Performance of GSMaP and PERSIANN dataset for precipitation estimation on tropical strom PABUK

Name: Fatah Masthawee

Organization : Thai Meteorological Department. Hydrometeorological Sub-Division

Email : fatah_m@yahoo.com

Name: Pattara Sukthawee

Organization : Thai Meteorological Department. Hydrometeorological Sub-Division

Name: Anujit Vansarochana

Organization : Natural Resources and Environment. Faculty of Agriculture

Name: Jeerapa Teianual

Organization : Thai Meteorological Department. Hydrometeorological Sub-Division

Name: Sanguanpran Amornpatanawat

Organization : Thai Meteorological Department. Hydrometeorological Sub-Division

Name: Rattana Prakhammintara

Organization : Thai Meteorological Department. Hydrometeorological Sub-Division

keyword: GSMaP

LCSH: Remote sensing

LCSH: Thunderstorms -- Forcasting

LCSH: Floods

Abstract: Tropical storm Pabuk is the severest tropical cyclone in decades that effecting southern part of Thailand during New year celebrating season, heavy rainfall occurring throughout this area. Rainfall Data set, rainfall gauge sensor (RS), play a vital role to warn and mitigate risk in water hazard. This study aims to assess performance of precipitation measurement with RS method as following: 1) GSMaP (Global Satellite Mapping of Precipitation) 2) Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network (PERSIANN). With Quantitative precipitation estimation (QPE). Five Statistic verification method utilized to point out the uncertainty of modification rainfall. Uncertainty comparing between GSMaP and PERSIANN is measured by Mean Absolute Error (MAE), Nash/ Sutcliffe model efficiency coefficient (NSE), Mean field bias (MFB), RMSE-observation standard deviation ratio (RSR) and Percent Bias (PBIAS). The final shown that PERSIANN based QPE dataset has better performance than GSMaP based QPE dataset, hence PERSIAN are recommended to utilized in early warning duty in study area.

King Mongkut's University of Technology North Bangkok. Central Library

Address: BANGKOK

Email: library@kmutnb.ac.th

Created: 2562

Modified: 2022-08-02

Issued: 2022-08-02

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BibliograpyCitation : ใน มหาวิทยาลัยสารคาม คณะวิศวกรรมศาสตร์ สาขาวิศวกรรมโยธา. การประชุมวิชาการวิศวกรรมโยธาแห่งชาติ ครั้งที่ 24 (NCCE 24) (WRE058) อุดรธานี : มหาวิทยาลัยสารคาม

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