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Using Forest Inventory & Analysis data for broad-scale assessments of vegetation effects on water resources

Status: 
Action
Dates: 
January, 2017 to December, 2020

A photo of snow melt turning into a stream within a densely forested mountain landscape
Forest cover affects snow accumulation, retention, and melt, as well as timing and magnitude of runoff (Photo by Sara Goeking).
Forest canopies exert a physical influence on the partitioning of precipitation into runoff versus evapotranspiration through several hydrologic processes. This project seeks to illuminate the ways that forest dynamics and disturbance affect hydrologic processes and availability of water for ecosystems and for people.

We combine data from Forest Inventory & Analysis (FIA) plots with remote sensing data and hydrologic models to assess past disturbance effects, test hypotheses about hydrologic process-level responses to disturbance, and make projections about future water resources based on future forest conditions. We seek to provide managers with projections of how various forest management scenarios, or anticipated future forest dynamics, may affect the timing and runoff supplied by forested watersheds.

Approach

Photograph of coniferous trees on a steep landscape with mountains in the background
The South Fork Flathead River Basin provides a test area for using Forest Inventory & Monitoring plots as inputs to hydrologic models that quantify the effects of forest disturbance on specific hydrologic processes such as snowmelt (Photo by Sara Goeking).

  1. Using FIA plot data to improve process-based hydrologic models: This project uses FIA tree and understory vegetation data to partition existing remote sensing LAI maps into overstory versus understory components, and then develops a spatially applied statistical model to create maps of overstory and understory LAI. Although several state-of-the-art hydrologic models are capable of representing overstory canopies, most applications are constrained by a lack of overstory Leaf Area Index (LAI) data. The pilot study area is the South Fork Flathead basin of Montana, and we plan to eventually produce LAI overstory and understory layers for all eight Interior West states. In the future we will update these layers regularly and make them publicly available.

  2. Using FIA-based disturbance maps to predict post-fire water quality: Disturbance maps based on FIA data are being used in the GeoWEPP (Water Erosion Prediction Product) model to predict post-fire water quality for several years following wildfire. This project is an ongoing collaboration between FIA and Weber State University.

    Photograph of rolling hills with coniferous trees and bright blue sky
    Recent broad-scale mortality due to drought, insects, and wildfire has led to increased interest in how forest disturbance interacts with hydrologic processes in forested watersheds (Photo by Sara Goeking).

  3. Using FIA-based datasets to assess the effects of forest disturbance: We plan to use leaf area index datasets based on FIA data to assess change in hydrologic fluxes that are linked to forest disturbance and dynamics. We will use a combination of process-based ecohydrologic models, which are useful for testing hypotheses about the linkage between forests and water, and simpler empirical models that may be more useful for management applications. We plan to provide these assessments as part of IW-FIA’s regular reporting process in the next 5 years.
  4. Using FIA-based datasets to project the effects of forest dynamics on future water resources: We will use a combination of FIA plot data, remote sensing data, simulations from the Forest Vegetation Simulator (FVS), and ecohydrologic models to make projections about future forest conditions and the associated changes in hydrologic fluxes. These projections will be used for management-based reports, e.g., for evaluating alternative management scenarios, and also for conducting research about the hydrologic response to forest disturbance.


Project Contact: 

Principal Investigators:
Co-Investigators:
Dave Tarboton - Utah Water Research Lab and Dept. of Civil and Environmental Engineering, Utah State University
Marek Maryjasik - Dept. of Earth and Environmental Sciences, Weber State University