We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
A continuation-dynamic constitution analysis approach based on digital stable marker tracing and study on simulation of ecological tidal water diversion
Summary
Researchers developed a digital water-tracing method to track how diverted river water mixes and moves through a local canal network in China, quantifying each water source's contribution over time to help engineers optimize water diversion projects that improve water quality in urban waterways.
Water Diversion Projects have become increasingly popular in improving water quality in various water ecosystems. However, these projects also require a more comprehensive evaluation. In this study, we introduced a digital stable marker tracing module and proposed a continuation-dynamic constitution analysis approach. We applied this approach to analyze the ecological tidal water diversion in Changshu town, China. The results showed that the mean diversion water age of the Yangtze River water source was 10.80 h, the residence time of the background water source in Baimaotang was approximately 4.0 h, and the contribution of inflow water sources from tributaries accounted for 15% of discharges. The results can demonstrate practicality of our approach in quantitatively evaluating water diversion impacts and optimizing cooperative diversion projects. Furthermore, our discussion led to the design of an ecological tidal water diversion based on optimized cooperative diversion, which showed element-complementary and whole-comprehensive effects. This indicates that the ecological tidal water diversion can extend the impact of cooperative diversion. The continuation-dynamic constitution analysis approach enhances the tracing capacity of inflow constitution and enables the distinction of different time-varying distributions of each inflow constitution. Therefore, this approach holds promise as an embedded "Digital stable marker tracing" module in the model.
Sign in to start a discussion.
More Papers Like This
Extended Strahler Ordering to Distinguish Mapped River Channels From Overland Flow Pathways and Consistently Compare Digital Networks
Researchers proposed an extension to standard Strahler stream ordering that assigns non-positive numbers to overland flow pathways, enabling digital river networks to consistently distinguish mapped river channels from overland flow segments. This methodological improvement supports more accurate river classification, simulation modeling, and policy-relevant freshwater analysis, including microplastic transport pathway mapping.
Optimal Allocation of Water Resources Considering Virtual Water Trade: A Case Study of the Yellow River
This study optimizes water resource allocation across the Yellow River basin in China by integrating both physical and virtual water flows. The study is focused on water resource management and is not directly related to microplastic research.
Hydrological Connectivity Patterns and Their Eco-hydrological Implications in the Dasha River, China
This study used graph theory and isotope tracing with weekly eco-hydrological monitoring to assess hydrological connectivity and ecological impacts in the heavily modified Dasha River, Shenzhen, providing a methodological framework for urban river management.
Methodology for the study of the traceability of runoff water feeding reservoirs
Not relevant to microplastics — this paper presents a GIS-based methodology for tracing the agricultural plots whose rainwater runoff feeds a reservoir, extending the D8 drainage algorithm with land-use and rainfall data to assess agrochemical contamination pathways.
A Comprehensive Method for Water Environment Assessment considering Trends of Water Quality
Researchers developed a comprehensive water quality assessment method that accounts for both current pollution levels and trends over time, applying it to rivers feeding a major Chinese reservoir. Water quality assessment frameworks are increasingly being adapted to include microplastic contamination as a standard monitoring parameter.