Evaluation of the methods for quantifying particle wash-off loadings in urban impervious surfaces at small scales

Modeling urban pollutant wash-off processes with ecological memory

Urbanization increases the extent of impervious surfaces, runoff, sediment, and nutrient loadings downstream, leading to the deterioration of urban surface waters. During pollutant wash-off from urban surfaces, the peak concentration of pollutants typically occurs after the rainfall peak. However, current urban wash-off models do not consider this time delay, assuming that the effect of rainfall on the wash-off process is immediate. Ecological memory (EM) is defined as the capacity of past states or experiences to influence the present or future ecological responses of a community ecosystem. In this study, ecological memory was calculated to reflect the lagging impact of rainfall on the wash-off process. Incorporating ecological memory into the original wash-off model improved its performance across all pollutant types and rainfall conditions, with the adjusted R-squared value increasing from -0.01-0.61 to -0.08-0.83. Among the factors impacting ecological memory, rainfall intensity significantly affected the distributions of ecological memory (p < 0.05 according to the Kolmogorov-Smirnov test). The first flush phenomenon, which involves a larger concentration or mass of pollutants in the initial portion of a storm event compared to the rest, showed no significant difference in the distributions of ecological memory between rain events with and without this phenomenon. The improved urban wash-off model can be applied for real-time simulation of urban pollutants and help develop site-specific measures for reducing urban nonpoint source pollution.

What is the relationship between land use and surface water quality? A review and prospects from remote sensing perspective

Good surface water quality is critical to human health and ecology. Land use determines the surface water heat and material balance, which cause climate change and affect water quality. There are many factors affecting water quality degradation, and the process of influence is complex. As rivers, lakes, and other water bodies are used as environmental receiving carriers, evaluating and quantifying how impacts occur between land use types and surface water quality is extremely important. Based on the summary of published studies, we can see that (1) land use for agricultural and construction has a negative impact on surface water quality, while woodland use has a certain degree of improvement on surface water quality; (2) statistical methods used in relevant research mainly include correlation analysis, regression analysis, redundancy analysis, etc. Different methods have their own advantages and limitations; (3) in recent years, remote sensing monitoring technology has developed rapidly, and has developed into an effective tool for comprehensive water quality assessment and management. However, the increase in spatial resolution of remote sensing data has been accompanied by a surge in data volume, which has caused difficulties in information interpretation and other aspects.

Particle size distribution and total suspended solid concentrations in urban surface runoff

An in-depth understanding of particle size distribution as well as total suspended solids (TSS) in surface runoff is essential for managing urban diffuse pollution. In this study, field experiments and model simulation were undertaken to explore and confirm the dynamic runoff behaviour of TSS and their influencing factors. Field observation results showed that samples with high TSS concentrations contained coarser particles (>100 μm) during three natural rainfall events. Particle size distribution as well as road-deposited sediments (RDS) amount before and after these rainfall events also confirmed that a higher percentage of washed-off coarser particles resulted in higher TSS concentrations in surface runoff water. The impacts of rainfall characteristics, urban-rural gradients, surface roughness, and climate difference on particle distribution as well as TSS concentration were analyzed using the wash-off formula of particle size. These factors mainly affected the contribution rate of RDS to TSS by altering particle size composition; rates ranged from 4% to 44% under different rainfall characteristics. The critical particle size (<100 μm) was developed according to the mass percentage of particles with different sizes in RDS and TSS. Our results can provide a simple and effective way of assessing RDS contribution to TSS in surface runoff.

Impact of rapid urbanization on the threshold effect in the relationship between impervious surfaces and water quality in shanghai, China

The threshold effect in the relationship between impervious surfaces and water quality has been a focus in past decades, but little attention has been paid to how the threshold effect changes during a rapid urbanization period. This study reveals the temporal variation of threshold effect in the relationship between the percentage of total impervious area (PTIA) and water quality indicators in a reticular river network area in Shanghai, China. The PTIA was surveyed and defined using the ISC method (impervious surface coefficients). A segmented regression model was used to disclose the non-linear relationship between PTIA and water quality. It is confirmed that the threshold effect was different in terms of water quality indicators, but the effect size became smaller as the threshold increased with urbanization level during the period of 1989-2010. Meteorological conditions make influence on the threshold effect, it can be found that the effect is more significant under higher air temperature conditions, while in the lower temperature situation, there is no significant threshold effect.