Geotechnical Reconnaissance of the 2016 ML6.6 Meinong Earthquake in Taiwan

On February 6, 2015, a local magnitude (M_L) 6.6 earthquake struck southern Taiwan, devastating the Tainan area. A field investigation was conducted by a survey team from the National Center for Research on Earthquake Engineering immediately after the earthquake. This paper summarizes the observed geotechnical damage features caused by the earthquake, including liquefaction, slope sliding, levee failure, and dam performance. Several liquefaction sites were observed despite the intensity of ground shaking being moderate (peak ground acceleration, ~0.2 g). Most of these sites were originally old ponds that were backfilled during different periods in the last three to eight decades. Two significant types of damage to the levee of the Tseng-wen River were observed. At the Jianshan site, a typical type of levee damage was observed, in which the level crest subsided and the side slope developed several cracks. At the Rixin site, a flow-type of failure caused tremendous loss of levee (~400 m in total) at three adjacent locations. The levee embankments had “flowed” up to 60 m into the river.     

The Location Invariance Theorem in Weberian Space Under Uncertainty

This paper examines the validity of the location invariance theorem in Weberian space under various types of uncertainty. The main results are: Given that the firm's location is constrained to remain at a specified distance from the output market, the optimal location is invariant to any change in product demand if and only if the production function is homothetic for a firm facing demand price uncertainty, or if the production function is homothetic and both inputs are risk-neutral for a firm facing technological uncertainty. Alternatively, given that the distance from the firm's location to the output market is a variable, location invariance occurs for a firm facing demand price uncertainty if the production function is linear homogeneous. In the presence of input price uncertainty the optimal location always varies with a change in product demand. The results can include those previously obtained for linear stochastic location models as special cases and some are new contributions to the literature.