A hybrid machine learning framework for real-time water level prediction in high sediment load reaches

2020 ◽  
Vol 581 ◽  
pp. 124422 ◽  
Author(s):  
Gang Zhao ◽  
Bo Pang ◽  
Zongxue Xu ◽  
Liyang Xu
Keyword(s):  
Machine Learning ◽  
Water Level ◽  
Real Time ◽  
Sediment Load ◽  
Learning Framework ◽  
Hybrid Machine ◽  
High Sediment ◽  
Water Level Prediction

EXAMINATION OF SHORT-TERM WATER LEVEL PREDICTION MODEL IN LOW-LYING LAKES USING MACHINE LEARNING

2020 ◽  
Vol 76 (2) ◽  
pp. I_439-I_444
Author(s):  
Masaomi KIMURA ◽  
Takahiro ISHIKAWA ◽  
Naoto OKUMURA ◽  
Issaku AZECHI ◽  
Toshiaki IIDA
Keyword(s):  
Machine Learning ◽  
Prediction Model ◽  
Water Level ◽  
Short Term ◽  
Water Level Prediction

Application of a flow-measurement structure for sediment-laden streams

2009 ◽  
Vol 36 (9) ◽  
pp. 1539-1543
Author(s):  
Mustafa Göğüş ◽  
A. Cüneyt Gerek ◽  
A. Burcu Altan-Sakarya
Keyword(s):  
Water Level ◽  
Flow Measurement ◽  
Sediment Load ◽  
Real Data ◽  
Flow Depth ◽  
Rating Curve ◽  
Natural Streams ◽  
The Relationship ◽  
High Sediment ◽  
Single Relation

Generally, measurement of flow in natural streams is accomplished by measuring the flow depth. Hence, the relationship between the water level and discharge should be obtained in advance. However, in streams with high sediment load, the bottom level may change due to sediment deposition, preventing the single relation between water level and discharge. This paper summarizes the application of a flow-measurement structure for sediment-laden streams. The proposed structure is designed and built in Turkey and has been under operation since 1998 without any sedimentation problem. The agreement between the real data obtained from the structure and the theoretical rating curve is quite reasonable.

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