scholarly journals Characterizing the variability of transit time distributions and young water fractions in karst catchments using flux tracking

2020 ◽  
Vol 34 (15) ◽  
pp. 3156-3174 ◽  
Author(s):  
Zhicai Zhang ◽  
Xi Chen ◽  
Qinbo Cheng ◽  
Chris Soulsby
Keyword(s):  
Transit Time ◽  
Water Fractions

scholarly journals New water fractions and transit time distributions at Plynlimon, Wales, estimated from stable water isotopes in precipitation and streamflow

2019 ◽  
Author(s):  
Julia L. A. Knapp ◽  
Colin Neal ◽  
Alessandro Schlumpf ◽  
Margaret Neal ◽  
James W. Kirchner
Keyword(s):  
Time Series ◽  
Stable Isotope ◽  
Transit Time ◽  
Transport Processes ◽  
Water Isotopes ◽  
Data Sets ◽  
Hydrograph Separation ◽  
Stable Water Isotopes ◽  
Isotope Data ◽  
Water Fractions

Abstract. Long-term, high-frequency time series of passive tracers in precipitation and streamflow are essential for quantifying catchment transport and storage processes, but few such data sets are publicly available. Here we describe, present, and make available to the public two extensive data sets of stable water isotopes in streamflow and precipitation at the Plynlimon experimental catchments in mid-Wales. Stable isotope data are available at 7-hourly intervals for 17 months, and at weekly intervals for 4.25 years. Precipitation isotope values were highly variable in both data sets, and the high temporal resolution of the 7-hourly streamwater samples revealed rich isotopic dynamics that were not captured by the weekly sampling. We used ensemble hydrograph separation to calculate new water fractions and transit time distributions from both data sets. Transit time distributions estimated by ensemble hydrograph separation were broadly consistent with those estimated by spectral fitting methods, suggesting that they can reliably quantify the contributions of recent precipitation to streamflow. We found that on average, roughly 3 % of streamwater was made up of precipitation that fell within the previous 7 hours, and 13–15 % of streamwater was made up of precipitation that fell within the previous week. The contributions of recent precipitation to streamflow were highest during large events, as illustrated by comparing new water fractions for different discharges and precipitation rates. This dependence of new water fractions on water fluxes was also reflected in their seasonal variations, with lower new water fractions and more damped catchment transit time distributions in spring and summer compared to fall and winter. We also compared new water fractions obtained from stable water isotopes against those obtained from concentrations of chloride, a solute frequently used as a passive tracer of catchment transport processes. After filtering the chloride data for dry deposition effects, we found broadly similar new water fractions using chloride and stable water isotopes, indicating that these different tracers may yield similar inferences about catchment storage and transport, if potentially confounding factors are eliminated. These stable isotope time series comprise some of the longest and most detailed publicly available catchment isotope data sets. They complement extensive solute data sets that are already publicly available for Plynlimon, enabling a wide range of future analyses of catchment behavior.

scholarly journals Technical note: Calculation scripts for ensemble hydrograph separation

2020 ◽  
Vol 24 (11) ◽  
pp. 5539-5558
Author(s):  
James W. Kirchner ◽  
Julia L. A. Knapp
Keyword(s):  
Robust Estimation ◽  
Transit Time ◽  
Technical Note ◽  
Hydrograph Separation ◽  
Estimation Techniques ◽  
Benchmark Data ◽  
Technical Details ◽  
Water Fractions ◽  
Passive Tracers

Abstract. Ensemble hydrograph separation has recently been proposed as a technique for using passive tracers to estimate catchment transit time distributions and new water fractions, introducing a powerful new tool for quantifying catchment behavior. However, the technical details of the necessary calculations may not be straightforward for many users to implement. We have therefore developed scripts that perform these calculations on two widely used platforms (MATLAB and R), to make these methods more accessible to the community. These scripts implement robust estimation techniques by default, making their results highly resistant to outliers. Here we briefly describe how these scripts work and offer advice on their use. We illustrate their potential and limitations using synthetic benchmark data.

scholarly journals New water fractions and transit time distributions at Plynlimon, Wales, estimated from stable water isotopes in precipitation and streamflow

2019 ◽  
Vol 23 (10) ◽  
pp. 4367-4388 ◽  
Author(s):  
Julia L. A. Knapp ◽  
Colin Neal ◽  
Alessandro Schlumpf ◽  
Margaret Neal ◽  
James W. Kirchner
Keyword(s):  
Time Series ◽  
Stable Isotope ◽  
Transit Time ◽  
Transport Processes ◽  
Water Isotopes ◽  
Data Sets ◽  
Hydrograph Separation ◽  
Stable Water Isotopes ◽  
Isotope Data ◽  
Water Fractions

Abstract. Long-term, high-frequency time series of passive tracers in precipitation and streamflow are essential for quantifying catchment transport and storage processes, but few such data sets are publicly available. Here we describe, present, and make available to the public two extensive data sets of stable water isotopes in streamflow and precipitation at the Plynlimon experimental catchments in central Wales. Stable isotope data are available at 7-hourly intervals for 17 months, and at weekly intervals for 4.25 years. Precipitation isotope values were highly variable in both data sets, and the high temporal resolution of the 7-hourly streamwater samples revealed rich isotopic dynamics that were not captured by the weekly sampling. We used ensemble hydrograph separation to calculate new water fractions and transit time distributions from both data sets. Transit time distributions estimated by ensemble hydrograph separation were broadly consistent with those estimated by spectral fitting methods, suggesting that they can reliably quantify the contributions of recent precipitation to streamflow. We found that on average, roughly 3 % of streamwater was made up of precipitation that fell within the previous 7 h, and 13 %–15 % of streamwater was made up of precipitation that fell within the previous week. The contributions of recent precipitation to streamflow were highest during large events, as illustrated by comparing new water fractions for different discharges and precipitation rates. This dependence of new water fractions on water fluxes was also reflected in their seasonal variations, with lower new water fractions and more damped catchment transit time distributions in spring and summer compared to fall and winter. We also compared new water fractions obtained from stable water isotopes against those obtained from concentrations of chloride, a solute frequently used as a passive tracer of catchment transport processes. After filtering the chloride data for dry deposition effects, we found broadly similar new water fractions using chloride and stable water isotopes, indicating that these different tracers may yield similar inferences about catchment storage and transport, if potentially confounding factors are eliminated. These stable isotope time series comprise some of the longest and most detailed publicly available catchment isotope data sets. They complement extensive solute data sets that are already publicly available for Plynlimon, enabling a wide range of future analyses of catchment behavior.

scholarly journals Quantifying new water fractions and transit time distributions using ensemble hydrograph separation: theory and benchmark tests

2019 ◽  
Vol 23 (1) ◽  
pp. 303-349 ◽  
Author(s):  
James W. Kirchner
Keyword(s):  
Transit Time ◽  
Time Lag ◽  
Isotopic Fractionation ◽  
Hydrograph Separation ◽  
Isotopic Tracers ◽  
Water Fraction ◽  
Benchmark Tests ◽  
Water Fractions ◽  
Lag Times ◽  
Over Time

Abstract. Decades of hydrograph separation studies have estimated the proportions of recent precipitation in streamflow using end-member mixing of chemical or isotopic tracers. Here I propose an ensemble approach to hydrograph separation that uses regressions between tracer fluctuations in precipitation and discharge to estimate the average fraction of new water (e.g., same-day or same-week precipitation) in streamflow across an ensemble of time steps. The points comprising this ensemble can be selected to isolate conditions of particular interest, making it possible to study how the new water fraction varies as a function of catchment and storm characteristics. Even when new water fractions are highly variable over time, one can show mathematically (and confirm with benchmark tests) that ensemble hydrograph separation will accurately estimate their average. Because ensemble hydrograph separation is based on correlations between tracer fluctuations rather than on tracer mass balances, it does not require that the end-member signatures are constant over time, or that all the end-members are sampled or even known, and it is relatively unaffected by evaporative isotopic fractionation. Ensemble hydrograph separation can also be extended to a multiple regression that estimates the average (or “marginal”) transit time distribution (TTD) directly from observational data. This approach can estimate both “backward” transit time distributions (the fraction of streamflow that originated as rainfall at different lag times) and “forward” transit time distributions (the fraction of rainfall that will become future streamflow at different lag times), with and without volume-weighting, up to a user-determined maximum time lag. The approach makes no assumption about the shapes of the transit time distributions, nor does it assume that they are time-invariant, and it does not require continuous time series of tracer measurements. Benchmark tests with a nonlinear, nonstationary catchment model confirm that ensemble hydrograph separation reliably quantifies both new water fractions and transit time distributions across widely varying catchment behaviors, using either daily or weekly tracer concentrations as input. Numerical experiments with the benchmark model also illustrate how ensemble hydrograph separation can be used to quantify the effects of rainfall intensity, flow regime, and antecedent wetness on new water fractions and transit time distributions.

scholarly journals Quantifying new water fractions and transit time distributions using ensemble hydrograph separation: theory and benchmark tests

2018 ◽  
Author(s):  
James Kirchner
Keyword(s):  
Transit Time ◽  
Isotopic Fractionation ◽  
Hydrograph Separation ◽  
Isotopic Tracers ◽  
Water Fraction ◽  
Benchmark Tests ◽  
Water Fractions ◽  
Lag Times ◽  
Storm Characteristics ◽  
Over Time

Abstract. Decades of hydrograph separation studies have estimated the proportions of recent precipitation in streamflow using end-member mixing of chemical or isotopic tracers. Here I propose an ensemble approach to hydrograph separation that uses regressions between tracer fluctuations in precipitation and discharge to estimate the average fraction of new water (e.g., same-day or same-week precipitation) in streamflow across an ensemble of time steps. The points comprising this ensemble can be selected to isolate conditions of particular interest, making it possible to study how the new water fraction varies as a function of catchment and storm characteristics. Even when new water fractions are highly variable over time, one can show mathematically (and confirm with benchmark tests) that ensemble hydrograph separation will accurately estimate their average. Because ensemble hydrograph separation is based on correlations between tracer fluctuations rather than on tracer mass balances, it does not require that the end-member signatures are constant over time, or that all the end-members are sampled or even known, and it is relatively unaffected by evaporative isotopic fractionation. Ensemble hydrograph separation can also be extended to a multiple regression that estimates the average (or "marginal") transit time distribution directly from observational data. This approach can estimate both "backward" transit time distributions (the fraction of streamflow that originated as rainfall at different lag times) and "forward" transit time distributions (the fraction of rainfall that will become future streamflow at different lag times), with and without volume-weighting. It makes no assumption about the shapes of the transit time distributions, nor does it assume that they are time-invariant, and it does not require continuous time series of tracer measurements. Benchmark tests with a nonlinear, nonstationary catchment model confirm that ensemble hydrograph separation reliably quantifies both new water fractions and transit time distributions across widely varying catchment behaviors, using either daily or weekly tracer concentrations as input. Numerical experiments with the benchmark model also illustrate how ensemble hydrograph separation can be used to quantify the effects of rainfall intensity, flow regime, and antecedent wetness on new water fractions and transit time distributions.

New water fractions, transit time distributions, and solute concentrations at Plynlimon, Wales.

2020 ◽  
Author(s):  
Julia Knapp ◽  
James Kirchner
Keyword(s):  
Transit Time ◽  
Water Isotopes ◽  
Water Fluxes ◽  
Hydrograph Separation ◽  
Stable Water Isotopes ◽  
Water Fractions ◽  
Lag Times ◽  
And Storage ◽  
Average Contribution ◽  
Insight Into

<p>Transit time distributions estimated from stable water isotopes (deuterium and oxygen-18) are frequently used to assess transport and storage of water in catchments. We analyzed 2.25 years of 7‑hourly and 4.5 years of weekly measurements of stable water isotopes in precipitation and streamwater at the Plynlimon catchments in Wales, UK using the ensemble hydrograph separation technique. We thereby quantified new water fractions – the average contribution of recent precipitation to streamflow – in the different subcatchments, and determined transit time distributions as the contribution of precipitation to streamflow over a range of lag times.</p><p>We found that on average only 3 % of streamwater was made up of precipitation that fell within the last 7 hours, and 13-15 % of streamwater was made up of precipitation that fell within the previous week. However, these new water fractions increased with discharge, indicating that more recent precipitation reached the stream when the catchment was wet, and the contributions of recent precipitation to streamflow were highest during large events. This dependence of new water fractions on water fluxes was also reflected in their seasonal variations, with lower new water fractions and more damped catchment transit time distributions in the drier spring and summer compared to fall and winter.</p><p>A comparison between changes in solute concentrations and new water fractions with discharge provides additional insight into the storage and release of water and solutes from the catchments. Our analysis demonstrates that changes in solute concentrations primarily reflect changes in flowpaths between dry and wet conditions, rather than changes in the fraction of recent precipitation in streamflow.</p>

scholarly journals Technical note: Calculation scripts for ensemble hydrograph separation

2020 ◽  
Author(s):  
James W. Kirchner ◽  
Julia L. A. Knapp
Keyword(s):  
Robust Estimation ◽  
Transit Time ◽  
Technical Note ◽  
Hydrograph Separation ◽  
Estimation Techniques ◽  
Benchmark Data ◽  
Technical Details ◽  
Water Fractions ◽  
Passive Tracers

Abstract. Ensemble hydrograph separation has recently been proposed as a technique for using passive tracers to measure catchment transit time distributions and new water fractions, introducing a powerful new tool for quantifying catchment behavior. However, the technical details of the necessary calculations may not be straightforward for many users to implement. We have therefore developed scripts that perform these calculations on two widely used platforms (MATLAB and R), to make these methods more accessible to the community. These scripts implement robust estimation techniques by default, making their results highly resistant to outliers. Here we briefly describe how these scripts work, and offer advice on their use. We illustrate their potential and limitations using synthetic benchmark data.

Sign in / Sign up

Export Citation Format

Share Document