Application of hydrological medelling to estimate flow using [XPSWMM] /Azmaya Noordin Ahmad
The impact of flow during extreme weather like heavy rainfall in short period of time may cause flash flood that the water discharged contains of soil. The aim of this research is to estimate the magnitude of flow using hydrological modeling in UiTM Arau. The data collection was obtained from sit...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2018
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/22519/1/TD_AZMAYA%20NOORDIN%20AHMAD%20AP%20R%2018.5.PDF |
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| Summary: | The impact of flow during extreme weather like heavy rainfall in short period
of time may cause flash flood that the water discharged contains of soil. The aim of
this research is to estimate the magnitude of flow using hydrological modeling in
UiTM Arau. The data collection was obtained from site measurements. The
measurement of drainage was taken with the depth and length of the drainage. The
results of flow measurements can be obtained from the simulation of XPSWMM. This
study is to analysis of the graph analysis and the estimation of flow in UiTM Perlis
either it high or low the water discharge specifically in campus area. The results will
display in graph analysis between RMSE Observed and RMSE Model. RMSE Model
for Catchment 1 is 0.38m^/s while RMSE Observed is 0.40mVs and the different is
only 0.04mVs. While for Catchment 2, RMSE Model is O.bSmVs and RMSE
Observed is 0.77mVs. Lastly, RMSE Model for Catchment 3 is O.SOmVs and RMSE
Observed is 0.517m^/s. The different between reading Catchment 2 and Catchment 3
are 0.1 Im^/s and 0.012m^/s respectively. It is shown that the RMSE Model is smaller
than RMSE Observed. In conclusion, the results obtained to prove that the data model
is more accurate compare to data observed. Therefore, it proves that the entire data
model is better and accurate beside it also can be the best line for Root Mean Square
Error. |
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