PRMS Potential Evapotranspiration Module

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Detailed Description

Presents the USGS Precipitation Runoff Modeling System (PRMS) Potential Evapotranspiration simulation modules.


Date Taken:

Length: 00:08:17

Location Taken: Lakewood, CO, US


Steve Markstrom: Welcome to the next video
on PRMS training.

We’re going to talk about the potential
ET process.

You can see quite a few different options.

Different module options.

You can set these in the control file just
like the other ones.

Climate by HRU is also an option here, but
I don’t go into that.

So I’m just going to go through these.

Talk about the equations and most interesting
on these is what kind of input data is required.

In this case, we’re looking at the Jensen-Haise
module, potet_jh.

And you can see the equation here.

If I click these yellow things are highlighting
parameters that you have to set for each HRU.

These are the variables, these green variables
are coming from the shortwave solar radiation

distribution module, either DD or CC solrad.

So that’s coming from somewhere else.

And these red ones, these are inputs.

So you’ve got to specify temperature.

This module is a temperature based estimate
of PET.

Going on to Hamon.

This is the second option you can choose,
the second module.

There’s one parameter, the Hamon coefficient.

Soltab_sunhours, that actually comes from
the solar radiation module.

In this case, we’re using average temperature
three times in the same equation to come up

with this humidity term.

So again, this is the Hamon equation here
the Hamon method is another temperature based,

basically all you have to do is input temperature.

This is the third module that we have in PRMS,
the Hargreaves-Samani formulation.

You can see the equation here.

In this case, you have to input this, hs_krs,
that’s a parameter.

HRU by month.

Again short wave radiation is coming from
the solrad module.

We’re using maximum, minimum and average
temperature, all three of those temperatures

in the same equation.

So another temperature based equation.

The fourth module that’s available for the
potential ET process is the Priestly-Taylor.

There’s a bunch of equations computing the
different terms.

The fundamental equation is down here, 1-60.

And you can see there are two parameters you
need to provide.

The elevation and this Priestly-Taylor alpha.

Latent heat of vaporization, I had the equation
for computing that in the previous one.

Again, solar radiation.

And then we’re computing this saturation
vapor pressure slope, and that depends on


And temperature is in here for this heat flux
to the ground.

Then the final one is the Penman-Monteith

The final equation is going to depend on dew

So you actually have to input the humidity,
the humidity per HRU.

You have to input the temperature.

Come up with the actual vapor pressure.

We need the saturated vapor pressure.

That can be computed from the temperature
on the HRUs.

Subtract those two and you get the deficit.

Which is what the equation is going to use.

Penman-Monteith also needs net long-wave radiation,
and this is the equation we’re using here.

We’ve got these green terms here, highlighted
green terms, they are coming from these other


Again, it’s using temperature.

And then we finally get to the big equation
that computes the potential ET.

This is the form of Penman-Monteith that we

All of these green terms are computed, are
variables computed elsewhere.

You see we’ve got three parameters in this
case, Penman-Monteith D, Penman-Monteith N

and D again.

So there’s really just two.

And this also requires wind speed as an input.

In this particular Penman-Monteith formulation,
you need to input the humidity, you need the

temperature, you need the wind speed and these
two parameters.

Then the final option is if you have pan data.

Very simple equation here.

You’ve got the actual evaporation from the

That has to be input in the data file.

And then, this is a parameter and from that
you’ll get the potential ET.

I put this in here, sometimes people want
to know what we are actually doing with the

potential ET.

And what we’re doing with it is, we’re
computing the actual ET.

So depending on the soil type, you get a ratio
of the actual to potential evapotranspiration

and the ratio of the antecedent soil moisture
to the total soil moisture and depending on

the soil type, you can come in with the water
availability and you’ll get the ratio of

actual to potential ET.

That’s what this is used for.

One thing that’s kind of good to know is
available is this atlas of potential ET values.

This comes from the National Weather Service,
NOAA, developed by Farnsworth.

It’s been a few years now, but these are
still useful climatological monthly means

for potential ET.

I just put this in here.

This is kind of a, I guess a personal issue.

We’ve had a lot of questions about PRMS
related to using these temperature index methods.

The problem, or I don’t know if it’s the
problem, but the issue is that as temperature

increases, so does potential ET.

Because potential ET is a function of temperature,
of only temperature in all but the Penman-Monteith


There has been many papers published where
people have actually observed that reference

ET or potential ET has decreased despite temperature

And that’s despite actual ET increasing.

If you think about the terms of the equations,
humidity, solar radiation, wind speed, as

well as temperature, those are all terms in
the equations.

So even though temperature is increasing,
some of these other things could be decreasing

with temperature.

Our rebuttal is that you could use the Penman-Monteith
module if you have all of that data, go ahead

and do it.

But, we would also say, does it really matter
that much if your application is in a soil

moisture limited basin?

Something to think about.

That concludes my presentation.