Integrated hydrological modelling for decision support to improve field and catchment scale water management in agriculture
- 1Water, Energy and Environmental Engineering Research Unit, University of Oulu, Oulu, Finland
- 2Centre d'Hydrogéologie et de Géothermie, University of Neuchâtel, Neuchâtel, Switzerland
- 3Division of Water Resources Engineering, Faculty of Engineering, Lund University, Lund, Sweden
Particularly in the Nordic region, water excess and shortage (drought) are becoming more frequent phenomena that challenge the development of agriculture and crop production. Identification of appropriate water management strategies is essential (i) to ensure sustainable water resources management for crop production and the functioning of healthy ecosystems; and (ii) to improve resilience to hydrological extremes. Integrated hydrological models offer that potential through understanding and forecasting of hydrological systems under anthropogenic and climatic influences, and providing information for improved decision-making. This study aims to develop a decision support instrument based on integrated hydrological modelling to identify appropriate management solutions and improve field- and catchment-scale water management in Nordic agriculture. The study area is Tyrnävä catchment, located in the northern part of Finland near Oulu city. Initially, the available hydro-climatological and hydrogeological data of the Tyrnävä catchment are characterized in detail. Then the hydrogeological parameters of the model are identified based on existing hydrogeological, climatic and remotely sensed data and their spatial, temporal and vertical variability. Next, a regional integrated surface-subsurface hydrological model is set up using HydroGeosphere. After successful calibration and validation using observed groundwater level, river discharge and soil moisture data, the model will be used in implementing and evaluating different management strategies (e.g., different irrigation options during droughts and controlled drainage management) for the future and their influence on the surface and groundwater systems. Uncertainty arising from different sources will be quantified using the Integrated Bayesian Multi-model Uncertainty Estimation Framework with the support of a supercomputer to improve the reliability and accuracy of the decision support instrument. Additionally, stakeholders’ involvement through local workshops is ensured throughout the modelling study, from the beginning to obtain reliable and useful decision support. Finally, based on these results, informed decisions regarding the appropriate water management can be made, which is important for sustainable water resources management for crop production and the functioning of healthy ecosystems particularly in Nordic agriculture.
How to cite: Mustafa, S. M. T., Autio, A., Haghighi, A. T., Marttila, H., Avellan, T., Schilling, O. S., Brunner, P., Scholz, M., and Klöve, B.: Integrated hydrological modelling for decision support to improve field and catchment scale water management in agriculture, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11823, https://doi.org/10.5194/egusphere-egu22-11823, 2022.