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Parameter uncertainty involved in hydrological and sediment modeling often refers to the parameter dispersion and the sensitivity of the parameter. However, a limitation of the previous studies lies in that the assignment of range and specification of probability distribution for each parameter is usually difficult and subjective. Therefore, there is great uncertainty in the process of parameter calibration and model prediction. In this study, the impact of probability parameter distribution on hydrological and sediment modeling was evaluated using a semi-distributed model—the Soil and Water Assessment Tool (SWAT) and Monte Carlo method (MC)—in the Daning River watershed of the Three Gorges Reservoir Region (TGRA), China. The classic types of parameter distribution such as uniform, normal and logarithmic normal distribution were involved in this study. Based on results, parameter probability distribution showed a diverse degree of influence on the hydrological and sediment prediction, such as the sampling size, the width of 95% confidence interval (CI), the ranking of the parameter related to uncertainty, as well as the sensitivity of the parameter on model output. It can be further inferred that model parameters presented greater uncertainty in certain regions of the primitive parameter range and parameter samples densely obtained from these regions would lead to a wider 95 CI, resulting in a more doubtful prediction. This study suggested the value of the optimized value obtained by the parameter calibration process could may also be of vital importance in selecting the probability distribution function (PDF). Such cases, where parameter value corresponds to the watershed characteristic, can be used to provide a more credible distribution for both hydrological and sediment modeling.

A three-dimensional flow-sediment model of the Wuhan portion of the Yangtze River was developed using the EFDC (Environmental Fluid Dynamic Code) in order to study the changing riverbed. The model was also calibrated and validated by daily measuring of the water surface elevation and using suspended sediment concentration data secured from June 1 to September 30, 2004. Based on this model, the mobile sediment on the riverbed was simulated for the high water period of the Yangtze River. The results indicate that erosion is the main issue, with maximum erosion (0.27m) occurring at the banks of Tian Xingzhou. In addition, according to a suspended sediment concentration analysis for the Han Kou Hydrologic Station section of the river, the concentration there increased from left bank to right bank.

With frequent disastrous weathers and increasingly prominent GHG effects in recent years, normal existence and development of mankind are facing unprecedented threats and challenges. GHG emissions mitigation for the global climate changes has been the focus of concern of the world. As the biggest developing country and the second largest country of carbon-emission, China attaches importance to the carbon emission reduction. The major GHG component is carbon dioxide and in China, the emission of carbon dioxide is mainly from industrial production. In the paper, the status and trend of Co2 emission from industrial departments, high-carbon emission and its specific industries are shown in statistics. Meanwhile, the policy environment, industrial organization structure and technology of carbon high emission are all discussed based on practical situations in these departments and industries. At the end, through the analysis of gray correlation, correlativity is explored for both fossil energy consumpt...

Based on Remote Sensing (RS), Geographical Information Systems (GIS), and the Spatial Principal Component Analysis (SPCA) method, the integrated assessment and changes in the ecological environment of Daning River Watershed are studied in this paper. The watershed is located in the Three Gorge Area in China. The result of the integrated assessment showed that level 9 had the biggest proportion in the year 1990, which was about 40%. In the year 2000, however, there were no levels with a proportion significantly bigger than the others. By comparing the assessment results in 1990 and 2000, it is discovered that the ecological environment in Daning River Watershed in 1990 was better than that in 2000.

A new method, node ordinal encoded genetic algorithm (NOEGA), is proposed for solving water resources optimal allocation problems, in which the capacity of water resources is split into a number of smaller parts so that successive operations can be overlapped. Our objective is to maximize the whole benefit function. To overcome the “dimensionality and algorithm complexity curse” while searching for solutions and looking for an optimal solution, the operations of ine-point crossover operator, gene exchange operator, gene random operator, gene shift operator and node ordinal strings are established. It is proved to be an effective optimal method in searching for global solutions. The NOEGA does not need a diversity of initial population, and it does not have the problem of immature convergence. The results of two cases show that using NOEGA to solve the optimal allocation model is very efficient and robust. In addition, the algorithm complexity of NOEGA is discussed. ∗Supported by National Natural ...