Physical Flood Vulnerability Mapping Applying Geospatial Techniques in Okazaki City, Aichi Prefecture, Japan

Flooding has been increasing since 2004 in Japan due to localized heavy rainfall and geographical conditions. Determining areas vulnerable to flooding as one element of flood hazard maps related to disaster management for urban development is necessary. This research integrated Remote Sensing data, the Geography Information System (GIS) method and Analytical Hierarchy Process (AHP) calculation to determine the physical flood-vulnerable area in Okazaki City. We developed this research by applying data from the Geospatial Information Authority of Japan (GSI) to generate the slope map and drainage density; AMEDAS (Automated Meteorological Data Acquisition System) from the Japan Meteorological Agency (JMA) to generate the rainfall data; Soil map from the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) data; and Sentinel-2 imagery to generate the land cover map. We applied the AHP calculation for weighting pairwise the parameters by comparing five iterations of the normalized matrix. We utilized the spatial analysis tool in ArcGIS to run the pairwise comparison to adjudicate the distribution of flooding according to the AHP procedure. The percentage of relative weight was slope (43%), drainage density (20%), rainfall intensity (17%), then both infiltration rate and land cover (10%). The consistency value was reasonable: consistency index (CI—0.007) and consistency ratio (CR—0.6%). We generated high accuracy for flood vulnerability prediction; 0.88 for Probability of Detection (POD), 0.28 for Probability of False Detection (POFD), 0.44 for Critical Success Index (CSI), 1.9 for Bias, and 95 of Area under Curve (AUC). The flood vulnerability was matched to the flood inundation survey of Okazaki City in August 2008 and indicated an excellent Relative Operating Characteristic (ROC).

[1]  川口 桂三郎,et al.  Major Soils of Southeast Asia and the Classification of Soils under Rice Cultivation: Paddy Soils , 1966 .

[2]  Thomas L. Saaty,et al.  DECISION MAKING WITH THE ANALYTIC HIERARCHY PROCESS , 2008 .

[3]  M. Ercanoglu,et al.  A new approach to use AHP in landslide susceptibility mapping: a case study at Yenice (Karabuk, NW Turkey) , 2012, Natural Hazards.

[4]  A. F. Marj,et al.  Drought vulnerability mapping using AHP method in arid and semiarid areas: a case study for Taft Township, Yazd Province, Iran , 2016, Environmental Earth Sciences.

[5]  E. Volpi,et al.  A new approach to account for the spatial variability of drainage density in rainfall-runoff modelling , 2014 .

[6]  A. Leahey,et al.  The Canadian System of Soil Classification and the Seventh Approximation1 , 1963 .

[7]  A. I. Johnson,et al.  A field method for measurement of infiltration , 1963 .

[8]  Kazunori Kohyama,et al.  Outline of the Comprehensive Soil Classification System of Japan ? First Approximation , 2012 .

[9]  Biswajeet Pradhan,et al.  Suitability estimation for urban development using multi-hazard assessment map. , 2017, The Science of the total environment.

[10]  R. Shakesby,et al.  Soil water repellency: its causes, characteristics and hydro-geomorphological significance , 2000 .

[12]  Fusanori Miura,et al.  Integration of Spatial Analysis for Tsunami Inundation and Impact Assessment , 2014 .

[13]  Eric Tate,et al.  Social vulnerability to floods: Review of case studies and implications for measurement , 2015 .

[14]  URBAN SOCIAL VULNERABILITY ASSESSMENT USING OBJECT-ORIENTED ANALYSIS OF REMOTE SENSING AND GIS DATA . A CASE STUDY FOR TEGUCIGALPA , HONDURAS , 2008 .

[15]  Mazlan Hashim,et al.  Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment , 2015, Scientific Reports.

[16]  Xuan Zhu,et al.  Evaluation of Model Validation Techniques in Land Cover Dynamics , 2013, ISPRS Int. J. Geo Inf..

[17]  Robert L. Wilby,et al.  Adapting to flood risk under climate change , 2012 .

[18]  Y. Ariki,et al.  Estimation of Tsunami Hazard Vulnerability Factors by Integrating Remote Sensing, GIS and AHP Based Assessment , 2016 .

[19]  Y. Amano.  Classification of Cultivated Soils in Japan , 1985 .

[20]  Benjamin M. Sleeter,et al.  Role of remote sensing for land-use and land-cover change modeling , 2012 .

[21]  J. Maršálek,et al.  Flood Risk Management: Hazards, Vulnerability and Mitigation Measures , 2006 .

[22]  R. Horton.  EROSIONAL DEVELOPMENT OF STREAMS AND THEIR DRAINAGE BASINS; HYDROPHYSICAL APPROACH TO QUANTITATIVE MORPHOLOGY , 1945 .

[23]  Bohn Stafleu van Loghum,et al.  Online … , 2002, LOG IN.

[24]  M. Tejedor,et al.  Soil Properties Controlling Infiltration in Volcanic Soils (Tenerife, Spain) , 2013 .

[25]  F. Miura,et al.  Evaluation of GSMaP Daily Rainfall Satellite Data for Flood Monitoring: Case Study—Kyushu Japan , 2016 .

[26]  Harold E. Brooks,et al.  TORNADO-WARNING PERFORMANCE IN THE PAST AND FUTURE A Perspective from Signal Detection Theory A Perspective from Signal Detection Theory A Perspective from Signal Detection Theory A Perspective from Signal Detection Theory A Perspective from Signal Detection Theory , 2004 .

[27]  J. Larsen,et al.  Forestry between land use intensification and sustainable development: Improving landscape functions with forests and trees , 2009 .

[28]  E. A. Baltas,et al.  Urban flood hazard assessment in the basin of Athens Metropolitan city, Greece , 2016, Environmental Earth Sciences.

[29]  Rafael L. Bras,et al.  On the sensitivity of drainage density to climate change , 1998 .

[30]  Desmond E. Walling,et al.  THE VARIATION OF DRAINAGE DENSITY WITHIN A CATCHMENT , 1968 .

[31]  T. L. Saaty.  A Scaling Method for Priorities in Hierarchical Structures , 1977 .

[32]  Y. Ouma,et al.  Urban Flood Vulnerability and Risk Mapping Using Integrated Multi-Parametric AHP and GIS: Methodological Overview and Case Study Assessment , 2014 .

[33]  R. W. Saaty,et al.  The analytic hierarchy process—what it is and how it is used , 1987 .

[34]  Georgios Aim. Skianis,et al.  Assessment of rural community and agricultural development using geomorphological–geological factors and GIS in the Trikala prefecture (Central Greece) , 2013, Stochastic Environmental Research and Risk Assessment.

[35]  N. Kazakis,et al.  Assessment of flood hazard areas at a regional scale using an index-based approach and Analytical Hierarchy Process: Application in Rhodope-Evros region, Greece. , 2015, The Science of the total environment.

[36]  R. Ghazavi,et al.  Impact of Flood Spreading on Infiltration Rate and Soil Properties in an Arid Environment , 2010 .

[37]  P. Kayastha,et al.  Application of the analytical hierarchy process (AHP) for landslide susceptibility mapping: A case study from the Tinau watershed, west Nepal , 2013, Comput. Geosci..

[38]  Attilio Castellarin,et al.  A look at the links between drainage density and flood statistics , 2008 .

[39]  B. Ahmed.  Landslide susceptibility mapping using multi-criteria evaluation techniques in Chittagong Metropolitan Area, Bangladesh , 2015, Landslides.

[40]  Susan L. Ustin,et al.  Population I: , 2020, Biodemography.

[41]  S. Kazama,et al.  Evaluating the cost of flood damage based on changes in extreme rainfall in Japan , 2009 .

[42]  Bayes Ahmed,et al.  Modeling Urban Land Cover Growth Dynamics Using Multi-Temporal Satellite Images: A Case Study of Dhaka, Bangladesh , 2012, ISPRS Int. J. Geo Inf..

[43]  F. Miura,et al.  Remote sensing and spatial multi-criteria analysis for tsunami vulnerability assessment , 2014 .

[44]  Joong‐Bae Ahn,et al.  Changes of early summer precipitation in the Korean Peninsula and nearby regions based on RCP simulations , 2015 .

[45]  Günter Blöschl,et al.  Flood frequency hydrology: 2. Combining data evidence , 2008 .

[46]  Kalliopi Gaki-Papanastassiou,et al.  Potential suitability for urban planning and industry development using natural hazard maps and geological–geomorphological parameters , 2012, Environmental Earth Sciences.

[47]  Bayes Ahmed,et al.  Landslide susceptibility modelling applying user-defined weighting and data-driven statistical techniques in Cox’s Bazar Municipality, Bangladesh , 2015, Natural Hazards.

[48]  J. Janeau,et al.  Rainfall/runoff processes in a small peri‐urban catchment in the Andes mountains. The Rumihurcu Quebrada, Quito (Ecuador) , 2001 .

[49]  Kevin E. Trenberth,et al.  The Impact of Climate Change and Variability on Heavy Precipitation, Floods, and Droughts , 2008 .

[50]  D. Rozos,et al.  Comparison of the implementation of rock engineering system and analytic hierarchy process methods, upon landslide susceptibility mapping, using GIS: a case study from the Eastern Achaia County of Peloponnesus, Greece , 2011 .

[51]  Evaluation of European Storm Forecast Experiment (ESTOFEX) forecasts , 2011 .

[52]  Proceso L. Fernandez,et al.  Analytic Hierarchy Process (AHP) in Spatial Modeling for Floodplain Risk Assessment , 2014 .

[53]  Victor R. Baker,et al.  A high magnitude storm and flood in a hyperarid catchment, Nahal Zin, Negev Desert, Israel , 1998 .

[54]  V. Jothiprakash,et al.  Impacts of land use–land cover change and urbanization on flooding: A case study of Oshiwara River Basin in Mumbai, India , 2016 .

[55]  Jing Ran,et al.  Integrating spatial planning and flood risk management: A new conceptual framework for the spatially integrated policy infrastructure , 2016, Comput. Environ. Urban Syst..

[56]  Chris Zevenbergen,et al.  Learning and Action Alliances for the integration of flood risk management into urban planning: a new framework from empirical evidence from The Netherlands , 2011 .

[57]  Bob Glahn,et al.  Tornado-Warning Performance in the Past and Future—Another Perspective , 2005 .

[58]  Erich J. Plate,et al.  Flood risk and flood management , 2002 .

[59]  Fred L. Ogden,et al.  Relative importance of impervious area, drainage density, width function, and subsurface storm drainage on flood runoff from an urbanized catchment , 2011 .

[60]  Louise J. Bracken,et al.  The relationship between rainfall inputs and flood generation in south–east Spain , 2008 .

[61]  James R. Anderson,et al.  A land use and land cover classification system for use with remote sensor data , 1976 .