A Critical Evaluation of the Water Supply and Stormwater Management Performance of Retrofittable Domestic Rainwater Harvesting Systems
Abstract
:1. Introduction
- Analyse the collected data and use it to validate a modelling tool for future simulations and examine the impact of different demand patterns on model accuracy.
- Determine the current water supply and stormwater performance of the three domestic systems monitored.
- Investigate the long-term future performance of these systems and identify and evaluate potential avenues for improvement.
2. Materials and Methods
2.1. Data Collection
2.2. Model Creation and Validation
2.3. Assessment Metrics
2.4. Long-Term Modelling and Assesment
- Scenario 1—Increase demand for non-potable waterUse of the downstairs toilet was increased and all washing machines were connected to the tank. Each of the five occupants was assumed to use the toilet four times per day on weekdays and six times per day on weekends with a partial flush ratio of 1(6 L):2(4 L) [3]. The washing machine was assumed to have 0.2 uses per day per person, with 50 L per use [3]. In total, demand from the RWH tank was assumed to be 156 L per household per day.
- Scenario 2—Model passive systemThe model was configured to enable passive releases from the tanks to occur. These systems have a slow-release discharge outlet and water below this outlet was stored for domestic consumption. The outlet was sized so that the water above it slowly discharged at the greenfield runoff rate (2 L/s/ha). The passive outlet was located at 0.68 m above the base of the tank, which created a storage capacity of 25% of the effective volume (0.17 m3). The objective of this system is to store runoff during events and allow it to slowly release to the environment.
- Scenario 3—Model active systemActive release systems were modelled. These were remotely controlled in real time, and they managed the release of water according to the rainfall forecast and available retention volume in the tank. The target was to minimize rainfall discharge by maximizing functional tank capacity prior to the forecasted storm event. The system was emptied at midnight as needed. The pre-storm release volume was calculated as the difference between the available tank storage volume at the end of the previous day and predicted runoff volume for the next 24 h. This pre-storm release was delivered through a 10 mm automated valve located at 0.1 m above the outlet to ensure that there was water above the pump at all times. The pre-storm release was driven by gravity. The objective of this system is to release water quickly in advance of an event in order to provide additional storage capacity.
3. Results
3.1. Collected Data
3.2. Model Validation and Short-Term Performace Assesment
3.3. Long-Term Modelling
The 30 Largest Events by Cumulative Volume
4. Discussion
5. Conclusions
- The short-term monitoring of RWH systems showed large differences in demand between identically sized households. In addition, all tanks were full for long periods, showing that the homes often had spare rainwater available for use.
- Uniform demand profiles, as opposed to a high-resolution time series of metered demand, did not significantly affect the accuracy of a yield-after-spillage RWH system model.
- The retention (ER) of the systems over a thirty year period was modelled to be between 0.17 and 0.30 depending on demand. However, this decreased to between 0.04 and 0.07 when the 30 largest events were examined.
- Modelling indicated that increasing demand from the system increases overall retention to a greater degree than converting them to passive or active systems. This illustrates the value of engaging the community and that, through maximizing their demand for the available non-potable water, greater benefits can be achieved than through engineering solutions alone.
- During the long-term modelling simulation, passive systems were the most effective at reducing overflow to below greenfield runoff, whereas active systems substantially increased flow rates above roof runoff during the 30 largest events.
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Measurement | House A (Demand: Toilet) | House B (Demand: Toilet and Washing Machine) | House C (Demand: Toilet) |
---|---|---|---|
Water Level (m) | 10 June 2018–28 August 2109 Missing data: 30 July 2018–25 October 2018 7 July 2019–18 July 2019 There was an unexplained jump from 1.62 to 1 m at 8 am on 20 June 2019 | 12 March 2019–28 August 2019 | 1 September 2018–28 August 2019 Missing data: 12 October 2018–29 October 2018 15 November 2018–20 November 2018 25 December 2018–30 December 2018 13 January 2019–19 January 2019 17 February 2019–10 March 2019 14 April 2019–01 June 2019 10 June 2019–16 June 2019 23 June 2019–20 July 2019 |
Borehole Inflow | 10 June 2018–5 February 2019 Missing data: 30 July 2018–25 October 2018 | None | 1 September 2018–28 August 2019 Missing data: Same as above |
Yield | 10 June 2018–5 February 2019 Missing data: 30 July 2018–25 October 2018 | None | 1 September 2018–28 August 2019 Missing data: Same as above |
House | Root Mean Square Error (RMSE) (m) | Coefficient of Determination (R2) | ||
---|---|---|---|---|
Measured | Constant | Measured | Constant | |
House A (Daily Demand = 46.1 L) | 0.25 | 0.24 | 0.78 | 0.8 |
House B (Daily Demand = 48.3 L) | - | 0.12 | - | 0.95 |
House C (Daily Demand = 26.5 L) | 0.2 | 0.12 | 0.97 | 0.94 |
Performance Metric | House A 26 October 2019–04 February 2019 | House B 12 March 2019–13 April 2019 | House C 11 March 2019–13 April 2019 |
Water Supply Efficiency (Ews) (-) | >0.99 | >0.99 | >0.99 |
Water Supply Frequency (Fws) (-) | >0.99 | >0.99 | >0.99 |
Overflow Frequency (Fo) (-) | 0.17 | 0.06 | 0.07 |
Retention (ER) (-) | 0.13 | 0.41 | 0.23 |
Frequency Above Greenfield Runoff (FGF) (-) | 0.15 | 0.05 | 0.06 |
Retention Below Greenfield Runoff (EGF) (-) | 0.14 | 0.41 | 0.23 |
Performance Metric | House A | House B | House C |
---|---|---|---|
Ews (-) | 0.98 | 0.98 | 0.99 |
Fws (-) | 0.98 | 0.98 | 0.99 |
Fo (-) | 0.06 | 0.06 | 0.07 |
ER (-) | 0.29 | 0.30 | 0.18 |
FGF (-) | 0.03 | 0.03 | 0.04 |
EGF (-) | 0.34 | 0.35 | 0.23 |
Performance Metric | Conventional (Conv) | Passive (Pass) | Active (Act) | ||
---|---|---|---|---|---|
Maximum Demand | House B | House C | House B | House C | |
Ews (-) | 0.65 | 0.78 | 0.91 | 0.96 | 0.99 |
Fws (-) | 0.65 | 0.78 | 0.91 | 0.96 | 0.99 |
Fo (-) | 0.02 | 0.29 | 0.34 | 0.01 | 0.01 |
ER (-) | 0.66 | 0.24 | 0.16 | 0.30 | 0.17 |
FGF (-) | 0.01 | 0.005 | 0.005 | 0.01 | 0.01 |
EGF (-) | 0.67 | 0.87 | 0.86 | 0.30 | 0.18 |
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Quinn, R.; Melville-Shreeve, P.; Butler, D.; Stovin, V. A Critical Evaluation of the Water Supply and Stormwater Management Performance of Retrofittable Domestic Rainwater Harvesting Systems. Water 2020, 12, 1184. https://doi.org/10.3390/w12041184
Quinn R, Melville-Shreeve P, Butler D, Stovin V. A Critical Evaluation of the Water Supply and Stormwater Management Performance of Retrofittable Domestic Rainwater Harvesting Systems. Water. 2020; 12(4):1184. https://doi.org/10.3390/w12041184
Chicago/Turabian StyleQuinn, Ruth, Peter Melville-Shreeve, David Butler, and Virginia Stovin. 2020. "A Critical Evaluation of the Water Supply and Stormwater Management Performance of Retrofittable Domestic Rainwater Harvesting Systems" Water 12, no. 4: 1184. https://doi.org/10.3390/w12041184
APA StyleQuinn, R., Melville-Shreeve, P., Butler, D., & Stovin, V. (2020). A Critical Evaluation of the Water Supply and Stormwater Management Performance of Retrofittable Domestic Rainwater Harvesting Systems. Water, 12(4), 1184. https://doi.org/10.3390/w12041184