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Hello and welcome back to this third session about
geographic information systems for diagnosis and simulation of metabolic systems.
In this session, the goal is to show the possibilities that
geographic information system offer to set
external constraints for particular territories.
And this 10-minute session,
we will present case studies where geographic information system is used to both provide
information for diagnosis and also
for simulating possible constraints for future scenarios.
So we'll start with this first example of the Mauritius Island.
Mauritius is an island in
the Indian Ocean that uses most of its agricultural resources to grow sugarcane.
It uses most of the agricultural land and most of
the water of the island to grow this. What is this for?
The sugarcane is used only to sell outside for export to Europe basically,
because Europe was demanding a lot of biofuel,
so they require a lot of ethanol coming from sugarcane.
But Europe lately, is changing
its policies and now it's not going to demand so much ethanol.
So, this island needs to know what to do with all this sugarcane that they are growing
now because maybe in the future they won't be able to sell it anymore.
For this purpose, we do a diagnosis of the whole system in the island,
the whole metabolic pattern.
And in this table we can see how we're representing at the same time food,
energy, water and monetary flows on different elements of human activity.
The time of the population, how it is located.
The land use, the surface of the country, how it is used.
And the power capacity;
the installed infrastructure and machinery they have.
This table, it is distributed among different compartments of the society.
It could be the household level,
the consumption part of the society and the productive parts;
the power and the paid work sectors,
agricultural sectors, energy and mining,
and some of the sectors we might be interested to split and analyze separately.
So, in this case, we are analyzing, for example,
the sugarcane as a compartment of export of agriculture here.
Then we have the sum of all the different flows,
imports, domestic supply also might be built on imports.
And we have the relation,
very important, of these flows and funds among them.
For example, for the hectares of land use located for agriculture,
we have an amount of labor, of work,
of time that is dedicated to this surface.
So, we have a technical coefficient of hours per hectare.
Also, we have added value in this surface of agricultural land.
So, we have a flow per fund.
We have an amount of money per hectare,
an amount of water consumption of the agricultural crops per hectare,
an amount of energy and amount of food that is produced per hectare.
So, we have technical coefficients that can be obtained through this table.
In this case, we have the information for the water consumption for urban part,
but not for the agricultural part.
So, how to know this data that is missing?
We can use GIS, Geographical Information Systems,
to use the crop water requirement models that are used to estimate the water consumption
of the different crops to
know how these crop water requirement for
every crop is being actually done in every part of the island,
depending on the crop and depending on other factors.
For example, these models require the information about the climatic areas,
the water supply distribution systems
and the type of crops that you are growing in the island.
Combining this with GIS,
we obtain a combination of layers.
Then we know the model, how to run it in every single polygon of this map and we get
a final water consumption in the island for agriculture
using GIS that we couldn't know without these maps,
this kind of graphical information.
Now we can use this number to put into the table.
Now, we will go to how to use the GIS also for simulations.
So, in this island,
it could be a good idea, maybe,
let's explore the possibility of using all the agricultural land to grow food,
to grow agricultural products that are actually
demanded in the island for their food consumption,
not to grow sugarcane only for export.
How do we know if this is a possible solution?
By simulating what is the mix of
agriculture products that are consumed in the island as food,
and simulating how much food you can grow in the island.
Then to know where are the plots of the farmers in the islands?
What are the slopes in the islands,
because if it's too steep you can to grow certain crops.
And what are the top soils in the island because,
depending on the soil you will be able to grow some crops and some others,
you need to grow in some other type of soils.
So you get a combination of layers and we can simulate
the final amount of hectares that you
can use in this island to grow the new mix of the crops that are demanded for food.
So, we get a final amount,
represented in green in this map,
and we can fill the table here with the new number of
hectares taken from the sugarcane to the food,
to the agricultural products that will provide food
and will make the imports to be lesser,
the imports of food.
And then everything else will change in
this table because the water consumption will be different,
the energy consumption is also different.
The monetary flow will be different, and the labor, very important,
will increase because the new crop mix is requiring more labor per hectare than before,
than the sugarcane that was very mechanized.
How to estimate the new water consumption in this simulation, in this new scenario.
Again, we will use
the new map to make a new estimation of the water consumption.
And we will be able,
not only to know the final amount of water in the island in the new scenario,
but also how the water consumption
will be different in different locations of the island.
We have the current pattern of crop water requirement by the crops,
mainly by the sugarcane in the island and we can simulate with the new crop mix,
the new water consumption by the new crops.
We will see in this map,
that we are looking at that
the water consumption is different depending on the location in the island.
So, in the eastern part of the island,
the water consumption has not decreased much,
and in the southern part the farmers probably will be very happy because the new scenario
is implying that the water consumption of the crops is lesser.
So, they have advantage with this new scenario.
This is representing not only a final amount of water for the tables,
but that also the system is heterogeneous,
and the system has different results depending on the location.
This is important to know that the system is not
homogeneous and it will have different results for different locations.
So the spatial analysis,
the geographic information system,
is providing a new type of information,
providing data for the different heterogeneous parts of the system,
not only as a single unit.
A new simulation we will do here for the case study of South Africa.
South Africa is a big country,
they have most of the population located only on certain parts of the country.
And we will simulate how to know what
is the possibilities to install
a new source of electricity as the concentrated solar power.
The concentrated solar power,
we can simulate with GIS again, what are the slopes,
what are the solar radiation in the country and what are the main grids for electricity.
So, we get a combination of layer and we get a final amount of
land that can be used to install concentrated solar power plants in the country.
In this final arrangement of this concentrated solar power scenario,
we see that still it is all located in the part of the country,
the Karoo, which is a desert where nobody lives.
All the people live somewhere very far away from this area.
So, we are seeing by GIS, by using maps,
that distance and the relative position of the feature might be also constrained,
but is not explicit in some other ways of analyzing the system.
By using GIS, digital maps and geographic information systems,
we can see new aspects important for the metabolic patterns of societies of systems.
We can see shape of particular polygons that might affect the performance of the system,
the degree of fragmentation of the system,
the coverage or the spreading of the land uses over the system.
We see that the coverage is not covering all the country,
but it is concentrated only in one part of the country.
The relative position of the features and the distance that might set new constraints for
our metabolic patterns for simulating the scenarios.