Calibration and validation of hydrological models is a challenge, particularly in remote regions that are minimally gauged. This paper develops a novel methodology for large-scale (>1000 km 2 ) hydrological model calibration and validation using stable water isotopes founded on the rigorous constraints imposed by the need to conserve both water mass and stable isotopes simultaneously. The isoWATFLOOD model is applied to five basins within the Fort Simpson, Northwest Territories region of northern Canada to simulate stream discharge and oxygen-18 signals over a 3-year period. The isotopic variation of river discharge, runoff components, and evaporative fractionation are successfully simulated on both a seasonal and continual basis over the watershed domain to demonstrate the application of isotope tracers to regional hydrologic calibration. The intended application of this research is to remote, large-scale basins, showing promise for improving predictions in minimally gauged basins and climate change research where traditional, rigorous approaches to constraining parameter uncertainty may be impractical. This coupled isotope-hydrological (i.e. iso-hydrological) approach to modelling reduces the number of possible parameterizations, resulting in potentially more physically-based hydrological predictions. isoWATFLOOD provides a tool for water resource managers and utilities to use operationally for water use, allocation, and runoff generation estimations. Copyright
Abstract. Tracer-aided hydrological models are becoming increasingly popular tools as they assist with process understanding and source separation, which facilitates model calibration and diagnosis of model uncertainty (Tetzlaff et al., 2015; Klaus and McDonnell, 2013). Data availability in high-latitude regions, however, proves to be a major challenge associated with this type of application (Tetzlaff et al., 2015). Models require a time series of isotopes in precipitation (δ18Oppt) to drive simulations, and throughout much of the world – particularly in sparsely populated high-latitude regions – these data are not widely available. Here we investigate the impact that choice of precipitation isotope product (δ18Oppt) has on simulations of streamflow, δ18O in streamflow (δ18OSF), resulting hydrograph separations, and model parameters. In a high-latitude, data-sparse, seasonal basin (Fort Simpson, NWT, Canada), we assess three precipitation isotope products of different spatial and temporal resolutions (i.e. semi-annual static, seasonal KPN43, and daily bias-corrected REMOiso), and apply them to force the isoWATFLOOD tracer-aided hydrologic model. Total simulated streamflow is not significantly impacted by choice of δ18Oppt product; however, simulated isotopes in streamflow (δ18OSF) and the internal apportionment of water (driven by model parameterization) are impacted. The highest-resolution product (REMOiso) was distinct from the two lower-resolution products (KPN43 and static), but could not be verified as correct due to a lack of daily δ18Oppt observations. The resolution of δ18Oppt impacts model parameterization and seasonal hydrograph separations, producing notable differences among simulations following large snowmelt and rainfall events when event compositions differ significantly from δ18OSF. Capturing and preserving the spatial variability in δ18Oppt using distributed tracer-aided models is important because this variability impacts model parameterization. We achieve an understanding of tracer-aided modelling and its application in high-latitude regions with limited δ18Oppt observations, and the value such models have in defining modelling uncertainty. In this study, application of a tracer-aided model is able to identify simulations with improved internal process representation, reinforcing the fact that tracer-aided modelling approaches assist with resolving hydrograph component contributions and work towards diagnosing equifinality.
Delineating spatial patterns of precipitation isotopes (''isoscapes'') is becoming increasingly important to understand the processes governing the modern water isotope cycle and their application to migration forensics, climate proxy interpretation, and ecohydrology of terrestrial systems. However, the extent to which these patterns can be empirically predicted across Canada and the northern United States has not been fully articulated, in part due to a lack of time series precipitation isotope data for major regions of North America. In this study, we use multiple linear regressions of CNIP, GNIP, and USNIP observations alongside climatological variables, teleconnection indices, and geographic indicators to create empirical models that predict the d
Challenges inherent in mesoscale (large domain) hydrologic modelling of remote ungauged basins include validation of model results and quantification of uncertainty in the predictions. Isotope equipped hydrological models, such as isoWATFLOOD, have the ability to simulate both quantity and isotopic composition of streamflow and runoff generation processes providing more options for model validation, but first require information about isotopic composition of precipitation across the model domain. 18 O PPT distributions, but also identified seasons and areas where the geographical and climatological parameters included in this analysis were not able to simulate the measured distributions. Spring, summer and fall model results were satisfactory; however, winter model results were more variable, indicating increased complexity in the driving forces of d 18O PPT patterns during this season. Overall, model results improve with the addition of time-variant climate parameters, this finding being especially significant during the winter. Improving the precipitation input fields within isotope-equipped hydrological models will provide a valuable tool for water use management within large, remote, and often ungauged Canadian rivers and will facilitate studies of both climate variability and surface hydrology in remote regions.
Results are reported from a 3-year monitoring initiative (2010-2013) of stable water isotopes (δ 18 O and δ 2 H) at over 50 hydrometric sites in the lower portion of the Nelson River Basin, a key freshwater-marine corridor in Canada with global significance. Data are collected from annual synoptic surveys and a time-series monitoring program. Water isotope signals exhibit significant long-term average (with reported standard deviation) differences between the upper Nelson River (-10.5‰ δ 18 O ± 0.18‰) and Burntwood River (i.e. Churchill Basin; -12.8‰ δ 18 O ± 0.4‰) regions which are attributed to the geographic extent and origin of the water. Upper Nelson River flow-isotope signals suggest a more temperate climate, and exhibit reverse seasonal cycling (i.e. ice-on isotope enrichment; ice-off isotope depletion) due to the connectivity with and influence of Lake Winnipeg. In contrast, the Burntwood River behaves like a snowmelt-dominated river heavily influenced by wetland storage and enrichment during ice-off periods, exhibiting isotopic signals negatively correlated with headwater river discharge. Flow-weighted δ 18 O and δ 2 H show decreased variability in both regions at extreme low-and high-flow regimes, indicating a tendency towards a single dominant end member: wetland release (low-flow regime) or snowmelt/rainfall (high-flow regime). Mid-to normal-flow regimes exhibit increased isotopic variability, as do small headwater catchments resulting from varied source water contributions, residence times, mixing patterns and the role of landscape-specific features. The Stable Water Isotope Monitoring Network (SWIMN) presented enables the closure of water-isotope mass balance modelling that will facilitate the understanding of changes to freshwater-marine linkages.Les résultats sont basés sur une étude d'échantillonnage de 3 ans (
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.