scholarly journals Variability of Water Transit Time Distributions at the Strengbach Catchment (Vosges Mountains, France) Inferred Through Integrated Hydrological Modeling and Particle Tracking Algorithms

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2637 ◽  
Author(s):  
Sylvain Weill ◽  
Nolwenn Lesparre ◽  
Benjamin Jeannot ◽  
Frederick Delay
Keyword(s):  
Transit Time ◽  
Particle Tracking ◽  
Temporal Variability ◽  
Hydrological Modeling ◽  
Mean Transit Time ◽  
Subsurface Water ◽  
Vosges Mountains ◽  
Tracking Algorithms ◽  
Magnetic Resonance Sounding ◽  
Low Dimensional

The temporal variability of transit-time distributions (TTDs) and residence-time distributions (RTDs) has received particular attention recently, but such variability has barely been studied using distributed hydrological modeling. In this study, a low-dimensional integrated hydrological model is run in combination with particle-tracking algorithms to investigate the temporal variability of TTDs, RTDs, and StorAge Selection (SAS) functions in the small, mountainous Strengbach watershed belonging to the French network of critical-zone observatories. The particle-tracking algorithms employed rely upon both forward and backward formulations that are specifically developed to handle time-variable velocity fields and evaluate TTDs and RTDs under transient hydrological conditions. The model is calibrated using both traditional streamflow measurements and magnetic resonance sounding (MRS)—which is sensitive to the subsurface water content—and then verified over a ten-year period. The results show that the mean transit time is rather short, at 150–200 days, and that the TTDs and RTDs are not greatly influenced by water storage within the catchment. This specific behavior is mainly explained by the small size of the catchment and its small storage capacity, a rapid flow mainly controlled by gravity along steep slopes, and climatic features that keep the contributive zone around the stream wet all year long.

Combined integrated hydrological modeling and particle tracking algorithms to infer the temporal variability of transit and residence time distributions within the Strengbach catchment (Vosges mountains, France)

2020 ◽  
Author(s):  
Sylvain Weill ◽  
Nolwenn Lesparre ◽  
Benjamin Jeannot ◽  
Frederick Delay
Keyword(s):  
Transit Time ◽  
Residence Time ◽  
Particle Tracking ◽  
Temporal Variability ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
Water Storage ◽  
Tracking Algorithms ◽  
Residence Time Distributions ◽  
Strengbach Catchment

<p>The temporal variability of transit-time distributions (TTDs) and residence-time distributions (RTDs) in hydrological systems has received particular attention recently because of their ability to inform on elementary processes impacting geochemical signatures and water fluxes in ecosystems. To date, these distributions and their temporal variability have been mainly investigated through concentration measurements of conservative geochemical or isotopic tracers. Even though physically-based and distributed hydrological models can render interpretations of TTDs/RTDs in terms of processes and physical controls, the variability of TTDs and RTDs has barely been studied using distributed hydrological modeling. In this study, an integrated hydrological model has been coupled with particle tracking algorithms and applied to the Strengbach Catchment – a small mountainous catchment belonging to the French network of critical zone observatories – to investigate the eventual link between water storage in the catchment and the temporal variability of TTDs and RTDs. The model calibration is performed relying upon both classical streamflow measurements and magnetic resonance sounding, a geophysical measure sensible to the water content in the subsurface. The model is then run over a 10-year period for which time distributions are calculated at various deadlines. The results show that the response of the Strengbach catchment is uncommon with short mean transit times (approximately 150-200 days) and a weak variability of TTDs and RTDs with the water storage. This specific behavior is mainly linked to the small size of the system and specific climatic and topographic conditions. Because the hydrological model was calibrated on the basis of unusual data (local water contents inferred via MRS measurements), ongoing investigations target the evaluation of the sensitivity of transit time distributions with respect to uncertainties plaguing calibrating data.</p>

scholarly journals ‘Teflon Basin’ or Not? A High-Elevation Catchment Transit Time Modeling Approach

Hydrology ◽  
2019 ◽  
Vol 6 (4) ◽  
pp. 92 ◽  
Author(s):  
Jan Schmieder ◽  
Stefan Seeger ◽  
Markus Weiler ◽  
Ulrich Strasser
Keyword(s):  
Transit Time ◽  
Amplitude Ratio ◽  
Mean Transit Time ◽  
High Elevation ◽  
Subsurface Water ◽  
Balance Model ◽  
Water Volume ◽  
Time Model ◽  
Water Fraction ◽  
Ice Melt

We determined the streamflow transit time and the subsurface water storage volume in the glacierized high-elevation catchment of the Rofenache (Oetztal Alps, Austria) with the lumped parameter transit time model TRANSEP. Therefore we enhanced the surface energy-balance model ESCIMO to simulate the ice melt, snowmelt and rain input to the catchment and associated δ18O values for 100 m elevation bands. We then optimized TRANSEP with streamflow volume and δ18O for a four-year period with input data from the modified version of ESCIMO at a daily resolution. The median of the 100 best TRANSEP runs revealed a catchment mean transit time of 9.5 years and a mobile storage of 13,846 mm. The interquartile ranges of the best 100 runs were large for both, the mean transit time (8.2–10.5 years) and the mobile storage (11,975–15,382 mm). The young water fraction estimated with the sinusoidal amplitude ratio of input and output δ18O values and delayed input of snow and ice melt was 47%. Our results indicate that streamflow is dominated by the release of water younger than 56 days. However, tracers also revealed a large water volume in the subsurface with a long transit time resulting to a strongly delayed exchange with streamflow and hence also to a certain portion of relatively old water: The median of the best 100 TRANSEP runs for streamflow fraction older than five years is 28%.

Cerebral vascular mean transit time determined by PET and DSC-MRI

2005 ◽  
Vol 25 (1_suppl) ◽  
pp. S676-S676
Author(s):  
Masanobu Ibaraki ◽  
Hiroshi Ito ◽  
Eku Shimosegawa ◽  
Hideto Toyoshima ◽  
Keiichi Ishigame ◽  
...  
Keyword(s):  
Transit Time ◽  
Mean Transit Time ◽  
Dsc Mri ◽  
Cerebral Vascular

Reproducibility of mean transit time for maximal myocardial flow assessment by videodensitometry

1990 ◽  
Vol 6 (2) ◽  
pp. 101-108 ◽  
Author(s):  
Nico H. J. Pijls ◽  
Gerard J. H. Uijen ◽  
Truus Pijnenburg ◽  
Karel van Leeuwen ◽  
Wim R. M. Aengevaeren ◽  
...  
Keyword(s):  
Transit Time ◽  
Mean Transit Time ◽  
Myocardial Flow

scholarly journals Serial Quantitative Computed Tomography Perfusion in Aneurysmal Subarachnoid Hemorrhage

2016 ◽  
Vol 43 (3) ◽  
pp. 375-380 ◽  
Author(s):  
Cheemun Lum ◽  
Matthew J. Hogan ◽  
John Sinclair ◽  
Shane English ◽  
Howard Lesiuk ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Subarachnoid Hemorrhage ◽  
Middle Cerebral Artery ◽  
Transit Time ◽  
Cerebral Artery ◽  
Computed Tomography Angiography ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Mean Transit Time ◽  
Arterial Diameter ◽  
Computed Tomography Perfusion

AbstractPurpose: Computed tomography perfusion (CTP) has been performed to predict which patients with aneurysmal subarachnoid hemorrhage are at risk of developing delayed cerebral ischemia (DCI). Patients with severe arterial narrowing may have significant reduction in perfusion. However, many patients have less severe arterial narrowing. There is a paucity of literature evaluating perfusion changes which occur with mild to moderate narrowing. The purpose of our study was to investigate serial whole-brain CTP/computed tomography angiography in aneurysm-related subarachnoid hemorrhage (aSAH) patients with mild to moderate angiographic narrowing. Methods: We retrospectively studied 18 aSAH patients who had baseline and follow-up whole-brain CTP/computed tomography angiography. Thirty-one regions of interest/hemisphere at six levels were grouped by vascular territory. Arterial diameters were measured at the circle of Willis. The correlation between arterial diameter and change in CTP values, change in CTP in with and without DCI, and response to intra-arterial vasodilator therapy in DCI patients was evaluated. Results: There was correlation among the overall average cerebral blood flow (CBF; R=0.49, p<0.04), mean transit time (R=–0.48, p=0.04), and angiographic narrowing. In individual arterial territories, there was correlation between changes in CBF and arterial diameter in the middle cerebral artery (R=0.53, p=0.03), posterior cerebral artery (R=0.5, p=0.03), and anterior cerebral artery (R=0.54, p=0.02) territories. Prolonged mean transit time was correlated with arterial diameter narrowing in the middle cerebral artery territory (R=0.52, p=0.03). Patients with DCI tended to have serial worsening of CBF compared with those without DCI (p=0.055). Conclusions: Our preliminary study demonstrates there is a correlation between mild to moderate angiographic narrowing and serial changes in perfusion in patients with aSAH. Patients developing DCI tended to have progressively worsening CBF compared with those not developing DCI.

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