Remote Sensing/Statistical Modeling
By combining 30m global forest disturbance datasets with long-term, ongoing USGS water gage data via Google Earth Engine, we are able to accurately monitor when and where disturbance occurs, and tie that to disruptions in the water outputs of critical watersheds across the nation. Currently, we're looking at the impacts to over 700 watersheds, from southern Florida to northwest Washington.
Most people assume disturbance = more water. Not so, when you start looking at the literature. It turns out there is a substantial amount of watersheds that have lower water post-disturbance. This is significant if you're a land manager who cares about their water supply and sees a wildfire cresting the ridge, as well as a home owner concerned about flooding post-mountain pine beetle outbreak.
Collaborative Hydrological Modeling
We are fusing the data on forest canopy damage with a high resolution hydrology model (DHSVM) to estimate the impact of these large disturbances on water yield now and in the future. These outputs are critical to land managers who are attempting to supply thirsty, populous regions.
One potential strategy that we've explored (see publications) is the possibility of planting more climatically suitable species post-disturbance, essentially using natural disturbances to kick start migration (semi-assisted migration, if you will). It appears to have some effect, but only in some types of forests/watersheds. Figuring out when and where such management tools are effective is a significant challenge, but important, for future forest management.