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A new signal processing approach was presented for acoustic emission source location using the dispersive waves in a thin plate. For wave propagation in dispersive media, the accuracy of source location can be improved by using the arrival times of a single frequency component in the output signals at an array of sensors. The wavelet transform (WT) was used to resolve this problem. By utilizing the time-frequency data of the WT, the frequency-dependent arrival time traveling with the group velocity was shown to be easily determined. Experiments were performed using a lead break as the simulated fracture source on the surface of an aluminum plate. Two plate modes corresponding to the S(0) and A(0) Lamb waves were identified, and their group velocities were accurately measured. The source location results based on the WT method agreed well with the true locations. The WT method was also compared with the cross correlation technique, and both methods provide similar results.

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Flood damage continues to be an issue in coastal cities. Impervious areas that contribute to flood damage are increasing due to the continuous development of ports in cities. However, previous research has not explored development in port hinterlands and in the coastal flood risk areas of coastal cities. Therefore, this study analyzed the impact of coastal city development on flood damage in Korea. A panel Tobit analysis was conducted on 58 coastal cities between 2002 and 2018. The results revealed that a 1% increase in impervious surfaces and one coastal development permit would increase damage costs by 1.29% and 2%, respectively. The analysis revealed that the increasing development of coastal cities had a significant impact on flood damage. The findings suggest that land-use plans highlight a conflict between port development and safety. This article provides insight that can be used by policy makers to manage risk areas near ports.

a b s t r a c tThis study used the United States Environmental Protection Agency's (US EPA) stormwater management model (SWMM) to quantify nonpoint source (NPS) pollutant load from the combined sewer in the Nakdong River basin, Korea. In the simulation using SWMM, the river basin consisted of 39 subwatersheds with 48 sanitation districts. For each sanitation district, combined sewer overflow (CSO) and bypass flow of the sewer treatment plant (STP) were estimated as NPS discharge. In the simulation, it assumed that a STP can receive up to three times the design peak flow rate of the STP and bypass the remainder of the intercepted stormwater during a storm event. The model was calibrated and validated with the observed water quantity and quality data in 2006 and 2007, respectively. As a result of the simulation, the estimated average load of biochemical oxygen demand (BOD) was 409.5 kg/ha/yr and 62.8 kg/ha/yr for the sanitation coverage (proportion of the area covered by the sewer system in a sanitation district) of above 40% and below 10%. The results showed that different unit loads of NPS can be estimated from each sanitation district depending on the degree of urbanization.

In recent, abnormal phenomena in nature occurs due to climate change, which result in increase of flood frequency and rainfall intensity by change of meteorologic and hydrological factors. Especially, flood inundation in urban watershed frequently happens on casualties expected and property damage. Scientific and technological adaptation are acutely needed for unexpected damage in nature, and that, it is considerably important to develop proper model of hydrological forecasting over the short periods and to build a real-time watershed monitoring system. One of important things for solving a variety of problems is to connect real-time watershed monitoring system with short term hydrologic forecasting model. In this research, Suyoung stream in Busan was determined as a study area. After that, real-time watershed monitoring system at ten minute interval has been established for flood warning and forecast in the field. The data from this system was applied to short-term hydrologic forecasting model based on the artificial neural network. When flood happens in urban, input data of forecasting model on each rainfall event was used. In conclusion, after establishing the model being possible to forecast water level from 10 to 60 minutes at 10 minute interval, as a result of simulating the model, the model performances are considerably good as RMSE 0.02~0.6 and R 2 more than 0.9. It makes possible effectively to manage the watershed in urban.

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