A modelling framework for demand-oriented irrigation control using SWMM and SWMM-UrbanEVA

Abstract

This study introduces a modelling framework integrating blue-green infrastructure modelling with demand-oriented irrigation management. By using Python-based applications, such as SWMM, SWMM-UrbanEVA and Smartin, the framework addresses key challenges, including insufficient representation of location- and plant-specific conditions or lack of integration for real-time control and model-predictive control. The framework supports dynamic irrigation control strategies, optimizing water use, enhancing evapotranspiration, and reducing urban runoff. In a case study in Münster, Germany, evapotranspiration increased by up to 60% for some BGI types, while sewer runoff decreased by up to 36%. The integration of rainwater harvesting and irrigation control demonstrates its capacity for resource efficiency. Flexible and adaptable, the framework enables practical applications across urban environments, allowing scenario analysis, efficient irrigation operations, and citizen engagement through real-time irrigation demand forecasting.