Dataset on the Impacts of Sand and Leaf Litter on the Hydrological Performance of Green Roofs as Surrogate for Infiltration-Based Blue-Green Infrastructure (BGI)

Abstract

[Abstract]: This dataset contains raw and processed data from controlled experiments conducted in a rainfall simulator to quantify the impacts of incremental sand and leaf litter accumulation on the hydrological performance of blue-green infrastructure (BGI). The tests were conducted in a controlled indoor environment using two BGI boxes (approximately 3.84 m² each), representing a typical infiltration-based BGI setup with vegetation, a 6-cm deep substrate, and storage layers. Soil moisture sensors and tipping buckets were installed to measure underdrain flow. In one box, sand was incrementally added (2–18 kg.m−²); in the other, leaf litter accumulation ranged from 0.3 to 1.725 kg (total). Each scenario received rainfall (16.66 mm.h−1 for Box 1; 18.66 mm.h−1 for Box 2) for 30 minutes, with intervals larger than four hours between tests. The dataset can be used to understand the impact of shock events that introduce high pollutant loads to the BGI surface and subsurface, affecting their hydrological performance. It can also be used to study the maintenance needs of BGI to sustain their hydrological functionality.