Simulation decomposition analysis of the Iowa food-water-energy system
This study applies global sensitivity analysis (GSA) to the Iowa Food-Water-Energy system, focusing on nitrogen export into the Mississippi River. A binning method combined with simulation decomposition (SimDec) quantifies and visualizes the influence of crucial aggregate input variables — manure nitrogen (MN), commercial nitrogen (CN), grain nitrogen (GN), and fixation nitrogen (FN) — on nitrogen surplus (NS) at the county level. Unlike traditional Sobol’ indices, the binning method captures dependent variables. In addition, the SimDec procedure provides a detailed visual representation of how these dependencies and interactions drive the nitrogen variability. MN is identified as the most influential factor, followed by CN, with FN and GN having less impact. The study also performs GSA on the low-level input variables, enhancing the overall interpretability of the sensitivity analysis. This approach offers actionable insights for improving nitrogen management practices and contributes to GSA literature by showcasing the analysis of aggregate variables. • SimDec shows nitrogen surplus is driven by county-level manure nitrogen variability. • Visualization reveals how aggregate variables interact in nitrogen export dynamics. • First study analyzing sensitivity transformation across multiple input levels. • Links original inputs to aggregate variables, offering insights into model behavior.
Authors
- Leifur Leifsson (ORCID: https://orcid.org/0000-0001-5134-870X)
- Julian Scott Yeomans (ORCID: https://orcid.org/0000-0001-7361-4060)
- Mariia Kozlova (ORCID: https://orcid.org/0000-0002-6952-7682)
- Taeho Jeong
Institutions
- York University (CA)
- Purdue University West Lafayette (US)
- Lappeenranta-Lahti University of Technology (FI)
Publication Details
- Journal
- Environmental Modelling & Software
- Published
- 2025-03-05
- DOI
- https://doi.org/10.1016/j.envsoft.2025.106415
- Citations
- 1
- Primary Topic
- Water-Energy-Food Nexus Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.82