Detecting the region of emergent events is an important application of wireless sensor networks. In recent years, research on fault-tolerant event region detection algorithms becomes a hot topic. By assuming that the occurrence of an event is spatially correlated, previous work distinguish fault and event by exchanging readings among neighboring sensors. Considering that in many cases, an event is both spatially and temporally correlated, this paper proposes a distributed and localized algorithm for fault-tolerant event region detection. Aiming at reducing the network traffic, this algorithm determines a faulty sensor by using statistical hypothesis test for matching the reading sequence of sensors and statistical characters of the event. The analysis shows that the proposed algorithm is more energy-efficient than existing ones. The simulation results show that the algorithm can detect as much as 93% of the event region and 88% of faults, when 10% of sensors are faulty. ; Department of Computing