yield of the Lao-Nung River during storms

• Published in: International journal of sediment research Vol. 26; no. 2; pp. 163 - 180
• Main Authors: HSU, Pi-Chih, CHEN, Ching-Nuo, TASI, Chang-Tai
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.06.2011; Lecturer, Department of Constructing Engineering, Nan Jeon Institute of Technology, and Ph.D. Candidate,Department of Hydraulic and Ocean Engineering, National Cheng-Kung University, Tainan 701, Taiwan, China.%Postdoctoral Researcher, Department of Hydraulic and Ocean Engineering, National Cheng-Kung University,Tainan 701, Taiwan, China.%Department of Hydraulic and Ocean Engineering, National Cheng-Kung University, Tainan 701,Taiwan, China
• Subjects: Freshwater; Lao-Nung River; Morakot; Peak suspended sediment concentration; PSED; Sediment; 实时预测; 平均降雨量; 悬浮泥沙浓度; 悬移质泥沙; 泥沙量; 老挝; 风暴; 高峰期; Taiwan; Peak suspended sediment concentration; Morakot; Sediment; Lao-Nung River; PSED
• ISSN: 1001-6279
• DOI: 10.1016/S1001-6279(11)60084-X

Based on rainfall erosion of soil and suspended sediment transport in storm events, a method is proposed to predict peak suspended sediment concentration and suspended sediment yield in watersheds based on rainfall characteristics prior to peak rainfall intensity. The rainfall characteristics factors that dominate peak suspended sediment concentration Cp are rainfall erosion factor Ref, first peak rainfall intensity of area-average rainfall ipl and antecedent precipitation index lap ; the rainfall characteristics factors that dominate suspended sediment yield Yss in storm events are total rainfall P, suspended sediment yield factor Rsf and antecedent precipitation index Iap. This research focuses on watersheds in Liau-Kwei observation station along Lao-Nung River in southern Taiwan as the research object, and adopts the PSED-model to simulate the discharge hydrograph, suspended sediment concentration hydrograph and suspended sediment yield in 11 storm events for analysis. The analytical results show that there is a good correlation between the above-mentioned rainfall characteristics factors and Cp as well as Yss, thus enabling Cp and Yss to be predicted by using Expressions （13） and （14）. These two expressions are utilized to predict Ce and Yss of Typhoon Morakot in 2009, and the results are compared with those from simulation by using the PSED-model. The result of comparison shows there is a good capability in predicting. For the watersheds where it is necessary to predict Cp and Yss of a storm event for the benefit of effective operation of water resource facilities, the aforesaid rainfall characteristics factors can be utilized to establish applicable models for prediction.