Intelligent Water-Saving Dewatering for High-Rise Building Sites: A Case Study in Taichung, Taiwan

Foundation engineering in high-rise building construction is an essential preliminary stage, as it provides the structural load-bearing capacity of the building, since foundation structures often extend into the subsurface layers, excavation becomes a critical part of construction, when groundwater is encountered during excavation, it is necessary to lower the groundwater level to provide a dry working environment. However, groundwater is a valuable and clean natural resource, in most high-rise construction projects, large volumes of groundwater are extracted through dewatering operations to maintain dry foundation conditions, therefore, minimizing groundwater extraction is particularly important for conserving this precious resource. In Taiwan, groundwater level monitoring at high-rise construction sites has traditionally relied on manually measuring observation wells using graduated rulers and labor-intensive shift schedules; A few construction companies have adopted continuous groundwater monitoring systems, but these require substantial financial investment and maintenance costs. To address these limitations, this study proposes an artificial intelligence (AI)-based groundwater level simulation model, the model integrates artificial neural networks (ANN) with fuzzy logic theory to develop a predictive model for dewatering operations in high-rise building foundations. Furthermore, a smart water-saving dewatering model is proposed to overcome the deficiencies of conventional dewatering practices, which typically consume excessive groundwater resources.