Tan Mou Leong

 

“The decision to further my study under INSTeG, UTM was definitely correct. The INSTeG
has provided me a positive learning environment, good facilities and so on. Besides that,
i also have many chances to travel overseas for attend different kind of conferences
especially the Asian Conference On Remote Sensing (ACRS). Finally, i would like to
thanks all INSTeG staff for their support and hard work.”

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 Name .. : ..  Tan Mou Leong
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 Research Interest .. : ..  Streamflow modeling using remote sensing and GIS
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 Contact No (Office) .. : ..  +6017-9720529
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 E-mail .. : ..  mouleong@gmail.com
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 Present Position .. : ..  Candidate of PhD Student (Full time)
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 Supervisor .. : ..  Assoc. Prof. Dr. Ab. Latif bin Ibrahim
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 Education .. : ..  2009 – B. Sc. (Remote Sensing), Universiti Teknologi Malaysia
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 Research Projects .. : ..  –
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Discription  …………..  : .. It is important to develop a framework for more accurate streamflow simulation that important in flood forecasting. The quality of
………….. .. streamflow model output is limited by the quality of the data used to drive, calibrate and validate the model. The most important input to any hydrological model is precipitation, hence inaccuracies in precipitation data are often cited as serious impediments to successful hydrological model. In developing countries, availability of spatially and temporally of precipitation data especially in ungauged basins remain a critical issue. To overcome these problems, this research will review and use some of the available globally gridded high resolution precipitation datasets: (1) Asian Precipitation highly Resolved Observational Data Integration Towards the Evaluation of Water Resources (APHRODITE), (2) Tropical Rainfall Measuring Mission (TRMM), (3) Precipitation Estimation from Remote Sensing Information using Artificial Neural Network (PERSIANN), (4) Global Precipitation Climatology Project (GPCP), and (5) a modified version of Global Historical Climatology Network (GHCN2) to compare with ground station data distributed within Johor River Basin, Malaysia. Statistical analysis such as linear correlation coefficient, mean error, mean absolute error and bias will perform to identify the best precipitation datasets performance. The data downscaling approach will use to improve the spatial variability of the best precipitation dataset.  A model will develop to process the best dataset in order to improve the precipitation estimation as input to streamflow model. The new precipitation datasets will input into SWAT, SWMM 5.0 and SOBEK model to simulate streamflow for Johor River. The hydrograph produce by three different streamflow model will compare with discharge data obtain from ground station to identify the most suitable streamflow model for tropical environment. The result of this research can be used for planning purposes such as flood control design and assessment of water resources.
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Publication .. : ..  1. .. Tan Mou Leong and Ab Latif Bin Ibrahim. (2012). Remote Sensing, Geographic Information System and Hydrological Model
.. .. .. for Rainfall Runoff Modeling . 33rd Asian Conference on Remote Sensing (ACRS 2012). 26-30 November 2012. Pattaya, Thailand.
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