Africa RiskView END OF SEASON REPORT | (2020)

This Africa RiskView End of Season Report is a publication by the African Risk Capacity (ARC). The report discusses Africa RiskView’s estimates of rainfall, drought and population affected, comparing them to information from the ground and from external sources. It also provides the basis of a validation exercise of Africa RiskView, which is conducted in each country at the end of an insured season. This exercise aims at reviewing the performance of the model and ensuring that the country’s drought risk is accurately reproduced by Africa RiskView for drought monitoring and insurance coverage. The End of Season reports are also being continuously refined with a view to providing early warning to ARC member countries.

Highlights:

Rainfall: Affected Populations: • The 2019/20 agricultural season was characterized by below • Africa RiskView estimated the total number of people affected normal and erratic rainfall. The average total rainfall amount by drought encountered in the 2019/20 agricultural season at received for the season was well below normal for the entire around 4.65 million. , Mashonaland East, Mashona- country. Some of the districts in southern and central parts of land Central, Mashonaland West and Manicaland provinces the country such as Masvingo and southern parts of Midlands are estimated to have the highest numbers of people affected did not have a sowing chance – as per the predefined criteria by drought. These estimates are consistent with the IPC pro- in Africa RiskView. jection of food insecure people for the duration Feb to June 2020 in Zimbabwe.

Drought: Risk Pool • Most of the districts had an end-of-season WRSI value well • Due to the overall poor performance of the season in most below average of the last ten years average – the reference parts of the country, a pay-out was triggered from ARC Ltd used for comparison of the current season. Significantly lower since the estimated number of people affected by drought WRSI values compared to the average of the last ten years exceeded the attachment selected by the country. Pay-out of were observed in the southern parts of the country. Some of about $1.47 million and $290,000 was triggered for the main the districts in southern and central parts of the country re- Government and WFP-Replica policies respectively. corded WSRI values of zero as they did not have any sowing opportunities within the sowing window.

Rainfall the TWG and the end of the season - covering a period between 2nd dekad of October and 1st dekad of June. The Africa RiskView drought risk customisation review process was completed in October 2019. The customisation was meant to The 2019/20 agricultural season was generally characterized by follow the progress of crop conditions in Zimbabwe and provide below normal rainfall in all the . Overall, the the basis for potential participation in ARC’s risk transfer pool. The average cumulative rainfall amount received between mid- start of the sowing window for the reference crop selected October and early May was 76% of the long-term average i.e. (maize) varies across provinces in Zimbabwe. Similarly, the length average for the years 2001 to 2019. The cumulative rainfall totals of the growing period is different among alternative seed varieties varied significantly across the country from as low as 317mm in and agro-ecological zones. As a result, district-specific sowing start to as high as 642mm in (see Fig. 1). The southern dates and length of the growing period have been adopted based regions receiving slightly better rainfall than the rest of the coun- on data received from relevant government departments. The try with Bulilima, Chivi, Mangwe, Matobo, Mwenezi, and rainfall performance analysis in this subsection, therefore, dwells Provinces receiving 80%, 81%, 81%, 83%, 87%, 88% and on the period between the earliest sowing date - as defined by 96% respectively of the normal rainfall (see Fig. 2). , Goromonzi, , and Provinces, were

For more information visit our website: www.africanriskcapacity.org Africa RiskView END OF SEASON REPORT | ZIMBABWE (2020) particularly dry receiving 52%, 59%, 61%, 62% and 63% respective- 2019/2020 rainfall season, with sufficient rain to support early ly, of normal rainfall (see Fig. 2). crop development beginning in the 32nd dekad in most Provinces, apart from southern parts of Matabeleland North and isolated Sowing in Africa RiskView is triggered when the country-specific areas in parts of Western Matabeleland South which had suffi- dekadal rainfall criterion is met. This criteria for Zimbabwe require cient rain occurring in the 31st dekad (see Fig. 3). The Province of at least one dekad within the sowing window in which a minimum Masvingo did not satisfy the sowing criteria at all. of 20mm of rainfall is received, followed by 5mm of rainfall in two subsequent dekads following the first. The findings of Africa RiskView have been confirmed by other reports. ZimVAC has reported that the spatial and temporal Conditionally, if this sowing criterion is not met, it is assumed that distribution of the rainfall ranged from poor to very poor across farmers would not have planted, or would have had unsuccessful the whole country. The SADC January Agromet2 Update also planting. Additionally, the “First” sowing opportunity aggregation suggests that rainfall for October 2019 to late-January 2020 method was assumed to model farmers' response to sowing period has been well below average for Zimbabwe and historical chances. According to this assumption, farmers are expected to analysis indicates that in most parts of the region, the October- take advantage of the first sowing opportunity when and if real- to-December 2019 period was one of the 10 driest seasons since ized. Zimbabwe experienced a delayed onset at the start of the 1981.

Fig 1: Cumulative rainfall (mm), dekad 29(Oct 11) – dekad 13 Fig 2: Cumulative rainfall (mm), compared to normal dekad 29 (May 10), Zimbabwe (RFE 2) (Oct 11) – dekad 13(May 10), Zimbabwe (RFE 2)

Fig 3: Sowing opportunities, Zimbabwe, 2019/20 agricultural sea- Fig 4: Projected end-of-season WRSI, Zimbabwe, dekad 29(Oct 11) – son. dekad 13(May 10), 2019/2020 agricultural season.

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Fig 5: Projected end-of-season WRSI, dekad 29(Oct 11) – dekad 13 Fig 6: Estimated population affected by drought, Zimbabwe, (May 10), compared to normal (Average of 2001-2019) 2019/20 agricultural season

Drought Africa RiskView uses the Water Requirement Satisfaction Index (WRSI) as an indicator of drought. WRSI is an indicator of crop performance based on the availability of water to the crop during a growing season. The index captures the impact of timing, amount and distribution of rainfall on staple annual rain-fed crops. The WRSI was initially developed by the Food and Agricul- ture Organisation of the United Nations (FAO), which, based on rainfall, calculates whether a particular crop’s water require- ments are met at different stages of its development. In Zimba- bwe, maize has been used as a reference crop and parameters in Africa RiskView have been customised to reflect the local condi- tions and agricultural practices. Fig 7: Estimated population affected by drought, Zimbabwe, 2001- 2019 In terms of adequacy and spatial distribution of rainfall received within the sowing window, Africa RiskView reveals that the crop Compared to the normal WRSI values (average of 2001-2019), water requirements for Maize, vary greatly in Zimbabwe. The end end-of-season WRSI in most parts of Zimbabwe was between -of-season WRSI values were mediocre in much of central and 70% and 110% of the normal (see Fig. 5), indicating average south Zimbabwe, while some of the districts in southern and growing conditions . While the eastern parts of Manicaland and central parts of the country recorded WSRI values of zero as they southern and central regions of Matabeleland South had above did not have any sowing opportunities within the sowing window, benchmark WRSI conditions at the end of the 2019/20 agricul- especially districts in the provinces of Masvingo where rainfall tural season. In line with the Africa RiskView findings, the Fam- sowing criteria was not met (see Fig. 4). Northern, eastern and ine Early Warning Systems Network (FEWS NET) reported that western Zimbabwe exhibits somewhat better WRSI values rang- rainfall levels across most of the country were below the long- ing from good to very good. term average, adversely affecting on-farm activities.

For more information visit our website: www.africanriskcapacity.org Africa RiskView END OF SEASON REPORT | ZIMBABWE (2020) Affected Populations 2020 which is a close match to the Africa RiskView estimate of Based on the customisation of Africa RiskView, around 9.3 mil- the number of people affected by drought encountered in the lion people are estimated as vulnerable to drought in Zimbabwe. 2019/20 agricultural season. However, we ought to note that Of these, the model estimates that around 4.65 million people food insecurity is driven by several factors whereas the estimates are affected by drought conditions at the end of the 2019/20 in Africa RiskView are limited to drought and as such, the esti- season. These are located mostly in Manicaland (565,834 peo- mates of Africa RiskView are only comparable when drought is ple), Mashonaland Central (586,412 people), Mashonaland East the main driving factor of food insecurity. (776,252 people) Mashonaland West (521,324 people), Masvin- ARC Risk Pool go, (1,272,072 people), Matabeleland North (184,910.00 people), This is the first year Zimbabwe participated in the ARC Risk Pool. Matabeleland South (404,632 people) and Midlands (338,109 During the current pool, the country did receive a payout, given people), as illustrated in Figure 7. Compared to historical drought that the attachment level selected by the Government of Zimba- years modelled by Africa RiskView, the number of people esti- bwe and the Replica partner (WFP), the equivalent of around mated as affected in the 2019/20 season is well above the 2.88 million drought-affected people as modelled by Africa attachment point of around 2.88 million people set by the coun- RiskView was reached. The pay-out is about $1.47 million and try. The Integrated Food Security Phase Classification (IPC) $290,000 to the government and the WFP respectively. reports estimates that more than 4.34 million people in Zimba- bwe are in Crisis (IPC Phase 3) or worse from February to June

Fig 8: Temporal distribution of rainfall in during the Fig 9: Temporal distribution of rainfall in Harare during the 2019/20 rain season 2019/20 rain season

Fig 10: Temporal distribution of rainfall in Manicaland during Fig 11: Temporal distribution of rainfall in Mashonaland Central the 2019/20 rain season during the 2019/20 rain season

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Fig 12: Temporal distribution of rainfall in Mashonaland East Fig 13: Temporal distribution of rainfall in Mashonaland West during the 2019/20 rain season during the 2019/20 rain season

Fig 14: Temporal distribution of rainfall in Masvingo during the Fig 15: Temporal distribution of rainfall in Matabeleland North 2019/20 rain season during the 2019/20 rain season

Fig 16: Temporal distribution of rainfall in Matabeleland South Fig 17: Temporal distribution of rainfall in Midlands during the during the 2019/20 rain season 2019/20 rain season

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About ARC: The African Risk Capacity (ARC) is a special- The Africa RiskView software is the tech- The ARC Insurance Company Limited is the ised agency of the African Union designed nical engine of ARC. It uses satellite-based financial affiliate of the ARC Agency, which to improve the capacity of AU Member rainfall information to estimate the costs of pools risk across the continent through issu- States to manage natural disaster risk, responding to a drought, which triggers a ing insurance policies to participating coun- adapt to climate change and protect food corresponding insurance payout. tries. insecure populations.

Note on Africa RiskView’s Methodology:

Rainfall: Africa RiskView uses Drought: Africa RiskView uses Affected Populations: Based on Response Costs: In a fourth and various satellite rainfall da- the Water Requirements Satis- the WRSI calculations, Africa final step, Africa RiskView con- tasets to track the progression faction Index (WRSI) as an indi- RiskView estimates the number verts the numbers of affected of rainy seasons in Africa. Coun- cator for drought. The WRSI is of people potentially affected people into response costs. For tries intending to participate in an index developed by the Food by drought for each country countries participating in the the ARC Risk Pool are required and Agriculture Organisation of participating in the insurance insurance pool these national to customise the rainfall com- the United Nations (FAO), pool. As part of the in-country response costs are the underly- ponent by selecting the dataset which, based on satellite rain- customisation process, vulnera- ing basis of the insurance poli- which corresponds the best to fall estimates, calculates wheth- bility profiles are developed at cies. Payouts will be triggered the actual rainfall measured on er a particular crop is getting the sub-national level for each from the ARC Insurance Compa- the ground. the amount of water it needs at country, which define the po- ny Limited to countries where different stages of its develop- tential impact of a drought on the estimated response cost at ment. To maximise the accura- the population living in a spe- the end of the season exceeds a cy of Africa RiskView, countries cific area. pre-defined threshold specified intending to take out insurance in the insurance contracts. customise the software’s pa- rameters to reflect the realities on the ground.

Disclaimer: The data and information contained in this report have been developed for the purposes of, and using the methodology of, Africa RiskView and the African Risk Capacity Group. The data in this report is provided to the public for information purposes only, and neither the ARC Agency, its affil- iates nor each of their respective officers, directors, employees and agents make any representation or warranty regarding the fitness of the data and information for any particular purpose. In no event shall the ARC Agency, its affiliates nor each of their respective officers, directors, employees and agents be held liable with respect to any subject matter presented here. Payouts under insurance policies issued by ARC Insurance Company Limited are calculated using a stand-alone version of Africa RiskView, the results of which can differ from those presented here.

For more information visit our website: www.africanriskcapacity.org