# 4 Conclusions

Tanzania’s economy is highly sensitive to climate. The national costs of climate-related hazards are estimated to be around 1% of GDP in recent years. With projected climate change impacts – higher temperatures and more unpredictable and concentrated rainfall - net economic costs due to climate change could reach 2 to 3% of GDP per year by 2030. Flooding is estimated to be the costliest hazard at the national level, causing 62% of losses from natural disasters from 1990 to 2014.<sup>36</sup> While the costs are unknown, flooding presents an economic burden for households. Studies estimating the impacts of climate hazards in Dar es Salaam have found that the city has infrastructure assets worth approximately US$5.3 billion at potential risk from projected flood impacts under climate change and sea level rise scenarios (Kebede and Nicholls, 2010). At the household level, the poor are disproportionately affected by flooding, and often do not have the means to recover. This study is an attempt to quantify the impacts for households living in Dar es Salaam both inside and outside known flood risk areas. It also sheds light on the characteristics of affected households and helps us understand the policy relevant link between poverty and flood exposure.

The impacts of floods on households in Dar es Salaam are more wide-spread and costly than previous evidence suggests. Urbanization and lack of investments in infrastructure have transformed the city into a place where families that used to not worry about floods are having their dwellings flooded every year. Families report that the situation continues to get worse. Female headed households, that face particular challenges, are more likely to live in areas affected by floods. Poorer people are particularly at risk of both direct and indirect impacts. The flood that affected Dar es Salaam in April 2018 was not a particularly severe event in terms of casualties and did not receive much attention outside Tanzania. Nonetheless, it affected 38% of the population and cost households an estimated US$110 to US$228 million, representing about 2-4% of the city’s GDP.

On average, affected households lost about 23% of their annual income due to the flood in April 2018. Asset losses represent 77% of total losses. The second largest source of losses were housing repairs. Consequently, to understand the impact of floods on households, it is necessary to assess asset losses and not only housing damage, highlighting potential flaws in the traditional modeling of disaster losses.

Losses caused by indirect impacts, including health and labor, are monetarily small but have large effects on well-being. A conclusion from the focus group discussions with affected households is that the welfare effects of illness and labor are not well-captured in monetary terms. For households living in areas affected by flood risk, health impacts tend to be highlighted as the worst, and missing work is associated with increased stress and fear of losing current and future income. Women are more likely than men to miss work due to floods. No support from the government is available to the households to deal with these losses that for many households happen repeatedly.

Informal support and financing are helping households to cope with the costs of floods – but it is not enough. Poorer households are less likely to have recovered from being affected by floods. However, access to informal sources of finance, including community saving groups, seems to help households recover. While community saving groups are a positive tool to assist households with recovery, the instrument is not ideal for dealing with aggregate shocks. When many members are affected at the same time, it puts strains on the

> 36 PreventionWeb, accessed 19 February 2019.

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