Spatio‑Temporal Model of Extreme Rainfall Data  in the Province of South Sulawesi for a Flood Early Warning System

Bakri, Bambang; Adam, Khaeryna; Rahim, Amran

doi:10.7494/geom.2021.15.2.5

Cited by 4 publications

(4 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This situation is exacerbated by human activities, which lead to environmental degradation, unsystematic and unplanned use, and the processing of natural resources [18]. Rainfall data can be used as landslide [19][20][21][22][23] and flood [24,25] early warning tools. Early Warning System provides useful data for making better decisions, such as providing alerts or triggering the necessary protection mechanisms [26].…”

Section: Rainfall Data For Early Warning Systemmentioning

confidence: 99%

“…For the purposes of EWS, prediction models are made using available rain data, both from direct measurements (rainfall gauges) and remote sensing data. There are many approaches to analysing precipitation thresholds, including using gauge-based precipitation [20] and remotely sensed data [25,27]. The rainfall threshold is the widely accepted alternative method for hydrological prediction, especially for flash flood early warning.…”

Section: Rainfall Data For Early Warning Systemmentioning

confidence: 99%

See 1 more Smart Citation

Identification of the rain gauge stations for the participatory flood and landslide mitigation in the Serayu river basin, Central Java

Savitri¹,

Wahyuningrum²,

Nugroho³

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

Rainfall data is vital in analysing hydro-meteorological disasters, e.g., floods, landslides, or droughts. Currently, the location of climatological stations or rain gauges is preferred in areas that require climatological data, such as airports and near settlements. On the other hand, rainfall analysis for disaster mitigation purposes is more for remote areas, which are often far from the nearest rainfall station. This study aims to obtain accurate rainfall data through the placement of suited rain gauge locations and utilising community participation. The method used in this study is a literature review. This preliminary study was held upstream of the Serayu river basin, an area where it is usually challenging to access rainfall data. The references used are information about tropical rain, how to utilise a rain gauge network, and how to take advantage of community participation. The result shows that an Early Warning System should be developed in line with determining the location of the rain gauge because each location has a different rainfall threshold in each disaster. The placement of the rain gauge is strongly influenced by the landscape, the altitude of the place as well as the slope and aspect. For this study, the location of schools in remote areas is another parameter to determine the placement of a rain gauge since school children will be involved in the community participation.

show abstract

Section: Rainfall Data For Early Warning Systemmentioning

confidence: 99%

Section: Rainfall Data For Early Warning Systemmentioning

confidence: 99%

Identification of the rain gauge stations for the participatory flood and landslide mitigation in the Serayu river basin, Central Java

Savitri¹,

Wahyuningrum²,

Nugroho³

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

show abstract

“…Extreme rainfall is divided into two, namely extreme high rainfall and extreme low rainfall. Extremely low rainfall is often associated with drought while extreme high rainfall is often associated with landslides and floods [1].…”

Section: Introductionmentioning

confidence: 99%

Modeling of Flood Prone Areas In The Kelara Watershed

Mustamin

Maricar

Karamma

2023

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

One of the efforts to minimize the negative impacts of flooding in the Kelara Watershed is to make model flood-prone areas that can be used as an initial reference for flood disaster mitigation. The analytical method used is hydraulic analysis using 2D HECRAS numerical simulations to determine areas affected by flooding based on flood discharge at a return period of 2 - 100 years. Based on the simulation results, it is found that the discovery area for Q2 is 331.42 Ha, Q5 is 547.21 Ha, Q10 is 798.76 Ha, Q20 is 925.11 Ha, Q25 is 925.79 Ha, Q50 is 1048.48 Ha, and Q100 is 1146.71 Ha. From the results of the flood depth verification, it was also known that the flood that occurred on January 22, 2019 was approaching the 100 year return period flood and June 12, 2020, was approaching the 20 year return period flood. So from the results of mapping and field verification, it is known that the 4 affected districts are Binamu District, Kelara District, Turatea District, and Biringbulu District with the location of the worst flooding occurred in Sapanang Village, Binamu District.

show abstract

“…In addition to the most frequent disasters, floods also have a wide scope and can cause great losses, including loss of life and property loss (Hallegatte et al 2013;Merz et al 2010;Wijayanti et al 2017). Floods in Indonesia have enormous potential when viewed from the topography which is mostly lowlands, basins, and oceans, and is also one of the countries that has extreme rainfall (Bakri et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation of Flood Propagation in the Kelara River Flood Early Warning System

Maricar¹,

Karamma²,

Mustamin³

et al. 2023

JWMM

View full text Add to dashboard Cite

Flood historical data from the Kelara River in the last 10 years shows that the river has often overflowed, and the worst floods happened on January 22, 2019. One of the efforts to minimize the negative impact of a flood disaster is to conduct flood tracking. Flood tracking is an analysis of the flood along the river, or also known as flood propagation, which can be used as a reference in the preparation of a flood early warning system. This study aims to determine the propagation of the Kelara River flood which can be used to determine flood-prone areas and as a reference in the preparation of a flood early warning system. This research was carried out in 3 stages, namely flood hydrology analysis using the HEC-HMS program, numerical simulation of 2D floods using the HEC-RAS program, spatial modeling of flood-prone areas using the ArcGIS program, and preparation of a flood early warning system. The results of this study showed that the flood that occurred on January 22, 2019, was a 100-year return period flood, and determined that 10 points of residential areas/villages must be alerted when the intensity of rain is high, with the fastest time to be alerted being 52 minutes.

show abstract

Spatio‑Temporal Model of Extreme Rainfall Data in the Province of South Sulawesi for a Flood Early Warning System

Cited by 4 publications

References 20 publications

Identification of the rain gauge stations for the participatory flood and landslide mitigation in the Serayu river basin, Central Java

Identification of the rain gauge stations for the participatory flood and landslide mitigation in the Serayu river basin, Central Java

Modeling of Flood Prone Areas In The Kelara Watershed

Numerical Simulation of Flood Propagation in the Kelara River Flood Early Warning System

Contact Info

Product

Resources

About