| Literature DB >> 34248273 |
François-Nicolas Robinne1, Dennis W Hallema2, Kevin D Bladon3, Mike D Flannigan1, Gabrielle Boisramé4, Christian M Bréthaut5, Stefan H Doerr6, Giuliano Di Baldassarre7, Louise A Gallagher8, Amanda K Hohner9, Stuart J Khan10, Alicia M Kinoshita11, Rua Mordecai12,13, João Pedro Nunes14, Petter Nyman15, Cristina Santín6, Gary Sheridan16, Cathelijne R Stoof14, Matthew P Thompson17, James M Waddington18, Yu Wei19.
Abstract
2020 is the year of wildfire records. California experienced its three largest fires early in its fire season. The Pantanal, the largest wetland on the planet, burned over 20% of its surface. More than 18 million hectares of forest and bushland burned during the 2019-2020 fire season in Australia, killing 33 people, destroying nearly 2500 homes, and endangering many endemic species. The direct cost of damages is being counted in dozens of billion dollars, but the indirect costs on water-related ecosystem services and benefits could be equally expensive, with impacts lasting for decades. In Australia, the extreme precipitation ("200 mm day -1 in several location") that interrupted the catastrophic wildfire season triggered a series of watershed effects from headwaters to areas downstream. The increased runoff and erosion from burned areas disrupted water supplies in several locations. These post-fire watershed hazards via source water contamination, flash floods, and mudslides can represent substantial, systemic long-term risks to drinking water production, aquatic life, and socio-economic activity. Scenarios similar to the recent event in Australia are now predicted to unfold in the Western USA. This is a new reality that societies will have to live with as uncharted fire activity, water crises, and widespread human footprint collide all-around of the world. Therefore, we advocate for a more proactive approach to wildfire-watershed risk governance in an effort to advance and protect water security. We also argue that there is no easy solution to reducing this risk and that investments in both green (i.e., natural) and grey (i.e., built) infrastructure will be necessary. Further, we propose strategies to combine modern data analytics with existing tools for use by water and land managers worldwide to leverage several decades worth of data and knowledge on post-fire hydrology.Entities:
Keywords: climate change; extreme events; fire regime restoration; forest ecosystem services; risk governance; socio‐hydrology; water security; watershed protection
Year: 2021 PMID: 34248273 PMCID: PMC8251805 DOI: 10.1002/hyp.14086
Source DB: PubMed Journal: Hydrol Process ISSN: 0885-6087 Impact factor: 3.565
FIGURE 3Risk governance in the wildfire‐watershed value chain. Wildfire‐watershed risks are recognized through the identification of interactions between upstream wildfire hazard (i.e., likelihood of a wildfire event of a given, potentially harmful, magnitude), watershed vulnerability, and downstream water security. After identification of water security vulnerabilities and their social and economic consequences, effective wildfire‐watershed risk governance will offer a set of options to deal with existing at‐risk situations. Rapid, slow, and prolonged onset drivers refer to the speed and depth at which changes in fire and forest management can occur: Rapid onset drivers can be acted upon quickly and have immediate effects (e.g., biomass reduction), while slow onset drivers are deeply ingrained and affect fire activity on the long term, even after changes have been made (e.g., fire exclusion policies). Icons made by Freepik and Eucalip
FIGURE 2Existing and emerging global wildfire‐watershed risk hotspots. (a) Water‐stressed watersheds (i.e., annual water withdrawal exceeds annual water supply, see Data S1) with a median wildfire‐watershed risk index >24 (n = 8280) (Robinne et al., 2018). (b) Occurrence of extreme wildfire events recorded between 2002 to 2013 (n = 478; Bowman et al., 2017). (c) Cities (n = 252) that declared current and expected water supply challenges linked to decreasing water quantity, decreasing water quality, and/or increasing water demand (see Data S1)