Drought affects not only water availability but also agriculture, the economy, and communities. This study explores how public policies help reduce these impacts in Ceará, Northeast Brazil. Using qualitative drought monitoring data, interviews, and policy analysis, we found that policies supporting local economies help lessen drought effects. However, most reported impacts are still related to water shortages, showing the need for broader strategies beyond water supply investment.

To reduce the consequences of landslides due to rainfall, such as loss of life, economic losses, and disruption to daily living, this study describes the process of building a machine learning model which can help to estimate the volume of landslide material that can occur in a particular region, taking into account antecedent rainfall, soil characteristics, type of vegetation, etc. The findings can be useful for land use management, infrastructure design, and rainfall disaster management.