AIDspat: Introduction of a model framework to estimate spatio-temporal agricultural irrigation demands – A study area in Germany

As climate change intensifies, information on agricultural water use is vital for planning. This study introduces AIDspat, a new framework for estimating agricultural irrigation demand (AID) that combines a soil water balance model with irrigation scheduling. Using location-based climate, soil and land use data – along with general crop-specific parameters, irrigation techniques and farmers’ irrigation management decisions – the model. objectively determines AID. The model enables scenario-based calculations at low computational cost across scales, from individual field to national assessments, for both past and future periods. Integrating crop-specific differences through intra-annual dynamic plant development and considering irrigation techniques enhances the model’s accuracy and practical applicability. The model’s ability to capture the spatial and temporal dynamics of AID provides valuable insights for the sustainable management of agricultural water. Calibrated and validated for a study area in southern Germany, the model demonstrates a high degree of alignment between modeled values and literature benchmarks for various agricultural crops. The modeled results show good agreement with measured irrigation volumes, with a mean absolute percentage error (MAPE) of approximately 16.9% over 2017–2023 and an annual percentage difference ranging from −34.7% to + 47.5%. Modeled and measured annual volumes are strongly correlated (r ≈ 0.93), and the overall bias is small (PBIAS ≈ +4.7%). Thus, the model provides planners and policymakers with an irrigation decision support system to analyze the impact of agricultural systems, climatic changes and agricultural decision-making processes, thereby facilitating sustainable agricultural irrigation management.