Flood deposits characterization in Citarum Riverbank Area in Bandung Regency, West Java, Indonesia

Oktaviani, Astiti Dana; Sahdarani, D. N.; Prayoga, J. J.; Indraswari, Asri Oktavioni; Haris, Abdul

doi:10.1088/1755-1315/846/1/012006

Cited by 3 publications

(1 citation statement)

References 9 publications

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“…As climate changes, increase rainfall frequency and intensity signi cantly impact the hydrological cycle and increase the likelihood of regional hydrological natural hazards such as ooding. For the past decades, Indonesia has experienced yearly oods across the country (Oktaviani et al 2021;Azizah et al 2022; Ni et al 2022). Indonesia is signi cantly more vulnerable to ooding disasters than other countries and when looking at the number of oods and the number of people impacted, it is ranked globally third and seventh, respectively.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Rainfall Projection in Majalaya basin, West Java, Indonesia under CMIP6 Scenarios

Sa’adi

Rohmat

Stamataki

et al. 2022

Preprint

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In this study, a Coupled Model Intercomparison Project Phase 6 (CMIP6), from the newest set of General Circulation Models (GCMs), was used to assess the spatiotemporal variability in rainfall regimes over the Majalaya basin in West Java, Indonesia. Twenty grid points of the gridded-based daily rainfall from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) datasets spanning from 1981 to 2014 were extracted. For the future projection, a set of 23 GCMs from the Shared Socioeconomic Pathways (SSPs) with SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 common to historical period were selected. Initially, the performance of the GCMs in simulating the local rainfall at each grid point was assess by using seven relative importance metrics. Then, compromise programming index (CPI) and Jenks optimised classification (JOC) were used to aggregate the results from the ranking of GCMs to select the best GCMs in simulating the local rainfall. It was found that EC-Earth3-Veg-LR ranked the best as Class I, followed by EC-Earth3-Veg, INM-CM4-8, EC-Earth3, MPI-ESM1-2-HR and MRI-ESM2-0 as Class II. Subsequently, the linear scaling (LS) method was used in bias correcting the selected GCM, EC-Earth3-Veg-LR using CHIRPS as reference observed data. The spatiotemporal assessment of bias-corrected LS-EC-Earth3-Veg-LR for the different months over the mid-future period 2041–2070 and 2071–2100 was compared with those under SSPs 126, 245, 370 and 585. Our results show a generally wetter tendency over Majalaya under all SSPs toward the end of the 21st century, particularly under SSP370 and SSP585. For the mid-future period, the results suggest a worsening drier period for the month of June to October. Meanwhile, the usually high rainfall month of November is projected to receive lower rainfall than normal. For the far-future period, all SSPs in most of the cases projected more increasing rainfall months as the typically drier period become shorter. The changes in rainfall were observed to move toward a more homogeneous increase in rainfall for all rainfall months across the basin from the mid-future to the far-future period. It is projected that rainfall events will become more frequent, more intense, and happen consecutively for the rainy months of December and January and followed by another consecutive rainy month for March and April.

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Section: Introductionmentioning

confidence: 99%