Infrastructure Leakage Index and Challenges in Water Loss Management in Developing Countries

Water losses in water distribution networks (WDNs) are unavoidable. Water losses are evaluated based on performance indicators (PIs) and used for future recommendations for network operators to take measures against water losses. However, these evaluations primarily focus on large and medium sized WDN and do not deal with the challenges of small WDNs (e.g., technical, and financial limitations, missing data). Therefore, an appropriate water loss management is a major challenge for operators in the federal state of Tyrol (Austria) due to the high number of small WDNs, e.g., low income in combination with long network lengths. In this regard, this work specifies and discusses state funding in Austria to support network operators to reduce water losses. To assess the impacts on management strategies, 40 WDNs, supplying 200 to 16,000 inhabitants, are investigated in detail. As the comparison of different PIs shows, a volume related PI (e.g., water loss volume divided by total water demand) is recommend as the decision criterion for local authorities due to minimal efforts and its easy calculation. Moreover, public funding helps to significantly reduce water losses in individual systems, but countermeasures should be different for small and larger WDNs. For example, leakage detection campaigns and rehabilitation planning based on pipe age should be established in future for larger WDNs in Tyrol. In contrast, an online flow metering system to monitor system inflows is suggested for small WDNs. Based on measurement data, leakages and burst can be detected and repaired swiftly.

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q-Rung Orthopair Fuzzy Geometric Aggregation Operators Based on Generalized and Group-Generalized Parameters with Application to Water Loss Management

Symmetry ◽

10.3390/sym12081236 ◽

2020 ◽

Vol 12 (8) ◽

pp. 1236

Author(s):

Muhammad Riaz ◽

Ayesha Razzaq ◽

Humaira Kalsoom ◽

Dragan Pamučar ◽

Hafiz Muhammad Athar Farid ◽

...

Keyword(s):

Decision Making ◽

Fuzzy Set ◽

Water Loss ◽

Intuitionistic Fuzzy Set ◽

Aggregation Operator ◽

Aggregation Operators ◽

Water Supply Systems ◽

Pythagorean Fuzzy Set ◽

Water Losses ◽

Water Loss Management

The notions of fuzzy set (FS) and intuitionistic fuzzy set (IFS) make a major contribution to dealing with practical situations in an indeterminate and imprecise framework, but there are some limitations. Pythagorean fuzzy set (PFS) is an extended form of the IFS, in which degree of truthness and degree of falsity meet the condition 0≤Θ˘2(x)+K2(x)≤1. Another extension of PFS is a q´-rung orthopair fuzzy set (q´-ROFS), in which truthness degree and falsity degree meet the condition 0≤Θ˘q´(x)+Kq´(x)≤1,(q´≥1), so they can characterize the scope of imprecise information in more comprehensive way. q´-ROFS theory is superior to FS, IFS, and PFS theory with distinguished characteristics. This study develops a few aggregation operators (AOs) for the fusion of q´-ROF information and introduces a new approach to decision-making based on the proposed operators. In the framework of this investigation, the idea of a generalized parameter is integrated into the q´-ROFS theory and different generalized q´-ROF geometric aggregation operators are presented. Subsequently, the AOs are extended to a “group-based generalized parameter”, with the perception of different specialists/decision makers. We developed q´-ROF geometric aggregation operator under generalized parameter and q´-ROF geometric aggregation operator under group-based generalized parameter. Increased water requirements, in parallel with water scarcity, force water utilities in developing countries to follow complex operating techniques for the distribution of the available amounts of water. Reducing water losses from water supply systems can help to bridge the gap between supply and demand. Finally, a decision-making approach based on the proposed operator is being built to solve the problems under the q´-ROF environment. An illustrative example related to water loss management has been given to show the validity of the developed method. Comparison analysis between the proposed and the existing operators have been performed in term of counter-intuitive cases for showing the liability and dominance of proposed techniques to the existing one is also considered.

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Drinking water loss management in Palestine: a case study of the Hebron city water distribution network

International Journal of Global Environmental Issues ◽

10.1504/ijgenvi.2017.10004151 ◽

2017 ◽

Vol 16 (1/2/3) ◽

pp. 91

Author(s):

Samah Jawad Jabari

Keyword(s):

Drinking Water ◽

Water Loss ◽

Water Distribution ◽

Distribution Network ◽

Water Distribution Network ◽

City Water ◽

Water Loss Management

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Performance Based Water Loss Management for Gweru, Zimbabwe

American Journal of Water Resources ◽

10.12691/ajwr-5-4-2 ◽

2017 ◽

Vol 5 (4) ◽

pp. 100-105

Author(s):

Eugine Makaya

Keyword(s):

Water Loss ◽

Water Loss Management

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Impact of active night population and leakage exponent on leakage estimation in developing countries

Water Practice & Technology ◽

10.2166/wpt.2021.124 ◽

2021 ◽

Author(s):

Peace Korshiwor Amoatey ◽

Abena Agyeiwaa Obiri-Yeboah ◽

Maxwell Akosah-Kusi

Keyword(s):

Developing Countries ◽

Water Balance ◽

Relative Error ◽

Water Loss ◽

Performance Indicators ◽

Water Utilities ◽

Loss Reduction ◽

Water Networks ◽

Minimum Night Flow ◽

Leakage Exponent

Abstract Methods for network leakage estimation include water balance, component analysis and minimum night flow (MNF) methods the latter of which involves subtracting the customer night use (QCNU) from night leakage and multiplying by the hour day factor (HDF). QCNU and HDF respectively depend on Active Night Population (ANP) and leakage exponent (N1). In most developing countries, these parameters are assumed in the MNF method thus introducing errors which makes setting realistic leakage reduction targets and key performance indicators (KPI) problematic. In this study, QCNU and HDF were evaluated by determining the relative error associated with ANP and N1 to establish localized rates for accurately estimating leakage in water networks. Between 7 and 11% relative error was associated with every 1% higher or lower ANP while up to 4% relative error was observed for every step considered. A linear relationship exists between the relative error associated with both and ANP although that of ANP is twice as high as This has technical implications on setting water loss reduction targets and investing in the water infrastructure. It is recommended that water utilities must establish localized ANP and values for accurate leakage estimation in water networks.

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