Stream water quality and its influencing factor in lower order streams in upriver sections of Ashihe River

For understanding the reasons that caused the degradation of water quality in lower order streams, systematic sampling was conducted at different spatial locations aiong the low order streams （1 st-5th） of Ashihe River continuum in Maoershan Experimental Forest of Northeast Forestry University, Sharlgzhi City, Heilongjiang Province, China. The indexes of stream water quality, i.e., the pH, dissolved oxygen（DO）, turbidity, temperature, PO43-P, NO3-N and NH4^＋-N concentrations, total dissolved inorganic nitrogen （TDIN-N, including concentrations of NO3^＋-N and NH4^＋-N）, and total phosphorus （inorganic and organic phosphorous, TP） were measured and analyzed. The stream order, related environmental settings and land-use type were recorded for each sampling location. The indexes of stream water quality at different locations with different stream orders and land use types were compared by ANOVA analysis. The indexes of stream water quality at different sampling locations were analyzed by Hierarchical cluster analysis. Result showed that water quality had significant difference in different stream orders and land use types; some locations with different stream features （stream order and land use type） were grouped into same clusters, indicating that random disturbances produced the variations in water quality, which made the spatial variances of stream water quality inconsistent with the general rules.

Exploring the Linkage between Land Use Type and Stream Water Quality of an Estuarine Island Applying GWR Model: A Case Study of Chongming, Shanghai

To understand the spatial correlations between land use type and water quality of an estuarine island is particularly essential to maintain its original ecological environment. Chongming Island is experiencing a rapid urbanization and agriculture land sprawl during the last decades, especially with the growth of agro-industry and the extension of old style residences. As a consequence, surface run-off from agricultural activities and domestic sewage discharge has a various linkage with stream water quality on the island. This study applied ageographical weight regression model approach to recognize the significance of the relationship between water quality and multiple land use. We also evaluated their spatial correlations which normally hidden from other traditional regression methods. The results reveal that the water quality of less-developed areas on Chongming Island was easily affected by land use types compared with other regions, TN, TP, BOD5, COD were shown as the most significant responses among all the water quality indicators. Green land and water area had a reduced effect on nutrients, expansion of industrial land would continuously make a contribution of pollutants to the water environment. Suggestions should therefore be taken into consideration during the process of development planning, in order to prevent water contamination.

QoE Assessment and Prediction Method for HighDefinition Video Stream Using Image Damage Accumulation

The accuracy of the traditional assessment method of the quality of experience(Qo E) has been facing challenges with the growth of high-definition(HD) video streaming services.Image display-quality damage is the main factor that affects the Qo E in HD video services through UDP network transmission.In this paper,we introduce a novel objective factor known as image damage accumulation(IDA) to assess user's Qo E in HD video services.First,this paper quantitatively analyzed the effect on user quality of experience by IDA and established a mapping relationship between mean opinion scores and IDA.Furthermore,the probability of image damage caused by compression and transmission were analyzed.Based on this analysis,an objective Qo E assessment and prediction method for HD video stream service that evaluated the user experience according to IDA are proposed.The proposed method can achieve assessment and prediction accuracy on three distinct subjective tests.