Developing a Framework for Smart Stormwater Management in Tallinn, Estonia †
Abstract
:1. Introduction
2. Materials and Methods
- What is the state-of-the-art for monitoring stormwater quality and quantity?
- What are the main stormwater pollutants and their pathways, effects, and real-time monitoring options?
- What is the status of existing best practices in Estonia’s largest water company, compared to the state-of-the-art, and which benefits could the company reap from the digitalization of stormwater management?
- What are the requirements for setting up systems for stormwater quality monitoring?
3. Results and Discussion
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Catchment Scale Impacts | Description | Points | Weights |
---|---|---|---|
Public health and safety issues | Frequency and severity of public health incidents linked to water quality per year. | None—0 Some—1 Multiple—2 | 0.4 |
Poor environmental status of the receiving waterbodies | Environmental quality status according to the European Water Framework Directive | High—0 Moderate—1 Bad—2 | 0.2 |
Exceedance of regulatory limits | Number of times that the regulatory limits have been exceeded in the past 5 years | None—0 Some—1 Multiple—2 | 0.2 |
Areas with increased pollution | Number of identified high-risk areas prone to runoff pollution. | None—0 Some—1 Multiple—2 | 0.1 |
Catchment imperviousness | Determined according to land use data (e.g., Estonian Land Board) | Low (<33%)—0 Avg. (33–66%)—1 High (>66%)—2 | 0.1 |
Technical considerations | Description | Points | |
Suitable monitoring station locations | Based on a review of technical requirements (placement of sensors, automatic samplers, rain gauges, etc.) and site accessibility and vicinity of pollution hotspots. | None—0 Some—1 Multiple—2 | 0.16 |
Integration of GIS into day-to-day workflows | Organizational assessment on the integration of GIS tools into their workflows. | None—0 Some—1 Multiple—2 | 0.16 |
Availability of IT infrastructure and hydro-informatics specialists | Organizational assessment on the level of digitalization and IT-related skills in the organization. | None—0 Some—1 Extensive—2 | 0.16 |
Experience with automatic samplers and water quality sensors | How much experience does the organization have with automatic samplers and/or water quality sensors? | None—0 Some—1 Extensive—2 | 0.16 |
Monitoring system architecture | Does the organization use open-access IoT solutions that allow the adjustment of data collection, storage, handling, and visualization? | None—0 Some—1 Extensive—2 | 0.16 |
Pre-existing network of monitoring nodes on the stormwater network | Does the organization have a pre-existing network of rain gauges, water quality sensors, flow meters, or other devices in the stormwater catchment? | None—0 Some—1 Extensive—2 | 0.16 |
Financial and HR | Description | Points | |
Efficient service area | Servicing area to number of consumers ratio. The higher the value, the more feasible it is. | Small—0 Medium—1 Large—2 | 0.14 |
Maintenance personnel availability | Servicing personnel ratio = (avg. nr. of visits per month x avg. time on site)/total time per month | Avg. (0.25–0.5)—1 Little (0–0.25)—0 Sufficient (0.5–1)—2 | 0.14 |
Total CAPEX ratio | What is the relationship between the new investment costs and the total value of existing investments? The lower the value, the more likely that the investment is feasible. | High (10%)—0 Avg. (5–10%)—1 Low (0–5%)—2 | 0.14 |
Operation cost ratio | What is the relationship between the new operational costs to the existing operational costs? The lower the value, the more likely it is that the investment is feasible. | High (10%)—0 Avg. (5–10%)—1 Low (0–5%)—2 | 0.14 |
Effect of investment on the asset to debt ratio | Investment impacts on the company’s asset-to-debt ratio; the lower the ratio, the more sustainable it is. Investment size is site-dependent. | High (10%)—0 Avg. (5–10%)—1 Low (0–5%)—2 | 0.14 |
Funding dependencies | How often is the organization dependent on external funding? | Never—0 Sometimes—1 Mostly—2 | 0.14 |
Infrastructure age | The higher the average age of the stormwater infrastructure, the more important it is to monitor it. | <20 years—0 20–35 years—1 >35years—2 | 0.14 |
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Suits, K.; Vassiljev, A.; Kaur, K.; Kõiv, K.; Kändler, N.; Annus, I. Developing a Framework for Smart Stormwater Management in Tallinn, Estonia. Eng. Proc. 2024, 69, 23. https://doi.org/10.3390/engproc2024069023
Suits K, Vassiljev A, Kaur K, Kõiv K, Kändler N, Annus I. Developing a Framework for Smart Stormwater Management in Tallinn, Estonia. Engineering Proceedings. 2024; 69(1):23. https://doi.org/10.3390/engproc2024069023
Chicago/Turabian StyleSuits, Kristjan, Anatoli Vassiljev, Katrin Kaur, Kerta Kõiv, Nils Kändler, and Ivar Annus. 2024. "Developing a Framework for Smart Stormwater Management in Tallinn, Estonia" Engineering Proceedings 69, no. 1: 23. https://doi.org/10.3390/engproc2024069023
APA StyleSuits, K., Vassiljev, A., Kaur, K., Kõiv, K., Kändler, N., & Annus, I. (2024). Developing a Framework for Smart Stormwater Management in Tallinn, Estonia. Engineering Proceedings, 69(1), 23. https://doi.org/10.3390/engproc2024069023