Application of an improved clustering approach on GPS height time series at CMONOC stations in Southwestern China

Abstract The hydrological, geological and meteorological conditions in southwestern China are relatively complex, so that the land surface deformation presents various features. Using 58 Crustal Movement Observation Network of (CMONOC) stations across four provinces Southwestern China, we adopt an improved clustering algorithm to classify 49 into 12 clusters with different similarity levels. Our results show average annual signals GPS within each cluster have strong consistency, while obvious differences exist among clusters, indicating helps describe features more accurately regions complex conditions. We then combine other earth observation techniques, such as Gravity Recovery Climate Experiment (GRACE) satellite datasets loading models (SLM), observe GPS, GRACE SLM correlation their monthly displacement series at stations. After excluding non-clustered according our previous results, coefficients GPS/GRACE GPS/SLM enhanced. Also, RMS reduction rates coordinate time been after deducting displacements obtained from SLM, thus proves be effective improving consistency three techniques joint detection deformation. Moreover, vertical riverside Three Gorges Reservoir (TGR) area significant negative water level TGR, hence conclude Dam (TGD) may directly affect its upstream downstream Graphical