Dynamic geographic phenomena., e.g. forest fires and oil spills, can have dire environmental, sociopolitical, and economic consequences. Mitigating, if not preventing such events can be facilitated by the use of advanced spatiotemporal information systems. One system that has gained widespread interest is the wireless sensor network (WSN), a deployment of sensor nodes, tiny untethered computing devices, each of which runs on batteries and is equipped with one or more commercial off-the-shelf or custom-made sensors and a radio transceiver. In this dissertation, an algorithm is developed to detect specific topological events, called connectivity events, by a deployed WSN. After introducing the mathematical and technical preliminaries, connectivity events are defined, a completeness proof on connectivity events is provided, and a formal Petri net model is used to prove network-level properties. With this foundation, subroutines are developed that comprise a distributed event detection algorithm suitable for 2-dimensional (2d) or 3-dimensional (3d) deployments. The algorithm is based on formal concepts from a field of algebraic topology known as homology. The research presented focuses on incremental events, events resulting from the change of sensor status of a single node between two states of network operation, though simulations indicate that the algorithm can compute connectivity events arising from the change of sensor status of multiple nodes. The algorithm is validated through formal proofs and in WSN simulation and testbed environments. Results indicate the algorithm correctly computes an incremental event associated with a region comprised of n nodes in O(n) time, using O(n) storage, and O (n) data passed via messages, and only nodes in physical proximity to an event are tasked, thereby conserving network resources and allowing multiple disparate events to be simultaneously monitored.