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Design and Construction of an Urban Runoff Research Facility
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A scale-adaptive method for urban rainwater harvesting simulation.

Catarina Lúcio1, Cristina Matos Silva2, Vitor Sousa3

  • 1Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001, Lisbon, Portugal.

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|April 12, 2019
PubMed
Summary

This study presents a new method to estimate urban rainwater harvesting (RWH) potential by considering building specifics. Results show RWH can save 16-86% of water, varying with building and occupancy details.

Keywords:
Accuracy/data requirements balanceParametric water savings potential functionsRainwater harvesting systems simulationUrban planningWater savings potential

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Area of Science:

  • Environmental Engineering
  • Urban Water Management
  • Sustainable Water Resources

Background:

  • Accurate assessment of rainwater harvesting (RWH) potential is crucial for urban water management.
  • Traditional urban-scale RWH potential estimation relies on simplified rainfall-consumption balances, neglecting building-specific factors and storage limitations.
  • Existing methods lack accuracy due to assumptions of infinite storage and disregard for building-level water use variability.

Purpose of the Study:

  • To develop and present a refined methodology for evaluating urban rainwater harvesting potential.
  • To incorporate building characteristics and consumption patterns into urban-scale RWH potential assessments.
  • To provide a practical and resource-efficient approach for estimating RWH benefits in cities.

Main Methods:

  • A balance equations model was adapted for building-scale RWH performance simulation.
  • A novel methodology was proposed to aggregate building-level data for urban-scale RWH potential evaluation.
  • The methodology was applied to Lisbon, Portugal, considering building characteristics and consumption patterns.

Main Results:

  • The study demonstrates significant water savings potential from RWH, ranging from 16% to 86%.
  • The potential savings are highly dependent on specific building characteristics and occupancy patterns.
  • Rainfall spatial variability within Lisbon was found to have a negligible impact on RWH potential evaluation.

Conclusions:

  • The developed methodology offers a more accurate and nuanced estimation of urban RWH potential compared to traditional approaches.
  • Building-specific data and consumption patterns are critical factors influencing the effectiveness of RWH systems at an urban scale.
  • This approach facilitates better planning and implementation of RWH strategies for sustainable urban water management.