Advances in Assessing the Reliability of Water Distribution Networks: A Bibliometric Analysis and Scoping Review
Abstract
:1. Introduction
2. Background
- The MCS method involves generating random values for uncertain variables, such as nodal demands and/or pipe roughness coefficients. The random variables are usually modeled by assuming that they follow a certain probability distribution with a deterministic mean and a certain percentage of the mean as the standard deviation. The network is then analyzed for each of these random samples of uncertain variables. The reliability is then estimated as the ratio of the number of times the system performed satisfactorily to the total number of samples. The system is in failure condition if at least one of the nodes has any deficit in supply. The advantage of this approach is that it is easy to implement, while the major disadvantage is that it requires a substantial amount of random sample generation, making it a very time-consuming process.
- The FOSM includes the estimation of the covariance matrix of output parameter(s) as a function of the variance of the model input parameters. In addition, the gradient of the model output with respect to the model input parameters is calculated. The WDN needs to be evaluated for K + 1 scenarios (K being the number of input parameters and one base scenario, where the parameters are assumed to be certain). The main advantage of the FOSM method is that it does not require the substantial number of simulations needed in the MCS method. The drawback of the method is that it becomes inefficient in cases of large variations in the random variables, since the effect of non-linearity in the model becomes dominant, thereby deteriorating the accuracy of the model.
- Node reliability factor is defined as the ratio of available outflow to desired outflow volume at a node. Volume reliability factor is defined as the ratio of the total outflow volume to desired outflow volume for the entire network, considering all the states during the analysis period. Network reliability factor is calculated by multiplying the time factor and node factor with the volume reliability factor. The advantage of considering these factors is that they provide a more accurate picture of the reliability values when compared to the normal approach followed in the MCS method. The drawback of this method is that it requires significant computational time, as it employs the MCS approach.
- Minimum cut set is defined as the minimum number of components that, upon collectively failing, causes a system failure. However, if any of the components is in a working state, the system failure would not occur. Thus, for a branched network, the failure of a single component can lead to the failure of the entire network; in a looped network, simultaneous failure of two or more components might be needed to cause system failure. This implies that the size of the cut set would be different for different networks. The reliability of the WDN is estimated as the demand satisfaction considering failure of each of these minimum cut sets.
- The probabilistic approach considers that the failure probability of each pipe is the same and thus estimates reliability as the demand satisfaction under the simulated failure of each pipe at a time and aggregate for all failure situations. Different tools exist to determine the failure scenarios, such as reliability block diagrams [65], failure tree analysis [66], etc.
3. Methodology
3.1. Research Questions
- What trends and patterns can be detected by analyzing articles on WDN reliability in terms of:
- a.
- The number of relevant publications and citations.
- b.
- The countries that contributed the most to the knowledge base.
- c.
- The top journals that have published the most cited articles on the topic.
- d.
- The top articles in the literature that have the greatest impact in terms of citation as well as page rank analysis.
- e.
- The top authors in the literature that have the greatest impact in terms of number of publications and citation.
- What is the nature of collaboration in the field of WDN reliability as evidenced by co-authored publications?
- What are the key concepts, tools, and applications that have been explored in the field of WDN reliability and how they are related?
3.2. Data Extraction
3.3. Bibliometric Analysis
- (1)
- The number of documents and citations in a defined period.
- (2)
- The top authors publishing articles in the field of WDN reliability by number of publications and citations and their collaborations.
- (3)
- Top articles by the number of citations.
- (4)
- The top countries producing articles in the field of WDN reliability and their collaborations.
3.4. Content Analysis
4. Results
4.1. Trend in Articles Output
4.2. Citation Analysis of Articles
4.3. Co-Authorship and Collaboration Analysis
4.3.1. Co-Author Analysis
4.3.2. Countries Network Map
4.3.3. Journal Impact
4.4. Co-Citation and Clustering Analysis
4.4.1. Co-Citation Analysis
Article | Cluster | Betweenness | PageRank |
---|---|---|---|
Todini (2000) [8] | 1 | 223.332 | 0.021 |
Alperovits and Shamir (1977) [20] | 1 | 48.809 | 0.021 |
Fujiwara and De Silva (1990) [82] | 1 | 1.811 | 0.020 |
Xu and Goulter (1999) [83] | 1 | 11.478 | 0.020 |
Simpson et al. (1994) [84] | 1 | 3.457 | 0.019 |
Farmani et al. (2005) [11] | 1 | 7.735 | 0.020 |
Prasad and Park (2004) [9] | 1 | 6.198 | 0.019 |
Savic and Walters (1997) [85] | 1 | 0.577 | 0.018 |
Tolson et al. (2004) [73] | 1 | 10.340 | 0.019 |
Deb et al. (2002) [86] | 1 | 2.421 | 0.019 |
Rossman (2000) [77] | 2 | 96.938 | 0.024 |
Wagner et al. (1988) [78] | 2 | 22.916 | 0.023 |
Bao and Mays (1990) [1] | 2 | 9.589 | 0.021 |
Walski (1993) [87] | 2 | 1.870 | 0.021 |
Tanyimboh et al. (2001) [72] | 2 | 6.720 | 0.021 |
Wagner et al. (1988) [88] | 2 | 5.422 | 0.023 |
Ostfeld and Salomons (2004) [89] | 2 | 4.448 | 0.022 |
Xu and Goulter (1998) [14] | 2 | 5.327 | 0.020 |
Germanopoulos (1985) [90] | 2 | 1.488 | 0.020 |
Fujiwara and Ganesharajah (1993) [91] | 2 | 1.670 | 0.021 |
Jayaram and Srinivasan (2008) [10] | 3 | 45.350 | 0.020 |
Raad et al. (2010) [79] | 3 | 42.236 | 0.020 |
Tanyimboh and Templeman (1993) [80] | 3 | 27.807 | 0.020 |
Tanyimboh and Templeman (2000) [71] | 3 | 42.326 | 0.020 |
Tanyimboh and Templeman (1993) [81] | 3 | 22.664 | 0.019 |
Prasad et al. (2004) [92] | 3 | 49.053 | 0.020 |
Gheisi and Naser (2015) [75] | 3 | 27.446 | 0.019 |
Atkinson et al. (2014) [74] | 3 | 15.626 | 0.019 |
Yassin-Kassab et al. (1999) [93] | 3 | 13.915 | 0.019 |
Tanyimboh and Templeman (1993) [94] | 3 | 0.080 | 0.020 |
4.4.2. Keywords Clustering Analysis
4.5. Thematic Clustering and Research Trends
5. Discussion
5.1. Major Research Areas
- Reliability-based single and multi-objective design of WDNs: The works in this category consists of the application and development of improved optimization tools for reliability-based design of WDNs. Various traditional methods, such as LP, NLP, and MINLP, were employed by past studies. Subsequently, advanced techniques, such as evolutionary algorithms, were employed and were found to possess several advantages over the traditional approaches. Article [11], published in JWRPM, is one of the most cited publications in this field. They formulated the problem as a multi-objective optimization problem for cost minimization and reliability maximization (estimated using resilience as surrogate) using NSGA-II as the optimization tool. Article [95], published in JWRPM, is also a highly cited study employing GA for solving a reliability-based single objective problem: cost minimization keeping reliability as a constraint, considering uncertainty in nodal demands using MCS. Some of the recent publications in this field are [12], that incorporates Self-Adaptive Differential Evolution (SADE) for reliability-based design of WDNs; [96], that presented a Dynamic Adaptive Approach for WDN design; and [97], that presented Self-Adaptive Solution-Space Reduction Algorithm for WDN design.
- Reliability Assessment Models: Development of reliability assessment techniques are the focus of this field. Some of the oldest techniques include minimum cut set method and simple probabilistic approach for mechanical reliability estimation; and MCS, FORM, and network reliability factor for hydraulic reliability estimation. Later, several RSMs evolved, including resilience, network resilience, and entropy etc., that have the advantage of reduced computational time compared to the traditional approaches. Article [8], published in Urban Water Journal, is one of the most cited articles in the field; it introduced resilience as a surrogate for reliability. Article [9], published in JWRPM, is another highly cited article; it introduced network resilience as an RSM. Several studies focused on performance assessment of one or more of these RSMs [6,13,79,98,99]. Studies reported different findings in terms of the performance of these RSMs under different conditions.
- Consideration of energy, life cycle cost (LCC), and GHG emissions for expansion and rehabilitation of WDNs: The research in this field focuses on the consideration of aspects such as optimal design and expansion, considering aspects such as LCC, energy consumption, and GHG emissions. Article [11] is a highly cited article that considered LCC in the formulation of WDNs. Article [100] is another highly cited article that presented a model for minimization of LCC and CO2 emissions and found that minimizing CO2 emissions can be achieved at a higher LCC. Article [101] presented a dynamic design for the expansion and rehabilitation of WDNs. It found that a dynamic design led to more reliable and lower cost networks. Articles [102,103] presented a enhanced evolutionary algorithm frameworks for the expansion of WDNs considering LCC in their model, and found that this framework led to better solutions when compared to traditional approaches.
5.2. Research Gaps
- Reliability-based single and multi-objective design of WDNs: Many optimization tools are provided in the literature. Different studies have shown different tools to be efficient for solving the WDN design problem. There is, however, a need to present a comprehensive review of the various optimization tools and to test their suitability, their advantages, and their drawbacks. The suitability of these algorithms has mostly been tested for consideration of objectives such as cost and reliability. A detailed analysis in terms of how the algorithms will perform on consideration of other objectives, such as GHG emissions, vulnerability etc., should be performed.
- Reliability Assessment Models: The last two decades have shown an emerging trend in the usage of RSMs. Studies presented and tested these RSMs under various conditions. However, different studies reported different conclusions regarding the suitability of these RSMs. Few studies compared the performance of the various RSMs and the outcomes varied for different studies. Surrogate measures such as entropy, resilience, and network resilience are based on the pressure and flow conditions that would prevail in case of probable failure scenarios. Some studies focused on the consumer’s perspective in terms of the damages caused by incorporating a damage function, when the requirements are not met. Thus, there is a lack of a comprehensive review in terms of the usage of these RSMs, the conditions under which they have been tested and found to be suitable, and their advantages and disadvantages. Findings in terms of which RSMs need further exploration, which RSMs are suitable under what conditions, and which RSMs are unsuitable for some specific conditions must be produced.
- Consideration of energy, LCC, and GHG emissions for the expansion and rehabilitation of WDNs: Some studies considered the aspects of energy, LCC, and GHG emissions for the optimal expansion and rehabilitation of WDNs. The benefit of considering these aspects in WDN optimization must be tested by acquiring real data in terms of emissions or cost under different scenarios but when implemented at similar locations. Improvements of the WDN expansion techniques are needed, as new optimization approaches continue to be developed.
6. Conclusions and Recommendations
- There is an increasing trend in the number of publications in the field of WDN reliability, revealing its growing importance over the past two decades. The number of citations, however, has an alternating increasing and decreasing cycle.
- Some of the most cited documents are comprised of articles focused on the introduction of RSMs, such as resilience, network resilience etc. This shows that the use of RSMs has gained considerable momentum over the last two decades.
- Bibliographic coupling led to identification of three major areas of publications: reliability, water distribution networks, and optimization. Thus, cluster 1 is comprised of articles on reliability-based design of WDNs, including aspects such as hydraulic and mechanical failures, uncertainty, vulnerability, and redundancy. Cluster 2 is comprised of articles focused on WDN design and modeling, including aspects such as single and multi-objective optimization, rehabilitation, leakage, calibration, etc. Cluster 3 includes articles on the development and application of various optimization tools for WDN design.
- Thematic maps revealed that the consideration of cost and energy constitute one of the emerging trends in this field. Detailed analysis of the articles sheds light on the need to assess the suitability and performance of various RSMs in WDN analysis.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Author, Journal | LC | GC | LC/GC (%) | NLC | NGC |
---|---|---|---|---|---|
Todini (2000) [8], Urban Water Journal | 91 | 517 | 17.60 | 5.39 | 5.60 |
Prasad and Park (2004) [9], Journal of Water Resources Planning and Management | 70 | 432 | 16.20 | 3.37 | 3.42 |
Tanyimboh and Templeman (2000) [71], Engineering Optimization | 38 | 97 | 39.18 | 2.25 | 1.05 |
Tanyimboh et al. (2001) [72], Journal of Water Resources Planning and Management | 30 | 129 | 23.26 | 2.45 | 2.08 |
Farmani et al. (2005) [11], Journal of Water Resources Planning and Management | 29 | 230 | 12.61 | 3.13 | 3.50 |
Tolson et al. (2004) [73], Journal of Water Resources Planning and Management | 27 | 186 | 14.52 | 1.30 | 1.47 |
Atkinson et al. (2014) [74], Journal of Water Resources Planning and Management | 23 | 52 | 44.23 | 5.95 | 1.66 |
Gheisi and Naser (2015) [75], Journal of Water Resources Planning and Management | 20 | 37 | 54.05 | 7.27 | 2.57 |
Kalungi and Tanyimboh (2003) [76], Reliability Engineering and System Safety | 20 | 91 | 21.98 | 2.14 | 2.27 |
Giustolisi and Savic (2010) [46], Urban Water Journal | 19 | 105 | 18.10 | 6.91 | 3.98 |
Author Name | h_Index | TC | NP | PY_Start | Institute | Country |
---|---|---|---|---|---|---|
Farmani R. | 9 | 779 | 11 | 2005 | University of Exeter | United Kingdom |
Tanyimboh T.T. | 14 | 646 | 20 | 2000 | University of the Witwatersrand, Johannesburg | South Africa |
Walters G.A. | 4 | 609 | 4 | 2000 | University of Exeter | United Kingdom |
Savic D. A. | 5 | 1061 | 9 | 2000 | National University of Malaysia | Malaysia |
Todini E. | 1 | 517 | 1 | 2000 | University of Bologna | Italy |
Kapelan Z. | 7 | 464 | 8 | 2005 | Delft University of Technology | Netherlands |
Jeffrey P. | 4 | 458 | 4 | 2011 | Cranfield University | United Kingdom |
Yazdani A. | 4 | 458 | 4 | 2011 | Princeton University | United States |
Park N.S. | 1 | 432 | 1 | 2004 | University of South Florida, Tampa | United States |
Prasad T.D. | 1 | 432 | 1 | 2004 | Gandhi Institute of Technology and Management | India |
Cluster | Country | NP | TC | TNP | TTC |
---|---|---|---|---|---|
1 | United States | 93 | 791 | 273 | 1955 |
Iran | 76 | 613 | |||
Canada | 39 | 207 | |||
Korea | 62 | 344 | |||
Qatar | 3 | 0 | |||
2 | United Kingdom | 84 | 2850 | 254 | 4738 |
Italy | 57 | 1410 | |||
South Africa | 13 | 56 | |||
Portugal | 7 | 16 | |||
China | 76 | 406 | |||
France | 9 | 0 | |||
Norway | 8 | 0 | |||
3 | India | 34 | 144 | 53 | 239 |
Australia | 19 | 95 | |||
4 | Poland | 26 | 159 | 49 | 476 |
Israel | 15 | 290 | |||
Czech Republic | 8 | 27 | |||
5 | Germany | 11 | 30 | 31 | 295 |
Spain | 20 | 265 |
Element | TC | TP | CPP | PY_Start |
---|---|---|---|---|
Journal of Water Resources Planning and Management | 2608 | 68 | 38.35 | 2001 |
Urban Water Journal | 1032 | 20 | 51.6 | 2000 |
Water Resources Management | 710 | 36 | 19.72 | 2008 |
Engineering Optimization | 472 | 11 | 42.91 | 2000 |
Reliability Engineering and System Safety | 377 | 11 | 34.27 | 2003 |
Journal of Hydroinformatics | 313 | 10 | 31.30 | 2006 |
Water Resources Research | 298 | 7 | 42.57 | 2011 |
Environmental Modelling and Software | 218 | 4 | 54.50 | 2009 |
Journal of Hydraulic Engineering | 207 | 4 | 51.75 | 2007 |
Water (Switzerland) | 182 | 15 | 12.13333 | 2013 |
Category | Keyword(s) | Occurrence | Total | Category | Keyword(s) | Occurrence | Total |
---|---|---|---|---|---|---|---|
Water Distribution Network | water supply | 11 | 228 | Genetic algorithm | genetic algorithm | 15 | 23 |
water supply network | 8 | genetic algorithms | 8 | ||||
WDN | 5 | Hydraulic analysis | hydraulic analysis | 9 | 18 | ||
water distribution | 18 | network analysis | 9 | ||||
water distribution network | 44 | Others | resilience | 14 | |||
water distribution networks | 48 | uncertainty | 14 | ||||
water distribution system | 38 | water quality | 14 | ||||
water distribution systems | 56 | entropy | 11 | ||||
pipe networks | 7 | EPANET | 9 | ||||
networks | 6 | hydraulic reliability | 9 | ||||
Reliability assessment and analysis | reliability | 76 | 116 | design | 8 | ||
reliability analysis | 9 | vulnerability | 8 | ||||
reliability assessment | 9 | graph theory | 7 | ||||
network reliability | 9 | redundancy | 6 | ||||
system reliability | 13 | rehabilitation | 6 | ||||
Multi-objective optimization | multi-objective | 6 | 21 | algorithms | 6 | ||
multi-objective optimization | 10 | calibration | 5 | ||||
Multi-objective optimization | 5 | demand-driven analysis | 5 | ||||
Optimization | optimization | 5 | 48 | MATLAB | 5 | ||
optimization | 43 | mechanical reliability | 5 | ||||
operation | 5 |
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Sirsant, S.; Hamouda, M.A.; Shaaban, M.F. Advances in Assessing the Reliability of Water Distribution Networks: A Bibliometric Analysis and Scoping Review. Water 2023, 15, 986. https://doi.org/10.3390/w15050986
Sirsant S, Hamouda MA, Shaaban MF. Advances in Assessing the Reliability of Water Distribution Networks: A Bibliometric Analysis and Scoping Review. Water. 2023; 15(5):986. https://doi.org/10.3390/w15050986
Chicago/Turabian StyleSirsant, Swati, Mohamed A. Hamouda, and Mostafa F. Shaaban. 2023. "Advances in Assessing the Reliability of Water Distribution Networks: A Bibliometric Analysis and Scoping Review" Water 15, no. 5: 986. https://doi.org/10.3390/w15050986
APA StyleSirsant, S., Hamouda, M. A., & Shaaban, M. F. (2023). Advances in Assessing the Reliability of Water Distribution Networks: A Bibliometric Analysis and Scoping Review. Water, 15(5), 986. https://doi.org/10.3390/w15050986