Towards a comprehensive implementation of the water-food-energy nexus for sustainable agricultural production: a modelling and remote sensing perspective

Abstract:

Motivated by the unprecedented 2018 drought that hit Sweden, we have developed a water-food-energy (WFE) nexus model that can be implemented as an irrigation management service in Sweden [1]. The current version of the model relies on climatological data generated by two mesoscale models from the Swedish Meteorological and Hydrological Institute (SMHI). The developed model provides WFE nexus guidelines on optimal allocation of water, energy and nutrients for crop production. A pilot WFE irrigation management system for Sweden, the SWEDish Irrigation Management System (SWEDIMS), has also been built upon the model using Google Earth Pro® for the interface [2].

We have further developed the model by assimilating remote sensing data, such as the leaf area index (LAI) from the Copernicus Global Land Service (CGLS) [3], to improve the model accuracy. Moreover, the model has been extended to include water consumption from other strategic sectors, such as the livestock, residential and industrial sectors, to analyze potential trade-offs and constraints on water balances. Water balances are assessed by combining the existing nexus model with the global hydrological model World-Wide Water model (W3) [4]. The hydrological model is also used to study the effects on water balances for two different scenarios: irrigation with and without the support of an irrigation management system.

The accuracy of the model can be significantly improved by assimilating the remotely sensed LAI data. We present an example of a comparison between field and modelled data for a location at the Lanna research station (58°20′N, 13°06′E, 75 m asl) of the ICOS National Networks. By analyzing the water balances, as demonstrated in previous studies (e.g., [5]), the adoption of an irrigation management system can lead to significant savings in terms of water and energy consumption as compared to normal practices.

References

[1] Campana, P. E., Zhang, J., Yao, T., Andersson, S., Landelius, T., Melton, F., & Yan, J. (2018). Managing agricultural drought in Sweden using a novel spatially-explicit model from the perspective of water-food-energy nexus. Journal of Cleaner Production, 197, 1382-1393.

[2] https://swedims.se/

[3] https://land.copernicus.eu/global/

[4] Van Dijk, A. I., Peña‐Arancibia, J. L., Wood, E. F., Sheffield, J., & Beck, H. E. (2013). Global analysis of seasonal streamflow predictability using an ensemble prediction system and observations from 6192 small catchments worldwide. Water Resources Research, 49(5), 2729-2746.

[5] Johnson, L. F., Cahn, M., Martin, F., Melton, F., Benzen, S., Farrara, B., & Post, K. (2016). Evapotranspiration-based irrigation scheduling of head lettuce and broccoli. HortScience, 51(7), 935-940.