Suitable Irrigation Schedule for Urban Green Space via Soil Moisture Sensor and Modeling

Under rising populations, urbanization growth, and water scarcity pressures, water conservation of urban green space is critical for governments and town planners. Nevertheless, traditional irrigation scheduling based on farmer expertise becomes outmoded and wastes water resources. Proper irrigation scheduling is essential for sustainable green urban development, as it decreases the water consumption of green spaces and lowers labor costs without leading to plant stress. This study aims to determine a suitable irrigation schedule for urban green space via soil moisture sensors and modeling. Initially, a resistivity sensor was employed to measure soil moisture. The Hydrus 1D model was then used to replicate the soil water movement. Soil moisture monitoring was used to determine the water retention parameters by reverse modeling. Thirdly, an appropriate irrigation schedule was created based on a sufficient irrigation amount and a soil moisture study. According to the results, The soil moisture was lost by 1% daily. The water irrigation scheduling by four days/time or three days/time can reduce water consumption by 29–33%. However, the study could focus only on reducing water irrigation but did not account for other criteria for optimal irrigation scheduling, such as the operation labor and electrical. The results provide the appropriate base irrigation scheduling, which can be adapted for innovative irrigation systems.