how dry am i?

This post may be mainly for the math nerds among you, but I think it could be interesting to any gardeners living in drought-prone parts of the world.

In my last post I mentioned that I’d used instructions in Olivier Filippi’s The Dry Gardening Handbook to figure out the drought stress index, or hydric deficit, for where I live in San Diego.

USDA zones are useful for dealing with minimum temperatures. For gardeners in the western U.S., Sunset zones provide more finesse, combining temperature with other climate conditions. The the drought stress numbers, however, are useful if you want to concentrate on understanding how many months a plant might be subjected to severe drying conditions due to lack of rainfall.

Filippi writes in his book that “everyone’s drought is different,” so be sure to consider factors other than this single number, things like total rainfall, humidity, the sun exposure a plant might get or the amount of wind your site experiences. The technique presented in The Dry Gardening Handbook derives from work of plant geographer Henri Gaussen.

Figuring out hydric deficit is pretty straightforward but will take a few minutes of your time. Either use a spreadsheet program like Excel or a sheet of paper. First, go to a site like World Climate where you can find your area’s monthly total rainfall and monthly average temperatures. On the spreadsheet or paper set up a column with the months of the year, January to December. Next fill in a column with the monthly average rainfall in millimeters, and another column with the average monthly temperature in degrees Celsius.

Now you have two options: Follow the instructions in the book, which isn’t that hard but requires making a graph with three different axes. Or use my simplified technique, which requires some calculations but no graphing. I’ll send you to the book for the somewhat more precise method, but here’s my easier method: In a fourth column, divide the rainfall number by the temperature and multiply by 2. That’s where the math comes in to play.

Here’s my result for San Diego:

Month Rainfall (mm) Temperature (Celsius) 2 x (Rainfall/Temperature)
Jan 55.6 14.1 7.890
Feb 41.3 14.7 5.62
Mar 49.9 15.3 6.52
Apr 19.8 16.6 2.39
May 4.8 17.8 0.54
Jun 1.9 19.3 0.2
Jul 0.5 21.6 0.05
Aug 2.1 22.5 0.19
Sep 4.7 21.8 0.43
Oct 8.6 19.8 0.87
Nov 29.5 16.6 3.56
Dec 35.4 14.1 3.62

Count up the numbers in the fourth column that are less than 1, and that’s your approximate hydric deficit number. The higher the hydric deficit number, the more severe your drying conditions. For the San Diego Airport, the number is 6. (If you have a month where the average temperature is below freezing, for my oversimplified method just throw out that month and consider that there’s minimal hydric deficit.)

Now what do you with the number? For one thing, you can use it to compare you growing conditions with the drought resistance code for a plant in Filippi’s book. For example, the matilija (“tree”) poppy (Romneya coulteri) has a drought tolerance rating of 6–perfect for an unwatered garden in San Diego. By contrast, Ceanothus ‘Ray Hartman’ has a code of 4, and Hidcote Blue lavender (Lavandula angustifolia ‘Hidcote Blue’) has a code of 3. These other plants would probably survive without supplemental water, but to look their best the ceanothus might benefit from a couple months of occasional supplemental watering, and the lander maybe three. You can also use the number to compare the drying forces where you live other regions around you, or apply the number to better understand your climate in relation to that of a plant’s origin.

For fun, I added four other sites in San Diego County. You can see how the county offers a huge number of growing conditions, from dry coastal conditions, mountain meadows, backcountry chaparral, and full-on desert.

City Hydric deficit
San Diego Airport 6
La Mesa 5-6
Cuyamaca 1

Campo 3
Borrego Springs 7


And then a few other cities in California. You can see a general moistening the farther north you go, and a general drying as you head east towards the deserts.

City Hydric deficit
Los Angeles 6
San Bernardino 4-5
Victorville 6
Santa Barbara 5
Monterrey 4
San Jose 4-5
Santa Cruz 3
San Francisco 4

Richmond 4

Sacramento 4-5
Fresno 5
Yosemite National Park 2
Eureka 1 2
Redding 2


I’d never played with mapping in Google Maps, but thought this might be a fun first little project. I took the numbers above and applied them to a map. The results are pretty impressive for something that’s not hard to do. So far the blips are in California only, but I might work on the map some more to include other locations. Take a look…


View Hydric Deficit Map in a larger map

10 thoughts on “how dry am i?”

  1. OMG, James! This post is too much! You are a gardener and a photographer – part poet, part mathematician! Too brilliant! I’m glad you included Santa Barbara, because I could NEVER have figured this out!

    I love reading your blog – you are such a complex guy. It is a pleasure.

  2. James, as always, you have one of the most informative blogs around. I ordered the book today so your post is timely.

    If you’re only planting a few things, I can see why someone wouldn’t want to bother, but if you’re planting a whole garden at once, or if you’re the kind of person who adds all the time, this would be great.

  3. Oh, blush, thanks everyone!

    Catzgarden, I guess my blog is what happens when I open up my head and commit some of what I find to print. I’m glad you’ve found some of it interesting!

    Susan, I’d be interested in hearing what you think of the book. This spring has seen me knee deep in native plants, so it was refreshing to pull back a bit and see the flora of other places.

    Tina, drought’s a tough one, isn’t it? Especially for our green friends who can’t walk over to a spot that would make them happier. Hopefully you year isn’t too painfully dry.

  4. This is so interesting, I’m going to try it myself when I have more brains. I have informally calculated for hydric deficit every time I planted – it might be nice actually to have a system for it.

  5. Really interesting, especially because we work in so many parts of the Bay Area. Their drought ratings for plants seems accurate and a really useful resource for those plants we haven’t grown much. Our house and San Francisco are 4’s, which sounds about right; some lavender cultivars need a bit of summer water, ceanothus, while matillija poppies never require an extra drop if you plant in the fall. I’ll calculate a few towns on the other side of the hills from us and at least some of them will be 4-5 like San Jose. We’ll use find their drought ratings pretty useful.

  6. Pomona, I’m a person who likes the certainties that live in numbers, and I find this system useful. But of course there’s no substitute for observing the plants themselves.

    Ryan, I’ll see what East Bay climate numbers I can dig up to add to the map.

  7. Just finished reading about hydric deficits in Olivier Filippe’s book myself, and googling ‘hydric deficit’ I found your blog. I like the way you did this with the math, and it looks fairly accurate to me, with the exception of Redding and Eureka. There is no way that both of these towns could have the same hydric deficit. Redding regularly tops 90’s for months at a time, with clear days, while Eureka is a cool 55 with coastal fog. I would have to check those numbers again. Thanks for the work though.

    1. Thanks for your comment, David. I re-ran the numbers for Redding and continued to come up with a hydric deficit of 2. The city has only 2 months, July and August, where the average rainfall is less than 1/2 an inch. I remember that result not being intuitive when I first saw it. This is definitely a limitation with this technique, in that it focuses on rainfall at the expense of other factors like fog and humidity, and Filippi does acknowledge this with his “everyone’s droughts are different” statement. I wouldn’t expect a coastal Eureka plant to thrive in Redding!

      1. David, on further inspiration I re-did Eureka’s numbers. The number varies depending in which Eureka stats you use, but it comes out closer to 1 than 2. I’ve changed my table above accordingly. Thanks for pointing this out.

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