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The impact of water-related disasters has become more acute in cities of the Amazon Basin. Socio-economic impact assessments have a key role in improving sustainable mitigation projects in order to increase resilience and reduce societal vulnerability. This paper reviews the current state of loss assessments and then explores how to improve estimates for the 2015 flood affecting the city of Rio Branco, Brazil, located on the headwaters of the Amazon Basin. Prevailing models, loss assessments, and databases are not applicable in this Amazonian context due to the lack of detailed cost administration, low levels of human and financial capital, and limited insurance coverage. This paper uses uncertainty ranges of the costs of water-related disasters to provide an assessment of the total impact. Our estimate ranges from 60 to 200 million USD of losses and damage solely due to this flood event, compared to the official estimate of 98 million USD. As floods in Rio Branco are recurrent nearly annually, the cumulative losses over the years may be significantly higher. Our study illustrates the need for improving impact assessments in order to increase the knowledge on the actual costs of flood disasters and avoiding silent impoverishment. Outcomes of impact assessments can show the necessity of mitigation activities which will reduce vulnerability of societies.

Drought poses a major threat to food security and maintenance of rural populations in dry lands, because it leads to losses in agriculture and other productive sectors. Given the intensification and recurrence of drought events and their impacts, it is necessary to deepen our knowledge as a key to subsidize mechanisms for drought preparation and mitigation plans. Therefore, this study aimed to develop and apply methodologies for drought characterization and impact assessment, considering different agro-ecosystems and the impact on smallholder farmers. The new approach developed included as dataset LULC maps, the limits of rural properties, and the Vegetation Supply Water Index (VSWI) time series. The z-score was used in order to identify areas affected by droughts and a zonal statistic was used to compare the results of VSWI in a municipal and rural property scale. Afterwards, the areas identified as significant statistics were used to determine the LCLU and rural property most affected. The results of the analysis showed that Agricultural Lands were the most affected LULC during the study period (about 50%), whereas Micro and Small Properties were the most affected by droughts, over than 65% and 15% respectively. Besides, an important finding is that the analysis at the municipality or rural property levels can affect the drought assessment. This can result in an underestimated or overestimated of drought intensity and in the expansion of impacts. Thus, these results contribute to the local drought mitigation actions and help determine the threshold to better spatialize drought impacts on smallholder farming.