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Related Experiment Video

Updated: Nov 9, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

Downstream Effects of Upstream Causes.

Bradley C Saul¹, Michael G Hudgens¹, Michael A Mallin²

¹Department of Biostatistics, University of North Carolina Chapel Hill.

Journal of the American Statistical Association

|April 8, 2021

Summary

Nutrient pollution impacts stream ecosystems, but inferring its effects is challenging. This study uses causal g-methods to link upstream nutrient levels to downstream chlorophyll a, revealing pollution impacts from industrial and municipal wastewater.

Keywords:

g-formula marginal structural models potential outcomes structural nested models

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Last Updated: Nov 9, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework

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Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Published on: September 26, 2017

Area of Science:

Environmental Science
Ecology
Causal Inference Methods

Background:

Nutrient pollution is a major environmental challenge in U.S. streams.
Challenges in causal inference include limited replication, randomization, and confounding variables.
Chlorophyll a serves as a proxy for algal production in aquatic ecosystems.

Purpose of the Study:

To extend causal g-methods for time- and space-varying exposures.
To assess the causal effects of nutrient pollution on chlorophyll a levels.
To estimate causal effects using publicly available water quality data.

Main Methods:

Utilized causal g-methods, including the parametric g-formula, marginal structural models, and structural nested models.
Applied methods to North Carolina's Cape Fear River data and a simulation study.
Accounted for time- and space-varying nutrient concentrations and their impact on downstream chlorophyll a.

Main Results:

Demonstrated the estimation of causal effects of upstream nutrient concentrations on downstream chlorophyll a.
Identified significant influence of upstream nitrate concentrations on downstream chlorophyll a levels.
Pinpointed specific upstream areas with major industrial and municipal point sources as contributors.

Conclusions:

Causal g-methods can effectively estimate nutrient pollution effects on chlorophyll a from monitoring data.
Upstream nutrient loads, particularly nitrate, have a measurable impact on downstream algal production.
Wastewater discharges from point sources are significant drivers of nutrient pollution and subsequent algal blooms.