Groundwater contamination can be hard to diagnose quickly when sources are hidden underground. We develop a new framework that integrate multiple search chains in two stages: first they scan widely using an evolutionary algorithm, then they cooperate to refine source locations with Tabu Search. Fast surrogate models replace part of the time-consuming simulations. In case studies, this approach identifies source information more accurately and saves substantial computing time.