| 29 Jan 2026
Explicit Representation and Calibration of Different Landscape Units for a Robust Catchment DOC Export Model
Abstract. Elevated dissolved organic carbon (DOC) concentrations are a major concern for ecosystems and drinking water supply. Data-driven studies revealed variable functioning of different landscape units (upland, riparian zone, and groundwater) in catchment DOC mobilization and export. However, lumped and landscape-explicit (separating upland and riparian zone) model structures are generally calibrated to stream DOC concentrations, while the internal DOC dynamics often do not receive sufficient attention. Here, we developed a flexible model with a lumped and landscape-explicit structure for four headwater catchments in the Harz Mountains, Germany. We evaluated these models under a baseline calibration (only using stream DOC concentration) and a constrained calibration (using stream DOC and internal DOC concentrations). Under the baseline calibration, both model structures can reasonably represent stream DOC dynamics in some catchments (Kling–Gupta efficiency of some behavioural simulations > 0.6), but with unreasonably high groundwater DOC. By contrast, the constrained calibration reduces the KGE for stream DOC concentrations but ensures a more realistic representation of internal DOC dynamics. Additionally, the landscape-explicit model structure is more robust than the lumped model structure under changing boundary conditions. Our study thus highlights the necessity of representing different landscape units explicitly in combination with constraining the calibration of DOC concentrations in these landscape units.
Competing interests: Rohini Kumar is a member of the editorial board of Hydrology and Earth System Sciences
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This manuscript addresses an important question in catchment-scale dissolved organic carbon (DOC) modelling: whether acceptable outlet DOC simulations are achieved for the right reasons—namely, through physically plausible internal DOC dynamics. By comparing lumped and landscape-explicit model structures across four headwater catchments, and by contrasting baseline and constrained calibration approaches, the study makes a valuable contribution to the field. The central conclusion is compelling: satisfactory stream DOC performance alone does not guarantee realistic internal behavior, and a landscape-explicit structure paired with internal constraints offers a more robust framework for interpretation and scenario analysis.
Overall, the manuscript is promising; however, several substantial issues must be addressed before it is suitable for publication.
Major Comments:
1. The constrained calibration framework requires greater transparency. While the manuscript explains that 100,000 parameter sets were generated, screened against internal constraints, and then filtered for the highest-KGE solution, it remains unclear how restrictive these constraints are and the extent to which they reduce the feasible solution space. I encourage the authors to explicitly report the number of parameter sets that satisfy each individual constraint, as well as all constraints jointly. Furthermore, it would be highly beneficial to better illustrate how the constrained calibration alters the distributions of both parameters and internal states.
2. The delineation of riparian areas necessitates stronger justification. Because the core argument of the paper is build on the explicit separation of upland and riparian units, the conclusions are highly likely to be sensitive to the definition of the riparian extent. Incorporating a brief sensitivity analysis, or at a minimum, a more comprehensive discussion regarding the uncertainties associated with the chosen delineation approach, would significantly strengthen the manuscript.
3. The scenario analysis should be interpreted with greater caution. Although the manuscript notes that the experiment focuses solely on increased upland carbon inputs without representing the hydrological alterations associated with forest dieback, this limitation must be stated more prominently. The exercise should be explicitly framed as a structural stress test rather than a comprehensive prediction of forest-dieback impacts.
4. The authors should more explicitly acknowledge that while the landscape-explicit structure represents a significant advancement, it is not yet a complete solution. The study demonstrates that baseline outlet calibration can yield unrealistic internal DOC dynamics, and that the landscape-explicit model performs better under constrained calibration and scenario testing. Nevertheless, the discussion also indicates that riparian DOC concentrations may still be underestimated relative to observations, underscoring the need for further process refinement.
Minor Comments:
1. Several formatting and technical errors must be addressed. Notably, the heading “3 Methodology” mistakenly appears at the beginning of the Results section. Additionally, the export equations should be carefully verified for consistency with the conceptual model description.
2. The reliance on Kling-Gupta Efficiency (KGE) as the primary evaluation criterion should be explicitly justified, particularly given the authors' observation that model ranking is sensitive to the choice of performance metric.
3. The manuscript would benefit from a clearer presentation of how many behavioral models satisfy the imposed internal constraints. For instance, the finding that only 53% of behavioral landscape-explicit models meet all constraints under baseline calibration is highly significant and warrants greater emphasis.
4. Several figures are visually dense and should be streamlined. Shifting some of the highly detailed material to the Supplementary Information would enhance overall readability.
5. Given that the study's novelty stems largely from its model implementation and calibration design, making the code and computational workflow openly accessible would substantially elevate the paper's impact and reproducibility.