Resolving spatiotemporal water quality variability in a river-influenced estuarine system using high-frequency...

Area of Science:

• Estuarine ecology
• Water quality science
• Coastal oceanography

Background:

• River-influenced estuaries are vital habitats but face threats from variable freshwater discharge, nutrient pollution, and climate change.
• Limited understanding of high-frequency variability and spatial heterogeneity in these systems hinders effective management.
• Autonomous surface vessels offer a solution for continuous, high-resolution data collection.

Purpose of the Study:

• To analyze multi-year, high-frequency water quality data from the Western Mississippi Sound.
• To identify seasonal and interannual variability, spatial patterns, and key drivers of water quality.
• To assess the effectiveness of autonomous observations for coastal management.

Main Methods:

• Collected multi-year (2021-2024) high-frequency data on ten water quality parameters using an autonomous surface vessel.
• Employed statistical analyses including Seasonal Mann-Kendall, Kruskal-Wallis, Generalized Additive Models, Principal Component Analysis (PCA), and hierarchical clustering.
• Calculated a Composite Water Quality Score (CWQS) to assess degradation.

Main Results:

• All ten parameters showed significant seasonal variability, with summer blooms and winter lows.
• PCA revealed dominant freshwater-marine mixing/metabolic gradients and carbon/oxygen dynamics.
• Discharge-water quality relationships were regime-dependent, strengthening under high discharge and reversing under low discharge.
• Transect 7 was identified as critically degraded due to eutrophication (CWQS = 0.54).

Conclusions:

• High-frequency autonomous observations are crucial for understanding complex estuarine dynamics.
• Regime-dependent relationships and spatial heterogeneity require tailored management approaches.
• Findings support spatially targeted interventions for coastal zone management and habitat preservation.