Modeling Post‐Wildfire Hydrologic Response: Review and Future Directions for Applications of Physically Based Distributed Simulation
Abstract Wildfire is a growing concern as climate shifts. The hydrologic effects of wildfire, which include elevated hazards and changes in water quantity and quality, are increasingly assessed using numerical models. Post‐wildfire application of physically based distributed models provides unique i...
Main Authors: | , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2023-02-01
|
Series: | Earth's Future |
Subjects: | |
Online Access: | https://doi.org/10.1029/2022EF003038 |
_version_ | 1797895002539425792 |
---|---|
author | Brian A. Ebel Zachary M. Shephard Michelle A. Walvoord Sheila F. Murphy Trevor F. Partridge Kim S. Perkins |
author_facet | Brian A. Ebel Zachary M. Shephard Michelle A. Walvoord Sheila F. Murphy Trevor F. Partridge Kim S. Perkins |
author_sort | Brian A. Ebel |
collection | DOAJ |
description | Abstract Wildfire is a growing concern as climate shifts. The hydrologic effects of wildfire, which include elevated hazards and changes in water quantity and quality, are increasingly assessed using numerical models. Post‐wildfire application of physically based distributed models provides unique insight into the underlying processes that affect water resources after wildfire. This work reviews and synthesizes post‐wildfire applications of physically based distributed models by examining the scales and geographic/ecohydrologic distribution of model applications, hydrologic response process representation, model parameterization, and model performance metrics. Highlighted gaps and opportunities for advancing physically based distributed hydrologic response modeling after wildfire include the following: (a) applying models in under‐represented geographic (S. America, Africa, Asia) and ecohydrologic regions (arid or dry subhumid climates), (b) incorporating all four major streamflow generation mechanisms (infiltration excess, saturation excess, subsurface storm flow, and groundwater flow), (c) representing integrated vadose zone and saturated zone processes to better capture subsurface streamflow generation, (d) building new remotely sensed model parameterization methods for precipitation interception, infiltration, and overland flow that account for burn severity and recovery, (e) incorporating distributed state variables (e.g., soil moisture, groundwater levels) in model performance assessment, (f) designing model intercomparison studies, including field datasets specifically for post‐wildfire model development and validation, (g) linking mechanistic vegetation regrowth models with hydrologic models to improve simulation of process shifts as ecosystems recover, and (h) creating a new community modeling framework to integrate modeling advances across the wildfire science community. |
first_indexed | 2024-04-10T07:18:30Z |
format | Article |
id | doaj.art-5f83712ca76a47d08499fb107834e12f |
institution | Directory Open Access Journal |
issn | 2328-4277 |
language | English |
last_indexed | 2024-04-10T07:18:30Z |
publishDate | 2023-02-01 |
publisher | Wiley |
record_format | Article |
series | Earth's Future |
spelling | doaj.art-5f83712ca76a47d08499fb107834e12f2023-02-24T17:18:32ZengWileyEarth's Future2328-42772023-02-01112n/an/a10.1029/2022EF003038Modeling Post‐Wildfire Hydrologic Response: Review and Future Directions for Applications of Physically Based Distributed SimulationBrian A. Ebel0Zachary M. Shephard1Michelle A. Walvoord2Sheila F. Murphy3Trevor F. Partridge4Kim S. Perkins5U.S. Geological Survey Water Resources Mission Area Burlington VT USAU.S. Geological Survey New Mexico Water Science Center Albuquerque NM USAU.S. Geological Survey Water Resources Mission Area Lakewood CO USAU.S. Geological Survey Water Resources Mission Area Boulder CO USAU.S. Geological Survey Water Resources Mission Area Lakewood CO USAU.S. Geological Survey Water Resources Mission Area Menlo Park CA USAAbstract Wildfire is a growing concern as climate shifts. The hydrologic effects of wildfire, which include elevated hazards and changes in water quantity and quality, are increasingly assessed using numerical models. Post‐wildfire application of physically based distributed models provides unique insight into the underlying processes that affect water resources after wildfire. This work reviews and synthesizes post‐wildfire applications of physically based distributed models by examining the scales and geographic/ecohydrologic distribution of model applications, hydrologic response process representation, model parameterization, and model performance metrics. Highlighted gaps and opportunities for advancing physically based distributed hydrologic response modeling after wildfire include the following: (a) applying models in under‐represented geographic (S. America, Africa, Asia) and ecohydrologic regions (arid or dry subhumid climates), (b) incorporating all four major streamflow generation mechanisms (infiltration excess, saturation excess, subsurface storm flow, and groundwater flow), (c) representing integrated vadose zone and saturated zone processes to better capture subsurface streamflow generation, (d) building new remotely sensed model parameterization methods for precipitation interception, infiltration, and overland flow that account for burn severity and recovery, (e) incorporating distributed state variables (e.g., soil moisture, groundwater levels) in model performance assessment, (f) designing model intercomparison studies, including field datasets specifically for post‐wildfire model development and validation, (g) linking mechanistic vegetation regrowth models with hydrologic models to improve simulation of process shifts as ecosystems recover, and (h) creating a new community modeling framework to integrate modeling advances across the wildfire science community.https://doi.org/10.1029/2022EF003038wildfirewildland firehydrologic modelstreamflowgroundwaterwater supply |
spellingShingle | Brian A. Ebel Zachary M. Shephard Michelle A. Walvoord Sheila F. Murphy Trevor F. Partridge Kim S. Perkins Modeling Post‐Wildfire Hydrologic Response: Review and Future Directions for Applications of Physically Based Distributed Simulation Earth's Future wildfire wildland fire hydrologic model streamflow groundwater water supply |
title | Modeling Post‐Wildfire Hydrologic Response: Review and Future Directions for Applications of Physically Based Distributed Simulation |
title_full | Modeling Post‐Wildfire Hydrologic Response: Review and Future Directions for Applications of Physically Based Distributed Simulation |
title_fullStr | Modeling Post‐Wildfire Hydrologic Response: Review and Future Directions for Applications of Physically Based Distributed Simulation |
title_full_unstemmed | Modeling Post‐Wildfire Hydrologic Response: Review and Future Directions for Applications of Physically Based Distributed Simulation |
title_short | Modeling Post‐Wildfire Hydrologic Response: Review and Future Directions for Applications of Physically Based Distributed Simulation |
title_sort | modeling post wildfire hydrologic response review and future directions for applications of physically based distributed simulation |
topic | wildfire wildland fire hydrologic model streamflow groundwater water supply |
url | https://doi.org/10.1029/2022EF003038 |
work_keys_str_mv | AT brianaebel modelingpostwildfirehydrologicresponsereviewandfuturedirectionsforapplicationsofphysicallybaseddistributedsimulation AT zacharymshephard modelingpostwildfirehydrologicresponsereviewandfuturedirectionsforapplicationsofphysicallybaseddistributedsimulation AT michelleawalvoord modelingpostwildfirehydrologicresponsereviewandfuturedirectionsforapplicationsofphysicallybaseddistributedsimulation AT sheilafmurphy modelingpostwildfirehydrologicresponsereviewandfuturedirectionsforapplicationsofphysicallybaseddistributedsimulation AT trevorfpartridge modelingpostwildfirehydrologicresponsereviewandfuturedirectionsforapplicationsofphysicallybaseddistributedsimulation AT kimsperkins modelingpostwildfirehydrologicresponsereviewandfuturedirectionsforapplicationsofphysicallybaseddistributedsimulation |