Study of Non-Point Pollution in the Ashe River Basin Based on SWAT Model with Different Land Use

Pollution load estimation and influencing factor analysis in the Tuhai River Basin in Shandong Province of China based on improved output coefficient method

Estimating the pollution loads in the Tuhai River is essential for developing a water quality standard scheme. This study utilized the improved output coefficient method to estimate the total pollution loads in the river basin while analyzing the influencing factors based on the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model. Findings indicated that the projected point source pollution loads for total phosphorus (TP), chemical oxygen demand (COD), and ammonia nitrogen (AN) would amount to 3937.22 ton, 335,523.25 ton, and 13,946.92 ton in 2021, respectively. Among these, COD pollution would pose the greatest concern. The primary contributors to the pollution loads were rural scattered life, large-scale livestock and poultry breeding, and surface runoff. Per capita GDP emerged as the most influential factor affecting the pollution loads, followed by cultivated land area, while the urbanization rate demonstrated the least impact.

Spatial Pattern Evolution and Influencing Factors on Agricultural Non-Point Source Pollution in Small Town Areas under the Background of Rapid Industrialization

To promote sustainable agricultural development in small town areas during rapid industrialization, it is important to study the evolution of agricultural non-point source pollution (ANSP) and its influencing factors in small town areas in the context of rapid industrialization. The non-point source inventory method was used to study the characteristics of ANSP evolution in 14 small town areas in Gongyi City from 2002 to 2019. Using the spatial Durbin model and geographical detectors, the factors influencing ANSP in small town areas were analyzed in terms of spatial spillover effects and the spatial stratified heterogeneity. The results showed a zigzagging downward trend of ANSP equivalent emissions over time. Spatially, the equivalent emissions of ANSP showed a distribution pattern of being high in the west and low in the east. There was a significant positive global spatial autocorrelation feature and there was an inverted "U-shaped" Environmental Kuznets Curve relationship between industrialization and ANSP. Affluence, population size, and cropping structure positively contributed to the reduction of ANSP. Population size, land size, and industrialization were highly influential factors affecting the spatial variation of ANSP and the interaction of these factors was bivariate or nonlinearly enhanced. This study provides a feasible reference for policymakers and managers to develop reasonable management measures to mitigate ANSP in small town areas during rapid industrialization.

Ecological health evaluation of rivers based on phytoplankton biological integrity index and water quality index on the impact of anthropogenic pollution: A case of Ashi River Basin

Based on the phytoplankton community matrices in the Ashi River Basin (ASRB), Harbin city, we developed an evaluation method using the phytoplankton index of biotic integrity (P-IBI) to evaluate ecological health while investigating the response of P-IBI to anthropogenic activities. We compared the effectiveness of P-IBI with that of the water quality index (WQI) in assessing ecological health. Between April and October 2019, phytoplankton and water samples were collected at 17 sampling sites in the ASRB on a seasonal basis. Our results showed that seven phyla were identified, comprising 137 phytoplankton species. From a pool of 35 candidate indices, five critical ecological indices (Shannon–Wiener index, total biomass, percentage of motile diatoms, percentage of stipitate diatom, and diatom quotient) were selected to evaluate the biological integrity of phytoplankton in the ASRB. The ecological status of the ASRB as measured by the P-IBI and WQI exhibited a similar spatial pattern. It showed a spatial decline in ecological status in accordance with the flow of the river. These results highlighted that P-IBI was a reliable tool to indicate the interaction between habitat conditions and environmental factors in the ASRB. Our findings contribute to the ecological monitoring and protection of rivers impacted by anthropogenic pollution.