How is the increasing uncertainty of water resources affecting food security in Sub-Saharan Africa? A case study of Malawi’s situation

This week I am going to talk about the economical effects of climate change in the agricultural sector. Achieving food security is one of the main goals for the sub Saharan countries governments. Although it is true that the agricultural output has improved due to the strong political commitment of investing in small-scale farming (Gathigah, 2012), achieving food security is becoming harder and harder. Climate change is one of the main reasons why this is happening. Rainfall volatility, one of the main effects of climate change, “threatens the production of the 93% of African agriculture that is rainfed” (Werner, K.,2015). Weather related production shortfalls and slow growth in agricultural production leads to price spikes contributing to food insecurity. Approximately 40% of Sub-Saharan African countries will be “at risk of significant declines in crop and pasture production due to climate change”(Ludi, 2009). As a result, millions of people are living under food insecurity that has resulted in millions of new environmental refugees in East African countries, which have devastating effects on the host regions (Werner, K.,2015).

The IFDRI (International Food Policy Research Institute) has carried out a study that assesses the economy wide effects of the floods and droughts in Malawi.

The study models scenarios for the impacts of both droughts and floods as well as mitigation options for both. In this entry I will explain how the study modelled the impacts of droughts and I will summarise the results in a simplified and clear way and next week that I will be talking about mitigation opportunities I will talk about the models that touch this aspect.

--> Introduction

Malawi is a small landlocked African country suffering frequent droughts and floods. It is their effect on agricultural production that is most detrimental to food-insecure Malawi. Agriculture and downstream agropocessing generate half of gross domestic product.

DGE models analyse the effect of droughts and floods with a focus on the agricultural sector. These models attach also a statistical probability of occurrence of each given severity. The analysis doesn't consider infrastructural losses associated with floods or the long-term implications of extreme weather events, such as the effects of soil erosion or changes in investment behaviour.

--> Drought and flood risk models

The RMSI models capture two dimensions of drought and flood impacts: Hazards and risk.

o   Hazard reflects the occurrence of an extreme climatic event. It is defined by the severity and the probability of an event’s occurring within a specific time period. Severity is measured in terms of the return period (RP). This is the expected length of time between recurrences of two events with similar characteristics. This means that a 1 in 5 year (RP5) is less severe than a RP15. Consequently, events with higher RPs are also less likely to occur.

o   Risk is the quantification of potential losses. It depends on the severity of the weather event, the location of the farmers and the cropping pattern.

The probability of a particular event occurring can be estimated on the basis of historical data. Production losses are calculated as the difference between observed production and expected production.

--> Economywide modelling framework

The following table summarises the structure of Malawi’s rural economy.

Table 1: Summary statistics by rural farm households in the economywide model

	Small-scale rural farmers	Medium-Scale rural farmers	Big-scale rural farmers
Population (millions)	3731	6240	363
Per capita expenditure (US dollars)	121,6	130,1	203,7
Poverty rate	61	55,6	30,6
Average farm land (ha)	0,69	1,44	8,02
--> Maize	0,36	0,70	3,67
--> Tobacco	-	0,03	1,79

-       Within crop agriculture, maize and tobacco are by far the most important.

-       Most farmers fall between the small and large-scale groups. About 55% of this population fall below the national poverty line, far above the poverty rate of small-scale farms and only slightly below that of small-scale farms.

--> The impact of national-level droughts and drought mitigation

·      Main assumptions

- The model includes only a single maize crop. Calculated by the average maize loss factor for each region using regional maize crop shares as weights.

- It doesn't consider infrastructural losses associated with floods
-It doesn't consider the long-term implications of extreme weather events

• Drought impacts

The following table shows the economic impact of droughts on maize and tobacco production and, by extension, on GDP. The general trend is that the more severe the drought, the larger the estimated loss in agricultural GDP. Since 2/5 of Malawi’s economy is in agriculture, the decline in agricultural GDP causes total GDP to fall substantially.

	Initial share (%)	RP5 drought	RP10	RP15	R25
Total GDP	100	-0.53	-3.48	-7.16	-10.42
Agriculture	40.15	-1.12	-7.27	-14.88	-21.53
--> Maize	10.02	-2.12	-15.88	-34.55	-51.24
--> Other food crops	14.18	-0.73	-5.33	-11.18	-16.12
--> Livestock	2.46	-0.45	-3.45	-7.87	-11.33
Industry	16.47	0.002	0.03	0.25	0.72
Services	43.38	-0.20	-1.31	-2.83	-4.36
Crop Agriculture
--> Small-scale	6.92	-1.49	-10.62	-22.31	-32.34
--> Medium-scale	17.25	-1.35	-9.43	-19.75	-28.66
--> Large-scale	10.24	-1.00	-4.63	-8.13	--11.24

*The "minus" values are calculated from the difference between the share in each scenario and the initial share 

There are 3 main points that can be extracted from these results:

1)   Agriculture crops in general, but mainly maize crops are very vulnerable to the severity of droughts. In the scenario of a 1-in-25 drought, the economic output from agriculture decreases by almost 22% (more than half of its initial share)

2)   The industry sector is positively affected by droughts. The reason behind this is that the exchange rate depreciates to favour exports and therefore, non-agricultural sectors see the demand for exporting their products increase and their share in GDP increases too.

3)   Small-scale farmers are the most affected by droughts. Total earnings generated fall by 32.34%. It is their grater reliance on maize production that makes smallholder farmers particularly vulnerable to droughts.