Urban trees face intensifying drought stress, and soil water storage and its dynamics are important for the drought resilience of urban trees. Existing evidence is based on process-based growth and ecosystem-service models, on water-balance studies of urban green spaces and irrigation, and on single-city monitoring campaigns, while multi-city in-situ observations under a consistent methodology are missing. We present a continuously growing database of 555 urban tree sites in 41 Central European locations, each instrumented with soil moisture sensors and paired with meteorological data, topographic, sun exposure and groundwater descriptors, manually digitised land use around the tree and tree characteristics. An event-based workflow detects rain and irrigation events and extracts two response metrics, the normalised soil moisture increase and the drying time. Random Forest models are built for all combinations of target (soil moisture increase, drying time), event type (rain, irrigation) and measurement depth (30, 60, 90 cm). The models explain up to 69 % of the variance of the moisture increase after irrigation and 40 to 55 % for the other combinations in cross-validation. Grouped cross-validation shows that the rain models transfer to unseen sites within 0.03 in <em>R</em><sup>2</sup> while the irrigation models lose 0.21 to 0.37, therefore encoding a site signature of the few heavily irrigating cities. Rain and irrigation responses differ markedly. The mean air temperature during the event and the pre-event rainfall dominate the rain responses, whereas the pre-event soil moisture and the storage capacity of the substrate control the irrigation responses and how long their effect persists. The unsealed, vegetated area around the tree is the only consistently relevant site characteristic, whereas depth to groundwater shows no effect. The database and workflow are openly available and turn the assessment of planting sites and the verification of irrigation into measurable quantities.