  Water current prediction is essential for understanding ecosystems, and to
shed light on the role of the ocean in the global climate context. Solutions
vary from physical modeling, and long-term observations, to short-term
measurements. In this paper, we consider a common approach for water current
prediction that uses Lagrangian floaters for water current prediction by
interpolating the trajectory of the elements to reflect the velocity field.
Here, an important aspect that has not been addressed before is where to
initially deploy the drifting elements such that the acquired velocity field
would efficiently represent the water current. To that end, we use a clustering
approach that relies on a physical model of the velocity field. Our method
segments the modeled map and determines the deployment locations as those that
will lead the floaters to 'visit' the center of the different segments. This
way, we validate that the area covered by the floaters will capture the
in-homogeneously in the velocity field. Exploration over a dataset of velocity
field maps that span over a year demonstrates the applicability of our
approach, and shows a considerable improvement over the common approach of
uniformly randomly choosing the initial deployment sites. Finally, our
implementation code can be found in [1].
