Can Improved Flow Partitioning in Hydrologic Models Increase Biogeochemical Predictability?

Abstract

Hydrologic models partition flows into surface and subsurface pathways, but their calibration is typically conducted only against streamflow. Here we argue that unless model outcomes are constrained using flow pathway data, multiple partitioning schemes can lead to the same streamflow. This point becomes critical for biogeochemical modeling as individual flow paths may yield unique chemical signatures. We show how information on flow pathways can be used to constrain hydrologic flow partitioning and how improved partitioning can lead to better water quality predictions. As a case study, an agricultural basin in Ontario is used to demonstrate that using tile discharge data could increase the performance of both the hydrology and the nitrogen transport models. Watershed‐scale tile discharge was estimated based on sparse tile data collected at some tiles using a novel regression‐based approach. Through a series of calibration experiments, we show that utilizing tile flow signatures as calibration criteria improves model performance in the prediction of nitrate loads in both the calibration and validation periods. Predictability of nitrate loads is improved even with no tile flow data and by model calibration only against an approximate understanding of annual tile flow percent. However, despite high values of goodness‐of‐fit metrics in this case, temporal dynamics of predictions are inconsistent with reality. For instance, the model predicts significant tile discharge in summer with no tile flow occurrence in the field. Hence, the proposed tile flow upscaling approach and the partitioning‐constrained model calibration are vital steps toward improving the predictability of biogeochemical models in tiled landscapes.

Hunting for Information in Streamflow Signatures to Improve Modelled Drainage

“…Water 2022, 13, x FOR PEER REVIEW 3 of 23 streams and artificial drainage have only been exploited to a limited extent to inform hydrological models [38]. The objective of this work is to evaluate the potential of using hydrological signatures to improve the representation of drain in regional-scale distributed hydrological models.…”

“…Hence, drain flow will have an effect on the hydrograph [37], even in streams that aggregate contributions from a variety of runoff-generating processes. So far, correlations between hydrological signatures in streams and artificial drainage have only been exploited to a limited extent to inform hydrological models [38].…”

Beyond the Mass Balance: Watershed Phosphorus Legacies and the Evolution of the Current Water Quality Policy Challenge

“…To further validate the model results, we compared simulated values for reservoir P accumulation with P accumulation magnitudes obtained from a sediment core obtained from a reservoir within the GRW (see Section 3.4). This independent estimate of reservoir P accumulation provides additional “soft” data for model validation—the use of which has been advocated as a means of better incorporating process understanding into model simulations (Shafii et al., 2019; Vaché et al., 2004). This additional “internal” calibration point increases our confidence in the robustness of internal processes represented in the model simulations.…”

Is a simple model based on two mixing reservoirs able to reproduce the intra-annual dynamics of DOC and NO3 stream concentrations in an agricultural headwater catchment?

“…Therefore, they could also increase the confidence in a model's parameters and physical plausibility. This is particularly true if the solutes spatial distribution and stream concentration dynamics differ greatly (Shrestha et al, 2013;Woodward and Stenger, 2018;Shafii et al, 2019), as is frequently observed for dissolved organic carbon (DOC) and nitrate (NO3 -) (Taylor and Townsend, 2010).…”