Learning Modules

These extended learning modules...[Notes: High level summary belongs here for each module, which will then link to a separate landing page for each module that has more details. For now, putting everything here since we only have one module.]

Learning Module 1: Simulating the impacts of extreme rainfall using Landlab

Chapter 0: Overview

This module is motivated by understanding drivers of land surface change and hazard during the the 2013 Colorado floods and landslides. The overview chapter sets the stage for an extended analysis of how stochastic rainfall impacts the surface. Students are introduced to Landlab, a Python-based modeling library, that is well-suited to building numerical models of surface dynamics that are custom-built by the user.

Chapter 1: When it rains, it pours (sometimes)

Chapter 1 focuses on describing and simulating rainstorm statistics both from data and via parametric models. Student learning outcomes include:

Analyzing time series data from a tipping bucket rain gauge.
Describing and comparing event-scale storm properties.
Simulating stochastic rainfall using a Landlab component.
Explaining how well historic events are captured by rainfall generators.

Chapter 2: From rainfall to runoff

Chapter 2 focuses on building Landlab grids with which to add process components. Student learning outcomes include:

Constructing and interpreting a 'bucket' model of surface water hydrology.
Explaining how root zone soil moisture evolves through time.
Planning and executing a model that couples two Landlab components.
Critiquing a hydrological model and modifying it to route water.

Chapter 3: Flow, floods, and failures

Chapter 3 focuses on using models based on real-world topographic data. Student learning outcomes include:

Building a model grid using real-world topography.
Interpreting fluxes by delineating watersheds.
Constructing an overland flow model driven by rainfall runoff.
Analyzing how the probability of hillside failure varies in space and time.