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Wastewater treatment plants are often assessed by compliance and cost, which leaves energy, carbon, resource recovery, asset condition, climate exposure and digital capability outside a single view. We reformulate the conceptual Water Infrastructure Sustainability Index (WISI) as a computable index for wastewater treatment plants. WISI v1.1 combines seven dimensions (technical performance, water, energy, circular economy, carbon, asset resilience, digital intelligence) through 22 normalised indicators and weighted arithmetic aggregation. The reformulation corrects inverted indicator directions, removes undefined and non-applicable indicators, and limits double counting by assigning each physical flow to one dimension. Because no complete operational dataset was available, we tested the index on 40 synthetic plants, with 50 replicate datasets, using Monte Carlo weight perturbation, varying weight distributions, and alternative model structures. Rankings were stable under moderate weight uncertainty (median Spearman ρ = 0.98 for Dirichlet κ = 50) and fell to 0.87 only when weights were nearly random (κ = 3); aggregation rule changed rankings most (ρ = 0.95 for geometric aggregation). Nominal weights did not match effective influence: technical performance, with the largest weight (0.20), accounted for about 7–8% of index variance. Class bands from the earlier framework placed a median of 70% of synthetic plants in the lowest class; data-derived bands were uncertain by about five score points. A feasibility check on two operating plants showed that routine laboratory data cover only 3 of the 22 indicators.
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AYMAN RAMADAN (2026) studied this question.
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