Nonpoint Source Pollution (NPSP) Induces Structural and Functional Variation in the Fungal Community of Sediments in the Jialing River, China

Nonpoint source pollution (NPSP) from human production and life activities causes severe destruction in river basin environments. In this study, three types of sediment samples (A, NPSP tributary samples; B, non-NPSP mainstream samples; C, NPSP mainstream samples) were collected at the estuary of the NPSP tributary of the Jialing River. High-throughput sequencing of the fungal-specific internal transcribed spacer (ITS) gene region was used to identify fungal taxa. The impact of NPSP on the aquatic environment of the Jialing River was revealed by analysing the community structure, community diversity and functions of sediment fungi. The results showed that the dominant phylum of sediment fungi was Rozellomycota, followed by Ascomycota, Chytridiomycota, Basidiomycota, Mortierellomycota and Zoopagomycota (relative abundance>1%). NPSP caused a significant increase in the relative abundances of Rozellomycota, Saccharomycetes, Microascales, Saccharomycetales, Branch02 and Branch03. In addition, it caused a significant decrease in the relative abundances of Chytridiomycota, Dothideomycetes, Capnodiales, Glomerellales, Xylariales and Chaetothyriales. Moreover, NPSP caused significant changes in the physicochemical properties of Jialing River sediments, such as pH and available nitrogen (AN), which significantly increased the species richness of fungi and caused significant changes in the fungal community β-diversity (P<0.05). pH, total phosphorus (TP) and AN were the main environmental factors affecting fungal communities in Jialing River sediments. The functions of sediment fungi mainly involved three types of nutrient metabolism (symbiotrophic, pathotrophic and saprotrophic) and 75 metabolic circulation pathways. NPSP significantly improved the NONOXIPENT-PWY, PENTOSE-P-PWY, and PWY-6837 metabolic circulation pathway functions (P<0.05) and inhibited the PWY-7118, PWY-5920, and PWY-6609 metabolic circulation pathway functions (P<0.05). Hence, NPSP causes changes in the community structure and functions of sediment fungi in Jialing River and destroys the stability of the Jialing River Basin ecosystem.

Validation of an In-Situ Observation Method for Nonpoint Source Pollution in Paddy Fields: A Case Study of a Beijing Paddy Field

A Beijing paddy field, along with in-situ experiments, was used to validate and refine the in-situ observation (IO) method to describe nonpoint source pollution (NPS) in paddy fields. Based on synchronous observed rainfall, water depth, and water quality data at two locations (1# (near inlet) and 2# (near outlet)) with large elevation differences, the evapotranspiration and infiltration loss (ET+F), runoff depth and NPS pollution load were calculated according to IO, and a common method was used to calculate ET+F. Then, the results of the different methods and locations were compared and analyzed. The results showed that 1# observation point was located at a lower position compared with 2# observation point. According to 1# observation point, there were 5 days of dry field in the drying period, which was consistent with the actual drying period, and there was a dry period of 9 days based on 2# observation point. The ET+F estimated by IO fit well with the calculated values. In the experiment, 6 overflows and 1 drainage event were identified from the observed data at locations 1# and 2#. The relative deviation of the NPS pollution of total nitrogen (TN), total phosphorus (TP), chemical oxygen demand (COD), nitrate-nitrogen (NO3−-N) and ammonia nitrogen (NH4+-N) was between 0.6% and 2.0%. The water level gauge location had little influence on IO but mostly affected the water depth observations during the field drying period. The mareographs should be installed in low-lying paddy field areas to monitor water depth variation throughout the whole rice-growing season.

Development and Assessment of a New Framework for Agricultural Nonpoint Source Pollution Control

The transport of agricultural nonpoint source (NPS) pollutants in water pathways is affected by various factors such as precipitation, terrain, soil erosion, surface and subsurface flows, soil texture, land management, and vegetation coverage. In this study, based on the transmission mechanism of NPS pollutants, we constructed a five-factor model for predicting the path-through rate of NPS pollutants. The five indices of the hydrological processes, namely the precipitation index (α), terrain index (β), runoff index (TI), subsurface runoff index (LI), and buffer strip retention index (RI), are integrated with the pollution source data, including the rural living, livestock and farmland data, obtained from the national pollution source census. The proposed model was applied to the headwater of the Miyun Reservoir watershed for identifying the areas with high path-through rates of agricultural NPS pollutants. The results demonstrated the following. (1) The simulation accuracy of the model is acceptable in mesoscale watersheds. The total nitrogen (TN) and total phosphorus (TP) agriculture loads were determined as 705.11 t and 3.16 t in 2014, with the relative errors of the simulations being 19.62% and 24.45%, respectively. (2) From the spatial distribution of the agricultural NPS, the TN and TP resource loads were mainly distributed among the upstream of Dage and downstream of Taishitun, as well as the towns of Bakshiying and Gaoling. The major source of TN was found to be farmland, accounting for 47.6%, followed by livestock, accounting for 37.4%. However, the path-through rates of TP were different from those of TN; rural living was the main TP source (65%). (3) The path-through rates of agricultural NPS were the highest for the towns of Wudaoying, Dage, Tuchengzi, Anchungoumen, and Huodoushan, where the path-through rate of TN ranged from 0.17 to 0.26. As for TP, it was highest in Wudaoying, Kulongshan, Dage, and Tuchengzi, with values ranging from 0.012 to 0.019. (4) A comprehensive analysis of the distribution of the NPS pollution load and the path-through rate revealed the towns of Dage, Wudaoying, and Tuchengzi as the critical source areas of agricultural NPS pollutants. Therefore, these towns should be seriously considered for effective watershed management. In addition, compared with field monitoring, the export coefficient model, and the physical-based model, the proposed five-factor model, which is based on the path-through rate and the mechanism of agricultural NPS pollutant transfer, cannot only obtain the spatial distribution characteristics of the path-through rate on a field scale but also be applicable to large-scale watersheds for estimating the path-through rates of NPS pollutants.