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

Bambang Bakri; Khaeryna Adam; Amran Rahim

doi:10.7494/geom.2021.15.2.5

Geomatics and Environmental Engineering, vol. 15, no. 2

Issue

Vol. 15 No. 2 (2021): Geomatics and Environmental Engineering

Issue Published : Mar 24, 2021

Date Log

Submitted

Sep 18, 2020

Accepted

Nov 19, 2020

Published

Mar 24, 2021

This work is licensed under a Creative Commons Attribution 4.0 International License.

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

https://doi.org/10.7494/geom.2021.15.2.5

Bambang Bakri

Hasanuddin University, Faculty of Technic, Department of Civil Engineering, Makassar, Indonesia

https://orcid.org/0000-0001-9006-2018

Khaeryna Adam

Hasanuddin University, Faculty of Mathematics and Natural Sciences, Department of Mathematics, Makassar, Indonesia

Amran Rahim

Hasanuddin University, Department of Mathematics, Faculty of Mathematics and Natural Sciences, Makassar, Indonesia

https://orcid.org/0000-0002-9832-8738

Corresponding Author(s) : Amran Rahim

amran@science.unhas.ac.id

Geomatics and Environmental Engineering, Vol. 15 No. 2 (2021): Geomatics and Environmental Engineering
Article Published : Mar 24, 2021

Abstract

In this study, we model extreme rainfall to study the high rainfall events in the province of South Sulawesi, Indonesia. We investigated the effect of the El Nino South Oscillation (ENSO), Indian Ocean Dipole Mode (IOD), and Madden‑Julian Oscillation (MJO) on extreme rainfall events. We also assume that events in a location are affected by events in other nearby locations. Using rainfall data from the province of South Sulawesi, the results showed that extreme rainfall events are related to IOD and MJO.

Keywords

spatioâ€‘temporal model extreme rainfall province of South Sulawesi El Nino South Oscillation Indian Ocean Dipole Mode Maddenâ€“Julian Oscillation

Bakri, B., Adam, K., & Rahim, A. (2021). Spatio‑Temporal Model of Extreme Rainfall Data in the Province of South Sulawesi for a Flood Early Warning System. Geomatics and Environmental Engineering, 15(2), 5–15. https://doi.org/10.7494/geom.2021.15.2.5

Download Citation

References

The Intergovernmental Panel on Climate Change (IPCC): Managing the Risk of Extreme Events and Disasters to Advance Climate Change Adaptation. Cam‑ bridge University Press, Cambridge, UK and New York, USA, 2012.
Coles S.: An Introduction to Statistical Modeling of Extreme Values. Springer, Bristol 2001.
Zhang Q., Li J., Singh V.P.: Application of Archimedean copulas in the analysis of the precipitation extremes: effects of precipitation changes. Theoretical and Applied Climatology, vol. 107, 2011, pp. 255–264.
Hendon H.H.: Indonesian Rainfall Variability: Impacts of ENSO and Local Air– Sea Interaction. Journal of Climate, vol. 16, issue 11, 2003, pp. 1775–1790.
Nur’utami M.N., Hidayat R.: Influences of IOD and ENSO to Indonesian Rainfall Variability: Role of Atmosphere‑ocean Interaction in the Indo‑pacific Sector. Procedia Environmental Sciences, vol. 33, 2016, pp. 196–203.
Hidayat R.: Modulation of Indonesian Rainfall Variability by the Madden‑Julian Oscillation. Procedia Environmental Sciences, vol. 33, 2016, pp. 167–177.
Keim B.D., Cruise F.J.: A Technique to Measure Trends in the Frequency of Discrete Random Events. Journal of Climate, vol. 11, 1998, pp. 848–855.
Wong H.L., Hsieh S.H., Tu Y.H.: Application of Non‑Homogeneous Poisson Process Modeling to Containership Arrival Rate. [in:] 2009 Fourth International Conference on Innovative Computing, Information and Control: ICICIC 2009; Kaohsiung, Taiwan, 7–9 December 2009, Institute of Electrical and Electronics Engineers, 2009, pp. 849–854.
Achcar J.A., Rodrigues E.R., Paulino C.D., Soares P.: Non‑homogeneous Pois‑ son models with a change‑point: an application to ozone peaks in Mexico city. Environmental and Ecological Statistics, vol. 17, 2010, pp. 521–541.
[Sirangelo B., Ferrari E., de Luca D.: Occurrence analysis of daily rain‑falls through non‑homogeneous poissonian processes. Natural Hazards and Earth System Sciences, vol. 11, 2011, pp. 1657–1668.
Mondal A., Mujumdar P.P.: Modeling non‑stationarity in intensity, duration and frequency of extreme rainfall over India. Journal of Hydrology, vol. 521, 2015, pp. 217–231.
Huang X., Grace P., Hu W., Rowlings D., Mengersen K.: Spatial prediction of N2O emissions in pasture: a Bayesian model averaging analysis. PLoS One, vol. 8(6), 2013, e65039.
Rusworth A., Lee D., Mitchell R.: A spatio‑temporal model for estimating the long‑term effects of air pollution on respiratory hospital admissions in Greater London. Spatial and Spatio‑temporal Epidemiology, vol. 10, 2014, pp. 29–38.
Sharkey P., Winter H.C.: A Bayesian spatial hierarchical model for extreme precipitation in Great Britain. 2017, arXiv:1710.02091v1.
[Marco M., Gracia E., López‑Quílez A.: Linking Neighborhood Characteristics and Drug‑Related Police Interventions: A Bayesian Spatial Analysis. ISPRS International Journal of Geo‑Information, vol. 6(3), 2017, 65. https://doi.org/10.3390/ijgi6030065.
Banerjee S., Carlin B., Gelfand A.: Hierarchical Modeling and Analysis for Spatial Data. Monographs on Statistics and Applied Probability, 101, Chapman and Hall/CRC Press, New York 2004.
Deni O.L., Edy S., Sabaruddin S., Iskhaq I.: Respective Influences of Indian Ocean Dipole and El Niño‑Southern Oscillation on Indonesian Precipitation. Journal of Mathematical and Fundamental Sciences, vol. 50, no. 3, 2018, pp. 257–272.
Lee H.S.: General Rainfall Patterns in Indonesia and the Potential Impacts of Local Season Rainfall Intensity. Water, vol. 7(4), 2015, pp. 1751–1768.
Jones Ch., Waliser D.E., Lau K.M., Stern W.: Global occurrences of extreme precipitation and the Madden–Julian Oscillation: observations and predictability. Journal of Climate, vol. 17(23), 2004, pp. 4575–4589.
Ashok K., Guan Z., Saji N.H., Yamagata T.: Individual and Combined Influences of ENSO and the Indian Ocean Dipole on the Indian Summer Monsoon. Journal of Climate, vol. 17, 2004, pp. 3141–3155.
Pourasghar F., Oliver E.C.J., Holbrook N.J.: Modulation of wet‑season rainfall over Iran by the Madden–Julian Oscillation, Indian Ocean Dipole and El Niño–Southern Oscillation. International Journal of Climatology, vol. 39, 2019, pp. 1–12. https://doi.org/10.1002/joc.6057.

References

The Intergovernmental Panel on Climate Change (IPCC): Managing the Risk of Extreme Events and Disasters to Advance Climate Change Adaptation. Cam‑ bridge University Press, Cambridge, UK and New York, USA, 2012.

Coles S.: An Introduction to Statistical Modeling of Extreme Values. Springer, Bristol 2001.

Zhang Q., Li J., Singh V.P.: Application of Archimedean copulas in the analysis of the precipitation extremes: effects of precipitation changes. Theoretical and Applied Climatology, vol. 107, 2011, pp. 255–264.

Hendon H.H.: Indonesian Rainfall Variability: Impacts of ENSO and Local Air– Sea Interaction. Journal of Climate, vol. 16, issue 11, 2003, pp. 1775–1790.

Nur’utami M.N., Hidayat R.: Influences of IOD and ENSO to Indonesian Rainfall Variability: Role of Atmosphere‑ocean Interaction in the Indo‑pacific Sector. Procedia Environmental Sciences, vol. 33, 2016, pp. 196–203.

Hidayat R.: Modulation of Indonesian Rainfall Variability by the Madden‑Julian Oscillation. Procedia Environmental Sciences, vol. 33, 2016, pp. 167–177.

Keim B.D., Cruise F.J.: A Technique to Measure Trends in the Frequency of Discrete Random Events. Journal of Climate, vol. 11, 1998, pp. 848–855.

Wong H.L., Hsieh S.H., Tu Y.H.: Application of Non‑Homogeneous Poisson Process Modeling to Containership Arrival Rate. [in:] 2009 Fourth International Conference on Innovative Computing, Information and Control: ICICIC 2009; Kaohsiung, Taiwan, 7–9 December 2009, Institute of Electrical and Electronics Engineers, 2009, pp. 849–854.

Achcar J.A., Rodrigues E.R., Paulino C.D., Soares P.: Non‑homogeneous Pois‑ son models with a change‑point: an application to ozone peaks in Mexico city. Environmental and Ecological Statistics, vol. 17, 2010, pp. 521–541.

[Sirangelo B., Ferrari E., de Luca D.: Occurrence analysis of daily rain‑falls through non‑homogeneous poissonian processes. Natural Hazards and Earth System Sciences, vol. 11, 2011, pp. 1657–1668.

Mondal A., Mujumdar P.P.: Modeling non‑stationarity in intensity, duration and frequency of extreme rainfall over India. Journal of Hydrology, vol. 521, 2015, pp. 217–231.

Huang X., Grace P., Hu W., Rowlings D., Mengersen K.: Spatial prediction of N2O emissions in pasture: a Bayesian model averaging analysis. PLoS One, vol. 8(6), 2013, e65039.

Rusworth A., Lee D., Mitchell R.: A spatio‑temporal model for estimating the long‑term effects of air pollution on respiratory hospital admissions in Greater London. Spatial and Spatio‑temporal Epidemiology, vol. 10, 2014, pp. 29–38.

Sharkey P., Winter H.C.: A Bayesian spatial hierarchical model for extreme precipitation in Great Britain. 2017, arXiv:1710.02091v1.

[Marco M., Gracia E., López‑Quílez A.: Linking Neighborhood Characteristics and Drug‑Related Police Interventions: A Bayesian Spatial Analysis. ISPRS International Journal of Geo‑Information, vol. 6(3), 2017, 65. https://doi.org/10.3390/ijgi6030065.

Banerjee S., Carlin B., Gelfand A.: Hierarchical Modeling and Analysis for Spatial Data. Monographs on Statistics and Applied Probability, 101, Chapman and Hall/CRC Press, New York 2004.

Deni O.L., Edy S., Sabaruddin S., Iskhaq I.: Respective Influences of Indian Ocean Dipole and El Niño‑Southern Oscillation on Indonesian Precipitation. Journal of Mathematical and Fundamental Sciences, vol. 50, no. 3, 2018, pp. 257–272.

Lee H.S.: General Rainfall Patterns in Indonesia and the Potential Impacts of Local Season Rainfall Intensity. Water, vol. 7(4), 2015, pp. 1751–1768.

Jones Ch., Waliser D.E., Lau K.M., Stern W.: Global occurrences of extreme precipitation and the Madden–Julian Oscillation: observations and predictability. Journal of Climate, vol. 17(23), 2004, pp. 4575–4589.

Ashok K., Guan Z., Saji N.H., Yamagata T.: Individual and Combined Influences of ENSO and the Indian Ocean Dipole on the Indian Summer Monsoon. Journal of Climate, vol. 17, 2004, pp. 3141–3155.

Pourasghar F., Oliver E.C.J., Holbrook N.J.: Modulation of wet‑season rainfall over Iran by the Madden–Julian Oscillation, Indian Ocean Dipole and El Niño–Southern Oscillation. International Journal of Climatology, vol. 39, 2019, pp. 1–12. https://doi.org/10.1002/joc.6057.