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Training Course on Early Warning Systems in Nairobi and Mombasa, Kenya

The training is aimed at helping participants and their respective organizations to design and implement Early Warning Systems. The course will help participants develop an early warning systems and risk management plans tailored to the needs of their respective organizations

Participants will be introduced to various aspects of early warning and disaster management. This training is designed to increase the audience's awareness of the process of Early Warning System, leading to better performance in disaster preparedness and response. The major objective of this training is to increase awareness about early warning mechanisms for different hazards, their potential benefits, challenges in taking decisions during such early warning, and capacity building in interpreting and taking suggested protective measures. The content in general follows the ISDR Early Warning System principles, procedures, and terminology.

Duration

5 days

Who Should Attend?

The training is intended for management teams working in government agencies, NGOs, and Community Members working in governments, funding agencies, and research and non-government organizations for Emergency response and other Development programmes.

Course Content

Upon completion of the course, participants will:

  • Understand operational mechanisms and procedures for the prediction, forecasting, monitoring and response to warning
  • Examine the kinds of tools and products that are available or could be developed to integrate information into forms most useful for them to make decisions at various levels; and set-up appropriate contingency plan or options to guide members of their organization against various hazards of different timescales.
  • Design end-to-end early warning systems for several types of hazards including, action planning for disaster preparedness, emergency management and social response with respect to early warning;
  • Develop tools for early warning audits, identify current gaps in existing early warning systems and put in place enhanced people-centered early warning system
  • Harmonization of early warning system and disaster mitigation for effective disaster risk reduction
  • Undertake risk assessment and design of multi-hazard end-to-end early warning systems for disaster risk reduction
  • Develop strategies to institutionalize early warning systems into the process cycle of disaster risk reduction and development planning, emergency response, and preparedness activities
  • Interpret and translate scientific information products into user friendly formats and prepare & communicate tailor made early warning information products to elicit response from at risk communities
  • Design and implement community based early warning systems that are people cantered and that can effectively contribute to the risk management process/risk reduction
  • Evaluate and introduce public education and training programme for the community based early warning systems
  • Apply emerging new generation climate prediction technologies for anticipating and managing disaster risks associated with climate change & variability

Course Content

Module I: Introduction to End-to-End Early Warning System

    • Overview to Basic Terminology & Concepts in DRM
    • Overview of Hazards and possibility of EWS
    • End-to-End EWS Framework and its Elements
    • Institutional mechanism/ framework for EWS

Module II: Hazard Detection, Monitoring, Forecasting & Information for Warning (HDMFW)

    • Hazard Identification Process
    • Risk Analysis: Probabilities and Consequences
    • Risk Management: Options Analysis
    • Detection, Monitoring, Forecasting & Information for Warning-Drought
    • Detection, Monitoring, Forecasting & Information for Warning-Flood/Flash Flood
    • Detection, Monitoring, Forecasting & Information for - Warning-Volcanoes, Earthquake and Tsunami

Module III: Application of Risk Assessment & Risk Communication for Early Warning

    • Use of Multi-Hazard Risk Assessment and Risk Maps for Early Warning
    • Risk Communication Process and Tools
    • Contingency Plans
    • Organizational Preparedness and Response Preparation
    • GIS and RS in Early Warning Systems

Module IV: Standard Operating Procedures (SOPs) for Early Warning Systems

    • Table-Top Exercise & SOP Development
    • Community-level focus
    • Good practice and lessons learned across the globe

Module V: Monitoring and Evaluation of EWS

    • Monitoring the performance of EWS through quantifiable indicators and tools
    • Post Training work plan
    • Course Evaluation

 

 

 

Methodology

The instructor led trainings are delivered using a blended learning approach and comprises of presentations, guided sessions of practical exercise, web-based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields.

Key Notes

i. The participant must be conversant with English.

ii. Upon completion of training the participant will be issued with an Authorized Training Certificate.

iii. Course duration is flexible and the contents can be modified to fit any number of days.

iv. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

v. One-year post-training support Consultation and Coaching provided after the course.

vi. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.

Course Schedule

Start Date End Date Register
16/09/2024 20/09/2024 Register
07/10/2024 11/10/2024 Register
21/10/2024 25/10/2024 Register
19/08/2024 23/08/2024 Register
05/08/2024 09/08/2024 Register
02/09/2024 06/09/2024 Register
04/11/2024 08/11/2024 Register
18/11/2024 22/11/2024 Register
02/12/2024 06/12/2024 Register
16/12/2024 20/12/2024 Register
Get In Touch

College House , Along University Way , Nairobi, Kenya

+254724527104/ +254734969612

info@datastatresearch.org

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