Various other optimisation algorithms have been developed that are beyond the scope of this research, for example, the impact of problem formulations, pipe selection methods and optimisation algorithms on the rehabilitation of existing water distribution systems (Wang et al. 2020). Transient flow modelling, which has been reviewed in significant detail by Duan et al. (2020), also falls beyond the scope of this research. A summary of the tools developed through earlier research that are related to this research is provided in Table 1.
Earlier tools for predicting required water and sewer pipeline infrastructure
| Description . | Reference . |
|---|---|
| Table linking sewer pipe lengths and diameters to population size | Dames & Moore (1978) |
| Virtual infrastructure benchmarking tool to generate complex case studies for urban water systems | Sitzenfrei et al. (2010a, 2010b) |
| Case study on 30 cities to show that the relationship between pipeline length and the number of pipes by length class can be defined by the power law | Venkatesh & Brattebø (2011) |
| A model to predict the distribution of water pipeline lengths based on road layouts | Kobayashi et al. (2011) |
| A generic model of length, diameter distribution and replacement costs for the sewer network in a settlement with fixed area | Maurer et al. (2012) |
| A model estimating total length, total pipelines mass and diameter distribution for sewer networks where only area and population density are known | Pauliuk et al. (2014) |
| Empirical equations developed through regression analyses linking the total installation cost of sewer networks to the population size | Balaji et al. (2015) |
| A cost benchmark for water services which provides typical unit costs of water services projects and individual infrastructure components | DWS (2016) |
| A graph theory-based methodology for sewer system optimisation, that generates a viable sewer network layout | Turan et al. (2019) |
| A graph theory-based framework for sewer system layout and a generic scheme for decentralised layouts in both steep and flat terrains | Hesarkazzazi et al. (2022) |
| A spatial algorithm for generating simplified sewer networks which represent key characteristics of real systems, using basic topographic, demographic and urban characteristics | Duque et al. (2022) |
| A multiple linear regression tool to estimate the total sewer pipeline length for a service zone using basic service zone characteristics | Winter et al. (2022) |
| Description . | Reference . |
|---|---|
| Table linking sewer pipe lengths and diameters to population size | Dames & Moore (1978) |
| Virtual infrastructure benchmarking tool to generate complex case studies for urban water systems | Sitzenfrei et al. (2010a, 2010b) |
| Case study on 30 cities to show that the relationship between pipeline length and the number of pipes by length class can be defined by the power law | Venkatesh & Brattebø (2011) |
| A model to predict the distribution of water pipeline lengths based on road layouts | Kobayashi et al. (2011) |
| A generic model of length, diameter distribution and replacement costs for the sewer network in a settlement with fixed area | Maurer et al. (2012) |
| A model estimating total length, total pipelines mass and diameter distribution for sewer networks where only area and population density are known | Pauliuk et al. (2014) |
| Empirical equations developed through regression analyses linking the total installation cost of sewer networks to the population size | Balaji et al. (2015) |
| A cost benchmark for water services which provides typical unit costs of water services projects and individual infrastructure components | DWS (2016) |
| A graph theory-based methodology for sewer system optimisation, that generates a viable sewer network layout | Turan et al. (2019) |
| A graph theory-based framework for sewer system layout and a generic scheme for decentralised layouts in both steep and flat terrains | Hesarkazzazi et al. (2022) |
| A spatial algorithm for generating simplified sewer networks which represent key characteristics of real systems, using basic topographic, demographic and urban characteristics | Duque et al. (2022) |
| A multiple linear regression tool to estimate the total sewer pipeline length for a service zone using basic service zone characteristics | Winter et al. (2022) |