Mobile radar provides insights into hydrologic responses in burn areas
Jonathan J. Gourley
A
B
C
D
E
Abstract
Wildfires often occur in mountainous terrain, regions that pose substantial challenges to operational meteorological and hydrologic observing networks.
A mobile, post-fire hydrometeorological observatory comprising remote-sensing and in situ instrumentation was developed and deployed in a burnt area to provide unique insights into rainfall-induced post-fire hazards.
Mobile radar-based rainfall estimates were produced throughout the burn area at 75-m resolution and compared with rain gauge accumulations and basin response variables.
The mobile radar was capable of resolving details in intra-basin rain fields as well as detecting storms approaching the burn area with accuracy equivalent to rain gauges. Runoff responses were complex and dependent on spatiotemporal patterns and magnitude of rainfall intensity over the burn area.
The complement of the mobile radar with the near-field, non-contact instruments measuring the hydrologic response provided valuable information in regions that are difficult to access and are not routinely monitored by conventional observing networks.
Post-fire observatories equipped with mobile radars deployed on burn areas provide real-time data, early alerting capabilities and visualizations to potentially guide impact-based decision support for local authorities.
Keywords: debris flows, extreme hydrologic response, mobile observatory, post-fire hazards, rainfall estimation, remote sensing, Rocky Mountains, stream radar, weather radar.
References
Abatzoglou JT, Williams AP (2006) Impact of anthropogenic climate change on wildfire across western US forests. Proceedings of the National Academy of Sciences 113, 11770-11775.
| Crossref | Google Scholar |
Alter JC (1937) Shielded storage precipitation gages. Monthly Weather Review 65, 262-265.
| Crossref | Google Scholar |
Colorado Encyclopedia (2020) Spring Creek Fire. Available at https://coloradoencyclopedia.org/article/spring-creek-fire [accessed 24 September 2024]
Dennison PE, Brewer SC, Arnold JD, Moritz MA (2014) Large wildfire trends in the western United States, 1984–2011. Geophysical Research Letters 41, 2928-2933.
| Crossref | Google Scholar |
Ebel BA, Moody JA, Martin DA (2012) Hydrologic conditions controlling runoff generation immediately after wildfire. Water Resources Research 48, W03529.
| Crossref | Google Scholar |
Eberts SM, Woodside MD, Landers MN, Wagner CR (2018) Monitoring the pulse of our Nation’s rivers and streams—The US Geological Survey streamgaging network, Fact Sheet 2018–3081, 2 p. (US Geological Survey) 10.3133/fs20183081
Fulton J, Hall N, Hempel L, Gourley JJ, Henneberg M, Kohn M, Famer W, Asquith W, Wasielewski D, Stecklein A, Mommandi A, Khan A (2024) Use of Doppler velocity radars to monitor and predict debris and flood wave velocities and travel times in post-wildfire basins. Journal of Hydrology X 24, 100180.
| Crossref | Google Scholar |
Germann U, Galli G, Boscacci M, Bolliger M (2006) Radar precipitation measurement in a mountainous region. Quarterly Journal of the Royal Meteorological Society 132, 1669-1692.
| Crossref | Google Scholar |
Gorgucci E, Scarchilli G, Chandrasekar V (1992) Calibration of radars using polarimetric techniques. IEEE Transactios on Geoscience and Remote Sensing 30, 853-858.
| Crossref | Google Scholar |
Gourley JJ (2017) In pursuit of flash flood data. Eos 98,.
| Crossref | Google Scholar |
Gourley J (2024) ‘Mobile radar data for 3 cases [Dataset].’ (Zenodo). 10.5281/zenodo.13334194
Gourley J (2025) ‘NOXP operator logs for 3 cases collected near Spring Creek burn area.’ (Zenodo). 10.5281/zenodo.14630315.
Habib E, Krajewski WF, Ciach GJ (2001) Estimation of rainfall interstation correlation. Journal of Hydrometeorology 2, 621-629.
| Crossref | Google Scholar |
Helmus JJ, Collis SM (2016) The Python ARM Radar Toolkit (Py-ART), a library for working with weather radar data in the Python programming language. Journal of Open Research Software 4(1), e25.
| Crossref | Google Scholar |
Hempel LA, Fulton JW, Gourley JJ, Mcdermott WR, Kohn MS, Bock AR, Henneberg MF (2025) Precipitation, river surface velocity, and river stage measurements within the Spring Creek Burn Scar, Colorado, USA, during select storms in 2019 and 2021. (US Geological Survey). 10.5066/P133XUDC
Highway of Legends (2024) Colorado Department of Transportation. Available at https://www.codot.gov/travel/colorado-byways/southeast/highway-legends [accessed 10 January 2025].
HyQuest Solutions (2018) TB6 Rain Gauge. Available at https://www.hyquestsolutions.com.au/fileadmin/user_upload/TB6_Brochure.pdf [accessed 24 September 2024]
Iowa State University (2025) Iowa Environmental Mesonet. Available at https://mesonet.agron.iastate.edu/lsr/ [accessed 10 January 2025].
Jorgensen DP, Hanshaw MN, Schmidt KM, Laber JL, Staley DM, Kean JW, Restrepo PJ (2011) Value of a dual-polarized gap-filling radar in support of southern California post-fire debris-flow warnings. Journal of Hydrometeorology 12(6), 1581-1595.
| Crossref | Google Scholar |
Kalogiros J, Anagnostou MN, Anagnostou EN, Montopoli M, Picciotti E, Marzano FS (2014) Evaluation of a new polarimetric algorithm for rain-path attenuation correction of X-band radar observations against disdrometer. IEEE Transactions on Geoscience and Remote Sensing 52, 1369-1380.
| Crossref | Google Scholar |
Kean JW, Staley DM, Cannon SH (2011) In situ measurements of post‐fire debris flows in southern California: comparisons of the timing and magnitude of 24 debris‐flow events with rainfall and soil moisture conditions. Journal of Geophysical Research: Earth Surface 116, F04019.
| Crossref | Google Scholar |
Khan MR, Gourley JJ, Duarte JA, Vergara H, Wasielewski D, Ayral PA, Fulton JW (2021) Uncertainty in remote sensing of streams using noncontact radars. Journal of Hydrology 603, 126809.
| Crossref | Google Scholar |
Krabbenhoft CA, Allen GH, Lin P, Godsey SE, Allen DC, Burrows RM, DelVecchia AG, Fritz KM, Shanafield M, Burgin AJ, Zimmer MA (2022) Assessing placement bias of the global river gauge network. Nature Sustainability 5(7), 586-592.
| Crossref | Google Scholar | PubMed |
Kumjian MR, Khain AP, Benmoshe N, Ilotoviz E, Ryzhkov AV, Phillips VTJ (2014) The anatomy and physics of ZDR columns: investigating a polarimetric radar signature with a spectral bin microphysical model. Journal of Applied Meteorology and Climatology 53, 1820-1843.
| Crossref | Google Scholar |
Kumjian MR, Lebo ZJ, Ward AM (2019) Storms producing large accumulations of small hail. Journal of Applied Meteorology and Climatology 58, 341-364.
| Crossref | Google Scholar |
Maddox RA, Zhang J, Gourley JJ, Howard KW (2002) Weather radar coverage over the contiguous United States. Weather and Forecasting 17, 927-934.
| Crossref | Google Scholar |
Moody JA, Shakesby RS, Robichaud PR, Cannon SH, Martin DA (2013) Current research issues related to post-wildfire runoff and erosion processes. Earth Science Reviews 122, 10-37.
| Crossref | Google Scholar |
MTBS (2020) Monitoring Trends in Burn Severity Data Access. (USDA Forest Service and US Geological Survey) Available at http://mtbs.gov/
NASA/METI/AIST/Japan Spacesystems and US/Japan ASTER Science Team (2009) ASTER Global Digital Elevation Model [Dataset]. NASA EOSDIS Land Processes Distributed Active Archive Center. [accessed 1 October 2025] 10.5067/ASTER/ASTGTM.002
National Weather Service (2025) La Veta Mountain, La Veta Pass. Available at https://www.weather.gov/wrh/timeseries?site=KVTP [accessed 10 January 2025]
Neary GD, Leonard MJ (2019) Physical Vulnerabilities from Wildfires: Flames, Floods, and Debris Flows. In ‘Natural Resources Management and Biological Sciences’. (Eds ER Rhodes, H Naser) pp. 581–603. (IntechOpen) 10.5772/intechopen.87203
NOAA Multi-Radar/Multi-Sensor System (MRMS) (2024) Operational Product Viewer. Available at https://mrms.nssl.noaa.gov/qvs/product_viewer/index.php?time_mode=update&zoom=7&clon=-97&clat=28&product_type=crefls&product=CREF [accessed 7 February 2024]
NOAA-USGS Debris Flow Task Force (2005) NOAA-USGS Debris-Flow warning system – final report 1283, 47 p. (US Geological Survey) 10.3133/cir1283
Osborne AP, Zhang J, Simpson MJ, Howard KW, Cocks SB (2023) Application of machine learning techniques to improve Multi-Radar Multi-Sensor (MRMS) precipitation estimates in the western United States. Artificial Intelligence for the Earth Systems 2, 220053.
| Crossref | Google Scholar |
Parks SA, Abatzoglou JT (2020) Warmer and drier fire seasons contribute to increases in area burned at high severity in western US Forests From 1985 to 2017. Geophysical Research Letters 47, e2020GL089858.
| Google Scholar |
QGIS Development Team (2024) QGIS Geographic Information System. (Open Source Geospatial Foundation Project) Available at http://qgis.osgeo.org.
Rengers FK, McGuire LA, Kean JW, Staley DM, Hobley DEJ (2016) Model simulations of flood and debris flow timing in steep catchments after wildfire. Water Resources Research 52(8), 6041-6061.
| Crossref | Google Scholar |
Staley DM, Negri JA, Kean JW, Laber JL, Tillery AC, Youberg AM (2017) Prediction of spatially explicit rainfall intensity–duration thresholds for post-fire debris-flow generation in the western United States. Geomorphology 278, 149-162.
| Crossref | Google Scholar |
United States Census Bureau (2020) La Veta town, Colorado. Available at https://data.census.gov/profile/La_Veta_town,_Colorado?g=160XX00US0844100) [accessed 10 January 2025]
US Geological Survey (2020) USGS water data for the Nation. (US Geological Survey National Water Information System database) [accessed 1 October 2021] 10.5066/F7P55KJN
USGS Post-Fire Debris Flow Hazard Assessment Viewer (2025) Available at https://usgs.maps.arcgis.com/apps/dashboards/c09fa874362e48a9afe79432f2efe6fe [accessed 10 January 2025]
Wang Y, Chandrasekar V (2009) Algorithm for estimation of the specific differential phase. Journal of Atmospheric and Oceanic Technology 26, 2565-2578.
| Crossref | Google Scholar |
Westerling AL, Hidalgo HG, Cayan DR, Swetnam TW (2006) Warming and earlier spring increase western US forest wildfire activity. Science 313, 940-943.
| Crossref | Google Scholar | PubMed |
Zhang J, Howard K, Langston C, Kaney B, Qi Y, Tang L, Grams H, Wang Y, Cocks S, Martinaitis S, Arthur A, Cooper K, Brogden J, Kitzmiller D (2016) Multi-Radar Multi-Sensor (MRMS) quantitative precipitation estimation: initial operating capabilities. Bulletin of the American Meteorological Society 97, 621-638.
| Crossref | Google Scholar |
Zhang J, Tang L, Cocks S, Zhang P, Ryzhkov A, Howard K, Langston C, Kaney B (2020) A dual-polarization radar synthetic QPE for operations. Journal of Hydrometeorology 21, 2507-2521.
| Crossref | Google Scholar |