The traditional ＂dephase and sum＂ algorithms for over/under data combination estimate the ghost operator by assuming a calm sea surface. However, the real sea surface is typically rough, which invalidates the calm s...The traditional ＂dephase and sum＂ algorithms for over/under data combination estimate the ghost operator by assuming a calm sea surface. However, the real sea surface is typically rough, which invalidates the calm sea surface assumption. Hence, the traditional ＂dephase and sum＂ algorithms might produce poor-quality results in rough sea conditions. We propose an adaptive over/under data combination method, which adaptively estimates the amplitude spectrum of the ghost operator from the over/under data, and then over/under data combinations are implemented using the estimated ghost operators. A synthetic single shot gather is used to verify the performance of the proposed method in rough sea surface conditions and a real triple over/under dataset demonstrates the method performance.展开更多
The impact of land-use on surface runoff and soil erosion is still poorly understood at basin scale. Thus in the Western Jilin Ecosystem (WJE), surface runoff and soil erosion were measured against identified land-use...The impact of land-use on surface runoff and soil erosion is still poorly understood at basin scale. Thus in the Western Jilin Ecosystem (WJE), surface runoff and soil erosion were measured against identified land-use types in the basin. Due to the spatial nature of the analysis, GIS ArcMap version 9.1 and the WetSpass model were used in the simulation process. In the study, the WetSpass model was extended with the Dynamic Sediment Balance Equation (Ziegler et al., 1997), to simulate and quantify soil erosion. A hypothetical natural grassland scenario was developed for the study area and compared with the present land-use management conditions. The results indicate significant differences in runoff and soil erosion across the different land-use types both within and between the two scenarios. Calculated averages of surface runoff and soil erosion for the present land-use management were 48.03 mm/a and 83.43 kg/(m 2·a) respectively. Those for the hypothetical natural grassland scenario were 24.70 mm/a and 78.36 kg/(m 2·a) . Thus an overall decrease in runoff and soil erosion was observed as the conditions changed from the present land-use management to the hypothetical natural grassland state. Under the present land-use management, urban settlements exhibited the highest surface runoff but one of the least soil erosions, while bare-lands showed the highest soil erosion. It was more generally observed that runoff and erosion varies with vegetation type/density. It was concluded based on the research findings that the present land-use management might not be the best scenario for the ecosystem as it showed increased basin runoff and soil erosion in comparison with the natural grassland vegetation. Since no best scenario was simulated for or advanced in the study, further research to develop a more balanced land management system is thus required. The findings of the study can assist in the identification of vulnerable/fragile ecosystems in the basin and to guide sustainable future planning and development of the basin.展开更多
文摘The traditional ＂dephase and sum＂ algorithms for over/under data combination estimate the ghost operator by assuming a calm sea surface. However, the real sea surface is typically rough, which invalidates the calm sea surface assumption. Hence, the traditional ＂dephase and sum＂ algorithms might produce poor-quality results in rough sea conditions. We propose an adaptive over/under data combination method, which adaptively estimates the amplitude spectrum of the ghost operator from the over/under data, and then over/under data combinations are implemented using the estimated ghost operators. A synthetic single shot gather is used to verify the performance of the proposed method in rough sea surface conditions and a real triple over/under dataset demonstrates the method performance.
文摘The impact of land-use on surface runoff and soil erosion is still poorly understood at basin scale. Thus in the Western Jilin Ecosystem (WJE), surface runoff and soil erosion were measured against identified land-use types in the basin. Due to the spatial nature of the analysis, GIS ArcMap version 9.1 and the WetSpass model were used in the simulation process. In the study, the WetSpass model was extended with the Dynamic Sediment Balance Equation (Ziegler et al., 1997), to simulate and quantify soil erosion. A hypothetical natural grassland scenario was developed for the study area and compared with the present land-use management conditions. The results indicate significant differences in runoff and soil erosion across the different land-use types both within and between the two scenarios. Calculated averages of surface runoff and soil erosion for the present land-use management were 48.03 mm/a and 83.43 kg/(m 2·a) respectively. Those for the hypothetical natural grassland scenario were 24.70 mm/a and 78.36 kg/(m 2·a) . Thus an overall decrease in runoff and soil erosion was observed as the conditions changed from the present land-use management to the hypothetical natural grassland state. Under the present land-use management, urban settlements exhibited the highest surface runoff but one of the least soil erosions, while bare-lands showed the highest soil erosion. It was more generally observed that runoff and erosion varies with vegetation type/density. It was concluded based on the research findings that the present land-use management might not be the best scenario for the ecosystem as it showed increased basin runoff and soil erosion in comparison with the natural grassland vegetation. Since no best scenario was simulated for or advanced in the study, further research to develop a more balanced land management system is thus required. The findings of the study can assist in the identification of vulnerable/fragile ecosystems in the basin and to guide sustainable future planning and development of the basin.
