Flood is known to be the leading cause of natural disasters globally leaving disastrous and devastating damages in its wake. Flood risk and their time of occurrence is usually difficult to monitor and predict without appropriate tools for continuous monitoring. Extreme and frequent rainfall is one of the major causes of flood disasters. Assessment of flood hazards and its subsequent analysis using the standardized precipitation index (SPI) is very effective in the prediction of flood risk with the strength of the SPI being the use of rainfall as the only input variable. The SPI is found to be valuable in prediction of meteorological and hydrological floods such as flash floods, groundwater floods and dam burst. The knowledge of the occurrence of these flooding events can be very beneficial in preventing extensive damages to property, infrastructure, agriculture, and loss of life. The aim of this study is to assess flood hazard in eThekwini metropolitan area by examining the trend of flood events from 1985 to 2016 by the use of the SPI and its potential to predict flood risk in the study area. The results show that SPI properly explains the development of the conditions leading up to the occurrence of floods events in the analyzed period. Thus, is indispensable in the assessment of flood risk leading to an accurate prediction. The knowledge of the pattern and trends obtained from the SPI analysis is valuable to decision‐makers for efficient flood risk management plans in the promotion of preventive actions for mitigating the impacts of floods.

Freshwater resources remain under constant pressure due to population growth, economic development, and changing weather patterns. Water supply utilities generally struggle to keep up with the growing demand for freshwater resources and consequently adopt demand management policies to address supply challenges. As water consumers, households can play a major role in water conservation. This paper examines the impact of biographic characteristics on water consumption behaviour and the adoption of water-efficient technologies in the city of Durban, South Africa. Probit regression models are estimated using survey data collected from 300 household heads sampled across the city. Among other results, the study finds income as the most consistent determinant of water consumption behaviours and the adoption of water-efficient technologies. Furthermore, the level of education was also found to be a consistent determinant of the adoption and installation of water-efficient technologies. These results are significant and serve to guide water utilities when implementing demand management water policies.