TY  - JOUR
T1  - Neyman Scott Rectangular Pulse (NSRP) Modeling and Spatial Analysis of
Storm Behavior in Peninsular Malaysia
AU - Yendra, Rado AU - , Anofrizen AU - Zawiah Wan Zin, Wan AU - Aziz Jemain, Abdul AU - Fudholi, Ahmad 
JO  - Journal of Engineering and Applied Sciences
VL  - 12
IS  - 24
SP  - 7604
EP  - 7611
PY  - 2017
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2017.7604.7611
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2017.7604.7611
KW  - Storm rainfall
KW  -NSRP
KW  -geostatistical kriging
KW  -probability
KW  -agriculture
KW  -rectangular
AB  - Nowadays, the analysis of rainfall behavior is becoming important in many areas, particularly in
water-related sectors such as hydrology, agriculture and water resource management. The expansion of irrigated
agriculture, coupled with the development of industrialization and the rapid growth of population, contribute
to the demand for the analysis of rainfall behaviour as such analysis can be utilized in rainfall forecasting and
decision making. The main objective of this study is to evaluate the application Neyman-Scott Rectangular
Pulse (NSRP) modeling in describing the storm rainfall in Peninsular Malaysia. This study also describing
spatial analysis for the important statistics (mean and probability rain) and the storm behavior by using NSRP
parameters in Peninsular Malaysia, based on hourly rainfall data from 50 selected rainfall stations which include
four sub regions, namely Northwest, West, Southwest and East for the periods of 1970-2008. The results of this
study proved that NSRP Model is able to imitate the pattern of actual rainfall in Peninsular Malaysia by
comparing the parameters as well as the spatial distribution of the means and probabilities of 1 and 24 h rain.
Thus, results from the NSRP model fitting for each station are valid to be used in further analysis that is to
evaluate the behavior of storm rainfall. Moreover, almost all areas in Peninsula experienced the same probability
of rain an hour between 0.03 and 0.09 also the probability of rain 24 h significantly increase on September with
value between 0.41 and 0.69 during SWM season.
ER  -