Rainfall Information System Based on Weather Radar for Debris Flow Disaster Mitigation

  • Authors

    • Ratih Indri Hapsari
    • Gerard Aponno
    • Rosa Andrie Asmara
    • Satoru Oishi
    2018-12-01
    https://doi.org/10.14419/ijet.v7i4.44.26976
  • Rainfall, Debris flow, Weather radar, Disaster, WebGIS.
  • Abstract

    Rainfall-triggered debris flow has caused multiple impacts to the environment. It. is regarded as the most severe secondary hazards of volcanic eruption. However, limited access to the active volcano slope restricts the ground rain measurement as well as the direct delivery of risk information. In this study, an integrated information system is proposed for volcanic-related disaster mitigation under the framework of X-Plore/X-band Polarimetric Radar for Prevention of Water Disaster. In the first part, the acquisition and processing of high-resolution X-band dual polarimetric weather/X-MP radar data in real-time scheme for demonstrating the disaster-prone region are described. The second part presents the design of rainfall resource database and extensive maps coverage of predicted hazard information in GIS web-based platform accessible both using internet and offline. The proposed platform would be useful for communicating the disaster risk prediction based on weather radar in operational setting.

     

     

  • References

    1. [1] Bradley DT, McFarland M & Clarke M (2014), The Effectiveness of Disaster Risk Communication: A Systematic Review of Intervention Studies. PLoS Curr 22(6).

      [2] Chen CV & Yu FC (2011), Morphometric analysis of debris flows and their source areas using GIS. Geomorphology 129, 387-397.

      [3] Di BF, Chen NS, Cui P, Li ZL, He YP & Gao YC (2008), GIS-based risk analysis of debris flow: an application in Sichuan, southwest China. International Journal of Sediment Research 23(2), 138-148.

      [4] Galgani G, Scozza G, Bolt RJ, Haider N (2017), Design and testing of a polarimetric X-band antenna for avionic weather radar. Proceeding of European Microwave Conference, 1167-1170.

      [5] Gill J (2008) Guideline on Communicating Forecast Uncertainty. World Meteorological Organization.

      [6] Gunes AE & Kovel JP (2000) Using GIS in Emergency Management Operations, Journal of Urban Planning and Development 126(3), 221–229.

      [7] Islam MM. & Sado K. (2000), Development of flood hazard map of Bangladesh using NOAA-AVHRR images with GIS. Hydrological Sciences 453(3), 337-401.

      [8] Jan M, Sokol Z, & Jana M (2018), Limits of precipitation nowcasting by extrapolation of radar reflectivity for warm season in Central Europe. Nat. Hazards Earth Syst. Sci. 18, 1395-1409.

      [9] Jeong C, Joo K, Lee W, Shin H, & Heo JH (2014). Estimation of optimal grid size for radar reflectivity using a SWAT model. Journal of Hydro-Environment Research 8(1), 20–31.

      [10] Kato A & Maki M (2009), Localized Heavy Rainfall Near Zoshigaya, Tokyo, Japan on 5 August 2008 Observed by X-band Polarimetric Radar: Preliminary Analysis. SOLA (2009), 89-92.

      [11] Mananoma T & Wardoyo W (2009) The influence of rainfall characteristics change on sediment migration pattern after Merapi eruption 2006. Proceeding of International Seminar on Climate Change Impacts on Water Resources and Coastal Management in Developing Countries, 1-10.

      [12] Maki M, Park SG & Bringi VN (2005), Effect of natural variations in rain drop size distributions on rain rate estimators of 3 cm wavelength polarimetric radar. Journal of the Meteorological Society of Japan 83(5), 871-893.

      [13] Mejsnar J, Sokol Z & Minarova J (2018) Limits of precipitation nowcasting by extrapolation of radar reflectivity for warm season in Central Europe. Atmospheric Research 213, 288-301.

      [14] Neary DG & Swift Jr LW (1987) Rainfall thresholds for triggering a debris avalanching event in the southern Appalachian Mountains, In: Costa, J.E., Wieczorek GF (ed) Debris flow, avalanches: process, recognition, and mitigation, GeolSoc Am Rev Engineering Geology (7), 81-92.

      [15] Neto ADL, Paz I, Borgez EC, Ichiba A, Tchiguirinskaia I & Schertzer D (2018), Hydrological responses to small scale rainfall variability over a semi-urban catchment using Multi-Hydro model: C-band vs. X-band radar data. Geophysical Research 20.

      [16] Palau RM, Berenguer M, Hürlimann M & Torres DS (2018), A prototype regional early warning system for shallow landslides and debris flows. Geophysical Research 20.

      [17] Pan HL, Jiang YJ. Wang J. & Ou GQ (2018), Rainfall threshold calculation for debris flow early warning in areas with scarcity of data, Nat. Hazards Earth Syst. Sci., 18, 1395-1409.

      [18] Park SG, Bringi VN, Chandrasekar V, Maki M & Iwanami K (2005a) Correction of Radar Reflectivity and Differential Reflectivity for Rain Attenuation at X Band: Part I: Theoretical and Empirical Basis. Journal of Atmospheric and Oceanic Technology (22) 1621-1631.

      [19] Park SG., Maki M, Iwanami K, Bringi VN & Chandrasekar V (2005b) Correction of radar reflectivity and differential reflectivity for rain attenuation at X Band: Part II: Evaluation and application. Journal of Atmospheric and Oceanic Technology (22) 1633-1655.

      [20] Reyniers M (2008), Quantitative precipitation forecasts based on radar observations. Royal Meteorological Institute of Belgium.

      [21] Ryzhkov AV, Schuur TJ, Burgess DW & Heinselman PL (2005), The joint polarization experiment. Bulletin of the American Meteorological Society 86(I.6), 809-825.

      [22] Scharfenberg KA, Miller DJ, Schuur TJ & Schlatter PT (2005) The joint polarization experiment: Polarimetric radar in forecasting and warning decision making. Weather and Forecasting 20(5), 775-788.

      [23] Shiiba M, Takasao T, Nakakita E (1984) Investigation of short-term rainfall prediction method by a translation model, Proceeding of Japan Conference on Hydraulic Engineering (28) 423-428.

      [24] Tran P, Shaw R, Chantry G & Norton J. (2009), GIS and local knowledge in disaster management: a case study of flood risk mapping in Viet Nam. Disasters 33(1), 152-169.

      [25] Ville NDL, Diaz AC & Ramirez D (2002,) Remote Sensing and GIS Technologies as Tools to Support Sustainable Management of Areas Devastated by Landslides. Geomorphology 129(3–4), 387-397.

      [26] Wang Y & Chandrasekar V (2018), Quantitative precipitation estimation in the CASA X-band dual-polarization radar network. Atmospheric Research 213, 288-301.

      [27] Westen JV & Daag AS (2005), Analysing the relation between rainfall characteristics and lahar activity at Mount Pinatubo, Philippines. Earth Surf. Process. Landforms, 30.

      [28] Wong KW (2003) Development of Meteorological Information System Using Geographic Information System Technology, Hong Kong Observatory.

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  • How to Cite

    Indri Hapsari, R., Aponno, G., Andrie Asmara, R., & Oishi, S. (2018). Rainfall Information System Based on Weather Radar for Debris Flow Disaster Mitigation. International Journal of Engineering & Technology, 7(4.44), 165-171. https://doi.org/10.14419/ijet.v7i4.44.26976

    Received date: 2019-02-02

    Accepted date: 2019-02-02

    Published date: 2018-12-01