# Precise Positioning of BDS, BDS/GPS: Implications for Tsunami Early Warning in South China Sea
## 1 Introduction  
As one of the most devastating natural coastal disasters, tsunamis are triggered mostly by shallow earthquakes in submarine subduction zones [1] producing the most damage in the near field but also propagating basin-wide. Consequently, traditional Tsunami Early Warning Systems (TEWS) mainly rely on seismic methods in order to evaluate source parameters (magnitude, epicenter) and forecast tsunamis as soon as possible. Corresponding seismic instrumentation mainly includes broadband seismometers as well as strong-motion sensors (accelerometers). Despite the fact that these traditional techniques have proved their reliability for most historical cases over the last decades, they have failed to provide correct rapid magnitude estimation for several important events like the 2004 Mw = 9.3 Great Sumatra earthquake, the 2010 Mw = 7.8 Mentawai tsunami earthquake and the 2011 Mw = 9.0 Great Tohoku event. For example, in the latter case, the true magnitude was significantly underestimated during the fifty minutes after the earthquake [2]. Magnitude underestimation, in turn, may result in the underestimation of the tsunami forecast in the near field [2]. The reasons for magnitude underestimation during the first several minutes after large earthquakes vary for different seismic instruments as well as earthquake evaluation procedures. Broadband seismometers saturate near the source in case of strong shaking so that the full rupture image can be analyzed only at larger epicentral distances, causing unavoidable delay due to the finite speed of seismic wave propagation. Strong motion sensors, in turn, do not saturate by amplitude and can be employed close to the source; however, the usual band-pass filtering of waveforms aimed to avoid processing unambiguity caused by co-seismic tilting [3] effectively leads to magnitude saturation due to removal of long periods which are essential for huge earthquakes [4]. See, for example, [2, 5] regarding the analysis of the strong-motion magnitude saturation during the Great Tohoku earthquake. The 2004 Great Mw = 9.3 Sumatra earthquake and tsunami boosted the development of new seismic approaches that are aimed toward the faster and more reliable characterization of tsunamigenic earthquakes. During the GITEWS Project (German-Indonesian Tsunami Early Warning System), [PERSON] and [PERSON] [6] proposed a fast, non-saturating cumulative magnitude estimator based on the P-wave train. The procedure was tested at epicentral distances starting from \(5^{\circ}\) and is currently operated by the INATEWS (Indonesian Tsunami Early Warning System) [7]. Additionally, [PERSON] and [PERSON] [8] suggested a new broadband W-phase source inversion algorithm, which is currently running in operation at PTWC (Pacific Tsunami Warning Center). During the 2011 Great Mw = 9.0 Tohoku event, this algorithm automatically detected the focal mechanism and came with magnitude estimate of Mw = 8.8 22 min after the earthquake (the true magnitude Mw = 9.0 was estimated 40 min after the earthquake) [9]. Another approach was suggested by [PERSON] and [PERSON] [10], who introduced an original duration-amplitude procedure to estimate the tsunamigenic potential of earthquakes. Significant efforts were also undertaken to improve the quality of real-time strong-motion data processing. New studies [4, 11, 12] proposed fast and effective procedures for automatic base-line correction. Furthermore, the novel technique of collocation of strong-motion and GPS sensors [13, 14] should help to overcome the problem of magnitude saturation since the band-pass filtering is no longer required [15]. Rapid improvement of the real-time GPS processing precision put GPS-technology at the front end of current progress in the earthquake and tsunami early warning system. Compared with seismic approaches, continuous GNSS real-time data processing provides arbitrary ground displacements that can be directly inverted into source parameters in (near-) real time.