Related Experiment Video
Updated: Aug 2, 2025
12:44
Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
8.1K
A raster-based estimation of watershed phosphorus load and its impacts on surrounding rivers based on process-based
Qi Li1, Jiacong Huang2, Jing Zhang2
1Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, 73 East Beijing Road, Nanjing 210008, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Journal of Environmental Management
|April 13, 2023
Summary
Estimating phosphorus (P) load in mixed mountain-lowland watersheds is challenging. This study developed a coupled model to quantify P load at a grid scale, identifying high-risk areas and sources for better watershed management.
Area of Science:
- Environmental Science
- Hydrology
- Water Quality Management
Background:
- Quantifying phosphorus (P) load at a fine scale is critical for understanding aquatic ecosystem health.
- Mountain-lowland mixed watersheds present unique challenges for accurate P load estimation.
- Existing methods struggle to capture the spatial heterogeneity of P sources in such complex landscapes.
Purpose of the Study:
- To develop and validate a framework for estimating P load at the grid scale in mountain-lowland mixed watersheds.
- To assess the risk of P load to surrounding river ecosystems.
- To identify key P contributing areas and sources within the watershed.
Main Methods:
- Coupled three models: Phosphorus Dynamic model for lowland Polder systems (PDP), Soil and Water Assessment Tool (SWAT), and Export Coefficient Model (ECM).
- Applied a raster-based approach for fine-scale P load estimation.
- Validated the coupled model using hydrological and water quality variables (Nash-Sutcliffe efficiency >0.5).
Main Results:
- Polder, non-polder, and mountainous areas contributed 211.4, 437.2, and 149.9 t yr-1 of P load, respectively.
- Non-polder areas exhibited the highest P load intensity (>3 kg ha-1 yr-1).
- In lowlands and mountains, irrigated croplands, aquaculture ponds, and impervious surfaces were major P contributors.
Conclusions:
- The coupled model provides a robust method for grid-scale P load estimation in complex watersheds.
- High P load risks were identified around urban areas during the rice season, linked to non-point source pollution.
- This approach aids in pinpointing hotspots and hot moments of P load for targeted environmental management.
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