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Drought Monitoring and Mitigationin the Horn of Africa

Are we prepared?

Somalia Water and Land Information Management System

Z. Balint, Chief Technical AdvisorP. Muchiri, Meteorologist

FAO SWALIM

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Integrated drought management

Whatto do ?

Whoshould do it?

Howto do?

Can we manage drought?Natural phenomena

Impacts of drought

Mitigating the impacts of drought

WHAT can we use?Tools, measures, facilities

HOW can we use?Response systems,

Preparedness

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WHAT? HOW?

• Drought resistant crops• Irrigation• Storage systems• Market systems• etc.

• Long term plans for sustainable production• Short term plans for adaptation• Rapid response plans for mitigating the impacts

MONITORING

Long term trends

Real-time drought evolution

Early warning

Impacts

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SOLUTION(example)

Proper identification:Env. Degradation

•export charcoal prod•plant degradation•soil erosion

Altern. income generationLand conservationLand use planningFarm development

Food distribution

Local market pricedown

SUSTAINABLE SUPPLY OF FOOD

SHORT TERMLONG TERM

DEPENDENCY

FUNDS

Based on Measurements

& analysis

More difficult to get

Relatively easy to mobilise

“DROUGHT”

Food shortage causedby drought or

env. degradation

Production stops(incl. seeds)

Skills degrade

SHORT + LONG TERM

Why monitor drought? Proper diagnosis is needed for proper response

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Drought is a frequent, recurrent event in the Horn of Africa. - Despite its frequency it always seems to be a surprise, causing an emergency.

Are we prepared?Do we have the common understanding of drought?

Do we know what to observe and do we have the equipment for that?

Do we have monitoring systems?

Do we have methodologies how to interpret the observations?

Do we have the pre-set mechanisms, the standard procedures how to react in a real emergency situation?

Do we know the measures, tools, how to mitigate the impacts of drought?

Do we have long term visions how to adapt the production system to show more resilience to drought?

There is a long way to go.

We can start with better understanding the drought and join our efforts in developing methodologies for monitoring, forecasting and mitigating its impacts.

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What is drought?

Animals die

overgrazing

Population growth

hail, cold rain

diseaseCrop failure

drought

armed conflicts

market problemsMalnutrition

grows

Food shortage

Armed conflicts

Market problems

drought

drought

disease

wrong crop type

drought

Drought – short term (end foreseen) – temporary deviation

Land degradation – long term - difficult to reverse

Treatment is much different

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Serious anomaly - Long duration

What is drought?

Drought is an extended period, during which, fresh water availability and accessibility for the ecosystem at a given time and place is below normal, due to unfavourable spatial and temporal distribution of rainfall, temperature, soil moisture and wind characteristics.

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region are:

•Rainfall amount

•Rainfall temporal distribution

•Soil moisture

•Soil moisture temporal distribution

•Temperature

•Temperature temporal distribution

•Wind characteristics

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How to measure the severity of drought?

Physical indices (water balance)Palmer’s Drought indices, namely, Palmer Drought Severity Index (PDSI), Palmer Hydrological Drought Index(PHDI), Palmer Z-index (PZI) and Crop Moisture Index (CMI)

Surface Water Supply Index (SWSI)

Reclamation Drought Index (RDI)

Statistical indexes (time series analysis)Percent Normal Drought Index (PNDI)

Standardized Precipitation Index (SPI)

Precipitation Decile Index

Weighted Anomaly Standardized Precipitation (WASP)

Drought indices analysed

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Multiple parameter

precipitation temperature soil moisture wind

Combined effect

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miVDImiTDImiPDImi VDIwTDIwPDIwCDI ,2,2,, ***

It is an index that measures how much the present conditions deviate from the reference level, which is the multi-year long-term average for a selected time duration (X dekads, Y months).

IP in the cessdeficit/excont oflength LTM

IP in the cessdeficit/excont oflength Actual*

IPfor LTM

IPfor average Actual DI

Step 1: Three different, individual drought indices are calculated, each reflecting the quantity deviation from LTM and the persistence of the deviation

Step 2: The combined effect is calculated in the CDI

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drought index

Temperature drought index

Vegetation drought index

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For more information please consult the CDIbrochure and the attached CDI calculator CD

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Kenyan stations

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Hargeisa

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

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4.5

1982 1983 1984 1985 1986 1987 1988 1989 1990 NO DATA 2005 2006 2007 2008 2009 2010

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(-) PDI VDI CDI Threshold

Baidoa

0.0

0.5

1.0

1.5

2.0

2.5

3.0

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4.5

5.0

1982 1983 1984 1985 1986 1987 1988 NO DATA 2004 2005 2006 2007 2008 2009 2010

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Afgooye

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1982 1983 1984 1985 1986 1987 1988 1989 1990 NO DATA 2005 2006 2007 2008 2009 2010

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Debrecen – Hungary, Europe

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CDI trends and comparison with drought reports 1

Year Month Kakamega Kisumu Lodwar Embu Dagoretti Wajiir Mandera County

Western Kenya North Kenya Central Kenya North East Kenya

1999 10 1.32 1 0.6 0.46 1.05 0.88 0.9 0.89

1999 11 1.08 0.9 0.69 0.81 1.21 0.65 0.78 0.87

1999 12 0.96 1.04 0.79 1.07 1.57 0.74 0.86 1

2000 1 0.77 1.06 0.71 1.37 1.47 0.9 1.06 1.05

2000 2 0.67 0.87 0.59 1.31 1.06 0.96 1.02 0.93

2000 3 0.42 0.68 0.42 0.64 0.58 0.63 0.61 0.56

2000 4 0.34 0.51 0.46 0.49 0.52 0.5 0.62 0.51

2000 5 0.49 0.49 0.33 0.31 0.51 0.34 0.89 0.56

2000 6 0.63 0.61 0.31 0.32 0.62 0.33 0.99 0.64 2000 7 0.75 0.82 0.25 0.34 0.67 0.45 1.53 0.86 2000 8 0.7 0.93 0.31 0.53 0.65 0.63 0.56 0.62 2000 9 0.6 0.95 0.36 0.65 0.66 1.22 0.42 0.66 2000 10 0.71 0.93 1.25 0.52 0.8 0.76 1.05 0.94

2000 11 0.86 1.12 1.77 0.48 0.72 0.53 1.09 1.03

2000 12 1.07 1.34 1.91 0.42 0.73 0.32 0.83 1

2001 1 1.33 1.91 1.55 0.68 1.42 0.34 0.45 1.1

2001 2 1.53 1.86 1.65 1.03 1.88 0.5 0.43 1.23

2001 3 1.14 1.3 1.7 1.34 2.57 0.85 0.61 1.36

Drought severity legend

         

Extreme

Severe

Moderate Mild None

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The CDI reflects: rainfall amount deficit and its critical duration

air temperature excess and its critical duration

NDVI deficit and its critical duration

It provides a time series of the indices that can be further analysed with statistical methods

Further research is suggested on

• Howe to use it for short time early warning

• How to extent it from point data series to spatial analysis

SUMMARY CONCLUSIONS ON CDI

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Somalia Water and Land Information Management System

Thank you for your attention