scholarly journals Modelling electrical conductivity variation using a travel time distribution approach

2021 ◽  
Author(s):  
ZAHRA RIAZI ◽  
Andrew W Western ◽  
Ulrike Bende-Michl
Keyword(s):  
Electrical Conductivity ◽  
Travel Time ◽  
Transit Time ◽  
Dynamic Equilibrium ◽  
Stream Water ◽  
Solute Concentration ◽  
Parameter Estimates ◽  
Time Varying ◽  
Water Age ◽  
Age Related

Water quality dynamics depend strongly on hydrologic flow paths and transit time within catchments. In this paper we use a travel time tracking method to simulate stream salinity (as measured by electrical conductivity) in the Duck River catchment, NW Tasmania, Australia. The approach couples the StorAge transit time modelling approach with two different approaches to model electrical conductivity. The first assumes the catchment has a cyclic salt balance (rainfall source, stream flow sink) that is in dynamic equilibrium and evapoconcentration of salt is the only process changing concentration. The second assumes that the salinity of water in catchment storages is a function of water age in those stores, without explicitly simulating salt mass balance processes. The paper compares these alternate approaches in terms of salinity simulation, simulated stream water age distributions, and simulated storage age distributions. Both salinity simulation approaches reproduce stream salinity with high fidelity under calibration and perform well under validation. The simulations using the age-related solute concentration approach produce less biased results and thus high model efficiencies for validation periods. This approach also produces more consistent model parameter estimates between periods. There are systematic differences in the resultant age distributions between models, particularly for the solute balance based simulations where parameters (catchment storage size) changed more between calibration periods. The effect of time varying versus static storage selection functions are compared, with clear evidence that time varying storage selection functions with parameters linked to catchment conditions (flow) are essential for adequate simulation of event concentration dynamics.

Effects of patchy shade on stream water temperature: how quickly do small streams heat and cool?

2004 ◽  
Vol 55 (8) ◽  
pp. 737 ◽  
Author(s):  
J. Christopher Rutherford ◽  
Nicholas A. Marsh ◽  
Peter M. Davies ◽  
Stuart E. Bunn
Keyword(s):  
Travel Time ◽  
Dynamic Equilibrium ◽  
Stream Water ◽  
Rate Of Change ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Small Streams ◽  
Maximum Temperatures ◽  
Strong Linear Relationship

Summer field observations in five 2nd order streams (width 1–2 m, depth 5–15 cm, velocity 5–10 cm s–1) in Western Australia and south-east Queensland showed that daily maximum temperatures changed by ±4°C over distances of 600–960 m (travel time 2–3 h) immediately downstream from 40–70% step changes in riparian shade. There was a strong linear relationship between the rate of change of daily maximum temperature and the change of shade such that downstream from a 100% change of shade the heating/cooling rates are ±4°C h–1 and ±10°C km–1 (upper bound ±6°C h–1 and ±15°C km–1) respectively. These high rates only apply over short distances and travel times because downstream water temperatures adjust to the new level of shade and reach a dynamic equilibrium. Shade was too patchy in the study streams to measure how long water takes to reach equilibrium, however, using an existing computer model, we estimate that this occurs after ~1200 m (travel time 4 h). Further modelling work is desirable to predict equilibrium temperatures under given meteorological, flow and shade conditions. Nevertheless, landowners and regulators can use this information to determine whether the presence/absence of certain lengths of bankside shade are likely to cause desirable/undesirable temperature decreases/increases.

scholarly journals A comparison of catchment travel times and storage deduced from deuterium and tritium tracers using StorAge Selection functions

2021 ◽  
Vol 25 (1) ◽  
pp. 401-428
Author(s):  
Nicolas Björn Rodriguez ◽  
Laurent Pfister ◽  
Erwin Zehe ◽  
Julian Klaus
Keyword(s):  
Stable Isotopes ◽  
Travel Time ◽  
Stream Water ◽  
Radioactive Decay ◽  
Specific Information ◽  
Time Varying ◽  
Travel Times ◽  
Data Limitations ◽  
Information Contents ◽  
And Storage

Abstract. Catchment travel time distributions (TTDs) are an efficient concept for summarizing the time-varying 3D transport of water and solutes towards an outlet in a single function of a water age and for estimating catchment storage by leveraging information contained in tracer data (e.g., deuterium 2H and tritium 3H). It is argued that the preferential use of the stable isotopes of O and H as tracers, compared to tritium, has truncated our vision of streamflow TTDs, meaning that the long tails of the distribution associated with old water tend to be neglected. However, the reasons for the truncation of the TTD tails are still obscured by methodological and data limitations. In this study, we went beyond these limitations and evaluated the differences between streamflow TTDs calculated using only deuterium (2H) or only tritium (3H). We also compared mobile catchment storage (derived from the TTDs) associated with each tracer. For this, we additionally constrained a model that successfully simulated high-frequency stream deuterium measurements with 24 stream tritium measurements over the same period (2015–2017). We used data from the forested headwater Weierbach catchment (42 ha) in Luxembourg. Time-varying streamflow TTDs were estimated by consistently using both tracers within a framework based on StorAge Selection (SAS) functions. We found similar TTDs and similar mobile storage between the 2H- and 3H-derived estimates, despite statistically significant differences for certain measures of TTDs and storage. The streamflow mean travel time was estimated at 2.90±0.54 years, using 2H, and 3.12±0.59 years, using 3H (mean ± 1 SD – standard deviation). Both tracers consistently suggested that less than 10 % of the stream water in the Weierbach catchment is older than 5 years. The travel time differences between the tracers were small compared to previous studies in other catchments, and contrary to prior expectations, we found that these differences were more pronounced for young water than for old water. The found differences could be explained by the calculation uncertainties and by a limited sampling frequency for tritium. We conclude that stable isotopes do not seem to systematically underestimate travel times or storage compared to tritium. Using both stable and radioactive isotopes of H as tracers reduced the travel time and storage calculation uncertainties. Tritium and stable isotopes both had the ability to reveal short travel times in streamflow. Using both tracers together better exploited the more specific information about longer travel times that 3H inherently contains due to its radioactive decay. The two tracers thus had different information contents overall. Tritium was slightly more informative than stable isotopes for travel time analysis, despite a lower number of tracer samples. In the future, it would be useful to similarly test the consistency of travel time estimates and the potential differences in travel time information contents between those tracers in catchments with other characteristics, or with a considerable fraction of stream water older than 5 years, since this could emphasize the role of the radioactive decay of tritium in discriminating younger water from older water.

scholarly journals Development of the reproduction number from coronavirus SARS-CoV-2 case data in Germany and implications for political measures

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Sahamoddin Khailaie ◽  
Tanmay Mitra ◽  
Arnab Bandyopadhyay ◽  
Marta Schips ◽  
Pietro Mascheroni ◽  
...  
Keyword(s):  
Structural Changes ◽  
Reproduction Number ◽  
National Level ◽  
Transmission Dynamics ◽  
Federal State ◽  
Parameter Estimates ◽  
Time Varying ◽  
Short Term ◽  
Robert Koch Institute ◽  
Federal States

Abstract Background SARS-CoV-2 has induced a worldwide pandemic and subsequent non-pharmaceutical interventions (NPIs) to control the spread of the virus. As in many countries, the SARS-CoV-2 pandemic in Germany has led to a consecutive roll-out of different NPIs. As these NPIs have (largely unknown) adverse effects, targeting them precisely and monitoring their effectiveness are essential. We developed a compartmental infection dynamics model with specific features of SARS-CoV-2 that allows daily estimation of a time-varying reproduction number and published this information openly since the beginning of April 2020. Here, we present the transmission dynamics in Germany over time to understand the effect of NPIs and allow adaptive forecasts of the epidemic progression. Methods We used a data-driven estimation of the evolution of the reproduction number for viral spreading in Germany as well as in all its federal states using our model. Using parameter estimates from literature and, alternatively, with parameters derived from a fit to the initial phase of COVID-19 spread in different regions of Italy, the model was optimized to fit data from the Robert Koch Institute. Results The time-varying reproduction number (Rt) in Germany decreased to <1 in early April 2020, 2–3 weeks after the implementation of NPIs. Partial release of NPIs both nationally and on federal state level correlated with moderate increases in Rt until August 2020. Implications of state-specific Rt on other states and on national level are characterized. Retrospective evaluation of the model shows excellent agreement with the data and usage of inpatient facilities well within the healthcare limit. While short-term predictions may work for a few weeks, long-term projections are complicated by unpredictable structural changes. Conclusions The estimated fraction of immunized population by August 2020 warns of a renewed outbreak upon release of measures. A low detection rate prolongs the delay reaching a low case incidence number upon release, showing the importance of an effective testing-quarantine strategy. We show that real-time monitoring of transmission dynamics is important to evaluate the extent of the outbreak, short-term projections for the burden on the healthcare system, and their response to policy changes.

Estimation of Path Travel Time Distributions in Stochastic Time-Varying Networks with Correlations

2021 ◽  
pp. 036119812110184
Author(s):  
Monika Filipovska ◽  
Hani S. Mahmassani ◽  
Archak Mittal
Keyword(s):  
Time Dependence ◽  
Travel Time ◽  
Correlation Structure ◽  
Time Varying ◽  
Travel Times ◽  
Trajectory Data ◽  
Time Varying Networks ◽  
Transportation Research ◽  
Search Approach ◽  
Stochastic Time

Transportation research has increasingly focused on the modeling of travel time uncertainty in transportation networks. From a user’s perspective, the performance of the network is experienced at the level of a path, and, as such, knowledge of variability of travel times along paths contemplated by the user is necessary. This paper focuses on developing approaches for the estimation of path travel time distributions in stochastic time-varying networks so as to capture generalized correlations between link travel times. Specifically, the goal is to develop methods to estimate path travel time distributions for any path in the networks by synthesizing available trajectory data from various portions of the path, and this paper addresses that problem in a two-fold manner. Firstly, a Monte Carlo simulation (MCS)-based approach is presented for the convolution of time-varying random variables with general correlation structures and distribution shapes. Secondly, a combinatorial data-mining approach is developed, which aims to utilize sparse trajectory data for the estimation of path travel time distributions by implicitly capturing the complex correlation structure in the network travel times. Numerical results indicate that the MCS approach allowing for time-dependence and a time-varying correlation structure outperforms other approaches, and that its performance is robust with respect to different path travel time distributions. Additionally, using the path segmentations from the segment search approach with a MCS approach with time-dependence also produces accurate and robust estimates of the path travel time distributions with the added benefit of shorter computation times.

TDR estimation of electrical conductivity and saline solute concentration in a volcanic soil

Geoderma ◽  
2005 ◽  
Vol 124 (3-4) ◽  
pp. 399-413 ◽  
Author(s):  
R. Muñoz-Carpena ◽  
C.M. Regalado ◽  
A. Ritter ◽  
J. Alvarez-Benedí ◽  
A.R. Socorro
Keyword(s):  
Electrical Conductivity ◽  
Solute Concentration ◽  
Volcanic Soil

scholarly journals Combined diurnal variations of discharge and hydrochemistry of the Isunnguata Sermia outlet of the Greenland Ice Sheet give in sight on sub glacial conditions

2016 ◽  
Author(s):  
Joseph Graly ◽  
Joel Harrington ◽  
Neil Humphrey
Keyword(s):  
Diurnal Cycle ◽  
Stream Water ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Solute Concentration ◽  
High Flow ◽  
Rock Material ◽  
Diurnal Changes ◽  
Stream Discharge ◽  
Pressure Threshold

Abstract. In order to examine daily cycles in meltwater routing and storage in the Isunnuguata Sermia outlet of the Greenland Ice Sheet, variation in outlet stream discharge and in major element hydrochemistry were assessed over a six day period in July, 2013. Discharge was assessed from hourly photography of the outlet from multiple vantages, including where mid-stream naled ice provided a natural gauge. pH, electrical conductivity, suspended sediment, and alkalinity were measured in samples of stream water collected every three hours. Element and ion concentrations were subsequently measured in a laboratory setting. Photography and stream observations reveal that although river width and stage have only slight diurnal variation, there are large changes in discharge shown in the portion of the width characterized by standing waves and fast flow. Width of this active channel approximately doubles over a diurnal cycle. Together with changes in flow over the naled, these features allow an observationally based relative record of stream discharge in this unconstrained alluvial setting. Peaks in discharge were offset by 3–7 hours from peak melt of the interior ice surface. Concentration of dissolved solutes follows a sinusoidal diurnal cycle, except for large and variable increases in dissolved solutes during the stream’s waning flow. Diurnal changes in solute concentration average 31 % of the base value. Diurnal solute concentration minima and maxima lag peak and minimum stream discharge by 3–6 hours. This phase shift between discharge and solute concentration suggests that during high flow, water is either encountering more rock material or is stored in longer contact with rock material. We suggest that expansion of a distributed subglacial hydrologic network into seldom accessed regions during high flow could account for these phenomena, and for a spike of partial silicate reaction products during waning flow, which itself suggests a pressure threshold-triggered release of stored water.

scholarly journals Karst hydrogeology of Lamprechtsofen (Leoganger Steinberge, Salzburg)

2019 ◽  
Vol 112 (1) ◽  
pp. 50-61 ◽  
Author(s):  
Katharina Gröbner ◽  
Wolfgang Gadermayr ◽  
Giorgio Höfer-Öllinger ◽  
Harald Huemer ◽  
Christoph Spötl
Keyword(s):  
Electrical Conductivity ◽  
Water Temperature ◽  
Water Level ◽  
Stream Water ◽  
Tracer Tests ◽  
Karst Water ◽  
Stream Flows ◽  
Surface Precipitation ◽  
Mineralized Water ◽  
Show Cave

AbstractThe Leoganger Steinberge are a heavily karstified massif largely composed of Dachstein dolomite and limestone hosting the deepest through-trip cave in the world, Lamprechtsofen, whose frontal parts are developed as a show cave. Many parts of this 60 km-long and 1724 m-deep system are hydrologically active. 1.5 km behind the lower cave entrance Grüntopf stream and Kneippklamm stream merge to form the main cave stream. Another underground stream, Stainerhallen stream, flows through the eponymous hall of the show cave. Since 2007 water temperature, electrical conductivity and water level have been monitored in the Grüntopf and Kneippklamm stream. Water temperature and water level in the Stainerhallen and main cave stream have been measured since 2016.The long-term dataset (2013–2017) shows that the water temperature of the cave streams (Grüntopf stream: 3.7–5.2°C; Kneippklamm stream: 5.1–5.9°C) is largely invariant, but the electrical conductivity varies strongly (Grüntopf stream: 107–210 µS/cm; Kneippklamm stream: 131–248 µS/cm) in response to snowmelt and precipitation events. The event water of the Kneippklamm stream is characterized by a low electrical conductivity and is then followed by slightly warmer and higher mineralized water derived from the phreatic zone. This dual flow pattern also explains the asymmetrical changes of the water level during snowmelt: the fast event water flows directly through vadose pathways to the measurement site, whereas the hydraulic (phreatic) response is delayed. The Grüntopf stream reacts to precipitation and snowmelt events by changes in the karst-water table, which can be explained by a piston flow-model. The Kneippklamm stream reveals evidence of a lifter system.The altitude of the catchments was calculated using δ18O values of water samples from the underground streams and from surface precipitation. The Grüntopf stream shows the highest mean catchment (2280 m a.s.l.), which is in agreement with its daily fluctuations of the water level until August caused by long-lasting snowmelt. The Stainerhallen stream has the lowest catchment (average 1400 m a.s.l.). The catchments of the other two streams are at intermediate elevations (1770–1920 m a.s.l.). The integration of the catchment analyses and observations from tracer tests conducted in the 1970s showed that the latter reflected only one aspect of the karst water regime in this massif. During times of high recharge the water level rises, new flow paths are activated and the karst watershed shifts.

Sign in / Sign up

Export Citation Format

Share Document