# Evaluation of Priority Control District Metered Area for Water Distribution Networks Using Water Quality-Related Big Data

^{1}

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## Abstract

**:**

## 1. Introduction

## 2. Methods

#### 2.1. PCDMA Selection Indicators

#### 2.1.1. Selection Criteria

#### 2.1.2. Particular Indicators

#### 2.2. Weighting Using AHP

_{max}) calculated through the eigenvalue analysis of the pairwise comparison matrix. The CI and the CR calculation equations are presented in Equations (1) and (2).

_{max}is principal eigenvalue, n is dimension of the matrix and RI is CI mean obtained from a random matrix of the same dimension.

#### 2.3. Total Score for PCDMA Selection

_{i}is the score of the particular indicator n, α

_{i}is the weight of the particular indicator n (second class) and β

_{i}is the weight of the selection criteria with particular indicators n (first class).

## 3. Application and Results

#### 3.1. Study Area and Data Investigation

#### 3.2. Weight Analysis by Selection Criteria

#### 3.2.1. Response Reliability Verification

^{−15}, lower than 0.2. After examining the CR by dividing the derived CI by a RI of 0.9, it was determined that the respondents’ answers were reliable because they were all calculated as 0.0, which is lower than 0.1.

#### 3.2.2. Pairwise Comparison

#### 3.3. Application of PCDMA Selection Indicators

#### 3.3.1. Complaints Indicator

#### 3.3.2. Pipe Deterioration Indicator

#### 3.3.3. Vulnerable Facility Indicator

#### 3.3.4. Unsuitable Water Quality Indicator

#### 3.4. Prioritization of PCDMA

## 4. Conclusions

## Author Contributions

## Funding

## Data Availability Statement

## Conflicts of Interest

## References

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**Figure 3.**Box plots of the calculation results of 481 DMAs for (

**a**) complaint indicator, (

**b**) pipe deterioration indicator, (

**c**) vulnerable facility indicator, (

**d**) unsuitable water quality indicator and particular indicators of the PCDMA selection criteria.

Selection Criteria | Particular Indicators | Equations | ||
---|---|---|---|---|

Indicator | Description | Indicator | Description | |

Complaints indicator | Whether there is a risk that water quality (WQ) accidents and WQ complaints occur or occur repeatedly | ①-1 | Percentage of WQ accidents and WQ complaints in a DMA compared to the entire target area | $\frac{\begin{array}{c}\mathrm{WQ}\mathrm{accidents}\mathrm{and}\mathrm{complaints}\\ \mathrm{in}\mathrm{a}\mathrm{DMA}\end{array}}{\begin{array}{c}\mathrm{WQ}\mathrm{accidents}\mathrm{and}\mathrm{complaints}\\ \mathrm{in}\mathrm{the}\mathrm{entire}\mathrm{target}\mathrm{area}\end{array}}$ |

①-2 | Percentage of WQ accidents and WQ complaints compared to the number of water meters in a DMA | $\frac{\mathrm{WQ}\mathrm{accident}\mathrm{and}\mathrm{complaints}\mathrm{in}\mathrm{a}\mathrm{DMA}}{\mathrm{water}\mathrm{meters}\mathrm{in}\mathrm{a}\mathrm{DMA}}$ | ||

①-3 | Percentage of highest WQ accidents and repeated occurrence of WQ complaints compared to the number of water meters in small zone units of DMA | $\frac{\begin{array}{c}\mathrm{highest}\mathrm{WQ}\mathrm{accident}\mathrm{and}\mathrm{complaints}\\ \mathrm{repeated}\mathrm{in}\mathrm{a}\mathrm{DMA}\end{array}}{\begin{array}{c}\mathrm{water}\mathrm{m}\mathrm{e}\mathrm{t}\mathrm{e}\mathrm{r}\mathrm{s}\mathrm{i}\mathrm{n}\mathrm{s}\mathrm{m}\mathrm{a}\mathrm{l}\mathrm{l}\mathrm{z}\mathrm{o}\mathrm{n}\mathrm{e}\mathrm{u}\mathrm{n}\mathrm{i}\mathrm{t}\mathrm{s}\\ \mathrm{w}\mathrm{h}\mathrm{e}\mathrm{r}\mathrm{e}\mathrm{h}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{e}\mathrm{s}\mathrm{t}\\ \mathrm{r}\mathrm{e}\mathrm{p}\mathrm{e}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{d}\mathrm{c}\mathrm{o}\mathrm{m}\mathrm{p}\mathrm{l}\mathrm{a}\mathrm{i}\mathrm{n}\mathrm{t}\mathrm{s}\mathrm{o}\mathrm{c}\mathrm{c}\mathrm{u}\mathrm{r}\mathrm{e}\mathrm{d}\mathrm{i}\mathrm{n}\mathrm{a}\mathrm{D}\mathrm{M}\mathrm{A}\end{array}}$ | ||

② Pipe deterioration indicator | Degree of aging of the water distribution network pipes | ②-1 | Percentage of old pipes in a DMA compared to the entire target area | $\frac{\mathrm{Length}\mathrm{of}\mathrm{old}\mathrm{pipe}\mathrm{in}\mathrm{a}\mathrm{DMA}}{\mathrm{Length}\mathrm{of}\mathrm{old}\mathrm{pipe}\mathrm{in}\mathrm{the}\mathrm{entire}\mathrm{target}\mathrm{area}}$ |

②-2 | Percentage of non-corrosion-resistant pipes in a DMA compared to the entire target area | $\frac{\begin{array}{c}\mathrm{L}\mathrm{e}\mathrm{n}\mathrm{g}\mathrm{t}\mathrm{h}\mathrm{o}\mathrm{f}\mathrm{n}\mathrm{o}\mathrm{n}-\mathrm{c}\mathrm{o}\mathrm{r}\mathrm{r}\mathrm{o}\mathrm{s}\mathrm{i}\mathrm{o}\mathrm{n}-\mathrm{r}\mathrm{e}\mathrm{s}\mathrm{i}\mathrm{s}\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{t}\mathrm{p}\mathrm{i}\mathrm{p}\mathrm{e}\mathrm{s}\\ \mathrm{i}\mathrm{n}\mathrm{a}\mathrm{D}\mathrm{M}\mathrm{A}\end{array}}{\begin{array}{c}\mathrm{L}\mathrm{e}\mathrm{n}\mathrm{g}\mathrm{t}\mathrm{h}\mathrm{o}\mathrm{f}\mathrm{n}\mathrm{o}\mathrm{n}-\mathrm{c}\mathrm{o}\mathrm{r}\mathrm{r}\mathrm{o}\mathrm{s}\mathrm{i}\mathrm{o}\mathrm{n}-\mathrm{r}\mathrm{e}\mathrm{s}\mathrm{i}\mathrm{s}\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{t}\mathrm{p}\mathrm{i}\mathrm{p}\mathrm{e}\mathrm{s}\\ \mathrm{i}\mathrm{n}\mathrm{t}\mathrm{h}\mathrm{e}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{i}\mathrm{r}\mathrm{e}\mathrm{t}\mathrm{a}\mathrm{r}\mathrm{g}\mathrm{e}\mathrm{t}\mathrm{a}\mathrm{r}\mathrm{e}\mathrm{a}\end{array}}$ | ||

②-3 | Percentage of old pipe length compared to total length in a DMA | $\frac{\mathrm{Length}\mathrm{of}\mathrm{old}\mathrm{pipes}\mathrm{in}\mathrm{a}\mathrm{DMA}}{\mathrm{Total}\mathrm{length}\mathrm{in}\mathrm{a}\mathrm{DMA}}$ | ||

②-4 | Percentage of non-corrosion-resistant pipe length compared to total length in a DMA | $\frac{\begin{array}{c}\mathrm{L}\mathrm{e}\mathrm{n}\mathrm{g}\mathrm{t}\mathrm{h}\mathrm{o}\mathrm{f}\mathrm{n}\mathrm{o}\mathrm{n}-\mathrm{c}\mathrm{o}\mathrm{r}\mathrm{r}\mathrm{o}\mathrm{s}\mathrm{i}\mathrm{o}\mathrm{n}-\mathrm{r}\mathrm{e}\mathrm{s}\mathrm{i}\mathrm{s}\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{t}\mathrm{p}\mathrm{i}\mathrm{p}\mathrm{e}\mathrm{s}\\ \mathrm{in}\mathrm{a}\mathrm{D}\mathrm{M}\mathrm{A}\end{array}}{\mathrm{Total}\mathrm{length}\mathrm{in}\mathrm{a}\mathrm{DMA}}$ | ||

③ Vulnerable facility indicator | Whether there is a risk of significant damage in the event of a water accident | ③-1 | Percentage of vulnerable facilities in a DMA compared to the entire target area | $\frac{\mathrm{vulnerable}\mathrm{facilities}\mathrm{in}\mathrm{a}\mathrm{DMA}}{\mathrm{vulnerable}\mathrm{facilities}\mathrm{in}\mathrm{the}\mathrm{entire}\mathrm{target}\mathrm{area}}$ |

③-2 | Percentage of vulnerable facilities compared to the number of water meters in a DMA | $\frac{\mathrm{vulnerable}\mathrm{facility}\mathrm{in}\mathrm{a}\mathrm{DMA}}{\mathrm{water}\mathrm{meters}\mathrm{in}\mathrm{a}\mathrm{DMA}}$ | ||

④ Unsuitable water quality indicator | Whether there are concerns about violating water quality standards | ④-1 | Percentage of unsuitable water quality test results in a DMA compared to the entire target area | $\frac{\begin{array}{c}\mathrm{u}\mathrm{n}\mathrm{s}\mathrm{u}\mathrm{i}\mathrm{t}\mathrm{a}\mathrm{b}\mathrm{l}\mathrm{e}\mathrm{W}\mathrm{Q}\mathrm{t}\mathrm{e}\mathrm{s}\mathrm{t}\mathrm{r}\mathrm{e}\mathrm{s}\mathrm{u}\mathrm{l}\mathrm{t}\mathrm{s}\\ \mathrm{i}\mathrm{n}\mathrm{a}\mathrm{D}\mathrm{M}\mathrm{A}\end{array}}{\begin{array}{c}\mathrm{u}\mathrm{n}\mathrm{s}\mathrm{u}\mathrm{i}\mathrm{t}\mathrm{a}\mathrm{b}\mathrm{l}\mathrm{e}\mathrm{W}\mathrm{Q}\mathrm{t}\mathrm{e}\mathrm{s}\mathrm{t}\mathrm{r}\mathrm{e}\mathrm{s}\mathrm{u}\mathrm{l}\mathrm{t}\mathrm{s}\\ \mathrm{i}\mathrm{n}\mathrm{t}\mathrm{h}\mathrm{e}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{i}\mathrm{r}\mathrm{e}\mathrm{t}\mathrm{a}\mathrm{r}\mathrm{g}\mathrm{e}\mathrm{t}\mathrm{a}\mathrm{r}\mathrm{e}\mathrm{a}\end{array}}$ |

④-2 | Percentage of unsuitable water quality test results compared to the number of water meters in a DMA | $\frac{\mathrm{unsuitable}\mathrm{WQ}\mathrm{test}\mathrm{results}\mathrm{in}\mathrm{a}\mathrm{DMA}}{\mathrm{water}\mathrm{meters}\mathrm{in}\mathrm{a}\mathrm{DMA}}$ |

Category | Variable (Unit) | Total |
---|---|---|

Water distribution network (WDN) | Water meters (-) | 357,232 |

District metered area (-) | 481 | |

Complaints indicator | Water quality complaints (-) | 1624 |

Pipe deterioration indicator | Total pipe length (km) | 8030.92 |

Old pipe length (over 21 years old) (km) | 1202.9 | |

Non-corrosion-resistant pipe length (km) | 2.99 | |

Vulnerable facility indicator | Medical facility (-) | 416 |

School (-) | 722 | |

Unsuitable water quality indicator | Water quality tests | 896 |

Suitable for water quality | 893 | |

Unsuitable for water quality | 3 |

Division | Pair Comparison Matrix | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|

First class | Selection Criteria | Division | Complaints indicator | Pipe deterioration indicator | Vulnerable facility indicator | Unsuitable water quality indicator | |||||||||||||||||||||||||||||||||||||||||||||||||||||||

Complaints indicator | 1.000 | 2.152 | 1.200 | 2.042 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Pipe deterioration indicator | 0.465 | 1.000 | 0.622 | 0.906 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Vulnerable facility indicator | 0.833 | 1.608 | 1.000 | 1.544 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Unsuitable water quality indicator | 0.490 | 1.104 | 0.648 | 1.000 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Second class | Complaints indicator | Division | ①-1 | ①-2 | ①-3 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||

①-1 | 1.000 | 1.277 | 1.151 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

①-2 | 0.783 | 1.000 | 0.933 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

①-3 | 0.869 | 1.072 | 1.000 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Pipe deterioration indicator | Division | ②-1 | ②-2 | ②-3 | ②-4 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||

②-1 | 1.000 | 0.893 | 0.735 | 0.606 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||

②-2 | 1.120 | 1.000 | 0.982 | 0.663 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||

②-3 | 1.361 | 1.019 | 1.000 | 0.641 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||

②-4 | 1.649 | 1.508 | 1.561 | 1.000 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Vulnerable facility indicator | Division | ③-1 | ③-2 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

③-1 | 1.000 | 1.201 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

③-2 | 0.832 | 1.000 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Unsuitable water quality indicator | Division | ④-1 | ④-2 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

④-1 | 1.000 | 1.000 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

④-2 | 1.000 | 1.000 |

Division | Standard Indicator | Weight |
---|---|---|

Selection Criteria | ① Complaints indicator | 0.361 |

② Pipe deterioration indicator | 0.170 | |

③ Vulnerable facility indicator | 0.286 | |

④ Unsuitable water quality indicator | 0.183 |

Division | Particular Indicators | Weight |
---|---|---|

Complaints indicator | ①-1 | 0.377 |

①-2 | 0.299 | |

①-3 | 0.324 | |

Pipe deterioration indicator | ②-1 | 0.194 |

②-2 | 0.225 | |

②-3 | 0.237 | |

②-4 | 0.343 | |

Vulnerable facility indicator | ③-1 | 0.546 |

③-2 | 0.454 | |

Unsuitable water quality indicator | ④-1 | 0.501 |

④-2 | 0.499 |

First Class | Second Class | Integrated Weight | Importance Rank |
---|---|---|---|

Sum of weighted score | 1.000 | ||

Complaints indicator (0.361) | ①-1(0.377) | 0.136 | 2 |

①-2(0.299) | 0.108 | 5 | |

①-3(0.324) | 0.117 | 4 | |

Pipe deterioration indicator (0.170) | ②-1(0.194) | 0.033 | 11 |

②-2(0.225) | 0.038 | 10 | |

②-3(0.237) | 0.040 | 9 | |

②-4(0.343) | 0.058 | 8 | |

Vulnerable facility indicator (0.286) | ③-1(0.546) | 0.156 | 1 |

③-2(0.454) | 0.130 | 3 | |

Unsuitable water quality indicator (0.183) | ④-1(0.501) | 0.092 | 6 |

④-2(0.499) | 0.091 | 7 |

Selection Criteria | Indicator | Max | Med | Min. | Avg. |
---|---|---|---|---|---|

① Complaints indicator | ①-1 | 1.000 | 0.004 | 0.000 | 0.013 |

①-2 | 1.000 | 0.008 | 0.000 | 0.022 | |

①-3 | 1.000 | 0.000 | 0.000 | 0.006 | |

Total score | 1.000 | 0.004 | 0.000 | 0.013 | |

② Pipe deterioration indicator | ②-1 | 1.000 | 0.145 | 0.000 | 0.173 |

②-2 | 1.000 | 0.000 | 0.000 | 0.006 | |

②-3 | 1.000 | 0.241 | 0.000 | 0.247 | |

②-4 | 1.000 | 0.000 | 0.000 | 0.006 | |

Total score | 0.679 | 0.092 | 0.000 | 0.096 | |

③ Vulnerable facility indicator | ③-1 | 1.000 | 0.143 | 0.000 | 0.165 |

③-2 | 1.000 | 0.014 | 0.000 | 0.034 | |

Total score | 0.805 | 0.081 | 0.000 | 0.105 | |

④ Unsuitable water quality indicator | ④-1 | 1.000 | 0.000 | 0.000 | 0.006 |

④-2 | 1.000 | 0.000 | 0.000 | 0.004 | |

Total score | 1.000 | 0.000 | 0.000 | 0.005 |

Selection Criteria | Max | Med | Min. | Avg. |
---|---|---|---|---|

① Complaints indicator | 1.000 | 0.004 | 0.000 | 0.013 |

② Pipe deterioration indicator | 0.679 | 0.092 | 0.000 | 0.096 |

③ Vulnerable facility indicator | 0.805 | 0.081 | 0.000 | 0.105 |

④ Unsuitable water quality indicator | 1.000 | 0.000 | 0.000 | 0.005 |

Total score | 0.373 | 0.040 | 0.000 | 0.052 |

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**MDPI and ACS Style**

Kim, T.; Oh, Y.; Koo, J.; Yoo, D.
Evaluation of Priority Control District Metered Area for Water Distribution Networks Using Water Quality-Related Big Data. *Sustainability* **2022**, *14*, 7282.
https://doi.org/10.3390/su14127282

**AMA Style**

Kim T, Oh Y, Koo J, Yoo D.
Evaluation of Priority Control District Metered Area for Water Distribution Networks Using Water Quality-Related Big Data. *Sustainability*. 2022; 14(12):7282.
https://doi.org/10.3390/su14127282

**Chicago/Turabian Style**

Kim, Taehyeon, Yoojin Oh, Jayong Koo, and Doguen Yoo.
2022. "Evaluation of Priority Control District Metered Area for Water Distribution Networks Using Water Quality-Related Big Data" *Sustainability* 14, no. 12: 7282.
https://doi.org/10.3390/su14127282