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Record W4408438261 · doi:10.5194/egusphere-egu25-6629

Are water-related Nature-based Solutions (NbS) assessed to their full multi-benefit potential? A systematic literature review.

2025· preprint· en· W4408438261 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicEnvironmental Science and Water Management
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsSystematic reviewEnvironmental scienceComputer scienceMEDLINEPolitical science

Abstract

fetched live from OpenAlex

Nature-based Solutions (NbS) leverage and mimic natural processes to address societal and environmental challenges. In recent years, they have attracted global interest for their significant contributions to the Sustainable Development Goals, offering integrated approaches to address multiple dimensions of resilience and sustainability in the context of global change. This potential is particularly promising in complex and rapidly evolving urban environments, where water resources represent both managing hazards and protecting resources. However, assessing and quantifying the full potential and impacts of NbS remains challenging, as their impacts span multiple disciplines and depend on local socio-geographical contexts and initial implementation goals. Holistic assessment frameworks are urgently required[ES1]  to demonstrate performance, capture the diverse effects of NbS along the process-impact chain, and enable stakeholders to monitor progress over time. This study presents a systematic literature review to map the current state of the art in NbS performance evaluation. 111 articles were reviewed to assess whether NbS evaluation methods associated with urban water resources provide holistic and transferable approaches while addressing the complexity of human-natural systems. Preliminary results indicate that most studies focused on existing sites where NbS were considered for implementation, often using modeling approaches. Performance evaluations spanned 16 parameter categories, with the majority addressing quantitative and qualitative hydrological aspects, consistent with the authors’ disciplinary backgrounds. Although many methods demonstrated reusability and supported decision-making processes, most studies assessed limited parameters, partly due to modeling assumptions. Notably, social aspects were frequently acknowledged, particularly regarding the involvement of local governments during the implementation phase. The results of this literature review can support scientists in developing robust assessment frameworks and provide stakeholders with a comprehensive overview of the current state of the art in NbS multi-benefit characterization. This, in turn, will provide stakeholders with greater confidence to invest in NbS, upscale their use, and influence NbS policies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.629
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.242
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it