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A Multiarmed Bandit Approach to Adaptive Water Quality Management.

David M Martin1, Fred A Johnson2

  • 1Maryland/DC Chapter, The Nature Conservancy, Bethesda, Maryland, USA.

Integrated Environmental Assessment and Management
|June 26, 2020
PubMed
Summary
This summary is machine-generated.

Multiarmed bandit strategies help balance exploiting known effective wastewater treatments with exploring new ones for better water quality management. Randomized probability matching offers a balanced approach for adaptive management.

Keywords:
Adaptive managementBayesianDecision makingNitrogen monitoring

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Area of Science:

  • Environmental Science
  • Water Quality Management
  • Ecological Restoration

Background:

  • Nonpoint source water quality management faces challenges in action allocation and performance monitoring without state-dependent decision-making.
  • Adaptive management can be framed as a multiarmed bandit problem, balancing action exploitation and exploration.

Purpose of the Study:

  • To test multiarmed bandit strategies for informing adaptive water quality management.
  • To evaluate the effectiveness of different strategies in allocating wastewater treatments to minimize nitrogen inputs.

Main Methods:

  • Applied two multiarmed bandit strategies (deterministic and randomized probability matching) and a nonadaptive strategy to wastewater treatment allocation data.
  • Used chronological (nonstationary) and random (stationary) datasets of nitrogen monitoring data for hypothetical experiments with 20 sequential decisions.

Main Results:

  • Equal allocation learned well in nonstationary conditions but overexplored inferior treatments.
  • Deterministic probability matching maximized performance in stationary conditions but under-explored in nonstationary ones.
  • Randomized probability matching balanced performance and learning in stationary conditions but risked converging on inferior treatments in nonstationary scenarios.

Conclusions:

  • Probability-matching strategies are effective tools for adaptive water quality management.
  • The choice of strategy impacts performance based on whether conditions are stationary or nonstationary.