One of our project managers in the Shasta asked me if I could determine if flow alteration was better after 2009 when they started a fall flow program. I think this will be a common request as people want to be able to track the results of their actions. I am envisioning a new dataframe with the following fields:
COMID
Gage_ID
Year
Functional Flow Metric Code
Observed Value
Water Year Type (specific to that COMID)
p10 (specific to that water year type)
p25(specific to that water year type)
p50(specific to that water year type)
p75(specific to that water year type)
p90(specific to that water year type)
Percentile group of observed (e.g., "less than P10", "between P75 and P90")
Altered status p25-p75 (e.g., 1 if less than p25 or greater than p75, 0 otherwise)
Altered status p10-p90 (e.g., 1 if less than p10 or greater than p90, 0 otherwise)
One of our project managers in the Shasta asked me if I could determine if flow alteration was better after 2009 when they started a fall flow program. I think this will be a common request as people want to be able to track the results of their actions. I am envisioning a new dataframe with the following fields: COMID Gage_ID Year Functional Flow Metric Code Observed Value Water Year Type (specific to that COMID) p10 (specific to that water year type) p25(specific to that water year type) p50(specific to that water year type) p75(specific to that water year type) p90(specific to that water year type) Percentile group of observed (e.g., "less than P10", "between P75 and P90") Altered status p25-p75 (e.g., 1 if less than p25 or greater than p75, 0 otherwise) Altered status p10-p90 (e.g., 1 if less than p10 or greater than p90, 0 otherwise)
One key piece of information for this dataframe will be the look up of water year type by COMID. Ted has already generated this table here: https://protect-us.mimecast.com/s/rHNlCDkZxRIQDXjjTW0hoy?domain=drive.google.com