Modeling of Heavy Rainfall Triggering Landslide Using WRF Model

Agromet

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Title Modeling of Heavy Rainfall Triggering Landslide Using WRF Model
Modeling of Heavy Rainfall Triggering Landslide Using WRF Model
 
Creator Nuryanto, Danang Eko
Fajariana, Yuaning
Pradana, Radyan Putra
Anggraeni, Rian
Badri, Imelda Ummiyatul
Sopaheluwakan, Ardhasena
 
Subject Heavy Rainfall
Kulonprogo
Landslide
Planetary Boundary Layer
Weather Research Forecasting (WRF)
Heavy Rainfall
Kulonprogo
Landslide
Planetary Boundary Layer
Weather Research Forecasting (WRF)
 
Description This study revealed the behavior of heavy rainfall before landslide event based on the Weather Research Forecasting (WRF) model. Simulations were carried out to capture the heavy rainfall patterns on 27 November 2018 in Kulonprogo, Yogyakarta. The modeling was performed with three different planetary boundary layer schemes, namely: Yonsei University (YSU), Sin-Hong (SH) and Bougeault and Lacarrere (BL). Our results indicated that the variation of rainfall distribution were small among schemes. The finding revealed that the model was able to capture the radar’s rainfall pattern. Based on statistical metric, WRF-YSU scheme was the best outperforming to predict a temporal pattern. Further, the study showed a pattern of rainfall development coming from the southern coastal of Java before 13:00 LT (Local Time=WIB=UTC+7) and continued to inland after 13:00 LT. During these periods, the new clouds were developed. Based on our analysis, the cloud formation that generated rainfall started at 10:00 LT, and hit a peak at 13:00 LT. A starting time of cloud generating rainfall may be an early indicator of landslide.
This study revealed the behavior of heavy rainfall before landslide event based on the Weather Research Forecasting (WRF) model. Simulations were carried out to capture the heavy rainfall patterns on 27 November 2018 in Kulonprogo, Yogyakarta. The modeling was performed with three different planetary boundary layer schemes, namely: Yonsei University (YSU), Sin-Hong (SH) and Bougeault and Lacarrere (BL). Our results indicated that the variation of rainfall distribution were small among schemes. The finding revealed that the model was able to capture the radar’s rainfall pattern. Based on statistical metric, WRF-YSU scheme was the best outperforming to predict a temporal pattern. Further, the study showed a pattern of rainfall development coming from the southern coastal of Java before 13:00 LT (Local Time=WIB=UTC+7) and continued to inland after 13:00 LT. During these periods, the new clouds were developed. Based on our analysis, the cloud formation that generated rainfall started at 10:00 LT, and hit a peak at 13:00 LT. A starting time of cloud generating rainfall may be an early indicator of landslide.
 
Publisher PERHIMPI (Indonesian Association of Agricultural Meteorology)
 
Date 2020-06-09
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://journal.ipb.ac.id/index.php/agromet/article/view/30016
10.29244/j.agromet.34.1.55-65
 
Source Agromet; Vol. 34 No. 1 (2020): JUNE 2020; 55-65
2655-660X
0126-3633
10.29244/j.agromet.34.1
 
Language eng
 
Relation http://journal.ipb.ac.id/index.php/agromet/article/view/30016/19945
 

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