@ARTICLE{Hartanto_Spatial_2024,
 author={Hartanto and Humaidi, Syahrul and Frida, Erna and Ananda, Naufal and Sinambela, Marzuki},
 number={No 62},
 pages={193-200},
 journal={Journal of Water and Land Development},
 howpublished={online},
 year={2024},
 publisher={Polish Academy of Sciences; Institute of Technology and Life Sciences - National Research Institute},
 abstract={Based on data from the National Disaster Management Agency (Ind.: Badan Nasional Penanggulangan Bencana – BNPB), throughout 2022, more than 91% of disaster events were hydrometeorological disasters, with floods at 43% and landslides at 17%. One of the factors for floods and landslides is high rainfall intensity. Automatic rain gauge (ARG) is a rainfall observation instrument that can accurately measure rainfall at observation points. However, it has problems such as communication systems that cause delays in data transmission, low instrument density, and inability to cover a wide spatial area, which can affect the accuracy of rainfall information. Weather radar is a remote sensing instrument that can estimate rainfall spatially so that weather radar observations can reach areas of the region that do not have ARG. However, before being used as rainfall information, estimation rainfall needs to be evaluated or calibrated. Evaluation of rainfall estimation on weather radar to ARG in Banten at a 30– 120 km distance range, shows a coefficient of determination above 0.8. Based on the studies that have been conducted, increase of root mean square error (RMSE) is due to influence of radar observation range and observation distance on ARG. Adjustment of rainfall estimation improves the accuracy of rainfall estimation. Adjusting rainfall estimation can reduce RMSE by 50%.},
 type={Article},
 title={Spatial evaluation rainfall estimation on weather radar using Marshall–Palmer reflectivity–rainfall rate in Banten},
 URL={http://ochroma.man.poznan.pl/Content/132983/2024-03-JWLD-22.pdf},
 doi={10.24425/jwld.2024.151567},
 keywords={estimation, Marshall–Palmer, rainfall, reflectivity, weather radar},
}