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Ecohydrological modeling for large-scale environmental impact assessment.

Sean A Woznicki1, A Pouyan Nejadhashemi1, Mohammad Abouali1

  • 1Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI, USA.

The Science of the Total Environment
|November 24, 2015
PubMed
Summary
This summary is machine-generated.

Developing large-scale ecohydrological models that incorporate stream thermal classes significantly improves accuracy in assessing biological integrity, offering detailed insights for stream health management.

Keywords:
Biological integrityFishFuzzy logicMacroinvertebrateStream healthStream thermal classSwat

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Area of Science:

  • Ecohydrology
  • Ecological modeling
  • Water resource management

Background:

  • Ecohydrological models are crucial for assessing biological integrity in unsampled streams.
  • Model scale presents a tradeoff between broad impact assessment and detailed reach-level analysis.
  • Existing models often necessitate a choice between large-scale applicability and regional-scale detail.

Purpose of the Study:

  • To develop large-scale stream health models with reach-level accuracy comparable to regional-scale models.
  • To enhance impact assessments and decision-making capabilities for stream management.
  • To improve the understanding of aquatic biota distribution based on thermal classes.

Main Methods:

  • Modeled four biological integrity measures (EPT, FIBI, HBI, IBI) across four Michigan stream thermal classes (cold, cold-transitional, cool, warm).
  • Utilized the Soil and Water Assessment Tool (SWAT) for streamflow and water quality simulation.
  • Employed the Hydrologic Index Tool to derive flow regime variables and adaptive neuro-fuzzy inference systems (ANFIS) for model development.

Main Results:

  • Bayesian variable selection identified unique, ecologically relevant variables for each thermal class.
  • Adaptive neuro-fuzzy inference systems (ANFIS) models demonstrated improved accuracy when stream thermal class was considered.
  • Accounting for thermal classes provided more precise predictions of biological integrity measures.

Conclusions:

  • Incorporating stream thermal class into large-scale ecohydrological models enhances predictive accuracy for biological integrity.
  • This approach bridges the gap between broad-scale assessments and detailed, regional-scale insights.
  • The developed models offer improved tools for effective stream health management and decision-making.