摘要
Rapid response is critical following natural disasters like wildfire. Fire, runoff, and erosion risks are highly heterogeneous in space, creating an urgent need for rapid, spatially-explicit assessment. In the past, data preparation has been time consuming and expensive, resulting in extensive losses in values-at-risk (VARs). The Rapid Response Erosion Database (RRED, http://rred.mtri.org/rred/) allows researchers and land managers to access properly-formatted spatial model inputs for the Water Erosion Prediction Project (WEPP) anywhere within the continental US and eventually beyond. Comprehensive support for post-fire hydrological modeling is provided by allowing users to upload spatial soil burn severity maps, and within moments download spatial model inputs. The database has been used to help assess and plan remediation on more than a dozen wildfires in the Western U.S. RRED has already saved $694,000 between May 2016-December 2018 in administrative costs. In the future, the potential to save time and money on data preparation can extend beyond wildfire to include tracking contaminated sediments, agricultural pollution, and construction site erosion. RRED may also be a useful tool to protect VARs as illustrated by our analysis of recreation, property values, and clean drinking water.
Rapid response is critical following natural disasters like wildfire. Fire, runoff, and erosion risks are highly heterogeneous in space, creating an urgent need for rapid, spatially-explicit assessment. In the past, data preparation has been time consuming and expensive, resulting in extensive losses in values-at-risk (VARs). The Rapid Response Erosion Database (RRED, http://rred.mtri.org/rred/) allows researchers and land managers to access properly-formatted spatial model inputs for the Water Erosion Prediction Project (WEPP) anywhere within the continental US and eventually beyond. Comprehensive support for post-fire hydrological modeling is provided by allowing users to upload spatial soil burn severity maps, and within moments download spatial model inputs. The database has been used to help assess and plan remediation on more than a dozen wildfires in the Western U.S. RRED has already saved $694,000 between May 2016-December 2018 in administrative costs. In the future, the potential to save time and money on data preparation can extend beyond wildfire to include tracking contaminated sediments, agricultural pollution, and construction site erosion. RRED may also be a useful tool to protect VARs as illustrated by our analysis of recreation, property values, and clean drinking water.
作者
Mary Ellen Miller
William S. Breffle
Michael Battaglia
David Banach
Peter R. Robichaud
William J. Elliot
Richard McClusky
Ina Sue Miller
Michael Billmire
Mary Ellen Miller;William S. Breffle;Michael Battaglia;David Banach;Peter R. Robichaud;William J. Elliot;Richard McClusky;Ina Sue Miller;Michael Billmire(Michigan Tech Research Institute, Michigan Technological University, Ann Arbor, MI, USA;College of Business, Michigan Technological University, Houghton, MI, USA;Department of Natural Sciences, University of Michigan-Dearborn, Dearborn, MI, USA;Formerly U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Moscow, ID, USA (Retired);Aquinas College, Grand Rapids, MI, USA)
