Analysis of Jiangsu Tidal Flats Reclamation from 1974 to 2012 Using Remote Sensing

Jiangsu has the most abundant tidal flat resources among China's coastal provinces.To ease the conflict between the growing population and shrinking usable land and to promote regional sustainable development,large-scale coastal reclamation development activities have been performed in Jiangsu Province since 1949.The present study has integrated multi-source remote sensing images during 1974 to 2012 by using a Multi-point Fast Marching Method(MFMM) to extract the Jiangsu coastal reclamation areas for different time periods.The temporal and spatial patterns of the extent and elevation of the reclamation areas were analysed in order to determine the unused potential for future reclamation.It will provide information necessary to support the development and construction of tidal flats in Jiangsu.Results show that:(1) the reclaimed tidal flats along the Jiangsu coast cover more than 19.86×104 hm2,of which 13.97×104 hm2 is located in Yancheng,4.84×104 hm2 in Nantong,and 1.05×104 hm2 in Lianyungang;(2) the average elevation of the reclaimed Jiangsu tidal flats has gradually decreased over the last 40 years,while those in Dongtai and Rudong have showed particularly accelerated decrease since the 1990s;and(3) in 2012,very few unused tidal flats two meters above the sea level are left along the Jiangsu coast,and mainly concentrated in Yancheng.As there are still reserving some coastal land resources between 0-2 m,providing us with a potential for future development.All of these findings may be useful for researchers and local authorities for the development and utilization of tidal flat resources in Jiangsu.     

Piecewise prediction model for watershed‐scale erosion and sediment yield of individual rainfall events on the Loess Plateau,China

Establishing a universal watershed‐scale erosion and sediment yield prediction model represents a frontier field in erosion and soil/water conservation. The research presented here was conducted on the Chabagou watershed, which is located in the first sub‐region of the hill‐gully area of the Loess Plateau, China. A back‐propagation artificial neural model for watershed‐scale erosion and sediment yield was established, with the accuracy of the model, then compared with that of multiple linear regression. The sensitivity degree of various factors to erosion and sediment yield was quantitatively analysed using the default factor test. On the basis of the sensitive factors and the fractal information dimension, the piecewise prediction model for erosion and sediment yield of individual rainfall events was established and further verified. The results revealed the back‐propagation artificial neural network model to perform better than the multiple linear regression model in terms of predicting the erosion modulus, with the former able to effectively characterize dynamic changes in sediment yield under comprehensive factor conditions. The sensitivity of runoff erosion power and runoff depth to the erosion and sediment yield associated with individual rainfall events was found to be related to the complexity of surface topography. The characteristics of such a hydrological response are thus closely related to topography. When the fractal information dimension is greater than the topographic threshold, the accuracy of prediction using runoff erosion power is higher than that of using runoff depth. In contrast, when the fractal information dimension is smaller than the topographic threshold, the accuracy of prediction using runoff depth is higher than that of using runoff erosion power. The developed piecewise prediction model for watershed‐scale erosion and sediment yield of individual rainfall events, which introduces runoff erosion power and runoff depth using the fractal information dimension as a boundary, can be considered feasible and reliable and has a high prediction accuracy. Copyright © 2013 John Wiley & Sons, Ltd.     

Estimation of Elastic Stress-Related Properties of Bottom Sediments via the Inversion of Very- and Ultra-High-Resolution Seismic Data

Izvestiya, Atmospheric and Oceanic Physics - This paper provides an overview of several seismic inversion approaches and their application to very- and ultra-high-resolution marine seismic...     

Exploring the interaction of surface roughness and slope gradient in controlling rates of soil loss from sloping farmland on the Loess Plateau of China

Surface roughness and slope gradient are two important factors influencing soil erosion. The objective of this study was to investigate the interaction of surface roughness and slope gradient in controlling soil loss from sloping farmland due to water erosion on the Loess Plateau, China. Following the surface features of sloping farmland in the plateau region, we manually prepared rough surfaces using four tillage practices (contour drilling, artificial digging, manual hoeing, and contour plowing), with a smooth surface as the control measure. Five slope gradients (3°, 5°, 10°, 15°, and 20°) and two rainfall intensities (60 and 90 mm/hr) were considered in the artificial rainfall simulation experiment. The results showed that the runoff volume and sediment yield increased with increasing slope gradient under the same tillage treatment. At gentle slope gradients (e.g., 3° and 5°), the increase in surface roughness prevented the runoff and sediment production, that is, the surface roughness reduced the positive effect of slope gradient on the runoff volume and sediment yield to a certain extent. At steep slope gradients, however, the enhancing effect of slope gradient on soil erosion gradually increased and surpassed the reduction effect of surface roughness. This study reveals the existence of a critical slope gradient that influences the interaction of surface roughness and slope gradient in controlling soil erosion on sloping farmland. If the slope gradient is equal to or less than the critical value, an increase in surface roughness would decrease soil erosion. Otherwise, the increase in surface roughness would be ineffective for preventing soil erosion. The critical slope gradient would be smaller under higher rainfall intensity. These findings are helpful for us to understand the process of soil erosion and relevant for supporting soil and water conservation in the Loess Plateau region of China.