Watershed health assessment using the coupled integrated multistatistic analyses and PSIR framework

Area of Science:

• Environmental Science
• Water Resource Management
• Ecosystem Health Assessment

Background:

• Effective watershed health assessment is vital for scientific planning and management, yet current methods often lack comprehensive, multi-dimensional data.
• Existing approaches inadequately capture watershed-scale dynamics, leading to incomplete understanding and fragmented management strategies.

Purpose of the Study:

• To quantitatively assess watershed health in the Chaohu Lake watershed (CLW) using a novel framework.
• To investigate the inter-relationships between socioeconomic and natural pressures, pollution, water quality, and management responses.
• To identify key factors limiting watershed health improvement.

Main Methods:

• Utilized monthly sampling data from 46 river sites in 2018.
• Applied the Pressure-State-Impact-Response (PSIR) framework to analyze four key dimensions.
• Integrated Canonical Correlation Analysis (CCA), Variance Partitioning Analysis (VPA), and an obstacle degree model.

Main Results:

• Socioeconomic and natural pressures led to increased phosphorus, nitrogen, and sediment exports, worsening river water quality in CLW.
• Water quality improvements correlated with increased woodland and grassland coverage.
• Socioeconomic activities were more closely linked to nutrient and sediment exports than natural factors.

Conclusions:

• The study presents a new evaluation framework for watershed health and its limiting factors, crucial for targeted management interventions.
• Understanding the distinct obstacle factors in urban versus agricultural sub-watersheds is key for tailored watershed management strategies.
• The findings highlight the need for integrated approaches that consider multiple dimensions of watershed health for effective restoration and protection.