Model structure uncertainty is seldom calculated because of the difficulty and time required to perform such analyses. Here we explore how a coastal model using the Monod versus Droop formulations and a 6 km × 6 km versus 2 km × 2 km computational grid size predict primary production and hypoxic area in the Gulf of Mexico. Results from these models were compared to each other and to observations, and sensitivity analyses were performed. The different models fit the observations almost equally well. The 6k-model calculated higher rates of production and settling, and especially a larger hypoxic area, in comparison to the 2k-model. The Monod-based model calculated higher production, especially close to the river delta regions, but smaller summer hypoxic area, than the model using the Droop formulation. The Monod-based model was almost twice as sensitive to changes in nutrient loads in comparison to the Droop model, which can have management implications.

由于执行此类分析的难度和时间，很少计算模型结构的不确定性。在这里，我们探讨了使用 Monod 与 Droop 公式和 6 km × 6 km 与 2 km × 2 km 计算网格大小的沿海模型如何预测墨西哥湾的初级生产和缺氧区域。将这些模型的结果相互比较并与观察结果进行比较，并进行敏感性分析。不同的模型几乎同样适合观察结果。与 2k 模型相比，6k 模型计算出更高的生产和沉降率，尤其是更大的缺氧区域。与使用 Droop 公式的模型相比，基于 Monod 的模型计算出的产量更高，特别是靠近河流三角洲地区，但夏季缺氧区域更小。