Nowadays, severe flooding frequently occurs in various parts of Thailand resulted from changes
in climatic condition and land use patterns. The flooding has caused great damages to properties
and lives and affects country economy. Experience from the most severe flooding in the northern
and central regions of Thailand in the year 2011 reveals that reliable flood warning system is still
lagging. For flood warning purpose, it is necessary to have an accurate flood routing system. This
study is aimed at developing mathematical models for flood routing so as to provide data for flood
warning. Two different models are developed, i.e., kinematic overland flow model and kinematic
stream flow model. The finite element method with Galerkin’s weighted residual technique is used
in model development. The second order Runge-Kutta method is applied to solve the set of
differential equations obtained from finite element formulation. The developed models are applied
to simulate flows in the Wang river basin in the northern region of Thailand during July 1 -
October 31, 2011 when severe flooding occurred in this region. Model calibration is made by
adjusting some parameters in the models and comparing the obtained results with measured data
recorded by RID at 5 stream flow gauge stations along the Wang river. For correlation analysis.
three statistical indices are determined, these include coefficient of determination, R2, Nash-
Sutcliffe model efficiency coefficient, NSE, and coefficient of variation of the root mean square
error, CV(RMSE). It is found that the model results at the upstream portion of the river
satisfactorily agree with the observed data, with the values of R2 greater than 0.55 and CV(RMSE)
less than 0.57. For the downstream portion of the river, there are remarkable differences between
the model results and the observed data. The values of R2 are less than 0.35, CV(RMSE) greater
than 0.76, and the NSE values are less than 0.16. This might be due to some errors in the input
data, including rainfall pattern, topography, land use, river cross-sectional area, and water seepage
along the river. More detailed field investigation and model calibration are still needed.
