Virtual Huanghe River System： Framework and Technology

1 Introduction Huanghe (Yellow) River basin is located in 32°–42°N, 96°–119°E. The area of the catchment is more than 752,000km2. The river is 5464km long with a drop in elevation of 4830m. Among the whole area, the moun- tainous and stone area accounts for 29%, loess and hills area 46%, sandy area 11% and plain area 14%, respec- tively. Different natural landscapes exist in this area. The Huanghe River flows through the Loess Plateau, where the soil is eroded seriously (Wang, 2002;…     

SDSS J143030.22-001115.1： A Misclassified Narrow-line Seyfert 1 Galaxy with Flat X-ray Spectrum

We used multi-component profiles to model the Hβ and [OⅢ]λλ4959,5007 lines of SDSS J143030.22-001115.1, a narrow-line Seyfert 1 galaxy (NLS1) in a sample of 150 NLS1 candidates selected from the Sloan Digital Sky Survey (SDSS), Early Data Release (EDR). After subtracting the Hβ contribution from narrow line regions (NLRs), we found that its full width half maximum (FWHM) of broad Hβ line is nearly 2900km s~(-1) , significantly larger than the customarily adopted criterion of 2000 km s~(-1) . With its weak Fe Ⅱ multiples, we believe that SDSS J143030.22-001115.1 should not be classified as a genuine NLS1. When we calculate the virial black hole masses of NLS1s, we should use the Hβ linewidth after subtracting the NLR component.     

Study of a model for correcting the effects of horizontal advection on surface fluxes measurement based on remote sensing

As well known, the methods of remote sensing and Bowen Ratio for retrieving surface flux are based on energy balance closure; however, in most cases, surface energy observed in experiment is lack of closure. There are two main causes for this: one is from the errors of the observation devices and the differences of their observational scale; the other lies in the effect of horizontal advection on the surface flux measurement. Therefore, it is very important to estimate the effects of horizontal advection quantitatively. Based on the local advection theory and the surface experiment, a model has been proposed for correcting the effect of horizontal advection on surface flux measurement, in which the relationship between the fetch of the measurement and pixel size for remote sensed data was considered. By means of numerical simulations, the sensitivities of the main parameters in the model and the scaling problems of horizontal advection were analyzed. At last, by using the observational data acquired in agricultural field with relatively homogeneous surface, the model was validated.

     

The grain-size characteristics of Quaternary deposits at Xingshan near Siping in Jilin province, China

This research paper analyses the grain-size characteristics of the Quaternary deposits at Xingshan near Siping, Jilin province in China by employing graphic measures to study the grain size distribution and its mode of transport and deposition. The Quaternary deposits at Xingshan lie unconformable on Cretaceous rocks made of siltstone, mudstone and sandstone. The average grain size is between 8.06 to 8.55Φ (0.002 6 ～0.003 7 mm). The Quaternary deposits at Xingshan mainly compose of very fine silt to clay. The compositions of the grade are clay 63% and silt 37%. The clay size components are weathered debris transported and deposited by flowing water from the SE highlands or hills to the low lying NW Xingshan plains whereas the silty components accumulated by aoelian process. The Quaternary deposits at Xingshan accumulated in the middle and late Pleistocene interglacial periods from (459.12～39.03) ka to (88.92～7.56) ka. The standard deviation ranged from 0.96 to 1.36Φ, indicating that the sediments are moderately to poorly sorted, Coefficient of skewness ranged from 0.16～0.31 with an average skewness of 0.218, (Positively skewed towards fine). Kurtosis values (0.84～1.05) from the grain size distribution and visual inspection of the frequency curves indicate platykurtic to mesokurtic curves and unimodal to bimodal grain-size distribution. The type of deposit formation is sand dune and the source is at a distal from its provenance.     

ANALYSIS OF DRIVING FORCES ON THE CHANGE OF HISTORICAL FARMLAND USE IN SHANDONG PROVINCE DURING THE QING DYNASTY （1644-1911）

How land-cover has been changed by human use over the last 300 years is one of the five overarching questions guiding the Land-use/Cover Change (LUCC) Science/Research Plan. China has variety of historical docu-ments providing unique data superiority. So the characteristics of farmland area in Shandong Province during the Qing Dynasty (1644-1911) are summarized firstly: 1) the rising trend of farmland area was striking; 2) farmland area had re-markable fluctuation; 3) farmland area per capita decreased dramatically; 4) wasteland reclamation index increased rapidly. Then, the driving forces of farmland area change are analyzed. It is concluded that natural and human factors are jointly influential. Among the driving forces, human dimensions are the main factors of farmland area change,which direct the general tendency of the changes mentioned above. And the natural factors influence the stability of farmland area as well. Variation of the natural factors would act as the major contributory factor to farmland area change during years or periods of abrupt climatic changes, or during the intensive occurring periods of natural hazards.Besides, the passive aspects of human factors, such as war chaos also influenced the fluctuation of the farmland area.This research indicates that it is feasible to study the land-use/cover change by Chinese historical literatures, which has huge potential to provide a comprehensive picture of the growing dominance of human land-use and land-cover pat-terns that can be used in many global change research oroiects.     

SIMULATION AND PREDICTION OF DEBRIS FLOW USING ARTIFICIAL NEURAL NETWORK

Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural haz-ard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting de-bris flow have been proposed, however, the accuracy of these methods is not high enough for practical use because of the stochastic and non-linear characteristics of debris flow. Artificial neural network has proven to be feasible and use-fill in developing models for nonlinear systems. On the other hand, predicting the future behavior based on a time se-ries of collected historical data is also an important tool in many scientific applications. In this study we present a three-layer feed-forward neural network model to forecast surge of debris flow according to the time series data collect-ed in the Jiangjia Ravine, situated in north part of Yunnan Province of China. The simulation and prediction of debris flow using the proposed approach shows this model is feasible, however, further studies are needed.     

Application of Grain Size Analysis to Study Sedimentary Environment of Sand Dune in the Vicinity of Tumen River

The dunes in estuary of Tumen River in China lie to the area between the Jiushaping and Fangchuan in the left bank of Tumen River (Fig.1). The dis-tance is about 15～20 km between the dunes and the coast. It ranges from China to D. P. R. Korea and Russia. The range of the height of dunes is about 15～20 m and the width is 100～200 m. By the re-connaissance, we protracted 9 section planes of the dunes and collected 40 sand samples of the dunes, and identified the sedimentary environment …