Supporting decision-makers in estimating irrigation demand for urban street trees

Abstract

Greening cities is of considerable significance to creating sustainable cities. Cost-benefit analyses have shown that urban green is not only ecologically and socially desirable but also economically advantageous. However, maintaining this urban green is becoming challenging due to changing climatic conditions. With frequent heat-waves, droughts and increasing water scarcity in many regions, it is crucial to establish systematic approaches to economise the available water used for irrigation. Currently, cities rely on rough approximations to assess irrigation demand. To address this gap, a linear time series model was developed based on soil water balance and Water Use Classifications of Landscape Species approach. The model uses publicly available data regarding trees, soil, and current and forecasted weather to estimate the irrigation demand of urban street trees on a weekly time scale. The developed model is applied in a case study of a metropolis in a moderate continental climate. The results show more distributed irrigation demand than the currently implemented soil moisture based model of the case study city. Accordingly, the model can support the decision-makers to not only assess the irrigation demand of existing trees but also help in water budgeting of new plantation under varying climatic conditions.