A Performance-Enhanced Water Distribution Model via EPANET Integrated with R

An efficient water distribution system is fundamental to achieving sustainable water management and ensuring consistent service delivery in both urban and rural communities. This study focuses on the development of an efficient water distribution system through an amalgamation of EPANET, Coefficient of Determination (R2), and Percent Bias (PBIAS) to evaluate and enhance hydraulic performance. The main objective is to design, simulate, and assess the efficiency and reliability of the distribution network in delivering adequate pressure and flow under varying demand conditions. The methodology involved developing a hydraulic model using EPANET based on actual system data, including pipe characteristics, nodal elevations, and water consumption patterns. Model calibration and validation were conducted by comparing simulated and field-observed pressure and flow data. Statistical indicators were applied—R2 measured the degree of correlation between simulated and observed values, while PBIAS quantified the average tendency of the model to over- or underestimate system performance. Results indicated a strong coefficient of determination (R2 > 0.9) and low percent bias, suggesting that the model effectively represents real system behavior with minimal deviation. Hence, the integration of EPANET with R2 and PBIAS provides a robust framework for designing and evaluating water distribution efficiency. It is recommended that the calibrated model be adopted for future expansion planning, leakage control, and operational optimization to ensure sustainable and equitable water supply management.

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Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2026-02-16
DOI
https://doi.org/10.1051/e3sconf/202669405006/pdf
Primary Topic
Water Systems and Optimization
Type
article
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article

A Performance-Enhanced Water Distribution Model via EPANET Integrated with R

Maryjay M. Sagario
Springer Link (Chiba Institute of Technology)
Water Systems and Optimization
article

A Performance-Enhanced Water Distribution Model via EPANET Integrated with R

Maryjay M. Sagario
article en

Abstract

An efficient water distribution system is fundamental to achieving sustainable water management and ensuring consistent service delivery in both urban and rural communities. This study focuses on the development of an efficient water distribution system through an amalgamation of EPANET, Coefficient of Determination (R2), and Percent Bias (PBIAS) to evaluate and enhance hydraulic performance. The main objective is to design, simulate, and assess the efficiency and reliability of the distribution network in delivering adequate pressure and flow under varying demand conditions. The methodology involved developing a hydraulic model using EPANET based on actual system data, including pipe characteristics, nodal elevations, and water consumption patterns. Model calibration and validation were conducted by comparing simulated and field-observed pressure and flow data. Statistical indicators were applied—R2 measured the degree of correlation between simulated and observed values, while PBIAS quantified the average tendency of the model to over- or underestimate system performance. Results indicated a strong coefficient of determination (R2 > 0.9) and low percent bias, suggesting that the model effectively represents real system behavior with minimal deviation. Hence, the integration of EPANET with R2 and PBIAS provides a robust framework for designing and evaluating water distribution efficiency. It is recommended that the calibrated model be adopted for future expansion planning, leakage control, and operational optimization to ensure sustainable and equitable water supply management.

Springer Link (Chiba Institute of Technology)
University of Southern Philippines Foundation (PH)
Openalex Percentile: Top 53%
Water Systems and Optimization
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A Performance-Enhanced Water Distribution Model via EPANET Integrated with R — Maryjay M. Sagario · Springer Link (Chiba Institute of Technology) (2026) | TGRS Research Map | TGRS