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The study was intended to determine whether the composition or distribution of humic substances from lake sediment could be characterized by spectroscopic data with chemometrics methods. The research materials were humic substances extracted from sediment samples collected in heavily polluted areas in Wuliangsuhai Lake. Humic substance extraction was performed using the method proposed by the International Humic Substances Society (IHSS). In extracted humic substances, the three-dimensional excitation–emission matrix (3DEEM) was determined, and parallel factor analysis (PARAFAC) with classification and regression trees (CART) and two-dimensional correlation spectra (2D-COS) was used to analyze spectroscopic data. Both the fulvic acid (FA) and the humic acid (HA) samples had five PARAFAC components (C1–C5), which contained Vis fulvic-like component (C1), Vis humic-like component (C2), UV humic-like component (C3), microbial fluorescent component (C4), and UV fulvic-like component (C5). This indicated the ubiquity of the humic substance components in the environment. For the CART analysis, C1 was the key factor used to differentiate FA and HA, while C1–C4 were the key parameters used to distinguish the humic substance samples in the eight units. Using 2D-COS and hetero 2D-COS, the PARAFAC components were formed with the increasing of sediment depth in the following order: C3 → C2 → C5 → C4 → C1, which suggested that the relatively labile structure appeared earlier than the relatively stable structure with the greater depth of the sediment. The Vis fulvic-like could be a key factor used to discriminate the FA and the HA fractions, while the latent factors of different depths of sediment were not identical. The order of the humic substance formations was Vis humic-like → UV humic-like → Vis fulvic-like → microbial fluorophore → UV fulvic-like.

Landscape patterns in a watershed potentially have significant influence on the occurrence, migration, and transformation of pollutants, such as nitrogen (N) and phosphorus (P) in rivers. Human activities can accelerate the pollution and complicate the problem especially in a peri-urban watershed with different types of land use. To characterize the heterogeneous correlations between landscape patterns and seasonal variations of N and P in a peri-urban watershed located upstream of Tianjin metropolis, China, observations of total nitrogen (TN) and total phosphorus (TP) at 33 locations were performed in the wet and dry seasons from 2013 to 2016. The data from individual locations were averaged for the wet and dry seasons and analyzed with geographical detector to identify influential landscape indices on seasonal water quality variations. The geographically weighted regression method, capable of analyzing heterogeneous correlations, was used to evaluate the integrated effects from different landscape indices. The results demonstrated that the location-weighted landscape contrast index (LWLI), the ratio of urban areas, and the ratio of forest areas were major influential indicators that affected TN and TP in river water. These indices also had integrated effects on variations of TN and TP together with other indices such as Shannon diversity index, landscape shape index, largest patch index, and contagion index. The integrated effects were different in the wet and dry seasons because of different effects of flushing and dilution by rainwater and the heterogeneity in landscape patterns. The LWLI had a positive relationship to water quality in the areas with high ratio of urban areas, indicating that domestic wastewater can be a major source of N and P pollution. The approaches and findings of this study may provide a reference for characterizing the major factors and integrated effects that control nonpoint source pollution in a watershed.

Nutrient discharge into peri-urban streams and reservoirs constitutes a significant pressure on environmental management, but quantitative assessment of non-point source pollution under climate variability in fast changing peri-urban watersheds is challenging. Soil and Water Assessment Tool (SWAT) was used to simulate water budget and nutrient loads for landscape patterns representing a 30-year progression of urbanization in a peri-urban watershed near Tianjin metropolis, China. A suite of landscape pattern indices was related to nitrogen (N) and phosphorous (P) loads under dry and wet climate using CANOCO redundancy analysis. The calibrated SWAT model was adequate to simulate runoff and nutrient loads for this peri-urban watershed, with Nash-Sutcliffe coefficient (NSE) and coefficient of determination (R2) > 0.70 and percentage bias (PBIAS) between −7 and +18 for calibration and validation periods. With the progression of urbanization, forest remained the main “sink” landscape while cultivated and urban lands remained the main “source” landscapes with the role of orchard and grassland being uncertain and changing with time. Compared to 1984, the landscape use pattern in 2013 increased nutrient discharge by 10%. Nutrient loads modelled under wet climate were 3–4 times higher than that under dry climate for the same landscape pattern. Results indicate that climate change could impose a far greater impact on runoff and nutrient discharge in a peri-urban watershed than landscape pattern change.

Carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) concentration, saturation and fluxes in rivers (Beitang drainage river, Dagu drainage rive, Duliujianhe river, Yongdingxinhe river and Nanyunhe river) of Tianjin city (Haihe watershed) were investigated during July and October in 2014, and January and April in 2015 by static headspace gas chromatography method and the two-layer model of diffusive gas exchange. The influence of environmental variables on greenhouse gases (GHGs) concentration under the disturbance of anthropogenic activities was discussed by Spearman correlative analysis and multiple stepwise regression analysis. The results showed that the concentration and fluxes of CO2, CH4 and N2O were seasonally variable with >winter>fall>summer, spring>summer>winter>fall and summer>spring>winter>fall for concentrations and spring>summer>fall>winter, spring>summer>winter>fall and summer>spring>fall>winter for fluxes respectively. The GHGs concentration and saturation were higher in comprehensively polluted river sites and lower in lightly polluted river sites. The three GHGs emission fluxes in two sewage draining rivers of Tianjin were clearly higher than those of other rivers (natural rivers) and the spatial variation of CH4 was more obvious than the others. CO2 and N2O air-water interface emission fluxes of the sewage draining rivers in four seasons were about 1.20-2.41 times and 1.13-3.12 times of those in the natural rivers. The CH4 emission fluxes of the sewage draining rivers were 3.09 times in fall to 10.87 times in spring of those in the natural rivers in different season. The wind speed, water temperature and air temperature were related to GHGs concentrations. Nitrate and nitrite (NO3-+NO2--N) and ammonia (NH4+-N) were positively correlated with CO2 concentration and CH4 concentration; and dissolved oxygen (DO) concentration was negatively correlated with CH4 concentration and N2O concentration. The effect of human activities on carbon and nitrogen cycling in river is great.