https://w3id.org/sciencelive/np/RA6V_jAy2OFjYBwQMOH92fIM6199bjez7hRkY90vkxx7U/Head https://w3id.org/sciencelive/np/RA6V_jAy2OFjYBwQMOH92fIM6199bjez7hRkY90vkxx7U http://www.nanopub.org/nschema#hasAssertion https://w3id.org/sciencelive/np/RA6V_jAy2OFjYBwQMOH92fIM6199bjez7hRkY90vkxx7U/assertion https://w3id.org/sciencelive/np/RA6V_jAy2OFjYBwQMOH92fIM6199bjez7hRkY90vkxx7U http://www.nanopub.org/nschema#hasProvenance https://w3id.org/sciencelive/np/RA6V_jAy2OFjYBwQMOH92fIM6199bjez7hRkY90vkxx7U/provenance https://w3id.org/sciencelive/np/RA6V_jAy2OFjYBwQMOH92fIM6199bjez7hRkY90vkxx7U http://www.nanopub.org/nschema#hasPublicationInfo https://w3id.org/sciencelive/np/RA6V_jAy2OFjYBwQMOH92fIM6199bjez7hRkY90vkxx7U/pubinfo https://w3id.org/sciencelive/np/RA6V_jAy2OFjYBwQMOH92fIM6199bjez7hRkY90vkxx7U http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.nanopub.org/nschema#Nanopublication https://w3id.org/sciencelive/np/RA6V_jAy2OFjYBwQMOH92fIM6199bjez7hRkY90vkxx7U/assertion https://w3id.org/sciencelive/np/RA6V_jAy2OFjYBwQMOH92fIM6199bjez7hRkY90vkxx7U/vogelbacher2026-pfr-independent-reproduction-outcome http://schema.org/endDate 2026-10-08 https://w3id.org/sciencelive/np/RA6V_jAy2OFjYBwQMOH92fIM6199bjez7hRkY90vkxx7U/vogelbacher2026-pfr-independent-reproduction-outcome http://www.w3.org/1999/02/22-rdf-syntax-ns#type https://w3id.org/sciencelive/o/terms/FORRT-Replication-Outcome https://w3id.org/sciencelive/np/RA6V_jAy2OFjYBwQMOH92fIM6199bjez7hRkY90vkxx7U/vogelbacher2026-pfr-independent-reproduction-outcome http://www.w3.org/2000/01/rdf-schema#label Building-level pluvial flood risk of Vogelbacher et al. (2026) reproduced with an independent open implementation https://w3id.org/sciencelive/np/RA6V_jAy2OFjYBwQMOH92fIM6199bjez7hRkY90vkxx7U/vogelbacher2026-pfr-independent-reproduction-outcome https://w3id.org/sciencelive/o/terms/hasConclusionDescription Validated. On the authors' own example, an independent open implementation reproduces the paper's building-level pluvial flood risk and its pattern: every building falls in the same risk class as in the authors' ArcGIS results, for both risk to well-being and risk to mobility and accessibility, and the highest risks are where high exposure and high hazard coincide, as the paper states. Reproducing the numbers required following the authors' results and scripts where they differ from the paper's text (sensitivity weights, TOPSIS normalisation, and rings that exclude neighbouring buildings). An existing open implementation run as is does not reproduce them, mainly because it recomputes exposure and keeps neighbouring footprints in the hazard rings. https://w3id.org/sciencelive/np/RA6V_jAy2OFjYBwQMOH92fIM6199bjez7hRkY90vkxx7U/vogelbacher2026-pfr-independent-reproduction-outcome https://w3id.org/sciencelive/o/terms/hasConfidenceLevel https://w3id.org/sciencelive/o/terms/HighConfidence https://w3id.org/sciencelive/np/RA6V_jAy2OFjYBwQMOH92fIM6199bjez7hRkY90vkxx7U/vogelbacher2026-pfr-independent-reproduction-outcome https://w3id.org/sciencelive/o/terms/hasEvidenceDescription Compared building by building with the authors' ArcGIS output (Zenodo 10.5281/zenodo.19860733, 37 buildings): sensitivity, coping capacity, social vulnerability and its transformed index match exactly (largest difference 4.4e-16); exposure is taken as published. Hazard to mobility differs by at most 0.0008 and hazard to well-being by at most 0.0016; risk to mobility by at most 0.013 and risk to well-being by at most 0.004. With the authors' iterated-mean class rule, 37 of 37 buildings are in the same class for both indices (well-being: 15 no risk, 13 low, 5 medium, 3 high, 1 very high; mobility: 6, 23, 5, 2, 1), with class breaks equal to three decimals. The authors' stored intermediate fractions for the 2 m ring (37 buildings x 8 depths) are matched within 0.05 percentage points when all building footprints are removed from the ring, against up to 27.8 percentage points (25 cells) when only the building's own footprint is. The authors' risk indices equal social vulnerability x published exposure x hazard to 1e-15. For comparison, the FAIR2Adapt urban_pfr toolbox run as is differs by up to 7.86 (risk to mobility) and 5.11 (risk to well-being). https://w3id.org/sciencelive/np/RA6V_jAy2OFjYBwQMOH92fIM6199bjez7hRkY90vkxx7U/vogelbacher2026-pfr-independent-reproduction-outcome https://w3id.org/sciencelive/o/terms/hasLimitationsDescription Tested on one worked example only: synthetic building-level data for one Hamburg city quarter (37 buildings) and one rainfall scenario, as published by the authors; this does not test real city data, other cities or the transferability the paper discusses, nor the sensitivity analysis of Sect. 4.3. The remaining differences, in the fourth decimal of the hazard and risk indices, are attributed to ArcGIS geometry processing (snapping tolerance, true curves); finer buffer arcs and intersecting in the flood layers' coordinate system did not remove them. Three method details were inferred from the authors' results and exported scripts because the paper's text differs: the sensitivity weights (results: children 0.3, elderly singles 0.7; text of Sect. 3.1.1: 0.7 and 0.3), the TOPSIS normalisation (scripts: vector norm; Eq. 4: sum), and the exclusion of all building footprints from the hazard rings; the number of class iterations (three) is inferred too. Buffers follow the authors' Web Mercator units, so a 2 m buffer is about 1.2 m on the ground. The authors' exported Python scripts need ArcGIS (arcpy). 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