New method for scaling nonpoint source pollution by integrating the SWAT model and IHA-based indicators.

Nonpoint source (NPS) pollution shows spatial scaling effects because it is affected by topography, river networks, and many other factors. Currently, the lack of an integrated methodology for quantifying the scaling effect has become a crucial barrier in evaluating NPS pollution. In this study, a new method was proposed for scaling NPS pollution by integrating hydrological model and hydrological alteration indicators. Nested catchments were delineated by eight-direction algorithm, and a semidistributed hydrological model was used to simulate the interannual process within the drainage area and to obtain data series of runoff, sediment, and total phosphorus (TP) at different spatial scales. In addition, the average, the extrema, the change rate and feature variables of each type of indicators were proposed to quantitatively describe the pattern of NPS pollution at different spatial scales. The results show the coefficients of variation (CVs) of most runoff and TP indicators are 0.6-0.8, while those of sediment vary greatly from 0.4 to 1.6 with the threshold of those indicators being 0.33. With the increase in drainage area, the NPS load-related indicators show an increasing trend, while load intensity indicators show a decreasing trend and their changing patterns are affected by the heterogeneity of topographic or hydrological information included. Based on logarithmic variance of the change rate, 825 km2 was identified as the turning point for scaling transformation where the slope changes dramatically. The proposed methodology comprehensively describes features of the NPS scaling effect that could be utilized for targeted monitoring and control of NPS pollution in other watersheds.

Copula-based analysis of socio-economic impact on water quantity and quality: A case study of Yitong River, China.

Socio-economic development has a significant impact on both water quantity and quality. However, few studies have considered the complex relationship between water quantity and quality when evaluating such impact. In this study, three indicators based on copula model were proposed, namely, water quantity improvement degree (WQIDw), water quality improvement degree (WQIDq) and water quantity and quality joint improvement degree (WQJID). These indicators were used to assess the impact of social economy on water quantity and quality, and applied to a case study in Yitong River in Northeast China from 2021 to 2025. Four scenarios were set to explore the impact of socio-economic development and water resources protection on WQIDw, WQIDq and WQJID. The maximum WQIDw, WQIDq and WQJID were <1 under the business-as-usual scenario, which showed that the present socio-economic pattern caused great damage to river water quantity and quality. The combined effect of socio-economic development and water resources protection increased the WQJID of COD and NH3-N by 1.67 and 1.30. This showed that attention should be paid to water resources protection while developing social economy. Compared with comprehensive evaluation, separate evaluation of water quality will underestimate the impact of social economy on rivers, while separate evaluation of water quantity will overestimate the impact. The relationships between WQIDw, WQIDq and WQJID were quantified. Meanwhile, the uncertainty of the evaluation was controlled by the selection of water quality indicators. The WQIDq, WQIDw and WQJID proposed in this study provide a comprehensive assessment tool for guiding water resources management.

[Simulation of Pollution Apportionment and Optimization of Control Methods in Watershed Scale: A Case Study of the Shun'an Watershed in Tongling City].

The protection of the Yangtze River is an important national strategy in China, but it faces many problems such as difficult water environment protection, unclear pollution sources, and low integration of measures. Aimed at addressing watershed scale multi-source pollution together with facing the bottleneck method, by combining research data analysis, mechanism model, and intelligent algorithm optimization, this study built the framework for accurate pollution apportionment, measures evaluation, and overall measure optimization. Shun'an watershed in Tongling City of Anhui Province was set as an example for the application. The results showed that the new method could accurately quantify the impacts of planting industry, rural life, livestock and poultry breeding, aquaculture, industrial sewage, and domestic sewage in the watershed and evaluate the overall effects of various measures. The multi-objective optimization algorithm provided a cooperative multi-source pollution control scheme with higher cost performance and better environmental benefit by comparing the cost effectiveness of various schemes systematically. The optimization scheme showed that total nitrogen could be reduced by 1274.24 t·a-1 in wet years, 855.24 t·a-1 in normal years, and 381.96 t·a-1 in dry years. Total phosphorus was reduced by 321.42 t·a-1 in wet years, 159.80 t·a-1 in normal years, and 42.93 t·a-1 in dry years, such that the water quality reached the surface class Ⅲ water quality standard. These research results can be extended to other watersheds and provide a method reference for water environment protection under the background of the high-quality development of watersheds.

A water quality management methodology for optimizing best management practices considering changes in long-term efficiency.

Optimizing long-term best management practices (BMPs) is of vital importance for water quality management, especially for nonpoint source (NPS) pollution. However, changes in the efficiency of BMPs over time have not been incorporated and a proper method for determining long-term BMP configuration strategies is still lacking. In this study, the long-term BMP optimization method (LBMP-OM) was developed for recommending the BMP maintenance-replacement strategies and optimizing the BMP configuration. This new method was then tested in the Daning Watershed, Three Gorges Reservoir Region, China. Based on the results, a 1-year maintenance period and a 3-year replacement period was recommended for a filter strip by considering a changing BMP effectiveness rather than a constant effectiveness and by discussing the rationality of experts' suggestions for maintenance and replacement strategies regarding the regulation of NPS pollution. At the watershed scale, the total cost dropped by 57.36% by introducing the LBMP-OM method compare to the original method. This new method extended the long-term management and configuration of BMPs.