Skip to main content
Erschienen in: Environmental Earth Sciences 6/2016

01.03.2016 | Original Article

Flood hazard mapping in Jamaica using principal component analysis and logistic regression

verfasst von: Arpita Nandi, Arpita Mandal, Matthew Wilson, David Smith

Erschienen in: Environmental Earth Sciences | Ausgabe 6/2016

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Jamaica, the third largest island in the Caribbean, has been affected significantly by flooding and flood-related damage. Hence assessing the probability of flooding and susceptibility of a place to flood hazard has become a vital part of planning and development. In addition to heavy rainfall from tropical storms and Atlantic hurricanes, several terrestrial factors play significant roles in flooding, including local geology, geomorphology, hydrology and land-use. In this study, a GIS-based multi-criteria statistical methodology was developed to quantify hazard potential and to map flood characteristics. Fourteen factors potentially responsible for flooding were identified and used as initial input in a hybrid model that combined principal component analysis with logistic regression and frequency distribution analysis. Of these factors, seven explained 65 % of the variation in the data: elevation, slope angle, slope aspect, flow accumulation, a topographic wetness index, proximity to a stream network, and hydro-stratigraphic units. These were used to prepare the island’s first map of flood hazard potential. Hazard potential was classified from very low to very high, nearly one-fifth (19.4 %) of the island was included within high or very high flood hazard zones. Further analysis revealed that areas prone to flooding are often low-lying and flat, or have shallow north- or northwest-facing slopes, are in close proximity to the stream network, and are situated on underlying impermeable lithology. The multi-criteria hybrid approach developed could classify 86.8 % of flood events correctly and produced a satisfactory validation result based on the receiver operating characteristic curve. The statistical method can be easily repeated and refined upon the availability of additional or higher quality data such as a high resolution digital elevation model. Additionally, the approach used in this study can be adopted to evaluate flood hazard in countries with similar characteristics, landscapes and climatic conditions, such as other Caribbean or Pacific Small Island Developing States.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Literatur
Zurück zum Zitat Abdul-Wahab S, Bakheit C, Al-Alawi S (2005) Principal component and multiple regression analysis in modelling of ground-level ozone and factors affecting its concentrations. Environ Model Softw 20(10):1263–1271CrossRef Abdul-Wahab S, Bakheit C, Al-Alawi S (2005) Principal component and multiple regression analysis in modelling of ground-level ozone and factors affecting its concentrations. Environ Model Softw 20(10):1263–1271CrossRef
Zurück zum Zitat Altman D (1991) Categorizing continuous covariates (letter to the editor). Br J Cancer 64:975CrossRef Altman D (1991) Categorizing continuous covariates (letter to the editor). Br J Cancer 64:975CrossRef
Zurück zum Zitat Altman D, Lausen B, Sauerbrei W, Schumacher M (1994) Dangers of using ‘optimal’ cutpoints in the evaluation of prognostic factors. J Nat Cancer Inst 86:829–835CrossRef Altman D, Lausen B, Sauerbrei W, Schumacher M (1994) Dangers of using ‘optimal’ cutpoints in the evaluation of prognostic factors. J Nat Cancer Inst 86:829–835CrossRef
Zurück zum Zitat Bates PD, Wilson MD, Horritt MS, Mason D, Holden N, Currie C (2006) Reach scale floodplain inundation dynamics observed using airborne Synthetic Aperture Radar imagery: data analysis and modelling. J Hydrol 328:306–318CrossRef Bates PD, Wilson MD, Horritt MS, Mason D, Holden N, Currie C (2006) Reach scale floodplain inundation dynamics observed using airborne Synthetic Aperture Radar imagery: data analysis and modelling. J Hydrol 328:306–318CrossRef
Zurück zum Zitat Bathrellos GD, Kalivas DP, Skilodimou HD (2009) GIS-based landslide susceptibility mapping models applied to natural and urban planning in Trikala Central Greece. Estud Geol Madr 65(1):49–65CrossRef Bathrellos GD, Kalivas DP, Skilodimou HD (2009) GIS-based landslide susceptibility mapping models applied to natural and urban planning in Trikala Central Greece. Estud Geol Madr 65(1):49–65CrossRef
Zurück zum Zitat Bathrellos GD, Gaki-Papanastassiou K, Skilodimou HD, Papanastassiou D, Chousianitis KG (2012) Potential suitability for urban planning and industry development by using natural hazard maps and geological—geomorphological parameters. Environ Earth Sci 66(2):537–548CrossRef Bathrellos GD, Gaki-Papanastassiou K, Skilodimou HD, Papanastassiou D, Chousianitis KG (2012) Potential suitability for urban planning and industry development by using natural hazard maps and geological—geomorphological parameters. Environ Earth Sci 66(2):537–548CrossRef
Zurück zum Zitat Bathrellos GD, Gaki-Papanastassiou K, Skilodimou HD, Skianis GA, Chousianitis KG (2013) Assessment of rural community and agricultural development using geomorphological-geological factors and GIS in the Trikala prefecture (Central Greece). Stoch Environ Res Risk Assess 27(2):573–588CrossRef Bathrellos GD, Gaki-Papanastassiou K, Skilodimou HD, Skianis GA, Chousianitis KG (2013) Assessment of rural community and agricultural development using geomorphological-geological factors and GIS in the Trikala prefecture (Central Greece). Stoch Environ Res Risk Assess 27(2):573–588CrossRef
Zurück zum Zitat Beven K, Kirby M (1979) A physically based, variable contributing area model of basin hydrology. Hydrol Sci B 24:43–69 Beven K, Kirby M (1979) A physically based, variable contributing area model of basin hydrology. Hydrol Sci B 24:43–69
Zurück zum Zitat Burgess C, Taylor M, Stephenson T, Mandal A (2013) Extreme precipitation for Jamaica: 1895–2100. International Conference on Flood Resilience: experiences in Asia and Europe. Exeter, United Kingdom: University of Exeter Burgess C, Taylor M, Stephenson T, Mandal A (2013) Extreme precipitation for Jamaica: 1895–2100. International Conference on Flood Resilience: experiences in Asia and Europe. Exeter, United Kingdom: University of Exeter
Zurück zum Zitat Burgess C, Taylor M, Stephenson T, Mandal A, Powell L (2015) A macro scale flood risk for Jamaica with impact of climate variability. Nat Haz 48(1):231–256CrossRef Burgess C, Taylor M, Stephenson T, Mandal A, Powell L (2015) A macro scale flood risk for Jamaica with impact of climate variability. Nat Haz 48(1):231–256CrossRef
Zurück zum Zitat Carby B (2011) Mid-term review of the hyogo framework for action in the caribbean. In: Hutchinson G, Harris D (eds) University of the west indies, in PIOJ, 2012a. A Growth-Inducement Strategy for Jamaica. Planning Institute of Jamaica. Kingston, Jamaica Carby B (2011) Mid-term review of the hyogo framework for action in the caribbean. In: Hutchinson G, Harris D (eds) University of the west indies, in PIOJ, 2012a. A Growth-Inducement Strategy for Jamaica. Planning Institute of Jamaica. Kingston, Jamaica
Zurück zum Zitat Chang H, Franczyk J, Kim C (2009) What is responsible for increasing flood risks? The case of Gangwon Province, Korea. Nat Haz 48(3):339–354CrossRef Chang H, Franczyk J, Kim C (2009) What is responsible for increasing flood risks? The case of Gangwon Province, Korea. Nat Haz 48(3):339–354CrossRef
Zurück zum Zitat Chubey M, Hathout S (2004) Integration of RADARSAT and GIS modeling for estimating Red River flood risk. GeoJour 59:237–246CrossRef Chubey M, Hathout S (2004) Integration of RADARSAT and GIS modeling for estimating Red River flood risk. GeoJour 59:237–246CrossRef
Zurück zum Zitat Chung C, Fabbri A (2003) Validation of spatial prediction models for landslide hazard mapping. Nat Haz 30:451–472CrossRef Chung C, Fabbri A (2003) Validation of spatial prediction models for landslide hazard mapping. Nat Haz 30:451–472CrossRef
Zurück zum Zitat Collymore J (2007) Disaster management in the Caribbean: perspectives on institutional capacity reform and development. Environ Haz 10(1):6–22CrossRef Collymore J (2007) Disaster management in the Caribbean: perspectives on institutional capacity reform and development. Environ Haz 10(1):6–22CrossRef
Zurück zum Zitat Collymore J (2011) Disaster management in the Caribbean: perspectives on institutional capacity reform and development. Environ Haz 10(1):6–22CrossRef Collymore J (2011) Disaster management in the Caribbean: perspectives on institutional capacity reform and development. Environ Haz 10(1):6–22CrossRef
Zurück zum Zitat CRIES (Comprehensive Resources Inventory and Evaluation Systems) (1985) Jamaica Resource Assessment, Comprehensive Resource Inventory and Evaluation System Project, Michigan State University, U.S. Department of Agriculture/Soil Conservation Service, Ohio State University, U.S.A. p 230 CRIES (Comprehensive Resources Inventory and Evaluation Systems) (1985) Jamaica Resource Assessment, Comprehensive Resource Inventory and Evaluation System Project, Michigan State University, U.S. Department of Agriculture/Soil Conservation Service, Ohio State University, U.S.A. p 230
Zurück zum Zitat Dai F, Lee C, Li J, Xu Z (2001) Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong Kong. Environ Geol 40:381–391CrossRef Dai F, Lee C, Li J, Xu Z (2001) Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong Kong. Environ Geol 40:381–391CrossRef
Zurück zum Zitat Dixon B (2005) Applicability of neuro-fuzzy techniques in predicting ground-water vulnerability: a GIS-based sensitivity analysis. J Hydrol 309:37–38CrossRef Dixon B (2005) Applicability of neuro-fuzzy techniques in predicting ground-water vulnerability: a GIS-based sensitivity analysis. J Hydrol 309:37–38CrossRef
Zurück zum Zitat ECLAC (2001) Jamaica: assessment of the damage caused by flood rains and landslides in association with hurricane Michelle, October 2001. Implications for economic, social and environmental development. p 46 ECLAC (2001) Jamaica: assessment of the damage caused by flood rains and landslides in association with hurricane Michelle, October 2001. Implications for economic, social and environmental development. p 46
Zurück zum Zitat Fekete A (2009) Validation of a social vulnerability index in context to river-floods in Germany. Nat Haz Earth Syst Sci 9:393–403CrossRef Fekete A (2009) Validation of a social vulnerability index in context to river-floods in Germany. Nat Haz Earth Syst Sci 9:393–403CrossRef
Zurück zum Zitat Ghalkhani H, Golian S, Saghafian B, Farokhnia A, Shamseldin A (2013) Application of surrogate artificial intelligent models for real-time flood routing. Water Environ J 27:535–548CrossRef Ghalkhani H, Golian S, Saghafian B, Farokhnia A, Shamseldin A (2013) Application of surrogate artificial intelligent models for real-time flood routing. Water Environ J 27:535–548CrossRef
Zurück zum Zitat Grabs T, Seibert J, Bishop K, Laudon H (2009) Modeling spatial patterns of saturated areas: a comparison of the topographic wetness index and a dynamic distributed model. J Hydro 373:15–23CrossRef Grabs T, Seibert J, Bishop K, Laudon H (2009) Modeling spatial patterns of saturated areas: a comparison of the topographic wetness index and a dynamic distributed model. J Hydro 373:15–23CrossRef
Zurück zum Zitat Guha-Sapir D, Below R, Hoyois PH (2010) EM-DAT: international disaster database. Université Catholique de Louvain, Brussels Guha-Sapir D, Below R, Hoyois PH (2010) EM-DAT: international disaster database. Université Catholique de Louvain, Brussels
Zurück zum Zitat Hilsenbeck S, Clark G (1996) Practical p-value adjustment for optimally selected cutpoints. Stat Med 15:103–112CrossRef Hilsenbeck S, Clark G (1996) Practical p-value adjustment for optimally selected cutpoints. Stat Med 15:103–112CrossRef
Zurück zum Zitat Hosmer D, Lemeshow S (2000) Applied logistic regression. Wiley, New York, p 383CrossRef Hosmer D, Lemeshow S (2000) Applied logistic regression. Wiley, New York, p 383CrossRef
Zurück zum Zitat Hsu K, Gupta HV, Gao X, Sorooshian S, Imam B (2002) Self-organizing linear output map (SOLO): an artificial neural network suitable for hydrologic modeling and analysis. Water Res Res 38(1):17–38 Hsu K, Gupta HV, Gao X, Sorooshian S, Imam B (2002) Self-organizing linear output map (SOLO): an artificial neural network suitable for hydrologic modeling and analysis. Water Res Res 38(1):17–38
Zurück zum Zitat Hu T, Lam K, Ng S (2001) River flow time series prediction with a range dependent neural network. Hydro Sci J 46(5):729–745CrossRef Hu T, Lam K, Ng S (2001) River flow time series prediction with a range dependent neural network. Hydro Sci J 46(5):729–745CrossRef
Zurück zum Zitat Hunter NM, Bates PD, Horritt MS, Wilson MD (2007) Simple spatially-distributed models for predicting flood inundation: a review. Geomorph 90(3–4):208–225CrossRef Hunter NM, Bates PD, Horritt MS, Wilson MD (2007) Simple spatially-distributed models for predicting flood inundation: a review. Geomorph 90(3–4):208–225CrossRef
Zurück zum Zitat Imric C, Durucan S, Korre A (2000) River flow prediction using artificial neural networks: generalisation beyond the calibration range. Hydrol 233:138–153CrossRef Imric C, Durucan S, Korre A (2000) River flow prediction using artificial neural networks: generalisation beyond the calibration range. Hydrol 233:138–153CrossRef
Zurück zum Zitat Jourde H, Lafare A, Mazzilli N, Belaud G, Neppel L, Dörfliger N, Cernesson F (2014) Flash flood mitigation as a positive consequence of anthropogenic forcing on the groundwater resource in a karst catchment. Environ Earth Sci 71(2):573–583CrossRef Jourde H, Lafare A, Mazzilli N, Belaud G, Neppel L, Dörfliger N, Cernesson F (2014) Flash flood mitigation as a positive consequence of anthropogenic forcing on the groundwater resource in a karst catchment. Environ Earth Sci 71(2):573–583CrossRef
Zurück zum Zitat Keating A, Campbell K, Mechler R, Michel‐Kerjan E, Mochizuki J, Kunreuther H, Bayer J, Hanger S, McCallum I, See L, Williges K, Atreya A, Botzen W, Collier B, Czajkowski J, Hochrainer S, Egan C (2014) Operationalizing resilience against natural disaster risk: opportunities, barriers and a way forward, Zurich Flood Resilience Alliance Keating A, Campbell K, Mechler R, Michel‐Kerjan E, Mochizuki J, Kunreuther H, Bayer J, Hanger S, McCallum I, See L, Williges K, Atreya A, Botzen W, Collier B, Czajkowski J, Hochrainer S, Egan C (2014) Operationalizing resilience against natural disaster risk: opportunities, barriers and a way forward, Zurich Flood Resilience Alliance
Zurück zum Zitat Kendall M (1957) A course in multivariate analysis. Griffin, London, p 185 Kendall M (1957) A course in multivariate analysis. Griffin, London, p 185
Zurück zum Zitat Kia MB, Pirasteh S, Pradhan B, Mahmud AR, Sulaiman WNA, Moradi A (2012) An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia. Environ Earth Sci 67:251–264CrossRef Kia MB, Pirasteh S, Pradhan B, Mahmud AR, Sulaiman WNA, Moradi A (2012) An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia. Environ Earth Sci 67:251–264CrossRef
Zurück zum Zitat Kim G, Barros A (2001) Quantitative flood forecasting using multisensor data and neural networks. J Hydrol 246(1–4):45–62CrossRef Kim G, Barros A (2001) Quantitative flood forecasting using multisensor data and neural networks. J Hydrol 246(1–4):45–62CrossRef
Zurück zum Zitat Kleinbaum DG, Klein M (2002) Modeling strategy for assessing interaction and confounding. In: Kleinbaum DG, Klein M (eds) Logistic regression: a self-learning text. Springer, New York Kleinbaum DG, Klein M (2002) Modeling strategy for assessing interaction and confounding. In: Kleinbaum DG, Klein M (eds) Logistic regression: a self-learning text. Springer, New York
Zurück zum Zitat Knebl M, Yang Z, Hutchison K, Maidment D (2005) Regional scale flood modeling using NEXRAD rainfall, GIS and HEC-HMS/RAS: a case study for the San Antonio river basin summer 2002 storm event. J Environ Manage 75:325–336CrossRef Knebl M, Yang Z, Hutchison K, Maidment D (2005) Regional scale flood modeling using NEXRAD rainfall, GIS and HEC-HMS/RAS: a case study for the San Antonio river basin summer 2002 storm event. J Environ Manage 75:325–336CrossRef
Zurück zum Zitat Lam K, Tau T, Lam MCK (2010) A Material supplier selection model for property developers using fuzzy principal component analysis. Auto Const 19:608–618CrossRef Lam K, Tau T, Lam MCK (2010) A Material supplier selection model for property developers using fuzzy principal component analysis. Auto Const 19:608–618CrossRef
Zurück zum Zitat Langhammer J (2010) Analysis of the relationship between the stream regulations and the geomorphologic effects of floods. Nat Haz 54(1):121–139CrossRef Langhammer J (2010) Analysis of the relationship between the stream regulations and the geomorphologic effects of floods. Nat Haz 54(1):121–139CrossRef
Zurück zum Zitat Lee S (2005) Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data. Int J Rem Sens 26(7):477–1491CrossRef Lee S (2005) Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data. Int J Rem Sens 26(7):477–1491CrossRef
Zurück zum Zitat Lee S, Sambath T (2006) Landslide susceptibility mapping in the Damrei Romel area, Cambodia using frequency ratio and logistic regression models. Environ Geol 50:847–855CrossRef Lee S, Sambath T (2006) Landslide susceptibility mapping in the Damrei Romel area, Cambodia using frequency ratio and logistic regression models. Environ Geol 50:847–855CrossRef
Zurück zum Zitat Lee S, Song KY, Kim Y, Park I (2012) Regional groundwater productivity potential mapping using a geographic information system (GIS) based artificial neural network model. Hydrogeol J 20(8):1511–1527CrossRef Lee S, Song KY, Kim Y, Park I (2012) Regional groundwater productivity potential mapping using a geographic information system (GIS) based artificial neural network model. Hydrogeol J 20(8):1511–1527CrossRef
Zurück zum Zitat Liu Y, De Smedt F (2005) Flood modeling for complex terrain using GIS and remote sensed information. Water Res Manage 19(5):605–624CrossRef Liu Y, De Smedt F (2005) Flood modeling for complex terrain using GIS and remote sensed information. Water Res Manage 19(5):605–624CrossRef
Zurück zum Zitat Lulseged A, Hiromitsu Y, Norimitsu U (2004) Landslide susceptibility mapping using GIS-based weighted linear combination—the case in Tsugawa area of Agano River, Niigata Prefecture, Japan. Landslides 1:73–81CrossRef Lulseged A, Hiromitsu Y, Norimitsu U (2004) Landslide susceptibility mapping using GIS-based weighted linear combination—the case in Tsugawa area of Agano River, Niigata Prefecture, Japan. Landslides 1:73–81CrossRef
Zurück zum Zitat Mahyat S, Tehrany, Moung-Jin L, Pradhan B, Mustafa NJ, Lee S (2014) Flood susceptibility mapping using integrated bivariate and multivariate statistical models. Environ Earth Sci 72(10):4001–4015CrossRef Mahyat S, Tehrany, Moung-Jin L, Pradhan B, Mustafa NJ, Lee S (2014) Flood susceptibility mapping using integrated bivariate and multivariate statistical models. Environ Earth Sci 72(10):4001–4015CrossRef
Zurück zum Zitat Mandal A, Maharaj A (2013) Flooding in Jamaica with assessment of riverine inundation of Port Maria, St Mary. Bull de la Soc Geol de Fr 184(1–2):165–170CrossRef Mandal A, Maharaj A (2013) Flooding in Jamaica with assessment of riverine inundation of Port Maria, St Mary. Bull de la Soc Geol de Fr 184(1–2):165–170CrossRef
Zurück zum Zitat Merwade V, Cook A, Coonrod J (2008) GIS techniques for creating river terrain models for hydrodynamic modeling and flood inundation mapping. J Environ Mod Soft 23:1300–1311CrossRef Merwade V, Cook A, Coonrod J (2008) GIS techniques for creating river terrain models for hydrodynamic modeling and flood inundation mapping. J Environ Mod Soft 23:1300–1311CrossRef
Zurück zum Zitat Mukerji A, Chatterjee C, Raghuwanshi N (2009) Flood forecasting using ANN, neuro-fuzzy, and neuro-GA Models. J Hydrol Eng 14(6):647–652CrossRef Mukerji A, Chatterjee C, Raghuwanshi N (2009) Flood forecasting using ANN, neuro-fuzzy, and neuro-GA Models. J Hydrol Eng 14(6):647–652CrossRef
Zurück zum Zitat Nandi A, Shakoor A (2010) A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses. Eng Geol 110:11–20CrossRef Nandi A, Shakoor A (2010) A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses. Eng Geol 110:11–20CrossRef
Zurück zum Zitat Nefeslioglu H, Gokceoglu C, Sonmez H (2008) An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps. Eng Geol 97:171CrossRef Nefeslioglu H, Gokceoglu C, Sonmez H (2008) An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps. Eng Geol 97:171CrossRef
Zurück zum Zitat Noori R, Karbassi AR, Moghaddamnia A, Han D, Zokaei-Ashtiani MH, Farokhnia A, Ghafari Gousheh M (2011) Assessment of input variables determination on the SVM model performance using PCA, Gamma test and forward selection techniques for monthly stream flow prediction. J Hydrol 401:177–189CrossRef Noori R, Karbassi AR, Moghaddamnia A, Han D, Zokaei-Ashtiani MH, Farokhnia A, Ghafari Gousheh M (2011) Assessment of input variables determination on the SVM model performance using PCA, Gamma test and forward selection techniques for monthly stream flow prediction. J Hydrol 401:177–189CrossRef
Zurück zum Zitat Papadopoulou-Vrynioti K, Bathrellos GD, Skilodimou HD, Kaviris G, Makropoulos K (2013) Karst collapse susceptibility mapping using seismic hazard in a rapid urban growing area. Eng Geol 158:77–88CrossRef Papadopoulou-Vrynioti K, Bathrellos GD, Skilodimou HD, Kaviris G, Makropoulos K (2013) Karst collapse susceptibility mapping using seismic hazard in a rapid urban growing area. Eng Geol 158:77–88CrossRef
Zurück zum Zitat Porporato A, Ridolfi L (1997) Nonlinear analysis of river flow time sequences. Water Res Res 33:1353–1367CrossRef Porporato A, Ridolfi L (1997) Nonlinear analysis of river flow time sequences. Water Res Res 33:1353–1367CrossRef
Zurück zum Zitat Pradhan B (2010) Flood susceptible mapping and risk area delineation using logistic regression, GIS and remote sensing. J Spat Hydrol 9:1–18 Pradhan B (2010) Flood susceptible mapping and risk area delineation using logistic regression, GIS and remote sensing. J Spat Hydrol 9:1–18
Zurück zum Zitat Quinn P, Beven K, Lamb R (1995) The ln(a/tanβ) index : how to calculate it a n d how to use it within the topmodel framework. Hydrol Proc 9:161–182CrossRef Quinn P, Beven K, Lamb R (1995) The ln(a/tanβ) index : how to calculate it a n d how to use it within the topmodel framework. Hydrol Proc 9:161–182CrossRef
Zurück zum Zitat Rajurkar M, Kothyari U, Chaube U (2004) Modeling of the daily rainfall runoff relationship with artificial neural network. J Hydrol 285:96–113CrossRef Rajurkar M, Kothyari U, Chaube U (2004) Modeling of the daily rainfall runoff relationship with artificial neural network. J Hydrol 285:96–113CrossRef
Zurück zum Zitat Remondo J, González A, Díaz de Terán JR (2003) Validation of landslide susceptibility maps; examples and applications from a case study in Northern Spain. Nat Hazards 30:437–449CrossRef Remondo J, González A, Díaz de Terán JR (2003) Validation of landslide susceptibility maps; examples and applications from a case study in Northern Spain. Nat Hazards 30:437–449CrossRef
Zurück zum Zitat Roohollah N, Khakpour A, Omidvar B, Farokhnia A (2010) Comparison of ANN and principal component analysis-multivariate linear regression models for predicting the river flow based on developed discrepancy ratio statistic. Expert Sys Appl 37:5856–5862CrossRef Roohollah N, Khakpour A, Omidvar B, Farokhnia A (2010) Comparison of ANN and principal component analysis-multivariate linear regression models for predicting the river flow based on developed discrepancy ratio statistic. Expert Sys Appl 37:5856–5862CrossRef
Zurück zum Zitat Rozos D, Bathrellos GD, Skilodimou HD (2011) Comparison of the implementation of rock engineering system (RES) and analytic hierarchy process (AHP) methods, based on landslide susceptibility maps, compiled in GIS environment. A case study from the Eastern Achaia County of Peloponnesus, Greece. Environ. Earth Sci 63(1):49–63CrossRef Rozos D, Bathrellos GD, Skilodimou HD (2011) Comparison of the implementation of rock engineering system (RES) and analytic hierarchy process (AHP) methods, based on landslide susceptibility maps, compiled in GIS environment. A case study from the Eastern Achaia County of Peloponnesus, Greece. Environ. Earth Sci 63(1):49–63CrossRef
Zurück zum Zitat Saleh S, Al-Hatrushi S (2009) Torrential Flood Hazards Assessment, Management, and Mitigation, in Wadi Uday, Muscat Area, Sultanate of Oman, a GIS & RS approach Egypt. J Rem Sens Space Sci 12:71–86 Saleh S, Al-Hatrushi S (2009) Torrential Flood Hazards Assessment, Management, and Mitigation, in Wadi Uday, Muscat Area, Sultanate of Oman, a GIS & RS approach Egypt. J Rem Sens Space Sci 12:71–86
Zurück zum Zitat Sanyal J, Lu XX (2004) Application of remote sensing in flood management with special reference to monsoon Asia: a review. Nat Hazards 33:283–301CrossRef Sanyal J, Lu XX (2004) Application of remote sensing in flood management with special reference to monsoon Asia: a review. Nat Hazards 33:283–301CrossRef
Zurück zum Zitat Schoof J, Pryor S (2001) Downscaling temperature and precipitation: a comparison of regression-based methods and artificial neural networks. Int J Clim 21:773–790CrossRef Schoof J, Pryor S (2001) Downscaling temperature and precipitation: a comparison of regression-based methods and artificial neural networks. Int J Clim 21:773–790CrossRef
Zurück zum Zitat Sivakumar B (2001) Rainfall dynamics at different temporal scales: a chaotic perspective. Hydrol Earth Sys Sci 5(4):645–651CrossRef Sivakumar B (2001) Rainfall dynamics at different temporal scales: a chaotic perspective. Hydrol Earth Sys Sci 5(4):645–651CrossRef
Zurück zum Zitat Sivakumar B, Berndtsson R, Olsson J, Jinno K (2001) Evidence of chaos in the rainfall-runoff process. Hydrol Sci 46(1):131–145CrossRef Sivakumar B, Berndtsson R, Olsson J, Jinno K (2001) Evidence of chaos in the rainfall-runoff process. Hydrol Sci 46(1):131–145CrossRef
Zurück zum Zitat Skilodimou H, Livaditis G, Bathrellos G, Verikiou-Papaspiridakou E (2003) Investigating the flooding events of the urban regions of Glyfada and Voula, Attica, Greece: a contribution to Urban Geomorphology. Geogr Ann A 85(2):197–204CrossRef Skilodimou H, Livaditis G, Bathrellos G, Verikiou-Papaspiridakou E (2003) Investigating the flooding events of the urban regions of Glyfada and Voula, Attica, Greece: a contribution to Urban Geomorphology. Geogr Ann A 85(2):197–204CrossRef
Zurück zum Zitat Sørensen R, Seibert J (2007) Effects of DEM resolution on the calculation of topographical indices: TWI and its components. J Hydrol 347(1–2):79–89CrossRef Sørensen R, Seibert J (2007) Effects of DEM resolution on the calculation of topographical indices: TWI and its components. J Hydrol 347(1–2):79–89CrossRef
Zurück zum Zitat Sousa S, Martins F, Alvim-Ferraz M, Pereira M (2007) Multiple linear regression and artificial neural networks based on principal components to predict ozone concentrations. Environ Mod Softw 22:97–103CrossRef Sousa S, Martins F, Alvim-Ferraz M, Pereira M (2007) Multiple linear regression and artificial neural networks based on principal components to predict ozone concentrations. Environ Mod Softw 22:97–103CrossRef
Zurück zum Zitat Taylor MA, Mandal A, Burgess C, Stephenson T (2014) Flooding and climate change: sectorial impacts and adaptation strategies for the caribbean region, Chap 10. In: Dave D, Chadee, Joan M, Sutherland, John B, Agard (eds) Flooding in Jamaica: causes and controls. Nova Science Pub Inc, New York, pp 163–187 Taylor MA, Mandal A, Burgess C, Stephenson T (2014) Flooding and climate change: sectorial impacts and adaptation strategies for the caribbean region, Chap 10. In: Dave D, Chadee, Joan M, Sutherland, John B, Agard (eds) Flooding in Jamaica: causes and controls. Nova Science Pub Inc, New York, pp 163–187
Zurück zum Zitat Tehrany MS, Pradhan B, Jebur MN (2014) Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS. J Hydrol 512:332–343CrossRef Tehrany MS, Pradhan B, Jebur MN (2014) Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS. J Hydrol 512:332–343CrossRef
Zurück zum Zitat Townsend PA, Walsh S (1998) Modeling floodplain inundation using an integrated GIS with Radar and optical remote sensing. Geomorph 21:295–312CrossRef Townsend PA, Walsh S (1998) Modeling floodplain inundation using an integrated GIS with Radar and optical remote sensing. Geomorph 21:295–312CrossRef
Zurück zum Zitat Tsai F, Li X (2008) Inverse groundwater modeling for hydraulic conductivity estimation using Bayesian model averaging and variance window. Water Res Res 44:W09434CrossRef Tsai F, Li X (2008) Inverse groundwater modeling for hydraulic conductivity estimation using Bayesian model averaging and variance window. Water Res Res 44:W09434CrossRef
Zurück zum Zitat UNISDR (United Nations Office of Disaster Risk Reduction) (2011) Global assessment report on disaster risk reduction. United Nations International Strategy for Disaster Reduction, Geneva UNISDR (United Nations Office of Disaster Risk Reduction) (2011) Global assessment report on disaster risk reduction. United Nations International Strategy for Disaster Reduction, Geneva
Zurück zum Zitat Verstraeten G, Poesen J (2001) Modelling the long term sediment trap efficiency of small ponds. Hydrol Proc 15:2797–2819CrossRef Verstraeten G, Poesen J (2001) Modelling the long term sediment trap efficiency of small ponds. Hydrol Proc 15:2797–2819CrossRef
Zurück zum Zitat Wang S, Xiao F (2004) AHU sensor fault diagnosis using principal component analysis method. Energy Build 36(2):147–160CrossRef Wang S, Xiao F (2004) AHU sensor fault diagnosis using principal component analysis method. Energy Build 36(2):147–160CrossRef
Zurück zum Zitat Yesilnacar E, Topal T (2005) Landslide susceptibility mapping: a comparison of logistic regression and neural networks methods in a medium scale study, Hendek region (Turkey). Eng Geol 79(3–4):251–266CrossRef Yesilnacar E, Topal T (2005) Landslide susceptibility mapping: a comparison of logistic regression and neural networks methods in a medium scale study, Hendek region (Turkey). Eng Geol 79(3–4):251–266CrossRef
Zurück zum Zitat Youssef AM, Pradhan B, Hassan AM (2011) Flash flood risk estimation along the St. Katherine road, southern Sinai, Egypt using GIS based morphometry and satellite imagery. Environ. Earth Sci 62(3):611–623CrossRef Youssef AM, Pradhan B, Hassan AM (2011) Flash flood risk estimation along the St. Katherine road, southern Sinai, Egypt using GIS based morphometry and satellite imagery. Environ. Earth Sci 62(3):611–623CrossRef
Zurück zum Zitat Zhu D, Ren Q, Xuan Y, Chen Y, Cluckie ID (2013) An effective depression filling algorithm for DEM-based 2-D surfaceflow modelling Guangzhou, China. Hydrol Earth Syst Sci 17:495–505CrossRef Zhu D, Ren Q, Xuan Y, Chen Y, Cluckie ID (2013) An effective depression filling algorithm for DEM-based 2-D surfaceflow modelling Guangzhou, China. Hydrol Earth Syst Sci 17:495–505CrossRef
Zurück zum Zitat Zwenzner H, Voigt S (2009) Improved estimation of flood parameters by combining space based SAR data with very high resolution digital elevation data. Hydrol Earth Syst Sci 13:67–576CrossRef Zwenzner H, Voigt S (2009) Improved estimation of flood parameters by combining space based SAR data with very high resolution digital elevation data. Hydrol Earth Syst Sci 13:67–576CrossRef
Metadaten
Titel
Flood hazard mapping in Jamaica using principal component analysis and logistic regression
verfasst von
Arpita Nandi
Arpita Mandal
Matthew Wilson
David Smith
Publikationsdatum
01.03.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Environmental Earth Sciences / Ausgabe 6/2016
Print ISSN: 1866-6280
Elektronische ISSN: 1866-6299
DOI
https://doi.org/10.1007/s12665-016-5323-0

Weitere Artikel der Ausgabe 6/2016

Environmental Earth Sciences 6/2016 Zur Ausgabe