Analysis of Weather Station Data and Impacts of SPAW based Designs of Dairy Lagoons in New Mexico

Abstract

Implementation of the SPAW model in design of agricultural waste ponds in New Mexico, generates larger sized ponds using a 20-30 year precipitation dataset, as compared to the traditional use of average monthly weather conditions using the 4% chance (25 year), 24-hour storm event. This analysis takes a critical look at the weather station data that is input into the SPAW model to determine the recurrence intervals of the daily and effects of summing 2-10 concurrent days of rainfall events based on the set of National Oceanic and Atmospheric Administration (NOAA) 2 day, 4 day, 7 day and 10 day storms. Thirty eight weather stations were analyzed in the study. The weather station data are analyzed using a user friendly Microsoft Excel spreadsheet that can be adapted to any state. The resultant recurrence intervals are compared with the 4% chance (25 year), 24-hour storm that are used in design of the agricultural waste ponds. The results of the analysis presented in this paper reveal that some storms in the 20-30 year precipitation dataset are at a higher recurrence interval than the standard 4% chance (25 year), 24-hour storm event, therefore creating larger pond sizes than the minimum sizing for the standard 4% chance (25 year), 24-hour storm event. If the input precipitation data contains a large rainfall event, SPAW will design a pond for that event. Usage of the SPAW model in designing agricultural waste ponds should be adapted to provide design results more consistent with historic design methodologies which have successfully contained waste streams.