ArticleScientific reports2023
A comparative analysis of urban forests for storm-water management.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- A global urban tree leaf area index dataset for urban climate modeling.Scientific data · 2025Article
- Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large-scale urban growth has modified the hydrological cycle of our cities, causing greater and faster runoff. Urban forests (UF), i.e. the stock of trees and shrubs, can substantially reduce runoff; still, how climate, tree functional types influence rainfall partitioning into uptake and runoff is mostly unknown. We analyzed 92 published studies to investigate: interception (I), transpiration (T), soil infiltration (IR) and the subsequent reduction in runoff. Trees showed the best runoff protection compared to other land uses. Within functional types, conifers provided better protection on an annual scale through higher I and T but broadleaved species provided better IR. Regarding tree traits, leaf area index (LAI) showed a positive influence for both I and T. For every unit of LAI increment, additional 5% rainfall partition through T (3%) and I (2%) can be predicted. Overall, runoff was significantly lower under mixed species stands. Increase of conifer stock to 30% in climate zones with significant winter precipitation and to 20% in areas of no dry season can reduce runoff to an additional 4%. The study presented an overview of UF potential to partition rainfall, which might help to select species and land uses in different climate zones for better storm-water management.
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