Planning and Managing the Integrated Water System: A Spatial Decision Support System to Analyze the Infrastructure Performances
Abstract
:1. Introduction
- Accessibility—Everybody needs fresh water;
- Affordability—Reasonable price for water;
- Environmental sustainability—Reasonable use of water;
- Efficiency of the infrastructure—Good service for a reasonable price of drinking water;
- Environmental Protection—Wastewater treatment mandatory for the protection of the ecosystems;
- Public health—Disposal and treatment of sewage for all urbanized areas.
1.1. Evaluating Performances of IWS Planning Actions
1.2. Aims and Scope
2. Materials and Methods
2.1. Regulation of the IWS Technical Quality
- prerequisites—the necessary conditions for the admission to the incentive mechanism associated with the general standards;
- specific standards—performance parameters to be guaranteed for services provided to individual users where the noncompliance requires automatic indemnities;
- general standards—these parameters are broken down into macro-indicators and simple indicators, both describing technical conditions to provide a service by an incentive mechanism.
2.2. National Federated Infrastructure Information Service
2.3. Spatial Decision Support Systems
2.4. The GeoTOPSIS Multi-Criteria Technique
3. The Methodology for Designing a SDSS
- macro-phase 1: construction of the knowledge domain;
- macro-phase 2: construction of the evaluation domain through the selection of a set of decision criteria measured by spatialized performances;
- macro-phase 3: construction of the domain of choices by mapping critical issues and selection of investment priorities.
3.1. Macro-Phase 1
3.2. Macro-Phase 2
- the representation of the relations between the M class of the technical quality macro-indicators and the C class of the critical categories catalogued in Annex 4 of Directive 1/2018 [15];
- the representation of the relations between the previous C class and the KPIs detailed in Directive 2/2016 [14];
- the representation of the relations between the KPI class and the F class of the n-formulas referring to the same KPIs;
- the representation of the relations between the F class and the V class of the variables belonging to the same formulas;
- the representation of the relations between the M and V classes. The frequency of each variable describes the weight that each of them expresses with respect to the variation of each Mi macro-indicator. Afterwards, the V variables are correlated at the spatial type attributes of the object class of the network data model, thus identifying the performance indicators.
3.3. Macro-Phase 3
4. Analyzing the Water System of a Municipality: A Case Study
4.1. Macro-Phase 1
- responsible for the operation of the network;
- position and localization;
- typology and function of nodes and traits;
- environmental conditions;
- year of construction;
- operating status and physical conditions;
- survey date;
- type of user connected to the network;
- state of the elements to be maintained or replaced;
- length and working pressure of the pipes.
4.2. Macro-Phase 2
- age of conduct;
- material;
- diameter of the pipe;
- length of the network section;
- the hydraulic load under static conditions on each node and section of the network;
- number of users served by each arc of the network.
4.3. Macro-Phase 3
- -
- CL1: This criterion allowed establishing that an arc of the water network maximizes losses when its length and diameter increase, age increases. Moreover, it depends on the type of material (cast iron/steel/plastic).
- -
- CL2: This criterion allowed establishing that a stretch of network maximizes losses when the pressure within its individual arcs and nodes increases.
- -
- CL3: This criterion allowed establishing that a section of the network maximizes losses when the number of users served increases.
5. Results and Discussion
6. Conclusions and Future Work
Author Contributions
Funding
Conflicts of Interest
Appendix A
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Macro-Indicator | Description |
---|---|
M1 | “Water losses” (to minimize losses, with effective monitoring of water infrastructure), taking into account both actual and percentage water losses; |
M2 | “Service interruptions” (to maintain service continuity, also through a suitable configuration of supply sources). It represents the ratio between the total length of interruptions in a year and the number of end users served by the supplier; |
M3 | “Quality of water supplied” (to ensure adequate quality of the resource for human consumption). It uses multi-stage logic, considering: (i) the incidence of non-potability orders; (ii) the rate of noncompliant internal samples; (iii) the level of parameters from noncompliant internal controls; |
M4 | “Adequacy of the sewage system” (to minimize environmental impact from wastewater). It uses multi-stage logic—considering: (i) the frequency of flooding and/or spills from sewers; (ii) the legal adequacy of flood drains; (iii) the control of flood drains; |
M5 | “Landfill sludge disposal” (to minimize the environmental impact of wastewater treatment, for sludge). It represents the ratio between the amount of sewage sludge measured dry that is disposed of in landfills and the total quantity of sewage sludge measured dry; |
M6 | “Quality of purified water” (to minimize the environmental impact of wastewater treatment, for the water line). This represents the rate of wastewater discharge samples exceeding the limits. |
Theme | Classes |
---|---|
theme 01: Water supply network (0701) | class 01: Section of the water supply network (TR_AAC-070101) |
class 02: Node of the water supply network (TR_AAC-070102) | |
class 03: Water supply network (TR_AAC-070103) | |
theme 02: Water disposal network (0702) | class 01: Section of the water disposal network (TR_AAC-070201) |
class 02: Node of the water disposal network (TR_AAC-070202) | |
class 03: Water disposal network (TR_AAC-070203) |
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Grimaldi, M.; Sebillo, M.; Vitiello, G.; Pellecchia, V. Planning and Managing the Integrated Water System: A Spatial Decision Support System to Analyze the Infrastructure Performances. Sustainability 2020, 12, 6432. https://doi.org/10.3390/su12166432
Grimaldi M, Sebillo M, Vitiello G, Pellecchia V. Planning and Managing the Integrated Water System: A Spatial Decision Support System to Analyze the Infrastructure Performances. Sustainability. 2020; 12(16):6432. https://doi.org/10.3390/su12166432
Chicago/Turabian StyleGrimaldi, Michele, Monica Sebillo, Giuliana Vitiello, and Vincenzo Pellecchia. 2020. "Planning and Managing the Integrated Water System: A Spatial Decision Support System to Analyze the Infrastructure Performances" Sustainability 12, no. 16: 6432. https://doi.org/10.3390/su12166432