DOCSLIB.ORG

Final Research Report

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Final Research Report Flood modeling and impact analysis using LiDAR data: A Case study for Ladyville Village, Belize. Final Research Report By: Alfred Cal Vancouver Island University August 31th, 2018 Abstract: Flooding is one of the most catastrophic natural disasters. Floods cause extensive damages on infrastructures and in some cases the loss of human life. Over the years flood frequency and severity has been increasing attributed to climate change. Coastal countries such as Belize have been impacted on a regular basis. A recent flood disaster in Ladyville, Belize, has shown a greater need for the monitoring of flood plain areas. In developed countries, flood mapping technologies and monitoring are at an advanced stage and can provide real-time early warnings. However, Belize is a developing country that is currently lacking reliable spatial data for disaster management. Considering this limitation, this research project contributes to the use of LiDAR as a technology that can be used for the extracting of relevant datasets for flood plain mapping. A PCA and image fusion technique of LiDAR with aerial photos was introduced to aid in the accurate extraction of structures. Ladyville village, Belize was chosen as a case study to evaluate the effectiveness of LiDAR technology in flood modeling and impact analysis. Ladyville was chosen as a study area because it is one of the most vulnerable communities in Belize that is prone to fluvial, pluvial and storm surge flooding. With the use of LiDAR derived datasets coupled with stream discharge data, 2D hydraulic modeling was completed in HEC- RAS to produce 2, 5, 10, 25, 50, and 100-year return period of flood depth, velocity, and extent. The boundary of the modeled flood plain was validated using photographs of past floods, anecdotal information from residents and NEMO personnel, and a comparison to past flood studies. A confusion matrix and a F measure statistic was used to determine the accuracy of the model with the locations of observed flood on the ground with the predicted flood model. The result of the F measure statistic shows an 80.6% reliability of the modeled flood plain. Based on the flood plain extents, impact analysis was conducted on the infrastructures and population of vulnerable areas. The results show that the most affected are residential infrastructures and 40% of the total population of study area can be impacted by a 100-year flood return period. In the absence of reliable spatial data, this study presented the effectiveness and advantage of using high resolution LiDAR data for flood modeling at an urban scale for Ladyville village, Belize. Keywords: Floods, 2D hydraulic model, LiDAR, DEM, DSM, nDSM, Land Cover, PCA, OBIA. i Table of Contents Abstract: ......................................................................................................................................... i List of Tables ................................................................................................................................ iv List of Figures ................................................................................................................................ v List of Symbols and Abbreviations ............................................................................................ ix Acknowledgements ....................................................................................................................... x Chapter 1: Introduction ............................................................................................................... 1 1.1 Background .............................................................................................................................. 1 1.2 Problem Statement ................................................................................................................... 3 1.3 Purpose and Research Question .............................................................................................. 4 1.4 Contribution to knowledge ...................................................................................................... 6 Chapter 2: Literature Review ...................................................................................................... 9 2.1 Importance of flood studies. ..................................................................................................... 9 2.2 Hydrology model ...................................................................................................................... 9 2.3 Importance of IDF and Peak Discharge for flood modelling. ................................................ 10 2.4 Importance of LiDAR data for flood modelling ..................................................................... 12 2.5 LiDAR Processing Software ................................................................................................... 14 2.6 LiDAR data filtering for flood modelling ............................................................................... 15 2.7 PCA and Image Fusion for feature extractions ....................................................................... 17 2.8 Floodplain modelling Software............................................................................................... 19 2.9 Floodplain model data inputs .................................................................................................. 21 2.10 Floodplain modelling Validation .......................................................................................... 22 2.11 Storm Surge Analysis ........................................................................................................... 23 2.12 Impact Analysis of floods ..................................................................................................... 24 2.13 Sensitivity Analysis .............................................................................................................. 26 Chapter 3: Methodology............................................................................................................. 28 3.1 Study Area Country Profile .................................................................................................... 28 3.2 Study Area .............................................................................................................................. 29 3.3.1 Data Collection .................................................................................................................... 31 3.3.2 Data Collection in a Developing Country ............................................................................ 35 ii 3.3.3 Field data collection ............................................................................................................. 38 3.4 Hydrological Analysis Component ......................................................................................... 41 3.5 LiDAR data processing component. ....................................................................................... 48 3.5.1 DEM (Digital Elevation Model) from LiDAR data ............................................................. 48 3.5.2 DSM (Digital Surface Model) from LiDAR data ................................................................ 50 3.5.3 Normalized Digital Surface Model (nDSM)........................................................................ 52 3.5.4 Intensity Image..................................................................................................................... 54 3.5.5 Building Foot Prints ............................................................................................................. 55 3.5.6 Building Extraction from LiDAR data only ........................................................................ 55 3.5.7 Pixel vs. object-based classification .................................................................................... 59 3.5.8 Object Based Building Extraction using PCA of LiDAR nDSM and Aerial Photos .......... 61 3.5.9 Land Cover from LiDAR data ............................................................................................. 78 3.5.10 OBIA Land Cover classification using image fusion of LiDAR Height and Intensity with Aerial photos. ................................................................................................................................ 82 3.6 Hydraulic component .............................................................................................................. 88 3.7 Flood plain validation component ........................................................................................ 103 3.8 Impact Analysis component .................................................................................................. 117 3.9 Storm Surge Analysis ........................................................................................................... 121 3.9.1 Storm Surge Validation...................................................................................................... 123 3.10 Sensitivity Analysis ............................................................................................................ 128 Chapter 4: Results and Discussion .......................................................................................... 131 4.1 Riverine Flood Results .......................................................................................................... 131 4.2 Storm Surge Results .............................................................................................................
Load more

Recommended publications
  • Belize), and Distribution in Yucatan
    University of Neuchâtel, Switzerland Institut of Zoology Ecology of the Black Catbird, Melanoptila glabrirostris, at Shipstern Nature Reserve (Belize), and distribution in Yucatan. J.Laesser Annick Morgenthaler May 2003 Master thesis supervised by Prof. Claude Mermod and Dr. Louis-Félix Bersier CONTENTS INTRODUCTION 1. Aim and description of the study 2. Geographic setting 2.1. Yucatan peninsula 2.2. Belize 2.3. Shipstern Nature Reserve 2.3.1. History and previous studies 2.3.2. Climate 2.3.3. Geology and soils 2.3.4. Vegetation 2.3.5. Fauna 3. The Black Catbird 3.1. Taxonomy 3.2. Description 3.3. Breeding 3.4. Ecology and biology 3.5. Distribution and threats 3.6. Current protection measures FIRST PART: BIOLOGY, HABITAT AND DENSITY AT SHIPSTERN 4. Materials and methods 4.1. Census 4.1.1. Territory mapping 4.1.2. Transect point-count 4.2. Sizing and ringing 4.3. Nest survey (from hide) 5. Results 5.1. Biology 5.1.1. Morphometry 5.1.2. Nesting 5.1.3. Diet 5.1.4. Competition and predation 5.2. Habitat use and population density 5.2.1. Population density 5.2.2. Habitat use 5.2.3. Banded individuals monitoring 5.2.4. Distribution through the Reserve 6. Discussion 6.1. Biology 6.2. Habitat use and population density SECOND PART: DISTRIBUTION AND HABITATS THROUGHOUT THE RANGE 7. Materials and methods 7.1. Data collection 7.2. Visit to others sites 8. Results 8.1. Data compilation 8.2. Visited places 8.2.1. Corozalito (south of Shipstern lagoon) 8.2.2.
    [Show full text]
  • Florida Hurricanes and Tropical Storms
    FLORIDA HURRICANES AND TROPICAL STORMS 1871-1995: An Historical Survey Fred Doehring, Iver W. Duedall, and John M. Williams '+wcCopy~~ I~BN 0-912747-08-0 Florida SeaGrant College is supported by award of the Office of Sea Grant, NationalOceanic and Atmospheric Administration, U.S. Department of Commerce,grant number NA 36RG-0070, under provisions of the NationalSea Grant College and Programs Act of 1966. This information is published by the Sea Grant Extension Program which functionsas a coinponentof the Florida Cooperative Extension Service, John T. Woeste, Dean, in conducting Cooperative Extensionwork in Agriculture, Home Economics, and Marine Sciences,State of Florida, U.S. Departmentof Agriculture, U.S. Departmentof Commerce, and Boards of County Commissioners, cooperating.Printed and distributed in furtherance af the Actsof Congressof May 8 andJune 14, 1914.The Florida Sea Grant Collegeis an Equal Opportunity-AffirmativeAction employer authorizedto provide research, educational information and other servicesonly to individuals and institutions that function without regardto race,color, sex, age,handicap or nationalorigin. Coverphoto: Hank Brandli & Rob Downey LOANCOPY ONLY Florida Hurricanes and Tropical Storms 1871-1995: An Historical survey Fred Doehring, Iver W. Duedall, and John M. Williams Division of Marine and Environmental Systems, Florida Institute of Technology Melbourne, FL 32901 Technical Paper - 71 June 1994 $5.00 Copies may be obtained from: Florida Sea Grant College Program University of Florida Building 803 P.O. Box 110409 Gainesville, FL 32611-0409 904-392-2801 II Our friend andcolleague, Fred Doehringpictured below, died on January 5, 1993, before this manuscript was completed. Until his death, Fred had spent the last 18 months painstakingly researchingdata for this book.
    [Show full text]
  • Chapter 1 Introduction
    Chapter 1 Introduction 1.1 General Background Semi-engineered buildings are often considered to be those built in an organized fashion with materials which are processed or engineered for the most part, but which include little or no formal structural engineering input during the design and construction stages. These structures along with non-engineered buildings are thought to constitute the majority of buildings typically built on an annual basis, particularly in developing countries. Even in developed countries such as the United States of America, semi-engineered residential buildings are very prevalent and often fare the worst after experiencing the effects of hurricanes. This is evidenced in the aftermath of the numerous storms that have ravaged the southern coast of the United States over the years. Hurricane Katrina was one of the strongest and most expensive storms to make landfall in the United States of America in recent history. The storm killed over 1,300 people and caused the destruction of thousands of homes in the states of Mississippi and Louisiana (FEMA April 2006). Of the buildings destroyed, the great majority was determined to be single family dwellings. Similarly, Hurricane Georges made landfall in Puerto Rico on September 21, 1998 and caused substantial damages to residential buildings. During this storm, it is reported that the majority of building losses were in \all-wood" residential buildings. The structural performance of buildings constructed of concrete and masonry, however, performed well, while those with
    [Show full text]
  • Colorado State Universtiy Hurricane Forecast Team Figure 1: Colorado State Universtiy Hurricane Forecast Team
    SUMMARY OF 2000 ATLANTIC TROPICAL CYCLONE ACTIVITY AND VERIFICATION OF AUTHORS' SEASONAL ACTIVITY FORECAST A Successful Forecast of an Active Hurricane Season - But (Fortunately) Below Average Cyclone Landfall and Destruction (as of 21 November 2000) By William M. Gray,* Christopher W. Landsea**, Paul W. Mielke, Jr., Kenneth J. Berry***, and Eric Blake**** [with advice and assistance from Todd Kimberlain and William Thorson*****] * Professor of Atmospheric Science ** Meteorologist with NOAA?AOML HRD Lab., Miami, Fl. *** Professor of Statistics **** Graduate Student ***** Dept. of Atmospheric Science [David Weymiller and Thomas Milligan, Colorado State University Media Representatives (970-491- 6432) are available to answer questions about this forecast.] Department of Atmospheric Science Colorado State University Fort Collins, CO 80523 Phone Number: 970-491-8681 Colorado State Universtiy Hurricane Forecast Team Figure 1: Colorado State Universtiy Hurricane Forecast Team Front Row - left to right: John Knaff, Ken Berry, Paul Mielke, John Scheaffer, Rick Taft. Back Row - left to right: Bill Thorson, Bill Gray, and Chris Landsea. SUMMARY OF 2000 SEASONAL FORECASTS AND VERIFICATION Sequence of Forecast Updates Tropical Cyclone Seasonal 8 Dec 99 7 Apr 00 7 Jun 00 4 Aug 00 Observed Parameters (1950-90 Ave.) Forecast Forecast Forecast Forecast 2000 Totals* Named Storms (NS) (9.3) 11 11 12 11 14 Named Storm Days (NSD) (46.9) 55 55 65 55 66 Hurricanes (H)(5.8) 7 7 8 7 8 Hurricane Days (HD)(23.7) 25 25 35 30 32 Intense Hurricanes (IH) (2.2) 3 3 4 3 3 Intense Hurricane Days (IHD)(4.7) 6 6 8 6 5.25 Hurricane Destruction Potential (HDP) (70.6) 85 85 100 90 85 Maximum Potential Destruction (MPD) (61.7) 70 70 75 70 78 Net Tropical Cyclone Activity (NTC)(100%) 125 125 160 130 134 *A few of the numbers may change slightly in the National Hurricane Center's final tabulation VERIFICATION OF 2000 MAJOR HURRICANE LANDFALL Forecast Probability and Climatology for last Observed 100 years (in parentheses) 1.
    [Show full text]
  • Florida Hurricanes and Tropical Storms, 1871-1993: an Historical Survey, the Only Books Or Reports Exclu- Sively on Florida Hurricanes Were R.W
    3. 2b -.I 3 Contents List of Tables, Figures, and Plates, ix Foreword, xi Preface, xiii Chapter 1. Introduction, 1 Chapter 2. Historical Discussion of Florida Hurricanes, 5 1871-1900, 6 1901-1930, 9 1931-1960, 16 1961-1990, 24 Chapter 3. Four Years and Billions of Dollars Later, 36 1991, 36 1992, 37 1993, 42 1994, 43 Chapter 4. Allison to Roxanne, 47 1995, 47 Chapter 5. Hurricane Season of 1996, 54 Appendix 1. Hurricane Preparedness, 56 Appendix 2. Glossary, 61 References, 63 Tables and Figures, 67 Plates, 129 Index of Named Hurricanes, 143 Subject Index, 144 About the Authors, 147 Tables, Figures, and Plates Tables, 67 1. Saffir/Simpson Scale, 67 2. Hurricane Classification Prior to 1972, 68 3. Number of Hurricanes, Tropical Storms, and Combined Total Storms by 10-Year Increments, 69 4. Florida Hurricanes, 1871-1996, 70 Figures, 84 l A-I. Great Miami Hurricane 2A-B. Great Lake Okeechobee Hurricane 3A-C.Great Labor Day Hurricane 4A-C. Hurricane Donna 5. Hurricane Cleo 6A-B. Hurricane Betsy 7A-C. Hurricane David 8. Hurricane Elena 9A-C. Hurricane Juan IOA-B. Hurricane Kate 1 l A-J. Hurricane Andrew 12A-C. Hurricane Albert0 13. Hurricane Beryl 14A-D. Hurricane Gordon 15A-C. Hurricane Allison 16A-F. Hurricane Erin 17A-B. Hurricane Jerry 18A-G. Hurricane Opal I9A. 1995 Hurricane Season 19B. Five 1995 Storms 20. Hurricane Josephine , Plates, X29 1. 1871-1880 2. 1881-1890 Foreword 3. 1891-1900 4. 1901-1910 5. 1911-1920 6. 1921-1930 7. 1931-1940 These days, nothing can escape the watchful, high-tech eyes of the National 8.
    [Show full text]
  • Belize: Hurricane Iris
    BELIZE: HURRICANE IRIS 30 August 2002 This Final Report is intended for reporting on emergency appeals The Federation’s mission is to improve the lives of vulnerable people by mobilizing the power of humanity. It is the world’s largest humanitarian organization and its millions of volunteers are active in 178 countries. For more information: www.ifrc.org Appeal No. 33/01; Launched on: 12 October 2001 for three months for CHF 655,000 to assist 4,350 beneficiaries. Extended by four months to 31 May 2002. Disaster Relief Emergency Fund (DREF) Allocated: None IN BRIEF Appeal coverage: 100.6% Related Appeals 01.32/2001; 01.23/2002 Caribbean Summary w Hurricane Iris, a category 4 hurricane, struck the southern coast of Belize on 8 October 2001, tearing apart houses and community buildings, ripping up trees and electricity lines, and flattening standing crops across an arc of coastal plain some sixty kilometres long and thirty kilometres wide throughout Toledo district. The southern area of Stann Creek district was also affected. An airborne and ground assessment was carried out on 10 October 2001 by Federation and Belize Red Cross Society (BRCS) staff. Subsequently, a detailed village-by-village assessment of the impacted areas was carried out by BRCS personnel from the Toledo branch in Punta Gorda. Based upon assessments and coordination with different organizations, 14 villages in the Toledo district were selected for assistance by the Toledo BRCS branch, for which the Federation launched an appeal on 12 October 2001, to assist 4,800 beneficiaries for three months. Remaining areas not covered by the Toledo branch were assisted by the National Emergency Management Organization (NEMO).
    [Show full text]
  • Disaster Mitigation Measures
    PREPAREDNESS AND MITIGATION IN THE AMERICAS Issue No. 82 News and Information for the International Disaster Community October 2000 Health: A Bridge to Peace in Colombia iolence has displaced much of the rural benefit that the remainder of Colombia’s popula- population of Colombia’s 40 million tion has been able to maintain. This number Vinhabitants. In its search for safer places includes those displaced by violence. By mid- to live, the internally displaced population (IDP) 1999, the situation had deteriorated to the point has lost its income and compromised access to that forced migration had overwhelmed approxi- health services. In the last four years, the number mately 100 of the 1,090 Colombian municipali- of displaced persons has grown at an alarming rate ties. The number also includes those who may not and each day affects a much broader geographical have been displaced, but who live in such an inse- area. In Colombia, the size of the internally dis- cure environment that health care providers have placed population increased from 89,000 in 1995 evacuated the area, resulting in the further disrup- to as many as 288,000 by the end of 1999 (figures tion of health services. from CODHES, Consultoría para los Derechos Other difficulties arise when IDPs resettle in Humanos y el Desplazamiento). areas that were already plagued with problems— Equity is a major issue in the debate over access lack of access to potable water or inadequate shel- to health services. Depending on the source of ter. The health services, which were not designed information, between 500,000 and 2 million per- to suddenly absorb such an increase in demand, I N S I D E sons have been deprived of access to health care, a (cont.
    [Show full text]
  • Assimilation of Goes Rapid-Scan Winds Into an Experimental Eta Model During Atlantic Hurricanes
    ASSIMILATION OF GOES RAPID-SCAN WINDS INTO AN EXPERIMENTAL ETA MODEL DURING ATLANTIC HURRICANES Howard I. Berger University of Wisconsin-Cooperative Institute for Meteorological Satellite Studies 1225 West Dayton Street, Madison, WI 53706, USA ABSTRACT Experiments designed to optimize the assimilation of winds derived from GOES rapid-scan data into the National Centers for Environmental Prediction's Eta model are being performed. These experiments have been performed on various Atlantic hurricanes in the 2000 and 2001 storm season. The wind data are being assimilated into parallel runs of the Eta model through the Eta Data Assimilation System. Although the assimilation experiments showed impact in the wind and height field aloft, continued experiments and optimizations will be needed to improve the surface features of the hurricanes. 1. Introduction The lack of in-situ data in the tropics makes it difficult to properly initialize tropical cyclones in Numerical Weather Prediction (NWP) models. To account for this data void, synthetic data has traditionally been used to initialize hurricanes within NWP models. An alternative solution to this initialization problem involves using remotely sensed data from satellites in addition to synthetic data. To examine this solution, experiments have been performed that are designed to optimize the assimilation of winds derived from GOES rapid-scan data into the National Centers for Environmental Prediction's (NCEP) Eta model. The wind data are assimilated into the Eta model through the Eta Data Assimilation System (EDAS). The preliminary case study evaluated is Atlantic Hurricane Keith, (Sept/Oct 2000) although additional cases, such as hurricane Humberto (Sept 2001), will be presented.
    [Show full text]
  • Atlantic Major Hurricanes, 1995–2005—Characteristics Based on Best-Track, Aircraft, and IR Images
    VOLUME 20 JOURNAL OF CLIMATE 15DECEMBER 2007 Atlantic Major Hurricanes, 1995–2005—Characteristics Based on Best-Track, Aircraft, and IR Images RAYMOND M. ZEHR AND JOHN A. KNAFF NOAA/NESDIS, Fort Collins, Colorado (Manuscript received 28 August 2006, in final form 1 May 2007) ABSTRACT The Atlantic major hurricanes during the period of 1995–2005 are examined using best-track data, aircraft-based observations of central pressure, and infrared (IR) satellite images. There were 45 Atlantic major hurricanes (Saffir–Simpson category 3 or higher) during this 11-yr period, which is well above the long-term average. Descriptive statistics (e.g., average, variability, and range) of various characteristics are presented, including intensity, intensification rate, major hurricane duration, location, storm motion, size, and landfall observations. IR images are shown along with IR-derived quantities such as the digital Dvorak technique intensity and IR-defined cold cloud areas. In addition to the satellite intensity estimates, the associated component IR temperatures are documented. A pressure–wind relationship is evaluated, and the deviations of maximum intensity measurements from the pressure–wind relationship are discussed. The Atlantic major hurricane activity of the 1995–2005 period distinctly exceeds the long-term average; however, the average location where major hurricanes reach maximum intensity has not changed. The maximum intensity for each 1995–2005 Atlantic major hurricane is given both as the highest maximum surface wind (Vmax) and the lowest minimum sea level pressure (MSLP). Comparisons are made to other Atlantic major hurricanes with low MSLP back to 1950. Maximum 24-h intensification rates average 21.1 m sϪ1 dayϪ1 and range up to 48.8 m sϪ1 dayϪ1 in terms of Vmax.
    [Show full text]
  • What Do I Need to Know About Hurricanes? Marty Casado Thu, Dec 7, 2006 Hurricanes 0 9686
    What do I need to know about hurricanes? Marty Casado Thu, Dec 7, 2006 Hurricanes 0 9686 The Caribbean and the east coast of Central America is in the hurricane belt. These occur between the months of July and November. Every 10 to 30 years a country may find itself directly in the path of a hurricane as happened in Belize in 1931, 1961, and 1978. The effects, although damaging to lightly constructed buildings and crops, are a natural calamity (as sometimes experienced on the eastern seaboard of the U.S.A.) Earthquakes, tornadoes and other similar natural phenomena are unknown in Belize. Click here for more on hurricanes in Belize. Generally, international weather authorities estimate that there will be 12 tropical depressions forming in the Gulf to the east and in the Pacific, west of Central America, each year. Four are predicted to be force four or higher due to the residual effects of the 1998 El Nino Pacific Ocean current; which accounts for the one additional tropical depression predicted over last year’s eleven. Of course, whether hurricanes will form from tropical depressions or where the hurricanes will track is always at random and the one in 25 year risk ratio of hitting Belize is still in effect, too. Weather watches are in effect at all times in the Cayes - ample warning of impending danger is readily at hand with predictions as long as a week in advance. Plan to leave the Cayes not later than four days before danger is predicted. Not later than three days if on the mainland coast.
    [Show full text]
  • Campeche, Mexico
    Coastal Cities and their Sustainable Future III 83 VULNERABLE AREAS IN TOURIST CITIES OF COASTAL ZONES: CAMPECHE, MEXICO BERTHA N. CABRERA SÁNCHEZ & JOEL F. AUDEFROY Instituto Politécnico Nacional, ESIA TEC, México ABSTRACT The expansion of cities located in coastal areas, primarily the emergence of settlements on the periphery of Mexican tourist resorts, makes them increasingly vulnerable in physical and urban terms to a variety of natural phenomena (like extreme precipitation, tropical storms and hurricanes), which can cause disasters for local populations. The coastal zone of Campeche is 425 km long and in the last 30 years has undergone increasingly rapid growth of its population and the urban occupation of its coastline, increasing the number of people that might be affected by weather like hurricanes. This paper focuses on two central aspects: first, identifying vulnerable areas that are threatened by hydro-meteorological hazards; and second, identifying strategies for adapting to such risks, based on the experiences of affected communities. This information supports the hypothesis that empowerment and participation of the people, in conjunction with government strategies, can help reduce the risk of disaster and strengthen the inhabitants’ resilience to hydro-meteorological hazards. We present a case study on the city of Campeche, in the state of Campeche, Mexico; a city popular among tourists, with highly valuable urban spaces rich in material, architectural, cultural and historical heritage. The process of urban growth reproduces and deepens inequalities, which directly affect the inhabitants’ resilience against frequent natural phenomena; but a variety of urban, social, economic and political conditions should be taken into account in determining the strategies for surviving hydro-meteorological hazards.
    [Show full text]
  • Shock-Responsive Social Protection in the Caribbean | Belize Case Study
    Shock -Responsive Social Protection in the Caribbean Belize Case Study Sarah Bailey and Francesca Ciardi July 2020 Funded by Shock-Responsive Social Protection in the Caribbean | Belize Case Study About Oxford Policy Management Oxford Policy Management is committed to helping low- and middle-income countries achieve growth and reduce poverty and disadvantage through public policy reform. We seek to bring about lasting positive change using analytical and practical policy expertise. Through our global network of offices, we work in partnership with national decision makers to research, design, implement, and evaluate impactful public policy. We work in all areas of social and economic policy and governance, including health, finance, education, climate change, and public sector management. We draw on our local and international sector experts to provide the very best evidence-based support. About the World Food Programme Assisting 86.7 million people in around 83 countries each year, the World Food Programme (WFP) is the leading humanitarian organisation saving lives and changing lives, providing assistance in emergencies and working with communities to improve nutrition and build resilience. In 2018, WFP established a Barbados Office for Emergency Preparedness and Response in the Caribbean, in support of the Caribbean Disaster Emergency Management Agency (CDEMA) and Participating States1 to strengthen systems and technical capacities for a more effective, efficient and predictable response to emergencies. WFP is applying its global mandate and expertise in food security, logistics and emergency telecommunications to address gaps in response capacity, improve regional and national preparedness and to strengthen systems to deliver rapid and appropriate assistance to people facing shocks.
    [Show full text]