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Science Report
Prepared by Corentin Liber

February 27, 2014 - Crew136: Mission To Mars UCL

IMPORTANT NOTICE: In this report, the International System of Units is used.


The aim of this project is to establish a model of the flow in a dry modern stream bed, using its
erosion traces left.
With an appropriate data sampling, we also aimed to get an accurate indication of the water
infiltration in the soil.
All these parameters have been used to give a useful indication of the aspect of the river, but also
the water content of this modern riverbed.

Same process could be used on a larger scale on Mars to appraise the water resource over the red
planet in its history.


The process could be described in four steps:

The first was to collect data on the main river bed: width, depth, slope and soil characterization
(clay or sand) by using the traces of erosion.
After that, using the Manning Formula (this formula give the velocity in an open channel by
computing the width, depth and slope) we implemented a model in MATLAB (script available on request)
under the hypothesis of a paraboloïd stream bed. It was therefore possible to get the measured
velocity and flow of the main stream.
As third step, a second campaign of data collecting on the secondary stream beds has been lead.
Flows of affluents were obtained by following the same process than in the main stream bed.
The last step was to describe a theorical flow by adding the affluent’s flows along the bed,
considering there is no water loss.

The effective infiltration between two sampling point is simply the difference between the
difference of theorical and measured flow at the two point. But this parameter is not reliable due
to high variation in bed width. Indeed, it is easily understandable that a wide bed would allow more
infiltration than a tight one.
Thus we decided to use a more accurate parameter: the relative infiltration: the ratio between
infiltration and stream’s width.

Those four data (velocity, theorical/experimental flow and relative infiltration) allowed us to get
a better understanding of this stream bed, not only its water capacity and its history but also the
soil type according to the infiltration rate.

We will further describe our results and which conclusion our model lead us to consider.


The data sampling did four EVA’s. During this campaign of data collecting we sampled more than 80
measurements of width depth and slope at over 40 different locations along the 600 meters of stream
bed. This high frequency of sampling gave us an accurate and continuous model of flow and velocity
of the river.
To describe our result we will consider three parts: first we will talk about flow and velocity,
then the theorical flow and we will finish by considering the infiltration. 


As said in the methodology, these results were obtained with the Manning formula.

The flow is in a linear increase (from 0.00032 till 0.01 cubic meters per second) over the first 250
meters. At this point the flow starts to rise faster and reach 0.03 cubic meters per second 125
meters farther. After this maximum of flow, it decreases steeply to reach again 0.015 cubic meters
per second in only 80 meters. After this point, data collecting became impossible due to the
presence of rocks in the stream bed, making the Manning formula useless.

Velocity being directly correlated with the flow, the shape of the curve remains comparable.  We
observe a minimum of 3 cm/second at 500 meters from the starting point and a maximum 7.1 cm/second
at the same maximum for the flow.


As said above, the theorical flow was used to establish a model of the flow contribution of the
affluents. We will see that it perfectly explains the steeply increase in flow in the main river
described above.

There is a high correlation between the two curves, the slope are most of the time really similar,
every bump of flow due to the affluent are closely followed by an increase of the measured flow in
the main bed. But after 300 meter, the theorical flow keeps a steep slope when the measured flow
starts to oscillate and then fall.


The natural question at this point in the study is: why does the flow in the main bed fall, despite
a constant increase of water flow due to the affluents?

This is here that the concept of infiltration becomes useful: we made the hypothesis that the «
missing » water disappear in infiltration in the soil. Thus the difference of theorical and real
flow gives the amount of water « missing ». If from this value at one sampling point we subtract the
difference at the previous sampling point, we get the rate of infiltration in cubic meter / second
between these points.  

The integration of the difference between theorical and measured flow give the total rate of
infiltration in the stream bed. We obtained the result of 338.2 liters disappearing each second by


From the values of infiltration it could be interesting to conclude a soil characterization.
The trick is that we could have a more or less accurate idea of the kind of soil, without any
drilling or borehole logging. With accurate telemetric sensors it become possible to evaluate the
soil in a stream bed on a remote location (-who said mars?-) without sending any remote drilling
robot, just by getting the width, depth, slope and an appropriate Manning coefficient of a stream
bed and his affluents.

Because it was not our highest priority, this study was not extensively developed, but we get some
interesting results.

As said in methodology we used the relative infiltration between two successive points. As example,
the distance between two of our sampling points is 12 meters, the relative infiltration is 0.29e-5,
and thus there is a loss of 3.5e-5 cubic meters / sec on a width of 1 meter along those 12 meters.
So each square meter loses 0.29e-5 cubic meters per second. The water has therefore a penetration
rate of 2.9e-6 meters per second which is precisely the hydraulic conductivity of dense sand. We
made a homemade borehole logging to confirm these data and the result corroborated the theory. 

This approach looks really promising but due to the lack of time it is not possible to process these
data further ahead, especially about the selection of an appropriate Manning coefficient.


To conclude this report, let’s get through all of our study. By using a simple method of data
collecting, we were able to find an accurate model of flow, velocity, and infiltration of a totally
dry stream bed…
Those informations make us able to have a better understanding of a disappeared hydrological system,
which could be really valuable on Mars.

Bruce Ngataierua
Mar 1

to Mission 
Science Report
Prepared by Benoit Pairet

Astrophysical spectra analysis


The location of Mars and the facts that it has a weak magnetic field or
almost no atmosphere make it
the perfect spot to observe our solar system. We combined the Musk
Observatory and an optic
spectrometer to proceed to measurements of the spectrum emitted by
planets from our solar system and
bright stars.
Once the spectra are recorded we compare them to the one of the Sun, we
can thus determine the
composition of the observed object.


An optic probe is fixed to an eyepiece that is attached to the
telescope. It is important to ensure
a good alignment and a precise focus in order to get enough light. The
optic probe is linked to an
optic spectrometer ranging from 400nm to 1100nm that sends the data to a
computer. Here, we used
spectrasuite for the recording. Those data are then sent back to Earth
to be analyzed because it
needs quite a big database.

The analysis of the data is quite different for planets than for stars.
The light emitted from a
planet is the light of the Sun that is remitted from that planet. Light
that is remitted is nothing
but light that has not been absorbed. The light absorbed by a body
depends on what it is composed
of. It is then possible to determine the composition of a body by
looking to the peaks of the
remitted spectrum and comparing it to known spectra. The deeper the peak
the more the body contains
that element.
For a star, that's quite different. The light coming from a star is
emitted by atoms in fusion
inside the star. The shape of the spectrum provides important
information about the composition of
the star. Hydrogen atoms in fusion does not yield the same spectrum than
lead atoms in fusion. We
are then able to determine if the star is made of the same elements as
the Sun. However, it is
important to keep in mind that Doppler effect and gravitational redshift
take place with stars and
the spectrum might need to be shifted to correspond.


It was not possible for us to conduct the analysis ourselves because
that requires a big database
that we did not find before leaving Earth. That is why we sent our data
to Earth and we are still
waiting on the results.