Developing composite indicators for ecological water quality assessment based on network interactions and expert judgment

Mao, Feng; Zhao, Xianfu; Ma, Pelosi; Chi, Shiyun; Richards, Keith; Clark, Julian; Hannah, David M.; Krause, Stefan

doi:10.1016/j.envsoft.2019.01.011

Cited by 10 publications

(6 citation statements)

References 69 publications

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“…Numerous methods can be used to create a CI, provided that the OECD standards (Joint Research Centre, 2008) are met. These methods include the analytic hierarchy process (Molinos-Senante et al, 2014;Sun et al, 2020), TOPSIS (Fu et al, 2020), multi-criteria analysis (El Gibari et al, 2018;Mao et al, 2019;Pérez et al, 2019;Cabello et al, 2020), and methods derived from any of these approaches, such as MRP-WSCI, which is based on multi-criteria analysis (Ruiz et al, 2020) and data envelopment analysis (DEA). More specifically, DEA has been used to create CIs for evaluation in different sectors: services in airports (Baltazar et al, 2014), suppliers' green performance (Dobos and Vörösmarty, 2014), tourism (Gómez-Vega and Picazo-Tadeo, 2019), and corporate social responsibility (Staessens et al, 2019;Aparicio et al, 2020).…”

Section: Composite Indicators Dea and Mcda In Water Managementmentioning

confidence: 99%

A composite indicator index as a proxy for measuring the quality of water supply as perceived by users for urban water services

González

Almenar-Llongo

Ramón

2022

Technological Forecasting and Social Change

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Section: Composite Indicators Dea and Mcda In Water Managementmentioning

confidence: 99%

A composite indicator index as a proxy for measuring the quality of water supply as perceived by users for urban water services

González

Almenar-Llongo

Ramón

2022

Technological Forecasting and Social Change

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“…An extension of the AHP that allows for interdependencies between criteria. Saaty, 1996 [28] Disaster resilience indicator [29], ecological water quality index [30] Criteria importance through intercriteria correlation (CRITIC)…”

Section: Analytic Hierarchy Process (Ahp)mentioning

confidence: 99%

Multiple Scenarios of Quality of Life Index Using Fuzzy Linguistic Quantifiers: The Case of 85 Countries in Numbeo

et al. 2022

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In economic development, in addition to comparing the gross domestic product (GDP) between nations, it is critical to assess the quality of life to gain a holistic perspective of their different aspects. However, the quality of life index (QOLI) is a subjective term that can be difficult to quantify. Although this composite index is typically calculated using universal weights proposed by experts to aggregate indicators, such as safety indexes, healthcare indexes, pollution indexes, and housing indicators, it is complicated to balance multiple dimensions whose weights are adjusted to account for different countries’ circumstances. Therefore, this paper aims to construct various scenarios of the QOLI, using linguistic quantifiers of the ordered weighted averaging (OWA) operator, and the 2-tuple linguistic model. Numbeo, one of the largest quality of life information databases, was used in this paper to estimate the QOLI in 85 countries. Uncertainty and sensitivity analyses were employed to assess the robustness of the QOLI. The results of the proposed model are compared with those obtained using the Numbeo formulation. The results show that the proposed model increases the linguistic interpretability of the QOLI, and obtains different QOLIs, based on diverse country contexts.

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“…Several institutional initiatives-by the United Nations Commission for Sustainable Development (UNCSD), the Institute of Chemical Engineers (IChemE), the Wuppertal institute-have led to the construction and maintenance of CI for monitoring countries' achievement of sustainability [32]. As for ecological sciences, CI indicators have been designed to: assess the level of resilience to floods and its interplay with the delivery of ecosystem services (ES) in Sri Lanka [33]; study the connection between ES and the effectiveness of urban forestry in Canada [34]; evaluate ecological water quality in riparian China [35]; measure the attitude of world countries toward cooperation for ecological resilience and climate change adaptation [5]; and study the level of ecosystem services and disservices in northern Italy [36].…”

Section: A State-of-the-art Summary On Composite Indicators Design: Gmentioning

confidence: 99%

Assessing Landscape Fragmentation: A Composite Indicator

et al. 2020

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The assessment and management of landscape fragmentation (LF), i.e., the subdivision of the habitat into smaller and more isolated patches, can benefit from the adoption of a composite indicator explaining, in a unique measure, the various concerns involved. However, the use of composite indicators may be affected by lack of data, subjectivity in algorithm design, and oversimplification connected to reduction to just one index. In these cases, the findings obtained might not provide the researcher with reliable information. In this paper, we design and apply the Composite Indicator of Landscape Fragmentation (CILF), a metric resuming three indicators concerning the effect on LF of transport and mobility infrastructures, human settlements, and patch density per se. The application concerns the measurement of LF spatial pattern and dynamics from 2003 to 2008 of 51 landscape units in the island of Sardinia (Italy). We considered a complete spatial data set, chose the generalized geometric mean as aggregation algorithm, and verified its robustness via sensitivity analysis of the results. We found that, in 2003 and 2008, the CILF spatial pattern shows higher values in coastal areas and has varied randomly, i.e., without a consistent tendency to converge to, or diverge from, a mean value. Overall, we demonstrate that the CILF is a powerful instrument for monitoring LF in Sardinia and advocate that it can be further implemented, following the same methodological framework, by extending the pool of indicators considered and assessing a weighted version of the composite indicator.

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Developing composite indicators for ecological water quality assessment based on network interactions and expert judgment

Cited by 10 publications

References 69 publications

A composite indicator index as a proxy for measuring the quality of water supply as perceived by users for urban water services

A composite indicator index as a proxy for measuring the quality of water supply as perceived by users for urban water services

Multiple Scenarios of Quality of Life Index Using Fuzzy Linguistic Quantifiers: The Case of 85 Countries in Numbeo

Assessing Landscape Fragmentation: A Composite Indicator

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