The value of instream stable water isotope and nitrate concentration data for calibrating a travel time‐based water quality model

The value of instream stable water isotope and nitrate concentration data for calibrating a travel time‐based water quality model. Borriero, A., Musolff, A., Kumar, R., Fleckenstein, J. H., Lutz, S. R., & Nguyen, T. V. Hydrological Processes, 38(5):e15154, May, 2024.

Paper doi abstract bibtex

Abstract Transit time‐based water quality models using StorAge Selection (SAS) functions are crucial for nitrate (NO 3 − ) management. However, relying solely on instream NO 3 − concentration for model calibration can result in poor parameter identifiability. This is due to the interaction, or correlation, between transport parameters, such as SAS function parameters, and denitrification rate, which challenges accurate parameters identification and description of catchment‐scale hydrological processes. To tackle this issue, we conducted three Monte‐Carlo experiments for a German mesoscale catchment by calibrating a SAS‐based model with daily instream NO 3 − concentrations (Experiment 1), monthly instream stable water isotopes (e.g. δ 18 O) (Experiment 2) and both datasets (Experiment 3). Our findings revealed comparable ranges of SAS transport parameters and median water transit times (TT 50 ) across the experiments. This suggests that, despite their distinct reactive or conservative nature, and sampling strategies, the NO 3 − and δ 18 O time series offer similar information for calibration. However, the absolute values of transport parameters and TT 50 time series, as well as the degree of parameter interaction differed. Experiment 1 showed greater interaction between certain transport parameters and denitrification rate, leading to greater equifinality. Conversely, Experiment 3 yielded reduced parameters interaction, which enhanced transport parameters identifiability and decreased uncertainty in TT 50 time series. Hence, even a modest effort to incorporate only monthly δ 18 O values in model calibration for highly frequent NO 3 − , improved the description of hydrological transport. This study showcased the value of combining NO 3 − and δ 18 O model results to improve transport parameter identifiability and model robustness, which ultimately enhances NO 3 − management strategies.

@article{borriero_value_2024,
	title = {The value of instream stable water isotope and nitrate concentration data for calibrating a travel time‐based water quality model},
	volume = {38},
	issn = {0885-6087, 1099-1085},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/hyp.15154},
	doi = {10.1002/hyp.15154},
	abstract = {Abstract
            
              Transit time‐based water quality models using StorAge Selection (SAS) functions are crucial for nitrate (NO
              3
              −
              ) management. However, relying solely on instream NO
              3
              −
              concentration for model calibration can result in poor parameter identifiability. This is due to the interaction, or correlation, between transport parameters, such as SAS function parameters, and denitrification rate, which challenges accurate parameters identification and description of catchment‐scale hydrological processes. To tackle this issue, we conducted three Monte‐Carlo experiments for a German mesoscale catchment by calibrating a SAS‐based model with daily instream NO
              3
              −
              concentrations (Experiment 1), monthly instream stable water isotopes (e.g. δ
              18
              O) (Experiment 2) and both datasets (Experiment 3). Our findings revealed comparable ranges of SAS transport parameters and median water transit times (TT
              50
              ) across the experiments. This suggests that, despite their distinct reactive or conservative nature, and sampling strategies, the NO
              3
              −
              and δ
              18
              O time series offer similar information for calibration. However, the absolute values of transport parameters and TT
              50
              time series, as well as the degree of parameter interaction differed. Experiment 1 showed greater interaction between certain transport parameters and denitrification rate, leading to greater equifinality. Conversely, Experiment 3 yielded reduced parameters interaction, which enhanced transport parameters identifiability and decreased uncertainty in TT
              50
              time series. Hence, even a modest effort to incorporate only monthly δ
              18
              O values in model calibration for highly frequent NO
              3
              −
              , improved the description of hydrological transport. This study showcased the value of combining NO
              3
              −
              and δ
              18
              O model results to improve transport parameter identifiability and model robustness, which ultimately enhances NO
              3
              −
              management strategies.},
	language = {en},
	number = {5},
	urldate = {2024-11-21},
	journal = {Hydrological Processes},
	author = {Borriero, A. and Musolff, A. and Kumar, R. and Fleckenstein, J. H. and Lutz, S. R. and Nguyen, T. V.},
	month = may,
	year = {2024},
	pages = {e15154},
}

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This is due to the interaction, or correlation, between transport parameters, such as SAS function parameters, and denitrification rate, which challenges accurate parameters identification and description of catchment‐scale hydrological processes. To tackle this issue, we conducted three Monte‐Carlo experiments for a German mesoscale catchment by calibrating a SAS‐based model with daily instream NO 3 − concentrations (Experiment 1), monthly instream stable water isotopes (e.g. δ 18 O) (Experiment 2) and both datasets (Experiment 3). Our findings revealed comparable ranges of SAS transport parameters and median water transit times (TT 50 ) across the experiments. This suggests that, despite their distinct reactive or conservative nature, and sampling strategies, the NO 3 − and δ 18 O time series offer similar information for calibration. However, the absolute values of transport parameters and TT 50 time series, as well as the degree of parameter interaction differed. 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However, relying solely on instream NO\n 3\n −\n concentration for model calibration can result in poor parameter identifiability. This is due to the interaction, or correlation, between transport parameters, such as SAS function parameters, and denitrification rate, which challenges accurate parameters identification and description of catchment‐scale hydrological processes. To tackle this issue, we conducted three Monte‐Carlo experiments for a German mesoscale catchment by calibrating a SAS‐based model with daily instream NO\n 3\n −\n concentrations (Experiment 1), monthly instream stable water isotopes (e.g. δ\n 18\n O) (Experiment 2) and both datasets (Experiment 3). Our findings revealed comparable ranges of SAS transport parameters and median water transit times (TT\n 50\n ) across the experiments. 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