um hi everyone my name is Wen-Ying Wu and I'm the PhD student and UT Austin I'm
working on you geological sciences but today we are going I'm going to tell you
a new project that we are working with a mechanical engineering group in our
school, so we are trying to put the flaw prediction into a hurricane
receipt and healthcare infrastructure modeling basically is about how to
optimize the resources for hospital evacuation
doing those flood events so here you can see the NASA satellite image that is
a MODIS image and you can see the the hurricane Harvey and how dramatic it is
in the Texas Gulf region
so I'm giving you an overview of the Harvey event so
Harvey is a hurricane and 2017 August and it's bring tremendous on renzo and
the Texas Gulf Coast on region
and eight minutes length for around August 26 and
the east part in the north part after Harvey brings a lot of rainfall in to
Texas Gulf region so actually it and this caused many hospital and a nursing
home had to evacuate
and unfortunately Harvey kills a hundred and six lives during several days
yeah so you might be thinking about there are so many hospital over Texas
and so many nursing home and we have very limited amount of the ambulance and
the buses so how to optimize all the resources to get the ambulance moving
around the Texas Gulf region and have the limited resources optimize and save the
life and I would like to say this framework is have the global impact
because globally water cycle is moving every, every day every time everywhere
and here is my visualization of the how the river moving over there event, so in
a water year you can see there is a big seasonality of river stream flow because
of like snow melting or the rain flow or the free throw process over the arctic
regions so about 35% of the precipitation will go into the runoff
and that accounts for 40 cubic 40,000 cubic kilometres amount of water running
to the ocean every year
so here's a year water cycle of the streamflow animation
so I run the river multi model with using the Geo DIS is a NASA learning
surface data assimilation product and to simulate it how the water transfer from
the upstream to the downstream
so let's move back to the Texas Gulf region so
this is the time Frame of where and when Harvey happens later on you will
see a dramatic amount of the water that is because of the way.. on the rain fall
bring from Harvey quit was appear in that region and would take all the
plains around and those thought actually is the location of the hospital
in a nursing home, so it's the really question that's all
for this amount of the water moving over the land, how do we optimize the
resources to save the life
so the Harvey when it made its first land fall
August 26 but the
flooding last for several days because Harvey's surrounding around in these
regions for a long time that's beyond our expectation so that its first test
test case um of the project I'm doing this semester to see how we can evacuate
the hospital resources um in this story
so that is our framework, um, I'm working on the Geo science team which is about this
part so we used national water model which is a continental scale flood
forecast model and we use the streamflow and then we use a method to simulate the
flood heads and that is for the river flooding from them I mean the the fresh
water flooding from the stream flow but also we use the / model to simulate
in the storm surge which is salient water that will also cause flooding especially
in the coastal region like this and that is from the front end to the break
backend the engineering team they would use the stochastic optimization model so
basically is optimization so it was minimize the resources between the
hospital and see how many so the final result of that is so we was simulated
that how the brute Map going to be like to try to optimize this resources
around different hospital so later on I'm going to show you the result of two
simulations one with using the national water model
only to, to account for the flooding from the river and the other ones use
both national water model and the slash model to account for the flash
freshwater flooding but also the storm surge together
so here's the result of
the Ruth meds for account for the natural water model only for the red
dots mean the hospital that's going to receive the patient that is come from
the sender so the the greens out mean that's the hospital that is really in the
dangerous because of the flooding they they have to send a patient to somewhere
else and the staging area means that the the location of the ambulance or
original is so here we are those centers is pick up because of those regions are
going to be flooded based on the weather forecast and then to the hydrological
forecast and to the optimization model and later I'm going to show you the
results with another model together so you might expect this for those coastal
regions those hospitals though are going to pick out because of the storm surge so
now you can see that those hospitals in those coastal regions are really I need
to evacuate the patient because of the storm surge so in this project we
account for the fresh water but also the storm surge together and we start to do
this project at the beginning of September so we have very limited
primary results but I'm happy to make the science from useful to usable to
make our science have the social impact and try to save some lives
yeah and for this project and like to thank for our engineering team and also
AGU and NASA to support this conference yeah thank you