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A  simplifiedrainfall-streamflownetwork  model  based  on  multivariate  linear  regression (MLR)  analysishas  been  proposed. To  determine  significant  coefficients  of  streamflow network,  eleven  MLR  models  were examined.  The  study’s  three  objectives  were  1) to develop a novel a mathematical model based on MLR analysis for forecasting optimal water levels;2) to determine the most significant coefficient of rainfall-streamflow network among in the area of interest in the vicinity of Klong Luang sub-watershedKGT.19 station; and3) to apply  the  optimal  MLR  model  forwater  level  andflood  forecasting  mapsin  Klong  Luang Sub-watershed. We  used  Geographic  Information  System  (GIS)  and  Remotely  Sensed  Data (RS) data recorded from Klong Luang (KGT.19 Station) sub-watershed, and Phanat Nikhom, Chonburi,  Ban  Bueng  and  Phan  Thong  districts,  in  Chonburi  Province,  Thailand.The findings indicated that the MLR based Model No. 8 is the most applicable and effective. The proposed model also could be applied in water level forecasting, water resource management, flood hazard planning, and flood early warning.

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A Simplified Rainfall-Streamflow Network Model on Multivariate Regression Analysis for Water Level Forecasting in Klong Luang (KGT.19 Station) Sub-watershed, Chon Buri Province, Thailand