Lag time and of concentration relationship quiz

BBC Bitesize - Higher Geography - Interpretation of hydrographs - Revision 1

The relation of time of concentration (Tc) and lag (L). 15–4 to the dimensionless unit hydrograph. Figure 15–4. Velocity versus slope for shallow. At such time, existing PK and efficacy data may be used to guide the experimental design, PK/PD analysis seeks to quantify drug concentration- pharmacological response-time relationships. In order to obtain a reliable drug concentration-effect relationship and Jan; 26(1); quiz Runoff is assumed to reach a peak at the time of concentration. The method of calculating the time of concentration for my model is the SCS lag equation.

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This article has been cited by other articles in PMC. Abstract Characterizing the relationship between the pharmacokinetics PK, concentration vs. Specific examples and case studies are highlighted to help demonstrate key points for consideration. In some cases pharmacokinetics are not determined in the same animals used in the PD study.

Interpretation of hydrographs

Rather, the PK and PD datasets might be generated completely independent of each other, not only in different laboratories but also different timeframes. In the latter scenario, generation and reporting of data can happen in isolation, and project teams are then faced with downstream integration and evaluation of results that lack an integrated analysis defining a concentration and effect relationship.

The resulting report thus reflects integration of all relevant data and addresses the hypothesis or question asked at the outset of the study. The report will capture any assumptions made in the analysis and suggest what subsequent studies the results enable, and reflects shared ownership and responsibility of both the DMPK and pharmacology experts. The major objective of early drug development is to select promising compounds and to identify potentially safe and effective doses and dosing regimens.

Rational study design is based on the assumption of a causal relationship between exposure to a medication and its therapeutic activity. Such relationships are generally complex.

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As data becomes available, initial models can be refined through an iterative process. Therefore I consider a length of approximately feet to be more representative of the basin. Design Storm Design storms are precipitation patterns used for hydrologic modeling.

Design storms are based on historical precipitation data for the area of interest.

WMS:Lag Time and Time of Concentration

The design storm used for the input for the model is the alternating block hyetograph. The incremental depth is calculated using discrete time intervals. A design storm of any frequency or duration can be calculated and converted to an alternating block hyetograph.

See the sample spreadsheet below. The hyetograph can be shown graphically as follows: The illustration below is a typical HEC1 input file used in my study. The following parameters were explored: The tables were inserted into Excel where they were rearranged into a useful form for analysis. Design Storms and HEC1 Keeping the Curve Number and the time of concentration constant, 5 different design storms were run in the model.

The following graph illustrates the different resulting outflows for each design storm. The year storm had the highest peak and volume the area under the curve and the 5 year storm had the lowest.

They each had the same duration time. The following hydrographs resulted.

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The higher curve numbers result in a larger amount of runoff and therefore a higher peak flow and flow volume. The curve number of 93 would be representative of the Shoal Creek watershed because of it being an urban watershed with substantial development.

The curve number of 77 would be representative of a undeveloped watershed with good soil infiltration and slower overland flow velocity. Note how the peak of CN77 is much lower and the curve is flattened out. A smaller lag time smaller time of concentration results in a higher peak flow over a smaller time interval. The peak flow occurs very close the time of peak rainfall where the curve is almost vertical. As the time of concentration is decreased the peak flow and the peak rainfall intensity get closer together.

The graph below shows the outflow hydrograph and the accumulated rain total for the period. Note the rainfall that occurred the day before the flood event. It was enough rain to saturate the soil and cause a higher proportion of the rainfall that occurred the next day to runoff.

In terms of the HEC1 model this situation would cause the Curve Number to be higher due to antecedent rain. One consequence of a higher curve number is that the time of concentration is lower as can be seen in the equation for time of concentration above.

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The graph below is the results of my first calculations of the time of concentration for the model using two different values for the CN. The two model hydrographs are plotted with the actual Shoal Creek hydrograph.