Getting a better grip on sanitation systems: Introducing a numerical model to identify, predict and mitigate hazardous events and measure the safety of on-site sanitation systems

Of the world's population, 59% of the people are not connected to a sewer system and use on-site sanitation (OSS) systems. A large amount of these systems is unsafe. The ultimate goal of this research is to gain knowledge on manners to improve and monitor the safety of on-site sanitation (OSS) systems. The performance and safety of OSS systems are highly dependent on the level of faecal sludge in OSS system which is largely dependent on the accumulation rate of the sludge. However, scientists have not found a simple method to assess the accumulation rate of sludge. Knowing the sludge accumulation rate and therefore, knowing how quickly a tank fills, makes it possible to the necessary time between two emptying events or, with other words, the required emptying frequency. With the research presented in this thesis, a dynamical approach to viewing and assessing the status of OSS systems is developed in the form of a model by combining sludge accumulation theory and only a small number of in-field measurements. The modelled simulation of sludge accumulation shows highly similar results to empirical sludge accumulation studies. On the basis of the model, also a user-friendly tool has been developed that allows tank owners, policymakers or regulators to get personal recommendations regarding the emptying frequency of their OSS systems. This offers a new approach and with that an improvement of the way OSS system can be safely managed and monitored. This thesis provides evidence for the feasibility of constructing a numerical model as a measure to simulate sludge accumulation in OSS systems that can lead to emptying frequency recommendations. The results of this thesis can help in obtaining safe sanitation throughout the world and is aimed to contribute to achieving the United Nation’s Sustainable Development Goal 6.2