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

Fuente: Wiley Open Access
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: A. Borriero, A. Musolff, R. Kumar, J. H. Fleckenstein, S. R. Lutz, T. V. Nguyen
Format: Artículo Open Access
Veröffentlicht: Wiley 2024
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1867018195307593728
author A. Borriero
A. Musolff
R. Kumar
J. H. Fleckenstein
S. R. Lutz
T. V. Nguyen
author_facet A. Borriero
A. Musolff
R. Kumar
J. H. Fleckenstein
S. R. Lutz
T. V. Nguyen
A. Borriero
A. Musolff
R. Kumar
J. H. Fleckenstein
S. R. Lutz
T. V. Nguyen
collection Wiley Open Access
contents The value of instream stable water isotope and nitrate concentration data for calibrating a travel time‐based water quality model A. Borriero A. Musolff R. Kumar J. H. Fleckenstein S. R. Lutz T. V. Nguyen Hydrological Processes AbstractTransit time‐based water quality models using StorAge Selection (SAS) functions are crucial for nitrate (NO3−) management. However, relying solely on instream NO3− 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 NO3− concentrations (Experiment 1), monthly instream stable water isotopes (e.g. δ18O) (Experiment 2) and both datasets (Experiment 3). Our findings revealed comparable ranges of SAS transport parameters and median water transit times (TT50) across the experiments. This suggests that, despite their distinct reactive or conservative nature, and sampling strategies, the NO3− and δ18O time series offer similar information for calibration. However, the absolute values of transport parameters and TT50 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 TT50 time series. Hence, even a modest effort to incorporate only monthly δ18O values in model calibration for highly frequent NO3−, improved the description of hydrological transport. This study showcased the value of combining NO3− and δ18O model results to improve transport parameter identifiability and model robustness, which ultimately enhances NO3− management strategies. 10.1002/hyp.15154 http://creativecommons.org/licenses/by/4.0/
doi_str_mv 10.1002/hyp.15154
format Artículo Open Access
id wiley_oa_10_1002_hyp_15154
institution Wiley Open Access
license_str_mv http://creativecommons.org/licenses/by/4.0/
publishDate 2024
publisher Wiley
record_format wiley_oa
spellingShingle The value of instream stable water isotope and nitrate concentration data for calibrating a travel time‐based water quality model
A. Borriero
A. Musolff
R. Kumar
J. H. Fleckenstein
S. R. Lutz
T. V. Nguyen
Hydrological Processes
The value of instream stable water isotope and nitrate concentration data for calibrating a travel time‐based water quality model A. Borriero A. Musolff R. Kumar J. H. Fleckenstein S. R. Lutz T. V. Nguyen Hydrological Processes AbstractTransit time‐based water quality models using StorAge Selection (SAS) functions are crucial for nitrate (NO3−) management. However, relying solely on instream NO3− 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 NO3− concentrations (Experiment 1), monthly instream stable water isotopes (e.g. δ18O) (Experiment 2) and both datasets (Experiment 3). Our findings revealed comparable ranges of SAS transport parameters and median water transit times (TT50) across the experiments. This suggests that, despite their distinct reactive or conservative nature, and sampling strategies, the NO3− and δ18O time series offer similar information for calibration. However, the absolute values of transport parameters and TT50 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 TT50 time series. Hence, even a modest effort to incorporate only monthly δ18O values in model calibration for highly frequent NO3−, improved the description of hydrological transport. This study showcased the value of combining NO3− and δ18O model results to improve transport parameter identifiability and model robustness, which ultimately enhances NO3− management strategies. 10.1002/hyp.15154 http://creativecommons.org/licenses/by/4.0/
title The value of instream stable water isotope and nitrate concentration data for calibrating a travel time‐based water quality model
topic Hydrological Processes
url https://onlinelibrary.wiley.com/doi/10.1002/hyp.15154