📦 Resource pdf

LID Performance Monitoring Protocol (ASCE/EWRI Standard)

The LID Performance Monitoring Protocol (ASCE/EWRI Standard 46-22) is a consensus-based technical standard that provides a systematic framework for designing, implementing, and evaluating monitoring programs to assess the hydrologic, water quality, and operational performance of Low Impact Development (LID) practices. It establishes minimum requirements for data collection, instrumentation, quality assurance, and reporting to ensure credible, reproducible, and comparable performance assessments across diverse sites and practitioners. The protocol supports evidence-based decision-making for LID design optimization, regulatory compliance, and long-term asset management.

📖 Overview

The ASCE/EWRI Standard 46-22—formally titled 'Standard Practice for Monitoring the Performance of Low Impact Development (LID) Practices'—was developed through rigorous peer review and stakeholder collaboration to address the lack of consistent, scientifically defensible methods for evaluating LID effectiveness. It emphasizes a tiered monitoring approach—from basic observational checks to comprehensive instrumented studies—tailored to project scale, regulatory context, and research objectives. Core principles include defining clear performance objectives (e.g., runoff volume reduction, peak flow attenuation, pollutant load removal), selecting appropriate metrics aligned with those objectives, and applying rigorous data quality objectives (DQOs) to guide sensor selection, calibration frequency, data validation protocols, and uncertainty quantification. The standard also integrates guidance on metadata documentation, data management best practices (including temporal resolution and storage), and statistical analysis techniques for interpreting time-series data under variable climatic and antecedent conditions. Crucially, it bridges engineering practice and scientific rigor by requiring explicit linkage between monitoring design and intended use—whether for regulatory verification, adaptive management, or advancing the broader LID knowledge base through standardized, shareable datasets.

📑 Key Components

1 Performance Objectives and Metrics
2 Monitoring Design and Instrumentation
3 Data Quality Assurance/Quality Control (QA/QC)

🎯 Applications

  • Regulatory compliance verification for municipal stormwater permits (e.g., NPDES)
  • Post-construction performance evaluation of green infrastructure projects
  • Calibration and validation of hydrologic/water quality models (e.g., SWMM, WEPP)

📐 Key Formulas

Runoff Volume Reduction Efficiency

RVR = [(V_control − V_LID) / V_control] × 100%

Calculates the percentage reduction in total runoff volume achieved by an LID practice relative to a control (unretrofitted) area.

Pollutant Load Reduction Efficiency

PLR = [(L_control − L_LID) / L_control] × 100%

Quantifies the percentage reduction in total pollutant mass load (e.g., TSS, TN, TP) discharged from an LID practice compared to a conventional drainage system.

Peak Flow Attenuation Ratio

PFAR = Q_LID_peak / Q_control_peak

Ratio of peak discharge from the LID practice to peak discharge from a control site or modeled impervious scenario; values < 1.0 indicate attenuation.

🔗 Related Concepts

Green Infrastructure Water Balance Analysis Data Quality Objectives (DQO) Process

📚 References

#stormwater #green-infrastructure #performance-monitoring