Quantifying the magnitude of an earthquake is very important for long-term and medium-term earthquake prediction,post-earthquake emergency rescue and seismic hazard assessment.Paleoseismology is the investigation of past earthquakes in the geological record,in particular their location,timing and size. Uncertainties remain in the paleoearthquake magnitudes determined by traditional surface rupture parameters,especially because most seismic events do not result in surface ruptures. This study is in order to address the problem of magnitudes evaluation of earthquakes that did not reveal major dislocations.Methods: This paper deals with the methods used to determine the seismic shaking based on the types and forms of soft- sediment deformation structures, including, maximum liquefaction distance, thickness of disturbed layer, empirical formulae, and thickness of rapidly- deposited sand layer. Then discuss and analyze these methods in terms of their theoretical basis, advantages and disadvantages, accuracy, applicability and problems. We chose two case studies: first, a typical seismics-related deposit (liquefied layer and dsirupted layer) represented by a seismite in the late-Pleistocene Lake Lisan section near Masada in the Dead Sea Basin; and second, the liquefied diapir triggered by an earthquake in the Luobozhai late-Quaternary lacustrine sediments in the upper reaches of the Minjiang River, east Tibet.Results: The six methods listed above are employed to determine earthquake magnitudes associated with the seismics- related deposit and liquefied diapir, yielding magnitudes of M 5.5~6.5 and M 6.0~7.0, respectively. Conclusions: The combination of the six methods, provided a new and relatively convenient method for determining seismic shaking, especially in lacustrine sediments. This study can serves as a valid reference for comparing methods of calculating the magnitude of a paleoearthquake based on surface rupture parameters, and provides a better understanding of the long-term seismic activity and risk in tectonically active regions.