Water Quality Analysis of Fuping Section of the Shichuan River Based on Different Evaluation Methods

In order to study the water quality of the Shichuan River basin in Fuping,Shaanxi Province,based on improved Nemerow index method,comprehensive pollution index method and principal component analysis method,eight water quality indexes such as pH,dissolved oxygen(DO),total dissolved solids(TDS),COD,total hardness,total phosphorus,total nitrogen and Zn in three monitoring sections of Fuping section of the Shichuan River in Shaanxi Province were detected and analyzed.The results show that the water quality of the surface water in the Shichuan River basin is gradeⅢorⅣwater,that is,the water is slightly polluted and moderately polluted.It is necessary to monitor the water quality after regulation and clarify the main factors causing the water pollution.

An improved particle tracking velocimetry(PTV) technique to evaluate the velocity field of saltating particles

Velocity is a key parameter characterizing the movement of saltating particles. High-speed photography is an efficient method to record the velocity. But, manually determining the relevant information from these photographs is quite laborious. However, particle tracking velocimetry（PTV） can be used to measure the instantaneous velocity in fluids using tracer particles. The tracer particles have three basic features in fluids： similar movement patterns within a small region, a uniform particle distribution, and high particle density. Unfortunately, the saltation of sand particles in air is a stochastic process, and PTV has not yet been able to accurately determine the velocity field in a cloud of blowing sand. The aim of the present study was to develop an improved PTV technique to measure the downwind（horizontal） and vertical velocities of saltating sand. To demonstrate the feasibility of this new technique, we used it to investigate two-dimensional saltation of particles above a loose sand surface in a wind tunnel. We analyzed the properties of the saltating particles, including the probability distribution of particle velocity, variations in the mean velocity as a function of height, and particle turbulence. By automating much of the analysis, the improved PTV method can satisfy the requirement for a large sample size and can measure the velocity field of blowing sand more accurately than previously-used techniques. The results shed new light on the complicated mechanisms involved in sand saltation.