EGU26-16005, updated on 14 Mar 2026
https://doi.org/10.5194/egusphere-egu26-16005
EGU General Assembly 2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Poster | Wednesday, 06 May, 14:00–15:45 (CEST), Display time Wednesday, 06 May, 14:00–18:00
 
Hall X3, X3.129
Hydro-Stochastic Model to Inform the Design of Environmental Impact Bonds for Wildfire Resilience 
Luke Mangney1, Matthew Brand1, Ariane Jong-Levinger2, Tessa Maurer3, Phil Saksa3, and Wren Raming3
Luke Mangney et al.
  • 1Louisiana State University, Department of Civil and Environmental Engineering, Baton Rouge, United States of America
  • 2Southern California Coastal Water Research Project, Costa Mesa, United States of America
  • 3Blue Forest, Sacramento, United States of America

We present a stochastic hydro-financial modeling framework that produces probabilistic forecasts of post-fire costs attributable to altered watershed hydrology under different wildfire regimes, estimating impacts borne by flood-control infrastructure managers and downstream communities. We then outline a practical framework for mobilizing capital from flood control infrastructure managers to finance forest management strategies that reduce wildfire risk via an Environmental Impact Bond (EIB). Our approach is valuable because economic assessments can emphasize direct wildfire damage while underrepresenting the long-term costs after an event including sedimentation in downstream infrastructure, elevated flood risk, and degraded water quality. This gap is particularly consequential for public entities that manage flood control infrastructure like debris basins and flood control channels and thus shoulder a large portion of post-fire sediment and water-quality management costs. Forest management strategies such as fuels reduction along high-risk corridors offer a pathway to reducing these wildfire costs by lowering fire occurrence and severity. However, entities hoping to implement these strategies can find it difficult to 1) raise the large volumes of capital needed to implement measurable changes and 2) justify the required expenditure without a robust assessment of cost effectiveness. To address these barriers, our model implements historical records of infrastructure maintenance, sediment accumulation and rainfall with wildfire simulation results to generate metrics indicating the benefits of an intervention. We then show how these results can be used to structure an EIB, a financial instrument where private investors provide upfront capital for implementation and are repaid through savings realized by infrastructure managers. We demonstrate the approach by analyzing flood-protection infrastructure operated by the Riverside County Flood Control and Water Conservation District (in Southern California).

How to cite: Mangney, L., Brand, M., Jong-Levinger, A., Maurer, T., Saksa, P., and Raming, W.: Hydro-Stochastic Model to Inform the Design of Environmental Impact Bonds for Wildfire Resilience , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16005, https://doi.org/10.5194/egusphere-egu26-16005, 2026.