This course examines post-fire watersheds as dynamic computational landscapes operating within flow space and phase space encompassing spatial, material, and systemic conditions in which flows of matter, energy, and information are structured, modulated, and made legible. Students will learn to work with dynamic landscapes as active computational systems using a stream table and AI methods to design interventions across dynamic post-fire watersheds.

Following fire, debris flows can mobilize within minutes as vegetation, soil structure, and hydrologic regimes are radically altered, while gravitational and climatic forces remain intact or intensified. In these conditions, risk does not arise from fixed form, but from continuous variation across gradients, thresholds, bottlenecks, and attractors.

The course employs a geomorphology simulation stream table as a physical computational laboratory where landscape processes unfold in accelerated time. This is paired with the development of AI-based methods that infer underlying system behavior from observation and measurement. Together, these tools support design interventions in evolving systems and cultivate fluency in working with landscape computation rather than imposing static form. Through close documentation of temporal changes in material states students examine how local interactions scale into watershed-level effects.

Framed through Computational Landscape Architecture, the course treats landscapes not as static compositions, but as active systems that continuously generate form through interaction. The core model describes two reciprocal fields: a Potential Field that carries energetic forces, and a Constraint Field that encodes structure, boundaries, and memory.

Experimental work focuses on altering material states to develop micro-infrastructures that operate intuitively at local scales while performing collectively across post-fire territories.

This course will be held in 7 Sumner Road, room B1.