How Much Rainwater Can You/Should You Store

Storing rainwater of course has cost associated with it.

You’ll want to store enough to make sense, but not too much.  There’s another issue too – in some drier areas, the amount of water you need for the dry months exceeds the amount of water you can collect and store in the wet months, so you need to calculate both the amount of water to store and then to confirm you’ll actually be able to collect that much during the wetter months.

Sadly, the final calculation is not as exact as it might seem.  Sure, you’ll have surrounded yourself with vast masses of rainfall data as part of your calculating, but as you’ll see from the worked example below, at the end of the process, you end up making some subjective guesses.  Feel free to ask us if you have questions or need help.

Getting the Raw Data You Need to Do Your Calculation

The key issue now is understanding the rainfall pattern you’ll experience at your location.  This involves both some science and some art.

The science is simply retrieving historical rainfall data.  The art lies in translating historic rainfall data, which varies from year to year, into the acceptably likely/moderately worst case scenarios that you want to build into your planning, and in taking rainfall data from weather stations that might not be close to your location and equating their rainfall data to what will actually happen at your location.

It is an easy thing to go to various different websites and get average monthly rainfall data for a range of different locations around the country.  We have some links in this article, just a bit further down.

Equating Rainfall at Weather Stations to Rainfall at Your Location

So how to equate this rainfall data with what happens where you are.  Maybe you are 50 miles away from where the nearest data is collected.  That could be okay, but maybe you’re in the rain shadow on the other side of a mountain range from where the data is obtained.  Ooops.  That’s not going to work, is it!

So find the best data you can, and if you can’t find any good data, maybe consider averaging the data from several reasonably close locations.  It is better than nothing.  In particular, use the National Weather Service rainfall maps (link below) to get a sense of the rainfall patterns and distributions for where you live compared to where the sampling stations are.

You can also ask local residents for reality checks about what they might remember or have recorded for past years.  Perhaps they can at least answer some simple questions like ‘how often is there no rain at all in July’ and ‘what is the longest gap between decent rains’ and ‘which month do you need to water the crops the most’.

If you want to get really obsessive, you can even go to the archives of the local newspaper and track daily weather from back issues of the paper.

How Much Information is Enough/Too Much

This last suggestion (going through back issues of the local paper) points out a happy fact.  Much of this information is ‘scientific guesswork’ – sure, the historical rain data is a matter of fact, but applying what happened last year, last decade, last century, to predict what will happen next week or month or year – there comes the guesswork.

So there’s only so much data you need.  There’s little point in spending lots of time and money to go from a 75% understanding of past rainfall to a 90% understanding, if you then go and make a guess with a huge +/- 100% factor in it anyway.

Averages, Maximums, Minimums

Now for the second part of the puzzle.  You’ve probably managed to find a chart of average monthly rainfall measurements, and you might have adjusted this a bit for any variations between the data you’ve found and the reality of your exact location.

But – here’s the problem.  To start off with an example, the average US family formerly used to consist of two adults and 2.5 children.  But have you ever seen a half child?  You can visit as many houses as you like, and while you’ll find many with two and many with three children, you’ll never find a house with half a child.

Another way of looking at an average is to say that an average is the number whereby half the time the reality is higher than this number, and the other half the time, the number is lower than this number.

What that means with rainfall numbers is that the monthly average rainfall will be, for half the time, higher than the actual rainfall.  Sometimes the actual rainfall might be a little less than the monthly average, and sometimes it might be a lot less.  This doesn’t matter to the statistician who has neatly calculated his 100 yr average number, but for you, it could mean the difference between having water and not having water – yes, the difference between life and death.

What you need to do is to establish a number a bit like flood plain numbers (you know, the 50 year and 100 year flood plain zones).  Do you want to base your needs on an average monthly rainfall figure that is half the time more positive than the actual rainfall will be in reality?  We suggest not.

But now comes the guesswork.  Do you want to use a monthly rainfall figure in your planning that is too high one year in three?  Or one year in five?  One year in ten?  How about one year in 50 or 100?

There is a cost associated with this, of course.  The more you want to plan for drier than normal years, the larger you’ll need to make your water storage capacity to carry you over from the good/wet months to the bad/dry months, and so the greater your cost will be.  Plus, sooner or later, you’ll end up with a number so huge that you’ll never be able to fill it based on the rainfall from the preceding wetter months (which circles us back, in such cases, to the need for a second water source).

You must look at a minimum of 10 years of data for each month you are studying.  If there is little variation from one year to the next, then you don’t have to build as big a safety margin into your figuring.  But if the numbers are all over the place, clearly you’re going to have to assume something close to the worst for planning your water needs.

But within what looks like a consistent set of data for perhaps 10 years can be other hidden longer term cycles – some weather cycles have a 60 or longer year period to go from minimum to maximum and back to minimum again.  Maybe the ten years you are looking at are the ten years at the best part of the cycle, which is now trending towards the worst part, which could show extremely different numbers.

At the very least, get an extended data series on an annual basis so you can see what overall variation there is, and if you’re looking at marginal weather and rainfall, you will need to be more careful about the data you are using.

Daily or Monthly or What Data

The longer the time period, the less variation in the numbers you’ll get.  If you look at annual rainfall totals, these will vary much less from year to year than if you look at each month’s data.  Whereas the chances are that your region’s annual rainfall is never zero, the chances may be that some months in some years, there’ll be an inch or more of rain, but in some months of other years, there might be not the slightest sprinkle for the entire 30 days.

The time period you need to drill down to depends to an extent on the size of the storage capacity you’ll be building.  The smaller the capacity, the more accurately you need to know when water will come in to replace the water going out.

Generally the monthly data is sufficient for most purposes.

However, daily data is useful for understanding how the rain falls during a month, so as to know whether to adjust the total rainfall to reflect light sprinkles that have little collectable net rain or not (see our section on Real World Imperfections in our earlier article on rainwater collection).

A Worked Example

Let’s have a look at some real world data for Seattle – not because we recommend that as a bug out location, of course, but just because there is readily obtainable information for the area.

First, let’s state our assumptions that we are using, above.  To be consistent with our earlier article on How Much Rainwater Can You Collect From Your Roof, let’s keep the same figure – 50 gallons of water a day or 1500 gallons a month for our basic household needs.  We also said that each inch of rain on our hypothetical roof will give us up to 763 gallons of collectible water.  So, by happy coincidence, it seems that as long as we are getting 2″ of water a month, we’re in good shape.

Can we be sure of getting at least 2″ of rain every month?  The first thing we do is look at the monthly average rainfall figures.  Let’s have a look at them on this page (other pages will have slightly different figures) :

 

Month	Rainfall
January	5.5
February	4.2
March	3.7
April	2.5
May	1.7
June	1.5
July	0.8
August	1.1
September	1.9
October	3.5
November	5.9
December	5.9
Annual Total	38.1

 

Which brings us to the first important point.  If we looked just at the total rainfall for the year, we’d see 38.1″.  We need 24″, so upon seeing 38.1″, we might mistakenly think ‘Great, we have no problem’ and not look any further.

But look at the individual months.  You’ll see that the five month block from May through September all show less than 2″ of rain per month.  And if we look back at April, its 2.5″ figure looks a bit anxiety-causing too – remember this average is the number which will be too high half the time.  So with a need to have 2″ of rain in April, and no opportunity to top up with extra rain in May, we need to get an understanding for the possible variation of rain in April too.

Let’s now look carefully at the six months we’re worried about (April through September) and not only look at their monthly averages, but at the actual real rainfall that was measured in recent years.

We’ll take the information from this site.  The next table took a lot of time to type in, so please be appropriately respectful of the information presented to you!  And, just to show another thing, we are using their averages rather than those in the preceding table – quite a big difference in some cases, too.  (It seems this service changes their averages on a shorter sample of years than some of the other time bases).

We immediately noticed that regularly, the September rainfall was less than the 2″ we needed, so for those years, we looked at the October rainfall too, and with a shaky 2.17″ in 2008 for October, we looked at that year’s November.  The same thing happened in 2006, although massive rains in November helped the region catch up on its very dry summer.  Although the averages above suggested there’d be no problem in October, for one of the ten years in this sample there was.  If we don’t want to risk running out of water in October one year in ten, we need to look at that month too.

There’s more, with another deceptive average.  We also noticed that April couldn’t guarantee us 2″ of rain in three of the ten years either, so we added March data for years where that was necessary.  Fortunately, March rain was always above the 2″ we needed, so there was no need to look further back.

Month	Avg	2011	2010	2009	2008	2007	2006	2005	2004	2003	2002
March	3.75				3.65	4.42	2.18		2.13	6.49
April	2.59	4.47	3.49	3.36	1.90	0.69	2.73	3.68	0.65	2.74	4.29
May	1.78	3.20	2.83	3.61	0.89	1.46	1.65	3.32	2.53	1.16	1.11
June	1.49	1.42	2.49	0.18	1.64	1.34	1.67	1.63	0.81	0.51	1.73
July	0.79	0.71	0.31	0.06	0.48	1.44	0.06	1.03	0.16	0.06	0.64
August	0.88	0.13	0.64	1.16	2.87	0.73	0.02	0.29	3.00	0.32	0.04
September	1.50	1.29	4.80	1.75	0.78	3.16	1.43	0.95	2.80	0.89	0.42
October	3.48	3.45		5.54	2.17		1.55	3.01		8.95	0.66
November	6.57				6.52		15.63				3.71

 

Okay, hopefully your eyes aren’t glazing over from the over 80 data points in the above table.  Let’s first quickly skim through the data, month by month, and note the huge difference between wet years and dry years.  August went from 0.02″ all the way up to 3.00″.  October in 2002 had a mere 0.66″ of rain, but the next year, it had 8.95″.

Clearly the average monthly figures obscure massive swings from one year to the next.

Let’s now look at both the worst and the second worst rainfall figures for each month.  If we want to allow for a ‘one time in ten’ being wrong, we’d take the worst figure.  If we were prepared to consider a ‘one time in five years’ then we’d take the second worst figure.

Month	Worst	Second
March	2.13	n/a
April	0.65	0.69
May	0.89	1.11
June	0.18	0.51
July	0.06	0.06
August	0.02	0.04
September	0.42	0.78
October	0.66	1.55
November	3.71	n/a

 

So we are now starting to make sort of progress, with an easy conclusion to draw and a difficult piece of further analysis.

The easy conclusion is that we can say we can reliably expect, on 1 April each year, to have full tanks due to having had more rain than we needed in March (and February and before).

We can also say that we can reliably expect, more or less on 1 November, that the rate of rainfall will start to increase above our offtake level.  We’d probably want to have a week or so remaining supply in case the November rains came late, but we know, for sure, that by the end of November, we’ll have received more rain than we consumed, and will end up the month with more water in our tanks than we started with.

Now for the really important part – the seven months of April through October.

If we wanted to be super conservative, we could simply take the lowest reading for each of these seven months and use that as the figure to work from.

But here’s an interesting thought.  Look at any of these months – let’s say August, for example.  In our table of lowest values, the lowest rainfall for August is 0.02″ (in 2006).  Now look at September.  Our lowest rainfall for September is 0.42″, in 2002.  Add these together, and you get 0.44″ for the two months.

But – and here’s the complicating factor.  In August 2006, we had the 0.02″, but in September 2006, we then had 1.43″ of rain – add these together and you get 1.45″ over two months.

If we look at the lowest September figure of 0.42″ in 2002, if we add the 2002 August figure of 0.04″ to that, we end up with 0.46″ – not very much more than the two lows, but still more.

So here’s the question.  We have one chance in ten that any given month’s figure is the lowest.  But what is the chance of the next month after that also being the lowest?  Does the weather in one month influence the weather the next month?  Sure, people talk about ‘dry summers’ or whatever, but is that a perception or a reality?

Let’s create another table, for the three most critical months (June, July, August).  We’ll compare the total of the lowest numbers from any year with the totals for each year.

Lowest	Second	2011	2010	2009	2008	2007	2006	2005	2004	2003	2002
0.26	0.61	2.26	3.44	1.40	4.99	3.51	1.75	2.95	3.97	0.89	2.41

 

So now we know that if we cherry pick the lowest months from each year, we can end up with the lowest total of 0.26″, and if we go to the second lowest, we are at 0.61″.  But if we insist that each month be linked to the month before and after, the lowest number now is 0.89″ and the next lowest number is 1.49″.

Confused yet?  So, what is your feeling – how much rain should we project to be sure of receiving in the three months of June, July and August?  We’re not going to answer that ourselves, because clearly there is no single right answer.

When you’ve answered that question to your own satisfaction, it is time for the key question :  How much rain do you think we’ll get for the entire period from 1 April through to sometime in early/mid November?

Clearly, there’s no exact or correct answer.  Depending on the level of risk you are prepared to accept for being wrong depends on the number you’ll choose.  If you guess wrong, then during the course of the dry months, you’ll realize the rain isn’t coming as it should, and you’ll see your water levels dropping below the levels you projected them to be, so you can start to adjust your water usage habits some.

That is relatively practical when you started off with a fair/generous projection of water usage to start with, and of course much harder if you were rather optimistic/aggressive about your water savings, giving you little room to cut back.

Further Interpretation of the Data

We’re going to look across the entire dry spell, from 1 April through to some time in November (let’s allow 500 gallons for November), and use our second worst numbers for each month.

But then we’re going to look at the individual months and see how the rain fell in those months and start adjusting for the less efficient collection of light sprinkles compared to the more efficient collection of downpours.

For example, in September’s 0.78″ result for 2008, we look at the relevant data and analyze the rainfall, day by day.

The first day with rain was the 20th, when temperatures ranged from 54 – 58, and the wind was 3.7 mph, and 0.54″ of rain fell.  We’ll say that 0.51″ of that was collected – after a long dry spell, albeit a damp day or two prior, there was probably a lot of moisture absorption and some evaporation off the roof going on.

On the next day another 0.02″ of rain fell, but the temperatures were warmer and the winds stronger, so we’re going to say none of that was collected.

On the 22nd, 0.01″ of rain fell, and that’s the minimum needed just to wet the roof, so we’ll ignore that.

On the 24th, we had 0.12″ of rain, and we’ll count 0.10″ as collectible.

On the 25th, temperatures were warm, the wind was strong, and 0.09″ of rain fell.  We’re going to say that only 0.045″ of that was collectible.

So add these adjusted figures together and round down, and instead of 0.78″, we have a net collection of 0.65″ of usable rain.

Let’s say after doing similar calculations for the other months, we end up with 3.8″ of rain in total that we can be sure will actually make it into our tanks.  This provides us with 2900 gallons of water.  But we are going to use 7 months of consumption at 1500 gallons a month, and we want 500 gallons left over on 1 November – a total requirement of 11,000 gallons.

So after adjusting for the rain that will come in , we need to start on 1 April with 8,100 gallons of water stored.  Now let’s adjust for evaporation – 0.25% a day, perhaps.  This means, for the seven month, 210 day period, we’ll lose 52.5% of our water.  We need to increase our storage from 8100 gallons up to say 12,500 gallons.

Can We Get the Rain We Need in the Wet Months to Fill Our Tanks

12,500 gallons is a lot of water.  It represents 16.4″ of rainfall.  Can we be sure of getting 16.4″ of rain during the wet months of November through March?

Yes, we probably can, even in a worst case scenario, but only just.  We’d simply repeat the analysis that we’ve already done for the dry season, and this time do it for the wet season to get a feeling for likely worst case scenarios.

In this case, our tanks will take the rest of the year to fill, and sometimes might not fill until early in the new year, giving only a few months of happily overflowing tanks and water-richness, before entering into another extended period of anxiously looking up at the sky each day.

The point to be aware of here, slightly obscured from using rainy Seattle’s data, is that the amount of rain we can collect in rainy months is sometimes insufficient for the drier months.  There’s no point in making the storage capacity any larger than the total amount of water likely to be collected off the roof.

Summary

So, we have learned both a general and a specific lesson from this example.  The specific lesson is how to work through a calculation for the water you’ll need based on your area’s rainfall patterns and your family’s water consumption.

The general lesson hasn’t yet been stated until now, but it needs to be considered.  Creating a water storage system capable of storing 12,500 gallons of water requires a sizeable amount of tankerage, and probably they will be at ground level so you’ll then need a water pump to transfer the water up to a holding tank in the ceiling for regular usage, so the water isn’t energy free.

Even a teensy-tiny well (2 gallons/hour capacity – barely a trickle) and perhaps a single 1500 gallon buffer/holding tank would give you the same results as your enormous 12,500 gallon rainwater collection system, and at massively lower cost.

These numbers were based on the climate in Seattle, an area renowned for its rain (albeit, as we’ve now seen in detail, somewhat unfairly).  Imagine how much worse it would be in a drier climate.  If we say 8 months with no water, that would call for 12,000 gallons, plus 500 for early November, and then if we say a higher 0.3% evaporation rate over 240 days, and you’d need to start off the dry season with 21,500 gallons of water stored.

There’s probably no way you could collect that much water during the shorter rainy season in this hypothetical alternate location, so like it or not, you’ll need a secondary water source right from the get-go in such cases.

One last point, if we may.  If you’re in a water scarce scenario, all other buildings on your property should also collect the water off their roofs too.  If you have a tool shed/workshop, an animal shed/barn, or whatever else, these could potentially double or more the rain you can collect.  And here’s the strange outcome of that.  If you are collecting twice as much rain, you don’t need as much storage.