Development of Hydro-Meteorological Hazard Early Warning System in Indonesia

Abstract

This paper discusses the result of the development of a hydrometeorological hazard early warning system (H-MHEWS) that combines weather prediction from Weather Research and Forecasting (WRF) and the hydrometeorological hazard index from the National Disaster Management Authority (BNPB), Indonesia. In its current development phase, the hazards that H-MHEWS predicts are floods, landslides, and extreme weather events. Potential hazard indices are obtained by using an overlay approach and resampling so that the data have a 100-m spatial resolution. All indices are classified into 4 status categories: "No alert", "Advisory", "Watch", and "Warning". Flood potential is produced by overlaying rainfall prediction at 3hour intervals with the flood index. Landslide potential is produced by overlaying rainfall prediction with the landslide index. Extreme weather potential is divided into 3 categories, i.e. heavy rain, strong winds, and extreme ocean waves. The whole prediction is dynamic, following weather predictions at 3-hour intervals. The hazard prediction results will trigger a 'Warning' alert in case of emergency status. This alert will be set up in a notification system to make it easier for the user to identify the most dangerous hydrometeorological hazard events.

Full Issue

“…Therefore, in the typology pattern of landslide vulnerability, it is necessary to study the category of vulnerability level. According to the research, there are four categories which is based on landslide typology, those are (1) "no warning" category, (2) "alert" category, (3) "attention" category, and (4) the "warning" category (Susandi et al, 2018). This category is adjusted to the level of correlation between the variables which become the typology of the landslide disaster.…”

Modeling of Heavy Rainfall Triggering Landslide Using WRF Model

“…Pendekatan WRF ini dapat digunakan sebagai upaya preventif kejadian bencana alam di masa depan, mengingat pengoperasian model WRF yang relatif mudah (Alvioli et al, 2018;Manor and Berkovic, 2015), dan tidak membutuhkan infrastruktur yang kompleks (Skamarock et al, 2008). Pemanfaatan WRF sudah diaplikasikan pada berbagai penelitian untuk: (i) menganalisis badai pemicu longsor di Italia (Alvioli et al, 2019;Zhuo et al, 2019), (ii) membangun aplikasi peringatan dini longsor di Indonesia (Susandi et al, 2018),…”

Climate Change and Sustainable Development Goals Program in Indonesia

“…Rainfall is the trigger and determines the disasters, such as floods, flash floods, landslides, and droughtthe natural parameter threshold Maximum daily rainfall is used to calculate the vulnerability of flood and landslide hazards index. As for the danger of drought, it used minimum daily rainfall as a parameter (Susandi et al 2018;Savitri and Pramono 2017;Pramono and Putra 2017;Susanti et al 2017;Amri et al 2016). It seems that extreme rainfall in Indonesia often occurs in this decade, even though it depends spatially (Siswanto and Supari 2015; Indonesia Climate Change Sectoral Roadmap 2010).…”

“…Orangutan, one of Indonesia's endemic species as a critical species, can be impacted by global warming by disrupting food availability and habitat destruction (Glaholt 2019). The flowering and fruiting of plants are disturbed due to climate change, which disrupts resources and the abundance of orangutan food (Suhud and Saleh 2007). Habitat loss through forest conversion and drought triggering forest fires pose a severe threat (Carne et al 2012).…”

“…Drought in Kalimantan in 1997/1998 due to El Nino has caused fires in hundreds of hectares of orangutan habitat. An estimated 1,000 orangutans (2.5% of the population) have died (Suhud and Saleh 2007).…”