A　novel　integrated　optimization　methodology　of　global　optimization(genetic　algorithm)and　local(quasi-Newton　algorithm)optimization　for　robust　and　rapid　parameter　estimation　in　the　initial　ODEs(ordinary　differential　equations)systems　was　proposed,　and　it　is　of　the　advantages　of　both　algorithms.　This　methodology　was　used　successfully　to　estimate　the　parameters　for　dynamic　variation　process　of　dissolved　oxygen(DO)in　the　two-step　nitrification　model　suggested,　and　a　high　correlation　coefficient　was　reached　0.9955.Accuracy　assessment　for　the　results　estimated　was　realized　based　on　a　comparison　of　the　confidence　regions　with　those　determined　by　Fisher　information　matrix　and　exact　directly　search.　The　assessment　results　indicated　that　using　this　method　most　of　the　parameters　in　the　two-step　model　could　be　reliably　estimated　and　only　two　did　not,　showing　that　it　could　be　a　novel　inspection　method　for　parameter　estimation　of　dynamic　system.　Furthermore,　DO　simulation　results　could　be　employed　as　a　tool　of　soft　measurement,　which　could　provide　some　process　information　about　rapid　degradation　of　COD,　oxygen　uptake　rate,　ammonia,　nitrite　and　nitrate　in　the　two-step　nitrification　model　and　related　parameters　estimated　from　DO　data.　©　All　Rights　Reserved.