This post shows the conversion of IR-DAY data in HEC-DSSVue to daily data for a variety of original data.
Example 1: Converting from one value per day at noon (instantaneous value)
In the figure below, the original data (second to last column) is given as one value each day at noon. The format of this value is given as INST-VAL (instantaneous value).
To compute the daily average value (which will be assigned to 24:00 hours of that day, a linear interpolation between known values is done. The values for the day are then averaged. For example, the computation for 03Jan2019 would be done as follows:
Value at 03Jan2019 at 00:00 hours is (45 + 58) / 2 = 51.5. This would mean that the average for the first 12 hours of 03Jan2019 is (51.5 + 58) / 2 = 54.75.
Value at 03Jan2019 at 24:00 hours is (58 + 33) / 2 = 45.5. This would mean that the average for the second 12 hours of 03Jan2019 is (58 + 45.5) / 2 = 51.75.
The average for the entire day would then be computed as (54.75 + 51.75) / 2 = 53.25.
The conversion is performed by performing an average over the period for 1DAY under the Math Functions options in the Tools menu. This is the function used for all of the examples in this post.
Example 2: Converting from one value per day at noon (period average value)
In the figure below, the original data (second to last column) is given as one value each day at noon. The format of this value is given as PER-AVG (period average).
When using period average values, the value is applied to the backward-looking period from the last known value. In the table above a value of 45.0 would then be applied from 01Jan2019 at 12:00 until 02Jan2019 at 12:00.
To compute the daily average value, for 02Jan2019, the following computation is done.
At 02Jan2019 at 00:00, the value is 45.0. This value remains in effect for the first 12 hours of 02Jan2019. It then changes to 58.0 for the final 12 hours of the day. To get the daily average, the average of 45.0 and 58.0 is computed, giving a daily average of 51.5.
Example 3: Converting from one value per day at noon (instantaneous value, missing a day)
To test what happens if a day is missing, the value for 03Jan2019 at 12:00 was removed from the data set. In the table below, it can be seen that no value is given for 03Jan2019 at 24:00. If an estimate is needed, a linear interpolation could be done on the daily values after the 1DAY dataset is created.
It should also be noted that the value for 02Jan2019 at 24:00 is computed as follows:
02Jan2019 at 00:00 = 47.5. The average of the instantaneous values given in this example is as follows:
(47.5 + 45) / 2 = 46.25
For 04Jan2019, the daily average is determined by using the second half of the day since that is what is available. The instantaneous value at 04Jan2019 at 24:00 is 50.0.
The average of the instantaneous values for 04Jan2019 is as follows:
(33.0 + 50.0) / 2 = 41.5
Example 4: Converting from one value per day at noon (period average value, missing a day)
The table below shows the result for a missing value if period average values are used. In the table below, the value for 03Jan2019 at 12:00 is missing.
For 02Jan2019, it appears that HEC-DSSVue is using the only value that it has for 02Jan2019 of 45.0. This is the value that would be applied to the first half of 02Jan2019.
For 03Jan2019, it appears that HEC-DSSVue is using the value for the period ending at 04Jan2019 at 12:00.
It should be noted that if the intent of the data was to apply the value of 33.0 from the time period of 02Jan2019 at 12:00 to 04Jan2019 at 12:00, the period average values would appear to be incorrect for 02Jan2019. I would have expected that value to be 39.0 (45.0 applied for the first half of the day and 33.0 applied for the second half of the day).
Example 1: Converting from one value per day at noon (instantaneous value)
In the figure below, the original data (second to last column) is given as one value each day at noon. The format of this value is given as INST-VAL (instantaneous value).
To compute the daily average value (which will be assigned to 24:00 hours of that day, a linear interpolation between known values is done. The values for the day are then averaged. For example, the computation for 03Jan2019 would be done as follows:
Value at 03Jan2019 at 00:00 hours is (45 + 58) / 2 = 51.5. This would mean that the average for the first 12 hours of 03Jan2019 is (51.5 + 58) / 2 = 54.75.
Value at 03Jan2019 at 24:00 hours is (58 + 33) / 2 = 45.5. This would mean that the average for the second 12 hours of 03Jan2019 is (58 + 45.5) / 2 = 51.75.
The average for the entire day would then be computed as (54.75 + 51.75) / 2 = 53.25.
The conversion is performed by performing an average over the period for 1DAY under the Math Functions options in the Tools menu. This is the function used for all of the examples in this post.
Example 2: Converting from one value per day at noon (period average value)
In the figure below, the original data (second to last column) is given as one value each day at noon. The format of this value is given as PER-AVG (period average).
When using period average values, the value is applied to the backward-looking period from the last known value. In the table above a value of 45.0 would then be applied from 01Jan2019 at 12:00 until 02Jan2019 at 12:00.
To compute the daily average value, for 02Jan2019, the following computation is done.
At 02Jan2019 at 00:00, the value is 45.0. This value remains in effect for the first 12 hours of 02Jan2019. It then changes to 58.0 for the final 12 hours of the day. To get the daily average, the average of 45.0 and 58.0 is computed, giving a daily average of 51.5.
Example 3: Converting from one value per day at noon (instantaneous value, missing a day)
To test what happens if a day is missing, the value for 03Jan2019 at 12:00 was removed from the data set. In the table below, it can be seen that no value is given for 03Jan2019 at 24:00. If an estimate is needed, a linear interpolation could be done on the daily values after the 1DAY dataset is created.
It should also be noted that the value for 02Jan2019 at 24:00 is computed as follows:
02Jan2019 at 00:00 = 47.5. The average of the instantaneous values given in this example is as follows:
(47.5 + 45) / 2 = 46.25
For 04Jan2019, the daily average is determined by using the second half of the day since that is what is available. The instantaneous value at 04Jan2019 at 24:00 is 50.0.
The average of the instantaneous values for 04Jan2019 is as follows:
(33.0 + 50.0) / 2 = 41.5
Example 4: Converting from one value per day at noon (period average value, missing a day)
The table below shows the result for a missing value if period average values are used. In the table below, the value for 03Jan2019 at 12:00 is missing.
For 02Jan2019, it appears that HEC-DSSVue is using the only value that it has for 02Jan2019 of 45.0. This is the value that would be applied to the first half of 02Jan2019.
For 03Jan2019, it appears that HEC-DSSVue is using the value for the period ending at 04Jan2019 at 12:00.
It should be noted that if the intent of the data was to apply the value of 33.0 from the time period of 02Jan2019 at 12:00 to 04Jan2019 at 12:00, the period average values would appear to be incorrect for 02Jan2019. I would have expected that value to be 39.0 (45.0 applied for the first half of the day and 33.0 applied for the second half of the day).
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