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

Abstract

In the face of ongoing climate change, information about agricultural water usage is crucial for policymakers and planners. This study introduces the AIDspat model, a new framework for estimating agricultural irrigation demand (AID). The model combines an existing soil water balance model with the principle of irrigation scheduling. In addition to location-based climate, soil and land use data, the model takes into account general crop-specific parameters, irrigation techniques and farmers’ irrigation management decisions. This enables an objective determination of AID. The model enables scenario-based calculations with low computational cost across various scales, ranging from the field to the national level and spanning both past and future time 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 a variety of agricultural crops. The modeled results show a good agreement with measured irrigation volumes, with yearly percentage differences ranging from -17.2% to +47% and a mean absolute percentage error (MAPE) of approximately 16.9% over the period from 2017 to 2023. 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.