A field-ready, rapidly deployable team based at UNM's Center for Water and the Environment — monitoring how wildfire disturbances propagate through fluvial networks across the American Southwest and beyond.
Who We Are
We are the Wildfire Impact and Longitudinal Disturbance Rapid Response Research (WILD-3R) Team, part of the Center for Water and the Environment (CWE) at UNM. Our mission is to stop relying on fortuitous datasets and instead build a pre-positioned, trained rapid response capacity that deploys quickly when wildfire events threaten downstream water resources.
Wildfires elevate concentrations of nutrients, organic carbon, ash, suspended sediments, and trace metals across fluvial networks — threatening agricultural, industrial, and municipal water supplies far downstream of burn sites.
Most stream research is confined to short reaches (<1 km) in 1st–3rd order headwater streams. The WILD-3R Team is specifically designed to address how disturbances propagate over hundreds of kilometers to 4th–12th order rivers where human water use is most intense.
Standard research funding cycles are incompatible with on-demand mobilization. Institutional constraints leave researchers without viable options for rapid deployment during the critical early window after wildfire events — perpetuating data deficits.
Fire, hydrology, atmospheric, and water quality data are dispersed across USGS, NOAA, the US Forest Service, and the EPA — collected under diverse protocols and largely siloed. Meta-analyses currently take years to decades to reach decision-makers.
Research Outputs
What We've Found
A fortuitously collected sensor dataset on the Rio Grande detected multiple severe hypoxic events (<2 mg/L DO) carrying ash and sediment hundreds of kilometers from the burn area. These events caused a two-month shutdown of Albuquerque's surface water intake — supplying ~70% of drinking water for the city's ~560,000 residents. This experience, combined with continental-scale analyses showing that ~11% of western US stream length has been affected by wildfire disturbances since 1984, directly motivated the creation of the WILD-3R protocol to stop relying on chance observations.
Precipitation events with recurrence intervals of less than two years triggered runoff responses typically associated with ~10-year events. Water quality disturbances were detectable at monitoring stations >160 km downstream across two fluvial networks of ~170 km each, spanning pronounced changes in turbidity, conductivity, dissolved oxygen, nutrients, and metals. (Nichols et al., 2024, Nature Communications)
We developed and deployed The Navigator — an autonomous GPS/LTE-connected surface vehicle — at Santa Rosa Lake (~175 km downstream of the Hermit's Peak–Calf Canyon burn scar) to characterize how wildfire-driven sediment pulses affect large-scale reservoir systems. Spatial mapping showed dissolved oxygen dropping from ~6 mg/L in the Pecos River to anoxic levels (~0 mg/L) within the lake delta before recovering near the dam. DO sags inversely correlated with turbidity, implicating wildfire sediment loads in driving microbial respiration and suppressing photosynthesis across sharp spatial gradients. (Khandelwal et al., 2023, Water Research)
Tools & Infrastructure
YSI sensors deployed at strategic fixed locations along impacted fluvial networks monitor temperature, specific conductivity, dissolved oxygen, turbidity, fDOM, and pH at 10-minute intervals. Networks remain active for at least one year post-fire, with data transmitted via telemetry and published in near-real time.
A custom-built GPS/LTE-connected boat equipped with water quality sensors, depth sonar, and a camera, paired with a real-time data visualization dashboard. Deployed during bi-weekly calibration trips to resolve fine-scale spatial variability — particularly within lakes and downstream impoundments — that fixed sensors cannot capture.
An open-source R framework and interactive Shiny application that links four decades of MTBS wildfire data with high-resolution USGS hydrologic observations across the contiguous US. RIO-FINDER allows users to systematically identify monitoring sites within fire-affected watersheds, explore pre- and post-fire data availability, and export custom datasets for analysis. Includes RAPID, a standalone tool for on-demand assessment of newly burned watersheds.
People
Core Team · University of New Mexico
Research Collaborators
Get Involved
We welcome collaboration with water utilities, land managers, agencies, and researchers interested in rapid response monitoring. Contact us to discuss partnerships, data sharing, or co-deployment opportunities.