JDR Vol.14 No.5 pp. 811-828
doi: 10.20965/jdr.2019.p0811


X-MP Radar for Developing a Lahar Rainfall Threshold for the Merapi Volcano Using a Bayesian Approach

Ratih Indri Hapsari*1,†, Satoru Oishi*2, Magfira Syarifuddin*3, Rosa Andrie Asmara*4, and Djoko Legono*5

*1Department of Civil Engineering, State Polytechnic of Malang
Jl. Soekarno Hatta 9, Malang 65141, Indonesia

Corresponding author

*2Research Center for Urban Safety and Security, Kobe University, Kobe, Japan

*3Department of Dryland Agricultural Management, State Agriculture Polytechnic of Kupang, Kupang, Indonesia

*4Department of Informatics Technology, State Polytechnic of Malang, Malang, Indonesia

*5Department of Civil and Environmental Engineering, Universitas Gadjah Mada, Yogyakarta, Indonesia

August 8, 2018
May 8, 2019
August 1, 2019
lahar, rainfall threshold, Bayesian probability, X-MP radar, uncertainty

Lahar flow is recognized as among the worst secondary hazards from volcanic disaster. Intense rainfall with long duration is frequently associated with lahar flow. In this study, estimation of a rainfall threshold likely to trigger lahar flow is presented in the first part. The second part discusses its implementation by assessing the growth of observed and predicted rainfall, including the uncertainties. The study area is Merapi Volcano, one of the most active volcanoes in Indonesia, including rivers on the flank of Mount Merapi that are vulnerable to debris flow. The rainfall indices needed to describe the conditions that generate lahars or not were determined empirically by evaluating the hourly and working rainfall using X-band multiparameter (X-MP) weather radar. Using past records of lahar flow, the threshold lines separating rainfall that triggers lahars or not were analyzed for the Putih, Gendol, Pabelan, and Krasak Rivers. The performance of several critical lines was evaluated using Bayesian probability based on skill rates from a contingency matrix. The study shows that the line intercept of the critical lines after a significant eruption in 2010 was higher than those lines developed before 2010, indicating that the rivers are currently at lesser risk. Good representation was shown by the thresholds verified with actual rainfall progression and lahar event information on February 17, 2016, at the Gendol and Pabelan Rivers. These rainfall critical lines were the basis for judging the debris flow occurrence by analyzing the track record of predicted rainfall progression. The uncertainty of rainfall short-term prediction from the extrapolation model was evaluated by perturbing the advection vector of rain echo motion. This ensemble forecast product could provide a plausible range of prediction possibility as assistance in gaining the confidence with which a lahar could be predicted. The scheme presented herein could serve as a useful tool for a lahar early warning system in the area of the Merapi Volcano.

Cite this article as:
R. Hapsari, S. Oishi, M. Syarifuddin, R. Asmara, and D. Legono, “X-MP Radar for Developing a Lahar Rainfall Threshold for the Merapi Volcano Using a Bayesian Approach,” J. Disaster Res., Vol.14 No.5, pp. 811-828, 2019.
Data files:
  1. [1] F. Lavigne, J.-C. Thouret, D. S. Hadmoko, and C. B. Sukatja, “Lahars in Java: Initiations, Dynamics, Hazard Assessment and Deposition Processes,” Forum Geografi, Vol.21, No.1, pp. 17-32, 2007.
  2. [2] L. J. Cobar, D. Legono, and K. Miyamoto, “Modeling of Information Flow for Early Warning in Mount Merapi Area, Indonesia,” J. Disaster Res., Vol.11, No.1, pp. 60-71, 2016.
  3. [3] C. L. Shieh, Y. S. Chen, Y. J. Tsai, and J. H. Wu, “Variability in rainfall threshold for debris flow after the Chi-Chi earthquake in central Taiwan, China,” Int. J. of Sediment Research, Vol.24, No.2, pp. 177-188, 2009.
  4. [4] M. T. Brunetti, S. Peruccacci, M. Rossi, S. Luciani, D. Valigi, and F. Guzzetti, “Rainfall thresholds for the possible occurrence of landslides in Italy,” Nat. Hazards Earth Syst. Sci., Vol.10, No.3, pp. 447-458, 2010.
  5. [5] Ministry of Land, Infrastructure, Transport and Tourism Japan (MLIT), “Guidelines for development of warning and evacuation system against sediment disasters in developing countries: Planning,” Planning of Warning and Evaculation System, 2004.
  6. [6] N. Caine, “The rainfall intensity: duration control of shallow landslides and debris flows,” Geografiska Annaler. Series A, Physical Geography, Vol.62, No.1/2, pp. 23-27, 1980.
  7. [7] N. Osanai, T. Shimizu, K. Kuramoto, S. Kojima, and T. Noro, “Japanese early-warning for debris flows and slope failures using rainfall indices with Radial Basis Function Network,” Landslides, Vol.7, No.3, pp. 325-338, 2010.
  8. [8] F. Lavigne, J. C. Thouret, B. Voight, H. Suwa, and A. Sumaryono, “Lahars at Merapi volcano, Central Java: an overview,” J. of Volcanology and Geothermal Research, Vol.100, No.1-4, pp. 423-456, 2000.
  9. [9] F. Lavigne and J.-C. Thouret, “Sediment transportation and deposition by rain-triggered lahars at Merapi Volcano, Central Java, Indonesia,” Geomorphology, Vol.49, No.1-2, pp. 45-69, 2003.
  10. [10] E. D. Bélizal, F. Lavigne, D. S. Hadmoko, J.-P. Degeai, G. A. Dipayana, B. W. Mutaqin, M. A. Marfai, M. Coquet, B. Le Mauff, A.-K. Robin, C. Vidal, N. Cholik, and N. Aisyah, “Rain-triggered lahars following the 2010 eruption of Merapi volcano, Indonesia: A major risk,” J. of Volcanology and Geothermal Research, Vol.261, pp. 330-347, 2013.
  11. [11] M. Syarifuddin, S. Oishi, D. Legono, R. I. Hapsari, and M. Iguchi, “Integrating X-MP radar data to estimate rainfall induced debris flow in the Merapi volcanic area,” Advances in Water Resources, Vol.110, pp. 249-262, 2017.
  12. [12] V. Montesarchio, E. Ridolfi, F. Russo, and F. Napolitano, “Rainfall threshold definition using an entropy decision approach and radar data,” Nat. Hazards Earth Syst. Sci., Vol.11, No.7, pp. 2061-2074, 2011.
  13. [13] T. Mananoma and W. Wardoyo, “The influence of rainfall characteristics change on sediment migration pattern after Merapi eruption 2006,” Proc. of Int. Seminar on Climate Change Impacts on Water Resources and Coastal Management in Developing Countries, pp. 1-10, 2009.
  14. [14] S. Hardjosuwarno, C. B. Sukatja, and F. T. Yunita, “Early warning system for lahar in Merapi,” Ministry of Public Works, Indonesia, 2013.
  15. [15] A. Kato and M. Maki, “Localized heavy rainfall near Zoshigaya, Tokyo, Japan on 5 August 2008 observed by X-band polarimetric radar – Preliminary analysis,” Scientific Online Letters on the Atmosphere, Vol.5, pp. 89-92, 2009.
  16. [16] F. Cecinati, M. A. Rico-Ramirez, G. B. M. Heuvelink, and D. Han, “Representing radar rainfall uncertainty with ensembles based on a time-variant geostatistical error modelling approach,” J. of Hydrology, Vol.548, pp. 391-405, 2017.
  17. [17] A. Bellon and G. L. Austin, “The accuracy of short-term radar rainfall forecasts,” J. of Hydrology, Vol.70, No.1-4, pp. 35-49, 1984.
  18. [18] J. H. Albert and A. K. Gupta, “Bayesian Estimation Methods for 2×2 Contingency Tables Using Mixtures of Dirichlet Distributions,” J. of the American Statistical Association, Vol.78, No.383, pp. 708-717, 1983.
  19. [19] L. D. Maxim and L. Harrington, “The application of pseudo-Bayesian estimators to remote sensing data: Ideas and examples,” Photogrammetric Engineering and Remote Sensing, Vol.49, No.5, pp. 649-658, 1983.
  20. [20] S. Lee, J. Choi, and K. Min, “Landslide susceptibility analysis and verification using the Bayesian probability model,” Environmental Geology, Vol.43, No.1-2, pp. 120-131, 2002.
  21. [21] M. Berti, M. L. V. Martina, S. Franceschini, S. Pignone, A. Simoni, and M. Pizziolo, “Probabilistic rainfall thresholds for landslide occurrence using a Bayesian approach,” J. of Geophysical Research, Earth Surface, Vol.117, No.F4, F04006, 2012.
  22. [22] F. Guzzetti, S. Peruccacci, M. Rossi, and C. P. Stark, “Rainfall thresholds for the initiation of landslides in central and southern Europe,” Meteorology and Atmospheric Physics, Vol.98, No.3-4, pp. 239-267, 2007.
  23. [23] T. Takahashi, “Debris Flow: Mechanics, Prediction and Countermeasures,” CRC Press, 2014.
  24. [24] H. L. Cloke and F. Pappenberger, “Ensemble flood forecasting: A review,” J. of Hydrology, Vol.375, No.3-4, pp. 613-626, 2009.
  25. [25] Surono, P. Jousset, J. Pallister, M. Boichu, M. F. Buongiorno, A. Budisantoso, F. Costa, S. Andreastuti, F. Prata, D. Schneider, L. Clarisse, H. Humaida, S. Sumarti, C. Bignami, J. Griswold, S. Carn, C. Oppenheimer, and F. Lavigne, “The 2010 explosive eruption of Java’s Merapi volcano – a ‘100-year’ event,” J. of Volcanology and Geothermal Research, Vol.241-242, pp. 121-135, 2012.
  26. [26] J. Ikhsan and G. Wicaksono, “Effect of Lahar from Merapi 2010 Post-eruption to the Physical Condition of Middle Progo River,” Konteks Proc., pp. K-17-K-24, 2012 (in Indonesian).
  27. [27] J. Hamada, M. D. Yamanaka, J. Matsumoto, S. Fukao, P. A. Winarso, and T. Sribimawati, “Spatial and Temporal Variations of the Rainy Season over Indonesia and their Link to ENSO,” J. of the Meteorological Society of Japan, Vol.80, No.2, pp. 285-310, 2002.
  28. [28] S. G. Park, M. Maki, K. Iwanami, V. N. Bringi, and V. Chandrasekar, “Correction of radar reflectivity and differential reflectivity for rain attenuation at X Band. Part II: Evaluation and application,” J. of Atmospheric and Oceanic Tech., Vol.22, No.11, pp. 1633-1655, 2005.
  29. [29] F. Fitriyadi, “Analysis of Effective Rainfall Intensity and Working Rainfall for Basic Warning Criteria Development on Lahar Flow Event,” J. of the Civil Engineering Forum, Vol.XXII/1, pp. 1335-1340, 2013.
  30. [30] D. Kristianto, “Determination of Emergency Status for Lahar in Mount Merapi Area,” Report of Experimental Station for Sabo, Research Center for Water Resource, Ministry of Public Works and Housing of Indonesia,, 2015.
  31. [31] T. Bayes, “An essay towards solving a problem in the doctrine of chances,” Philosophical Trans. of the Royal Society, Vol.53, pp. 370-418, 1763.
  32. [32] M. Reyniers, “Quantitative precipitation forecasts based on radar observations: principles, algorithms and operational systems,” Royal Meteorological Institute of Belgium, 2008.
  33. [33] M. Shiiba, T. Takasao, and E. Nakakita, “Investigation of short-term rainfall prediction method by a translation model,” Proc. of 28th Japan Conf. on Hydraulics, Vol.28, pp. 423-428, 1984.
  34. [34] R. I. Hapsari, S. Oishi, K. Sunada, E. Nakakita, and T. Sano, “Singular vector method on short-term rainfall prediction using radar for hydrologic ensemble prediction,” J. of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol.67, No.4, pp. I_109-I_114, 2011.
  35. [35] P. J. Roebber, “Visualizing Multiple Measures of Forecast Quality,” Weather and Forecasting, Vol.24, No.2, pp. 601-608, 2009.
  36. [36] D. S. Wilks, “Statistical Methods in the Atmospheric Sciences,” Academic Press, 2011.
  37. [37] J. Ikhsan, “Management of potency and danger of sediment from 2010 Eruption,” Proc. of Symp. on Mt. Merapi, pp. 153-156, 2011.
  38. [38] M. D. Munir and Djudi, “Damages of Sabo Dams After Merapi 2010 Eruption,” Proc. of National Seminar of Earth Science, pp. 124-141, 2015 (in Indonesian).
  39. [39] A. Rovira, R. J. Batalla, and M. Sala, “Response of a river sediment budget after historical gravel mining (the lower Tordera, NE Spain),” River Research and Applications, Vol.21, No.7, pp. 829-847, 2005.
  40. [40] S. R. Mead and C. R. Magill, “Probabilistic hazard modelling of rain-triggered lahars,” J. of Applied Volcanology, Vol.6, No.1, Article: 8, 2017.
  41. [41] T. M. Over, E. A. Murphy, T. W. Ortel, A. and L. Ishii, “Comparisons between NEXRAD Radar and Tipping-Bucket Gage Rainfall Data: A Case Study for DuPage County, Illinois,” Proc. of World Environmental and Water Resources Congress, pp. 1-14, 2007.
  42. [42] J. V. Umbal and K. S. Rodolfo, “The 1991 Lahars of Southwestern Mount Pinatubo and evolution of the lahar-dammed Mapanuepe Lake,” Fire and Mud: Eruptions and Lahars of Mount Pinatubo, Philippines, USGS Publication, pp. 1-31, 1996.
  43. [43] G. Crosta and P. Frattini, “Rainfall thresholds for triggering soil slips and debris flow,” Proc. of the 2nd EGS Plinius Conf. on Mediterranean Storms, pp. 463-487, 2001.
  44. [44] M. Jakob, T. Owen, and T. Simpson, “A regional real-time debris-flow warning system for the District of North Vancouver, Canada,” Landslides, Vol.9, No.2, pp. 165-178, 2012.
  45. [45] X. Yao and L. Li, “Spatial-Temporal Assessment of Debris Flow Risk in the Ms8.0 Wenchuan Earthquake-Disturbed Area,” J. Disaster Res., Vol.11, No.4, pp. 720-731, 2016.
  46. [46] T. M. Hamill, C. Snyder, and R. E. Morss, “A Comparison of probabilistic forecasts from bred, singular-vector, and perturbed observation ensembles,” Monthly Weather Review, Vol.128, No.6, pp. 1835-1851, 2000.
  47. [47] S. Kim, Y. Tachikawa, and K. Takara, “Flood Forecasting System Using Weather Radar and a Distributed Hydrologic Model,” Annuals of Disas. Prev. Res. Inst., Kyoto Univ., No.49 B, pp. 55-65, 2006.
  48. [48] D. Rezacova and Z. Sokol, “Radar verification approach to the QPF for local flash flood storms,” Proc. of the European Conf. on Radar in Meteorology and Hydrology 2004, pp. 193-196, 2004.
  49. [49] National Research Council, “Assessment of Hydrologic and Hydrometeorological Operations and Services,” The National Academies Press, 1996.
  50. [50] R. Buizza and T. N. Palmer, “Impact of Ensemble Size on Ensemble Prediction,” Monthly Weater Review, Vol.126, No.9, pp. 2503-2518, 1998.
  51. [51] L. Stefanova and T. N. Krishnamurti, “Interpretation of Seasonal Climate Forecast Using Brier Skill Score, The Florida State University Superensemble, and the AMIP-I Dataset,” J. of Climate, Vol.15, No.5, pp. 537-544, 2002.
  52. [52] P. Novák, L. Březková, and P. Frolík, “Quantitative Precipitation Forecast Using Radar Echo Extrapolation,” Atmospheric Research, Vol.93, No.1-3, pp. 328-334, 2009.
  53. [53] R. E. Kalman, “A New Approach to Linear Filtering and Prediction Problems,” Trans. of the ASME-J. of Basic Engineering, Vol.82, Series D, pp. 35-45, 1960.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on May. 19, 2024