Rainwater Harvesting Tool Readme Spreadsheet tool associated with "How much of demand can be met by rainwater harvesting?" https://doi.org/10.5518/972 cc_by_v4_0 Eric Laurentius Peterson 2022 Supporting on-line material for "Digging Deeper - HOW MUCH OF DEMAND CAN BE MET BY RAINWATER HARVESTING?" In WATER EFFICIENCY, CHAPTER TWELVE In ASHRAE Greenguide: Design, Construction, and Operation of Sustainable Buildings, 6th edition (2022). American Society of Heating, Refrigeration, and Air-conditioning Engineers (ASHRAE), Atlanta, Georgia. Please find two MS Excel files (SI and US IP versions of units): Example City Rainwater Harvesting SI.xlsx Example City Rainwater Harvesting IP.xlsx Eric Laurentius Peterson, PhD, Professional Engineer (Mechanical and Environmental), M-ASHRAE University of Leeds Visiting Research Fellow (Bioclimatic Design and Blue-Green Infrastructure) ORCID 0000-0002-7504-7669 email address e.peterson@leeds.ac.uk alternative contact dr.eric.peterson@gmail.com Abstract Simulations with different combinations of roof catchment area, storage capacity, and demand can be assessed at any location where daily rainfall data is available. For the present consider a building in example city in Georgia with an impervious roof area of 100 m² roof (1076 ft²) and a non-potable demand of 200 L/d (26 gal/d). After establishing the water demand, then any supply-storage-demand problem can be iteratively experimented with a spreadsheet if local daily rainfall data is available to cover many decades. An example is provided for a simple rainwater harvesting example notionally in Atlanta, Georgia (33.64° N latitude, 84.43° W longitude), which is referred to as “Example City, GA, USA” in the 2021 ASHRAE Handbook – Fundamentals Chapter 14, with bogus ID WMO777777/WBAN99999 identifier to indicate it is unchanged from the 2017 Handbook Atlanta Hartsfield-Jackson with actual ID WMO 722190/WBAN13874. Within the U. S., the best source of rainfall data is found in National Oceanic and Atmospheric Administration’s (NOAA) Daily Observations Data Map (https://gis.ncdc.noaa.gov/maps/ncei/cdo/daily/). There are several different datasets available, but for the current discussion we are using the Global Historical Climatology Network to illustrate one possible spreadsheet form you could construct. So in this case select GHCN and enter the coordinates so you can zoom out to select station “GHCND:USW00013874”. Then select “custom GHCN Daily CSV” with the earliest possible date range (1930-01-01 through yesterday) and select only precipitation “PRCP”. Open your GHCN order with precipitation data (“PRCP”) in a spreadsheet and there will be 4 columns wide and thousands of rows long, with the first four rows shown above to explain that if there were for example 100,000 rows below the starting date it would be a record of 273 years of daily rainfall records. Beware that start dates prior to 01/01/1900 will not be recognized in Excel spreadsheets as a number readable in date formats that specify the day, month and year of record. The second column will be used to provide input and output parameters in your analysis of the date and precipitation records in the 3rd and 4th columns, as well as running accounts of a rainwater harvesting system to occupy the 5th, 6th , and 7th columns titled “Cache”, “Makeup” and “Overflow”.