Exploring a multisource-data framework for assessing ecological environment conditions in the Yellow River Basin,...

Area of Science:

• Environmental Science
• Ecology
• Geographic Information Systems (GIS)

Background:

• Ecological environment conditions (EEC) assessment is crucial for watershed management but challenged by limited field data in large areas.
• Existing methods often require extensive fieldwork, hindering scalability and efficiency.

Purpose of the Study:

• To develop an effective EEC assessment framework reducing reliance on field data.
• To integrate multisource data for a comprehensive EEC evaluation.
• To validate the framework's effectiveness in large-scale watershed management.

Main Methods:

• Developed three key indicators: landscape ecological risk index (LERI), road network density (RND), and industry density (ID) from multisource data.
• Employed a knowledge-based raster mapping approach to integrate indicators into an overall EEC score.
• Validated the model using principal components of water quality data through Pearson correlation analysis.

Main Results:

• Bad EEC areas, primarily in the northern Yellow River Basin (YRB), constituted 19.87% of the total area.
• High LERI, RND, and ID were significant contributors to poor EEC, with LERI being the most impactful.
• The framework successfully distinguished spatial variations in EEC, correlating with water quality indicators (P < 0.05).

Conclusions:

• Ecological risk factors pose the primary challenge to improving EEC, followed by industrial and road network factors.
• Adaptive management strategies are recommended, as factors influencing EEC vary across provinces.
• The developed framework provides effective support for large-scale watershed management by accurately assessing spatial EEC variations.