Predicting watershed post-fire sediment yield with the InVEST sediment retention model: Accuracy and uncertainties

By: , and 

Links

Abstract

Increased sedimentation following wildland fire can negatively impact water supply and water quality. Understanding how changing fire frequency, extent, and location will affect watersheds and the ecosystem services they supply to communities is of great societal importance in the western USA and throughout the world. In this work we assess the utility of the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) Sediment Retention Model to accurately characterize erosion and sedimentation of burned watersheds. InVEST was developed by the Natural Capital Project at Stanford University (Tallis et al., 2014) and is a suite of GIS-based implementations of common process models, engineered for high-end computing to allow the faster simulation of larger landscapes and incorporation into decision-making. The InVEST Sediment Retention Model is based on common soil erosion models (e.g., USLE – Universal Soil Loss Equation) and determines which areas of the landscape contribute the greatest sediment loads to a hydrological network and conversely evaluate the ecosystem service of sediment retention on a watershed basis. In this study, we evaluate the accuracy and uncertainties for InVEST predictions of increased sedimentation after fire, using measured postfire sediment yields available for many watersheds throughout the western USA from an existing, published large database. We show that the model can be parameterized in a relatively simple fashion to predict post-fire sediment yield with accuracy. Our ultimate goal is to use the model to accurately predict variability in post-fire sediment yield at a watershed scale as a function of future wildfire conditions.

Publication type Conference Paper
Publication Subtype Conference Paper
Title Predicting watershed post-fire sediment yield with the InVEST sediment retention model: Accuracy and uncertainties
Year Published 2015
Language English
Publisher Joint Federal Interagency Conference
Contributing office(s) Southwest Biological Science Center
Description 12 p.
First page 987
Last page 998
Conference Title 3rd Joint Federal Interagency Conference
Conference Location Reno, NV
Conference Date April 19-23, 2015
Google Analytic Metrics Metrics page
Additional publication details