This paper characterizes part of an interdisciplinary research effort on AI techniques applied to environmental decision-support systems. The architectural design of the OntoWEDSS decision-support system for wastewater management is presented. This system augments classic rule-based reasoning and case-based reasoning with a domain ontology, which provides a more flexible management capability to OntoWEDSS. The construction of the decision-support system is based on a specific case study. But the system is also of general interest, given that its ontology-underpinned architecture can be applied to any wastewater treatment plant and, at an appropriate level of abstraction, to other environmental domains. The OntoWEDSS system helps improve the diagnosis of faulty states of a treatment plant, provides support for complex problem-solving and facilitates knowledge modeling and reuse. In particular, the following issues are dealt with: (1) modeling information about wastewater treatment processes, (2) clarifying part of the existing terminological confusion in the domain, (3) incorporating ontology-modeled microbiologic knowledge related to the treatment process into the reasoning process and (4) creating a decision-support system that combines information through a novel integration between knowledge-based systems and ontologies.