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Related Experiment Video

Updated: Aug 19, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
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Source appointment at large-scale and ungauged catchment using physically-based model and dynamic export coefficient.

Wenzhuo Wang1, Lei Chen1, Chen Lin2

  • 1State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, PR China.

Journal of Environmental Management
|November 27, 2022
PubMed
Summary

A new framework integrating physical and surrogate models addresses data scarcity for non-point pollution source apportionment in large, ungauged catchments. This method accurately identifies pollution sources and their contributions, even under varying rainfall conditions.

Keywords:
Chaohu lakeLarge scale catchmentNon-point sourceParameter extrapolationSource apportionmentUngauged area

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Area of Science:

  • Environmental Science
  • Hydrology
  • Water Quality Management

Background:

  • Data scarcity poses significant challenges for accurate non-point pollution prediction and source apportionment.
  • Existing models often struggle with application in large-scale, ungauged catchments due to limitations in transfer and transplantation processes.

Purpose of the Study:

  • To develop and validate a novel framework for large-scale, ungauged catchment source apportionment.
  • To improve the application of physically-based models in data-scarce regions by enhancing transfer and transplantation processes.

Main Methods:

  • Integration of a physically-based model with a surrogate model to create a robust framework.
  • Application and testing of the framework in the Chaohu Lake basin, China.
  • Evaluation of model performance through comparison of simulated and observed data.

Main Results:

  • The integrated framework demonstrated a good match between simulated and observed data.
  • The planting industry, while the largest emitter (48.16% N), contributed only 12.61% to N flux in Chaohu Lake.
  • Ungauged catchments were identified as significant phosphorus (P) sources (8.46% contribution).
  • Rainfall variability greatly influenced source apportionment, with planting industry P contribution ranging from 68.17t (dry year) to 436.02t (wet year).

Conclusions:

  • The developed framework effectively addresses data limitations in non-point pollution source apportionment for large, ungauged catchments.
  • The study highlights the importance of considering contributions from ungauged areas and rainfall variability in water quality management.
  • The framework's adaptability suggests its potential for application in other data-limited watersheds globally.