Developing drought detection and mitigation systems in the Greater Horn of Africa

2. Improving National and Regional Drought Early
Warning Systems in the Greater Horn of Africa
Tsegaye Tadesse, Ph.D.
Research Associate Professor
Climatologist and Remote Sensing Expert
Geospatial Science Coordinator
National Drought Mitigation Center
University of Nebraska-Lincoln, NE 68583
Co-authors: Nicole Wall, Mark Svoboda, Deborah Bathke, Michael Hayes, and Andualem Shiferaw
WATER FOR FOOD INTERNATIONAL FORUM, Washington, D.C., January 29 - 30, 2018

3. Introduction
 Drought adversely affects the lives of millions of people
each year, causing significant damage to economies, the
environment, and property.
 Drought is one of the biggest challenges facing farmers in
Africa that significantly impact food security.
 has both a natural and social dimension.
 The risk associated with drought for any region is a product of both
the region’s exposure to the event (i.e., probability of drought
occurrence at various severity levels) and the vulnerability of society
to drought.
 In most cases, the social dimension is the factor that turns drought
into a disaster.

4. Building/Improving Drought Early Warning System
 We need to improve drought management
to reduce its impact.
 Paradigm shift from crisis to drought risk
management (DRM)
 Improving Drought Early Warning System
(DEWS) helps
 Among the factors to build/improve DEWS
 Need for new and improved seasonal prediction
tools and climate information
 Engaging users/decision makers (farmers,
experts, policy makers, etc.) in developing
forecasting tools is efficient for DEWS

5. NASA-fundedproject
“Seasonal Prediction of Hydro-Climatic Extremes in the Greater Horn of Africa under Evolving
Climate Conditions to Support Adaptation Strategies.”
NASA Theme: Understanding Earth system
Vulnerabilities to Climate Extremes
GHA Countries
Developing Seasonal Prediction Tools

6. Figure. VegOut database, process (regression-tree
rules generation), and outlook map production.
(Tadesse et al., 2010, GIScience & Remote Sensing)
(Tadesse et al. 2018)
(VegOut-GHA)
Experimental Prediction Tool

7. May – Sep 2017
(Senay et al, 2015)
USGS FEWSNET

8. Participatory Research Workshops on Seasonal Prediction of Hydro-
climatic Extremes in the Greater Horn of Africa
(Tadesse et al., 2016 - BAMS)
Second Workshop, 28-29 July, 2015 Third Workshop, 22-25 October, 2017First Workshop, 11-12 August, 2014
(Tadesse et al., 2015 - BAMS)

9. Assessing Farmer’s Existing Level of Climate Information
 Study area: Ada District, Ethiopia (Preliminary Results):
 Method: survey, focused group discussions, and various informal
interactions with farmers and extension agents
 About 60% of farmers interviewed have access to forecast
information via the national radio/TV and agricultural
extension agents (as the primary sources).
 Awareness and access to forecast information do not
necessarily translate into action/use
 Only 6% of farmers who have access (11 out of 180) said they
have used the climate information provided for decision
making (EIAR/World Bank Project).
 The preliminary study indicates that farmers relied more
on their traditional knowledge and experiences and/or
advices from elderly farmers at a farm-level decision-
making.
 Case study conducted by: NDMC (NASA-funded) and the Ethiopian Institute of Agricultural Research
(EIAR/Partially supported by World Bank)

10. Lesson Learned: general observation and project findings
 Generally, considerable gaps exist between the small-scale farmers and climate
information providers
 Lack of proper understanding of farmers’ needs (e.g., specific info. at local-level)
 Lack of spatial explicitness of the forecast products (local area)
 Little or no dialogue between users/farmers and producers of climate information
 Lack of trust by farming community on climate information provided by Met services
 Skill of seasonal climate and/or weather forecasts and their reliability
 Lack of understanding of the probabilistic nature of forecast information
 Lack of effective methods of communicating the available information to farmers
 Formats of the climate products are not suitable for an easy use
 Non-traditional communication methods should also be used (e.g., mobile phones)
 Agro-meteorological infrastructure/services are not yet strong
 Limited human capacities and resources

11. Final Thought
To improve DEWS:
 Provide not only useful BUT useable prediction tools
tailored to specific users (e.g., farmers’) needs
 The primary steps in improving or establishing an
effective and farmers-oriented climate service should
include:
 understanding of farmers’ climate information needs,
 identifying factors that would encourage them to use the
information, and
 engage them in the design and improvement of a Drought
Early warning System (DEWS).
 Education and capacity building

12. Contact Information
Tsegaye Tadesse
Associate Professor
Climatologist & Remote Sensing Expert
Geospatial Science coordinator
National Drought Mitigation Center
University of Nebraska
Phone: (402) 472 3383
e-mail: ttadesse2@unl.edu