Bushfire CRCResearch Utilisation and knowledge transfer

Erosion in burned catchments of Australia:Regional synthesis and guidelines for evaluating risk

Petter Nyman and Gary J SheridanThe University of MelbourneDecember 2014

 

   

Acknowledgements    This  document  is  a  synthesis  that  builds  upon  more  than  a  decade  of  post-­‐fire  hydro-­‐geomorphic  research  within  the  Forest  Hydrology  Research  Group,  in  the  School  of  Ecosystem  and  Forest  Sciences  at  The  University  of  Melbourne.  We  would  like  to  acknowledge  and  thank  our  key  research  sponsors  including  the  Victorian  Department  of  Environment,  Land,  Water  and  Planning  (DELWP),  Melbourne  Water,  the  Australian  Research  Council,  the  Bushfire  Cooperative  Research  Centre  and  the  CRC  for  Forestry.  Many  thanks  also  to  the  many  researchers,  students  and  technical  staff  who  have  contributed  in  numerous  ways  to  the  data  and  concepts  in  this  report  including  Associate  Professor  Patrick  Lane,  Dr  Christoph  Langhans,  Dr  Hugh  Smith,  Dr  Owen  Jones,  Dr  Jane  Cawson,  Rene  van  der  Sant,  Phillip  Noske  and  Christopher  Sherwin.  Finally  we  would  like  to  thank  the  many  staff,  partners  and  stakeholders  in  the  Bushfire  CRC  who  provided  valuable  feedback  during  the  development  of  this  report.                                          Disclaimer:    This  document  is  constructed  from  consultation  and  research  between  Australasian  Fire  and  Emergency  Service  Authorities  Council  Limited  (AFAC),  its  member  agencies  and  stakeholders.  It  is  intended  to  address  matters  relevant  to  fire,  land  management  and  emergency  services  across  Australia  and  New  Zealand.    The  information  in  this  document  is  for  general  purposes  only  and  is  not  intended  to  be  used  by  the  general  public  or  untrained  persons.  Use  of  this  document  by  AFAC  member  agencies,  organisations  and  public  bodies  does  not  derogate  from  their  statutory  obligations.  It  is  important  that  individuals,  agencies,  organisations  and  public  bodies  make  their  own  enquiries  as  to  the  currency  of  this  document  and  its  suitability  to  their  own  particular  circumstances  prior  to  its  use.    AFAC  does  not  accept  any  responsibility  for  the  accuracy,  completeness  or  relevance  of  this  document  or  the  information  contained  in  it,  or  any  liability  caused  directly  or  indirectly  by  any  error  or  omission  or  actions  taken  by  any  person  in  reliance  upon  it.    Before  using  this  document  or  the  information  contained  in  it  you  should  seek  advice  from  the  appropriate  fire  or  emergency  services  agencies  and  obtain  independent  legal  advice.        

 

   

 

Table  of  Contents  1  Summary  .........................................................................................................................................  1  

2  Project  objectives  .........................................................................................................................  3  3  Background  ....................................................................................................................................  4  

4  Risk  models  and  their  applications  in  land  management  ..............................................  5  

5  Fire,  storms  and  erosion  in  Australia  ....................................................................................  7  5.1  Fire,  rainstorms  and  landforms  ...........................................................................................  7  

5.2  Wildfire  and  erosion  in  Australia:  early  research  (1970  -­‐2000)  .............................  9  5.3  Wildfire  and  erosion  in  Australia:  recent  research  (2000-­‐2012)  .........................  10  

5.4  Summary  of  research  ...........................................................................................................  13  

5.5  Bushfire  CRC  research  in  south  eastern  Australia  –  summary              recent  advances  .......................................................................................................................  15  

6  Fire  and  rainfall  regimes  as  drivers  –  a  regional  analysis  ..........................................  20  7  Guidelines  ....................................................................................................................................  24  

8  Recommendation  for  future  research  priorities  ............................................................  27  

9  References  ...................................................................................................................................  29  Appendix  1  ......................................................................................................................................  34    

       

 

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1  Summary    Predictions  of  erosion  in  burned  catchments  provide  land  managers  with  information  to  carry  out  post-­‐bushfire  risk  assessments  and  optimise  planned  burn  operations  to  minimise  potential  impacts.    The  assessment  of  risk  resulting  from  hydro-­‐geomorphic  processes  can  be  difficult  because  of  factors  such  as  heterogeneous  landscapes  and  patchy  rainfall  as  well  as  transient  and  variable  fire  effects.  There  are  trade-­‐offs  between  i)  the  requirements  from  land  management  agencies,  ii)  data  availability,  and  iii)  the  need  to  generalise  models  beyond  the  exact  conditions  from  which  research  originated.    The  impact  of  fire  on  catchment  properties  has  been  shown  to  increase  erosion  rates  throughout  fire-­‐prone  regions  of  Australia.  The  magnitude  of  the  increase  relative  to  the  unburned  state  is  highly  variable,  ranging  from  10-­‐1000  times  the  background  levels.  Factors  such  as  the  nature  of  the  terrain,  fire  regimes  and  the  frequency  of  intense  rainstorms  all  contribute  to  high  variability  from  region  to  region.  The  largest  documented  erosion  responses  are  those  in  steep  terrain  of  southeast  Australia  where  debris  flow  processes  seem  to  operate  regularly  after  bushfire.      In  parts  of  the  Sydney  basin,  where  the  impacts  of  fire  on  erosion  have  been  studied  intensively,  the  landform  associated  with  the  Hawkesbury  Sandstone  results  in  low  connectivity  between  hill  slopes  and  rivers.  The  plateaux,  cliffs  and  gentle  foot  slopes  in  this  region  contrast  with  the  long,  steep  and  uniform  slopes  of  dissected  uplands  in  the  Alpine  regions  of  southeast  Australia.  This  potentially  causes  differences  in  debris  flow  potential  and  post-­‐fire  erosion  response.  There  is  a  general  lack  of  knowledge  about  south  and  Western  Australia.  However,  the  mountain  ranges  in  these  two  regions  typically  have  lower  slopes  and  are  therefore  subject  to  less  catchment-­‐scale  erosion  potential.  Nevertheless,  studies  in  these  regions  show  that  local  impacts  on  erosion  can  be  large,  especially  where  the  slopes  are  steep.      There  is  significant  variation  in  post-­‐fire  erosion  within  regions  due  to  factors  such  as  variable  soils  and  variable  fire  severity.  Recent  research  with  the  Bushfire  Cooperative  Research  Centre  indicates  that  in  southeast  Australia  the  aridity  of  the  landscape  can  be  an  important  predictor  of  post-­‐fire  erosion.  The  most  sensitive  catchments  are  those  that  are  located  in  dry  sclerophyll  forests  as  opposed  to  those  in  wet  forests.  Using  an  aridity  index  as  a  predictor  significantly  improves  the  spatial  representation  of  surface  runoff  from  hill  slopes  in  landscapes  with  variable  rainfall  and  solar  exposure.  Another  study  with  the  Bushfire  CRC  investigated  the  relative  impacts  of  planned  fire  bushfire  on  erosion  in  small  uniformly  burned  headwater  catchments.  The  results  indicate  that  planned  fire  can  have  significant  impacts  on  erosion,  but  that  these  are  usually  modest  compared  to  the  impacts  of  bushfire.  Differences  in  surface  runoff  (peak  discharge)  seemed  to  drive  the  differences  between  low  severity  and  high  severity  fire.  It  is  unclear  how  these  differences  in  local  erosion  rates  play  out  in  terms  of  water  quality  and  sediment  transport  at  larger  scales  where  patchiness  within  burns,  their  frequency,  their  size  and  their  density  (burns  per  area  per  time)  become  important.                    

 

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The  overall  exposure  of  different  regions  to  erosion  from  burned  areas  can  be  evaluated  by  combining  data  on  fire  regimes,  rainfall  regimes  and  terrain  attributes.  Fire  and  rainfall  regimes  determine  how  frequently  the  landscape  is  primed  for  an  erosion  response.  Terrain  attributes  determine  how  this  ‘priming  process’  translates  to  an  erosion  response.  An  evaluation  of  this  exposure  to  erosion  indicates  that  the  research  efforts  to  date  largely  reflect  the  varying  levels  of  fire-­‐related  erosion  risk  across  the  Australian  landscape.  With  the  exception  of  Tasmania,  the  knowledge  base  is  stronger  in  areas  where  the  potential  for  fire-­‐related  erosion  is  high.      Risk  assessments  provide  critical  information  to  minimize  impacts  of  planned  burning  and  to  respond  to  threats  associated  with  post-­‐wildfire  erosion.  A  measure  of  risk  can  be  obtained  quantitatively  or  qualitatively  by  following  a  set  of  generic  steps  that  link  the  likelihood  of  a  response  at  a  particular  location  with  the  potential  consequence  of  that  response  at  a  valuable  asset.  A  list  of  steps  is  provided  (alongside  spatial  data  on  topographic  erosion  potential)  to  help  guide  this  type  of  risks  assessment.        

 

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2  Project  objectives    The  objective  of  this  project  is  to  develop  guidelines  for  evaluating  erosion  risk  in  burned  catchments.  The  guidelines  are  developed  by  drawing  on  recent  research  on  post-­‐erosion  processes  in  Australia  and  New  Zealand.  The  report  therefore  includes  a  review/synthesis  of  post-­‐fire  erosion  research  in  the  Australian/New  Zealand  region.  The  synthesis  leads  to  a  regional  assessment  of  erosion  risk  as  a  result  of  fire.  The  regional  assessment  allows  for  a  preliminary  screening  of  the  areas  in  Australia  (and  New  Zealand)  that  are  most  at  risk  and  where  the  knowledge  base  is  lacking.  The  synthesis  and  regional  assessment  of  risk  are  used  in  the  development  of  guidelines  for  i)  assessing  risk  associated  with  erosion  in  burned  catchments,  and  ii)  monitoring  and  evaluation  of  impacts  of  management  interventions.      The  key  questions  to  be  addressed  in  the  guidelines  are:    

� What  are  the  key  relevant  Bushfire  CRC,  and  other,  research  findings  and  how  are  these  related  to  geomorphic  landscapes  of  Australia  and  New  Zealand?    

� What  are  the  implications  for  operational  applications  in  fire  and  land  management  agencies  in  Australia  and  New  Zealand?  

� What  are  the  limitations  (data,  process  understanding,  conceptual  analogues,  etc.)  to  quantifying  the  post  fire  hydro-­‐geomorphic  risks  across  diverse  landscape  and  climate  conditions?    

The  approach  to  developing  the  guidelines  involves:      

� A  desk-­‐top  synthesis  of  the  current  knowledge  of  post-­‐fire  erosion  process  in  Australia  and  New  Zealand.  

� An  assessment  of  the  degree  to  which  the  existing  knowledge  base,  largely  developed  following  the  2001  Sydney  fires  and  recent  Victoria  fires  (2003-­‐2009),  can  be  extended  to  different  geographic  and  climatic  regions.    

� Developing  qualitative  guidelines  based  on  risk  factors  in  particular  geomorphic  regions  to  assess  risk  to  water  quality.    

 This  is  seen  as  the  first  phase  in  an  utilisation  pathway  that  has  the  potential  to  lead  to  the  development  of  GIS  algorithms  and  further  intensive  and  specific  studies  for  agencies.  Additional  research  could  lead  to  parameterisation  of  catchment  models  to  optimise  burn  scheduling,  placement  and  erosion  risk  in  water  supply  catchment  that  are  exposed  to  wildfire.                    

 

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3  Background    Erosion,  flash  floods  and  debris  flows  are  hydro-­‐geomorphic  processes  that  intensify  due  to  catchment  disturbance  by  fire.  Predictive  models  of  these  processes  can  be  and  are  used  by  land  managers  to  assess  risk  to  assets,  prioritise  resources  and  evaluate  trade-­‐offs  between  different  management  strategies.  Assessing  risk  as  a  result  of  hydro-­‐geomorphic  processes  can  be  difficult  because  of  factors  such  as  heterogeneous  landscapes,  patchy  rainfall,  and  the  transient  and  variable  effects  of  fire  (Nyman  et  al.  2013a).  There  are  trade-­‐offs  between  i)  the  requirements  from  land  management  agencies,  ii)  data  availability,  and  iii)  the  need  to  generalise  models  beyond  the  exact  conditions  in  which  the  research  originated.      Recent  research  with  the  Bushfire  CRC  (Fire  in  the  Landscape)  has  provided  new  insights  into  the  impacts  of  prescribed  fire  and  bushfire  on  catchment  processes,  although  the  lack  of  site-­‐specific  data  across  different  regions  means  that  the  magnitude  of  impact  is  unknown  for  most  systems  in  southeast  Australia.  The  lack  of  site-­‐specific  data  means  that  exact  predictions  of  post-­‐fire  erosion  in  different  fire-­‐management  regions  is  generally  not  feasible.  However,  our  research  shows  that  there  are  fundamental  components  of  hydro-­‐geomorphic  processes  that  can  be  used  to  develop  a  general  framework  and  guidelines  for  evaluating  risk  associated  with  post-­‐fire  runoff  and  erosion.  Broad  guidelines  help  ensure  that  the  procedures  for  evaluating  risk  are  consistent  with  the  current  knowledge  of  processes  that  constitute  risk.  More  specific  risk  models  can  be  tailored  for  different  geographic  regions,  with  different  levels  of  detail  in  the  risk  metrics,  depending  on  data  availability  and  underlying  management  questions.                                    

 

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4  Risk  models  and  their  applications  in    land  management    Risk  models  vary  in  the  confidence  of  predictions  and  they  vary  in  terms  of  the  physical  processes  that  are  represented  (Nyman  et  al,  2013a).  Suitable  approaches  for  modelling  risk  depend  on  the  land  management  issue  and  the  availability  of  data  for  a  particular  catchment  or  region  (Figure  1).  Managing  risk  to  water  quality  in  a  water  supply  reservoir,  for  instance,  may  require  models  with  accurate  predictions  of  the  frequency  and  magnitude  of  sediment  yields  that  are  produced  as  a  result  of  fire.  Our  research  team  is  working  towards  this  type  of  model  as  part  of  an  ongoing  project  with  Melbourne  Water  (Smith  et  al.  2009).  This  type  of  quantitative  risk  model  (situated  at  the  bottom  right  of  figure  1);  is  parameter  intensive  and  requires  a  large  amount  of  data  to  be  applied  and  validated  in  a  particular  catchment.    In  some  land  management  applications,  the  quantitative  approach  may  result  in  models  that  are  over-­‐parameterised,  providing  more  information  than  required,  and  too  much  detail  for  effective  implementation  in  existing  management  procedures.  This  may  be  the  case  during  rapid  assessment  of  post-­‐wildfire  hydro-­‐geomorphic  risks,  where  models  need  to  be  applied  to  large  areas  where  data  is  limited  and  where  there  is  a  need  to  rapidly  identify  potential  hazards  (Department  of  Environment  and  Primary  Industries,  2013).  For  this  type  of  application,  the  level  of  detail  in  risk  models  must  be  aligned  with  the  type  of  management  setting  in  which  they  are  used  (Sheridan  et  al,  2011).  A  set  of  risk  categories  (situated  at  the  centre  of  figure  1),  or  a  qualitative  risk  model,  is  therefore  more  suitable  for  supporting  decision  making  than  the  predictions  of  actual  sediment  loads  at  a  particular  asset.      Both  types  of  risk  models  (quantitative  and  qualitative)  may  be  needed  when  planning  and  managing  the  potential  impacts  associated  with  prescribed  burning.  In  high  value  catchments  (e.g.  water  supply  reservoir),  for  instance,  a  catchment  manager  may  want  to  understand  the  magnitude  of  the  risk  associated  with  prescribed  burning  in  a  critical  water  supply  catchment,  in  which  case  the  model  needs  to  capture  the  relation  between  fire  severity  and  sediment  delivery  to  the  reservoir,  which  is  a  large  undertaking  requiring  detailed  knowledge/data  on  the  conditions  in  a  particular  catchment.  In  other  cases,  it  may  be  more  practical  to  have  simple  models  that  highlight  where  within  the  landscape  that  a  burn  is  most  likely  to  cause  erosion  with  adverse  impacts  on  water  quality.  This  would  provide  fire  managers  with  the  means  to  mitigate  some  of  the  potential  impacts.  Mitigation  can  take  place  before  a  fire,  during  planned  fire  (Russell-­‐Smith  et  al.  2006);  through  investment  in  treatment  capacity  (White  et  al.  2006);  or  it  can  take  place  after  a  wildfire  in  post-­‐fire  emergency  risk  assessments  (e.g.  Sheridan  et  al.  2009).              

 

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   Figure  1.  The  type  of  models  used  for  risk  assessments  vary  depending  on  the  management  setting  (top  axis)  and  the  scientific  knowledge  (left  axis)  of  the  underlying  hydro-­‐geomorphic  processes.    In  an  ideal  world,  all  risk  assessments  would  be  quantitative,  and  conducted  using  site-­‐specific  erosion  models  as  shown  in  the  bottom  right  corner  of  figure  1.  However,  the  application  of  these  models  may  not  be  feasible  because:  i)  data  may  not  be  available  for  a  particular  catchment,  or  ii)  the  models  are  complex,  time-­‐consuming  and  difficult  to  work  with,  and  thus  unsuitable  for  a  particular  land  management  setting.  The  risk  assessment  approach  described  in  this  report  is  situated  toward  the  middle  and  upper  left  of  this  diagram.    The  suitability  of  particular  risk  models  for  the  different  needs  of  agencies  will  vary  due  to  a  range  of  factors  such  as  their  different  management  settings  and  different  levels  of  knowledge.  The  process  of  research  utilisation  across  a  region  may  therefore  take  different  trajectories  for  different  agencies.  The  first  step  is  to  identify  risk  factors  through  a  broad  landscape  analysis  and  a  review  of  the  erosion  literature  from  the  region.  This  provides  an  overview  of  the  erosion  processes  likely  to  operate  in  different  landforms  where  topography,  vegetation,  soil  and  fire  properties  vary.  This  information  can  be  mapped  across  the  landscape  according  to  different  geomorphic  response  units.      One  example  of  a  geomorphic  response  unit  is  the  dissected  uplands  of  eastern  Victoria,  a  landform  which  might  extend  into  to  the  Snowy  Mountains  (NSW)  and  the  Namadgi  National  Park  (ACT).  Another  landform  is  the  scarps  and  cliffs  associated  with  the  Hawkesbury  Sandstone  in  the  Nattai  Catchments  near  Sydney.  Landform  classification  provides  a  basis  on  which  to  identify  key  risk  factors  and  to  extrapolate  research  findings  from  one  region  to  another.  Erosion  processes  in  some  landforms  may  have  been  studied  in  detail  and  risk  models  for  these  areas  can  be  devised  without  much  additional  research  effort.  The  main  challenge  is  to  ensure  that  models  developed  for  one  set  of  catchment  conditions  can  be  transferred  and  applied  in  another  catchment.  Some  of  the  issues  regarding  the  transfer  of  models  from  one  location  to  another  can  be  addressed  as  part  of  a  broad-­‐scale  analysis  of  the  landscape.  However,  additional  site  visits  would  be  required  for  validation.  Other  landforms  for  which  there  is  limited  data  and,  in  the  case  of  high  value  assets,  there  may  be  a  case  for  doing  more  field-­‐based  research  to  provide  a  stronger  basis  for  quantifying  risk.      

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Figure 1. The type of models used for risk assessments vary depending on the management setting (top axis) and the

scientific knowledge (left axis) of the underlying hydro-geomorphic processes. In an ideal world, all risk assessments

would be quantitative, and conducted using site-specific erosion models shown in bottom right corner of the figure.

However, the application of these models may not be feasible because: i) data may not be available for a particular

catchment, or ii) the models are complex, time-consuming and difficult to work with, and thus unsuitable for a particular

land management setting. The grey box in the figure shows the region of the knowledge-management space that this

report is targeting.

Different management settings (agency needs) and different levels of knowledge means that suitable risk models for a

particular agency will vary. The process of research utilization across a region may therefore take different trajectories for

different agencies. The first step is to identify risk factors through a broad landscape analysis and a review of the erosion

literature from the region. This provides an overview of the erosion processes likely to operate in different landforms

where topography, vegetation, soil and fire properties vary. This information can be mapped across the landscape

according to different geomorphic response units.

One example of a geomorphic response unit is the dissected uplands of eastern Victoria, a landform which might extend

into to the Snowy Mountains (NSW) and the Namadgi National Park (ACT). Another landform is the scarps and cliffs

associated with the Hawkesbury sandstone in the Nattai Catchments near Sydney. Landform classification provides a

basis on which to identify key risk factors and to extrapolate research findings from one region to another. Erosion

processes in some landforms may have been studied in detail and risk models for these areas can be devised without

much additional research effort. The main challenge is to ensure that models developed for one set of catchment

conditions can be transferred and applied in another catchment. Some of the issues regarding the transfer of models

from one location to another can be addressed as part of a broad-scale analysis of the landscape. However, additional

site visits would be required for validation. Other landforms for which there is limited data and, in the case of high value

assets, there may be a case for doing more field-based research to provide a stronger basis for quantifying risk.

 

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5  Fire,  storms  and  erosion  in  Australia    

5.1  Fire,  rainstorms  and  landforms    Fire  results  in  increased  erosion  because  of  increases  to  runoff  production  and  reduced  resistance  of  soil  to  erosion  (Prosser  and  Williams  1998).  Following  fire,  increases  in  erosion  result  in  sediment  being  supplied  from  hill  slopes  and  headwaters  to  streams  and  rivers  at  higher  rates  than  before  the  fire.  This  has  implications  for  water  quality  (Smith  et  al.  2011).    The  role  of  fire  in  causing  changes  to  erosion  rates  and  water  quality  depends  on  three  key  factors:    

� Fire  regime.  � Rainfall  regime.  � Landscape  attributes  (terrain  and  soil).  

 These  factors  contribute  to  regional  variation  in  the  strength  of  the  interaction  between  fire  and  surface  processes  (Moody  et  al.  2013;  Nyman  et  al.  2013a).    In  areas  with  frequent  fire  (but  very  little  rainfall),  such  as  semi-­‐arid  parts  of  interior  Australia,  there  is  likely  to  be  frequent  impacts  of  fire  on  soil  and  vegetation,  but  little  impact  on  water  erosion.  Low  rainfall  in  these  areas  may  mean  that  erosion  by  wind  is  more  important.  Conversely,  the  erosion  in  a  flat  area  with  frequent  fires  and  frequent  rainstorms,  such  as  the  savannah  landscapes  of  Northern  Australia  may  be  relatively  insensitive  to  fire  because  the  low  slope  gradient  results  in  low  stream  power.  In  New  Zealand,  the  relatively  low  flammability  of  the  forest  probably  means  that  fire  is  not  an  important  control  on  erosion  and  sediment  transport.      The  impact  of  fires  on  erosion  rates  is  likely  to  be  at  a  maximum  in  steep  forested  areas  where  i)  background  erosion  rates  are  low,  ii)  fire  severity  is  high,  ii)  where  there  is  high  relief  and  where  iv)  fire  results  in  large  changes  to  surface  runoff.  In  very  broad  terms  one  would  expect  these  to  vary  with  landscape  relief  (or  areas  with  steep  slopes)  and  the  biome  (figure  2  a  and  b).    In  general,  the  variable  terrain  is  likely  to  contribute  towards  much  higher  erosion  along  the  Great  Dividing  Ranges  in  the  east  and  southeast.  In  terms  of  fire  regimes,  the  main  regional  effect  is  that  some  systems,  such  as  tropic  al  rainforests  in  Queensland  or  wet  temperate  forest  in  New  Zealand,  very  rarely  burn  in  wildfire.  In  wet  forests  of  the  temperate  region  in  southeast  Australia  and  Tasmania  the  fire  frequency  is  low  but  the  severity  and  size  of  fires  can  be  significant.  In  Mediterranean–type  biomes  along  the  South/Western  Australia  coast,  the  dry  conditions  mean  more  frequent  fire,  but  because  the  fuel  loads  are  relatively  low,  the  severity  is  lower  and  bushfires  are  smaller.      In  the  following  section,  the  existing  literature  on  fire  and  erosion  in  Australia  and  New  Zealand  is  synthesised  with  the  aim  of  1)  identifying  the  relative  importance  of  fire  in  controlling  erosion  rates  and  2)  assessing  the  degree  to  which  the  existing  knowledge  base  can  be  used  to  assess  erosion  risk  in  different  geographic  and  climatic  regions.  The  synthesis  draws  on  early  research  from  the  south  eastern  Australia  region,  as  well  as  more  recent  studies  carried  out  in  response  to  the  large  regional  bushfires  that  have  burned  throughout  Canberra,  Victoria  and  NSW  over  the  last  decade  or  so.      

 

8    

   Figure  2.  a)  Slope  (in  degrees)  calculated  from  a  90  m  Digital  Elevation  Model  (SRTM:  http://srtm.csi.cgiar.org/).  b)  Biomes  of  Australia  (Olson  et  al.  2001).        

 

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5.2  Wildfire  and  erosion  in  Australia:  early  research  (1970  -­‐2000)    Some  of  the  earliest  literature  on  post-­‐fire  erosion  in  Australia  dates  back  to  a  robust  catchment-­‐scale  study  by  (Brown  1972)  in  the  Upper  Tumut  of  the  Snowy  Mountain  Region  of  NSW,  which  was  burned  by  a  ~700  km2  bushfire  in  1965.  The  area  consisted  of  dry  Eucalypt  forests  and  some  alpine  woodland  at  higher  elevation.  The  study  documented  substantial  increases  in  sediment  loads,  as  a  result  of  increased  sediment  availability  and  overland  flow.  The  maximum  sediment  concentration  in  the  post-­‐fire  period  was  high  (120-­‐157  gL-­‐1)  and  1-­‐2  orders  of  magnitude  higher  than  the  maximum  concentration  measured  in  the  decade  prior  to  the  bushfire.  The  majority  of  the  erosion  occurred  as  a  result  of  a  few  large  rainstorms.  Within  about  two  years,  the  sediment  concentration  had  returned  towards  background  values,  although  surface  runoff  remained  above  background  levels  for  more  than  four  years.      Another  body  of  literature  emerged  following  a  series  of  bushfires  in  south  eastern  Australia  between  1979  and  1983.  Plot-­‐scale  studies  in  Hawkesbury  Sandstone  catchments  in  Sydney  Basin  (NSW)  showed  that  bushfire  (moderate  severity)  has  the  potential  to  increase  plot-­‐scale  sediment  yield  by  up  to  1000  times  the  background  rate,  but  that  the  extent  of  the  increase  was  strongly  dependent  on  the  intensity  of  rainfall  during  the  post-­‐fire  window  of  disturbance  (Blong  1982;  Atkinson  1984).  A  later  study  (Prosser  and  Williams  1998),  conducted  within  the  same  geomorphic  setting,  measured  similar  responses  and  reinforced  the  idea  that  rainfall  is  a  large  source  of  variation  in  post-­‐fire  erosion  rates.  At  the  plot  scale,  the  erosion  rates  on  burned  hill  slopes  increased  sharply  for  30  minute  rainfall  intensities,  I30  >  13  mm  h-­‐1.      In  a  contrasting  geomorphic  setting,  Leitch  et  al.  (1984)  measured  the  sediment  yield  from  a  small  and  steep  headwater  catchment  in  the  Central  Highlands  of  Victoria  that  had  been  subject  to  an  intense  rainfall  event  (17  mm  in  less  than  1  hour)  weeks  after  bushfire  in  1983.  The  catchment,  which  is  typical  of  the  mountainous  regions  of  eastern  Victoria,  produced  a  sediment  yield  of  22  t  ha-­‐1  which  is  equivalent  to  more  than  20  years  of  background  erosion  (<  1  t  ha-­‐1  year-­‐1)  in  these  forested  systems.  The  event  resulted  in  2  900  kg  of  nitrogen  and  220  kg  of  phosphorus  being  eroded  from  hill  slopes.      In  the  far-­‐east  Gippsland  region  of  Victoria,  also  following  bushfires  in  1983,  a  catchment-­‐scale  (40-­‐560  km2)  study  of  water  quality  indicated  that  the  impacts  of  wildfire  could  be  substantial  with  sediment  concentrations  increasing  by  up  to  2  orders  of  magnitude  (from  monthly  pre-­‐fire  peaks  of  10  mgL-­‐1  to  post-­‐fire  peaks  of  1000  mg  L-­‐1)  (Chessman  1986).  The  majority  of  the  erosion  occurred  in  response  to  two  or  three  rainstorms  within  the  first  few  months  of  the  bushfire,  with  daily  rainfall  totals  between  50  and  100  mm.  The  erosion  was  highest  in  the  drier  forests  where  poorly  developed  soils  promoted  surface  run-­‐off  and  strong  peaks  in  discharge.  The  deeper,  more  permeable  soils  in  catchments  with  wet  forests  seemed  to  limit  the  erosion  response,  despite  the  terrain  being  similar.        

 

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5.3  Wildfire  and  erosion  in  Australia:  recent  research  (2000-­‐2012)    5.3.1  Hawkesbury  Sandstone,  Sydney  Basin  -­‐  Dry  sclerophyll  forests    Erosion  in  the  catchments  above  Lake  Burragorang  near  Sydney  following  bushfire  in  2001  resulted  in  large  sediment  yields  from  hill  slopes  (5-­‐20  t  ha-­‐1  )  (Shakesby  et  al.  2003),  but  most  of  this  sediment  was  redistributed  locally  on  the  slopes  and  only  1  per  cent  was  delivered  to  the  Nattai  River  (Tomkins  et  al.  2007).  The  relatively  subdued  impact  on  sediment  transport  and  water  quality  in  the  Nattai  River  was  attributed  to  i)  low  connectivity  between  drainage  networks  and  hill  slopes  (Blake  et  al.  2009;  Wilkinson  et  al.  2009)  and  ii)  few  high  intensity  rainstorm  following  the  bushfire  (Tomkins  et  al.  2008).  Research  following  the  Sydney  bushfires  in  2001  indicates  that  post-­‐fire  erosion  within  the  Hawkesbury  Sandstone  in  the  Sydney  Basin  is  strongly  affected  by  features  that  are  distinctive  to  that  particular  geology  (Shakesby  et  al.  2007).  Gentle  slopes  on  the  plateaux  and  sandstone  cliffs  as  well  as  the  deep  colluvial  deposits  on  foot  slopes  and  valley  floor  are  in  many  ways  unique  to  Hawkesbury  Sandstone  and  not  representative  of  catchments  that  characterise  a  large  proportion  of  Australian  uplands  (e.g.  the  Great  Dividing  Ranges  in  south  eastern  Australia,  eastern  Tasmania  and  Mt  Lofty  Ranges  in  South  Australia).      5.3.2  Cotter  River  catchments,  Canberra  -­‐  Dry  sclerophyll  forests  and  sub-­‐alpine  woodland    An  intense  wildfire  in  2003  caused  extreme  erosion  response  and  large  impacts  on  water  quality  in  the  Cotter  catchments  (White  et  al.  2006).  In  the  Bendora  Dam,  where  fire-­‐related  erosion  response  was  most  severe,  a  total  of  19  300  tonnes  of  sediment  and  1900  tonnes  of  organic  matter  was  delivered  into  the  reservoir  from  upstream  catchment  (White  et  al.  2006).  The  erosion  was  primarily  caused  by  two  intense  rainstorms  with  total  rainfall  in  the  range  30-­‐50  mm  and  annual  exceedance  probabilities  of  two  to  five  years.  The  exact  intensities  are  unknown.  The  effects  on  water  quality  in  the  reservoir  were  substantial  with  turbidity  exceeding  previous  maximums  by  a  factor  of  30  and  with  an  order  of  magnitude  increase  in  iron  and  manganese;  ultimately  resulting  in  the  construction  of  a  new  treatment  plant  to  reduce  vulnerability  of  water  supply  should  similar  events  occur  in  the  future.  Investigations  into  the  frequency  of  these  extreme  fire-­‐related  erosion  responses  indicate  that  the  last  event  of  similar  magnitude  occurred  about  400  years  ago  (Worthy  and  Wasson  2004).      5.3.3  North-­‐east  Victoria  -­‐  Wet  sclerophyll  forests    Large  bushfires  in  2003  affected  much  of  the  alpine  region  in  northeast  Victoria,  NSW,  and  Canberra.  An  intensive  study  on  post-­‐fire  water  quality  impacts  and  erosion  processes  was  carried  out  in  wet  (Alpine  Ash)  forests  in  northeast  Victoria  (Lane  et  al.  2006;  Sheridan  et  al.  2007a;  Noske  et  al.  2010;  Nyman  et  al.  2010;  Lane  et  al.  2011).  The  study  showed  that  the  macro  porous  soil  in  these  wet  ecosystems  resulted  in  high  infiltration  rates  and  hill  slopes  that  were  largely  disconnected  from  the  stream  network  in  terms  of  erosion,  even  during  intense  rainfall.  Most  of  the  sediment  was  sourced  from  within  a  few  metres  of  the  channels.  Relative  to  unburnt  conditions  there  was  a  nine-­‐fold  increase  in  sediment  yield  in  first  year  after  the  fire.  In  terms  of  total  yield,  this  was  relatively  low  compared  to  the  post-­‐fire  erosion  measured  in  similar  landforms  but  in  drier  forest  environments  (e.g.  Leitch  et  al.  1984;  White  et  al.  2006).  However,  given  that  50  per  cent  of  the  sediment  was  produced  during  a  single  storm  event,  this  meant  that  the  maximum  sediment  concentration  was  very  high  within  the  event  (~  45  000  mg  L-­‐1)  compared  to  background  levels  (250  -­‐1000  mg  L-­‐1)  (Sheridan  et  al.  2011).          

 

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5.3.4  Alpine  Region,  south  eastern  Australia  –  Sub-­‐alpine  woodlands    In  higher  elevation  in  alpine  and  sub-­‐alpine  environments  (Snow  Gum  and  Alpine  Ash)  the  effects  of  wildfire  on  erosion  and  water  quality  are  poorly  documented.  A  study  of  surface  lowering  of  burned  and  unburned  hill  slopes  by  (Smith  and  Dragovich  2008)  showed  substantial  increase  in  hill  slope  erosion  as  a  result  of  wildfire  but  that  the  overall  rates  of  hill  slope  erosion  (3.3  –  26.1  t  ha-­‐1)  were  low  compared  to  rates  measured  in  lower  elevation  dry  sclerophyll  forests  (>  100  t  ha-­‐1).  Data  from  alpine  environment  in  the  Bogong  High  Plains  indicate  that  fire  had  significant  effects  on  erosion  with  monthly  post-­‐fire  sediment  fluxes  between  135  and  178  g  m-­‐2,  which  is  equivalent  to  1.35  t  ha-­‐1  per  month.  While  these  11  rates  are  low  compared  to  post-­‐fire  erosion  rates  in  steep  forested  regions  of  SE  Australia,  they  do  represent  a  risk  in  terms  of  land  degradation  in  sensitive  alpine  environments  (Dunkerley  et  al.  2009).      5.3.5  Eastern  Upland  of  Victoria  -­‐  Dry  sclerophyll  forests    Adopting  a  landscape  scale  approach  to  quantifying  post-­‐fire  erosion,  Nyman  et  al.  (2011)  found  that  water  quality  impacts  following  bushfire  can,  more  often  than  not,  be  attributed  to  extreme  erosion  events  that  occur  in  patches  where  high  intensity  storm  cells  overlap  with  steep  terrain,  high  severity  burns  in  dry  forest  environments.  Reports  of  mud  torrents  and  flash  floods  were  followed  up  with  detailed  surveys  which  could  establish  that  runoff-­‐generated  debris  flows  were  the  main  process  by  which  sediment  was  transported  from  hill  slopes  and  headwaters  to  streams  and  rivers.  The  events  were  triggered  by  surface  run-­‐off  and  widespread  sheet  erosion  on  hill  slopes  in  steep  headwater  catchments.  When  slurries  of  ash,  sediment  and  water  entered  the  drainage  network,  the  channel  sediment  was  also  eroded,    contributing  to  efficient  delivery  of  sediment  first  to  third  order  drainage  networks.  The  events  described  in  (Nyman  et  al.  2011)  are  similar  to  the  study  by  (Leitch  et  al.  1984)  and  extreme  erosion  events  described  in  fire-­‐prone  and  mountainous  regions  elsewhere  such  as  the  Mediterranean  (García-­‐Ruiz  et  al.  2012)  and  western  US  (Cannon  et  al.  2003).  The  sediment  eroded  by  these  localised  debris  flows  resulted  in  a  large  volume  of  sediment  (>  100  t  ha-­‐1)  being  released  into  upland  rivers  and  streams  where  clay,  silt  and  water  quality  constituents  are  transported  by  rivers  to  downstream  lakes  and  reservoirs  (Sheridan  et  al.  2007b),  posing  considerable  risk  to  aquatic  ecosystems  (Lyon  et  al.  2008)  and  water  supply  (Smith  et  al.  2011).      5.3.6  Mt  Lofty  Ranges  and  Darling  Ranges  –  Dry  sclerophyll  forest,  Jarrah  and  shrubby  woodland    At  Mt  Bold  in  the  Mt  Lofty  Ranges,  South  Australia,  (Morris  et  al.  2012)  measured  a  mean  surface  lowering  of  ~  20  mm  after  a  bushfire  in  steep,  rocky  and  dry  shrubby  forest  catchments.  The  degree  of  erosion  was  strongly  dependent  on  slope  gradient  (very  sharp  increase  in  erosion  for  slopes  greater  than  25  degrees).  Slope  curvature  was  also  important  with  concave  portions  of  the  hill  slope  being  more  susceptible  to  erosion  than  linear  slopes.  Most  of  the  erosion  took  place  during  an  intense  rainfall  event  with  annual  exceedance  probability  of  ~20%.  A  study  into  long-­‐term  depositional  processes  in  valley-­‐fill  at  the  Mt  Lofty  Ranges  (Buckman  et  al.  2009)  indicates  that  fire  events  throughout  the  Holocene  (i.e.  in  the  last  6000  years  or  so)  have  usually  been  associated  with  increased  in  sediment  delivery  from  hill  slopes.  So  fire  in  this  landscape  is  likely  to  be  an  important  control  on  erosion.                    

 

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In  the  Jarrah  Forest  of  Western  Australia,  there  is  not  much  research  on  fire  and  erosion  However,  observations  following  a  large  bushfire  in  January  2005  indicate  that  large  erosion  events  can  occur  in  this  environment,  given  high  intensity  fire  and  subsequent  heavy  rainfall.  The  fire  burned  through  three  water  supply  catchments  including  some  steep  sections  of  the  Darkin  River  catchment  which  feeds  the  Mundaring  Reservoir  and  which  had  high  fuel  loads  due  to  a  long  period  without  fire  (Cheney  2010).  The  impacts  on  water  quality  at  the  reservoir  wall  were  minimal  despite  some  heavy  rainfall  (44  mm  and  72  mm  on  March  28  and  May  19  respectively)  (Bartini  and  Barrett  2007).  In  the  river  system,  however,  and  within  the  upper  part  of  reservoir,  there  was  evidence  of  some  severe  erosion,  with  a  total  of  ~  1000  m3  of  sediment,  ash  and  organic  material  having  to  be  removed  from  the  stilling  pond  the  Little  Darkin  Weir.      5.3.7  Eastern  Tasmania-­‐  Dry  sclerophyll  forest  and  shrubby  woodland    In  Tasmania,  there  has  been  very  little  research  in  post-­‐fire  erosion  and  water  quality  impacts.  However,  a  hill  slope  experiment  (Wilson  1999)  on  erodible  granite  near  St  Helens  on  the  east  coast  indicates  that  the  effect  of  fire  on  erosion  can  be  large  even  for  relatively  gentle  slopes  (15  degrees).  The  erosion  rate  was  strongly  dependent  on  the  stream  power  (or  discharge).  Erodibility  of  the  burned  slopes  was  very  high,  but  the  relatively  high  infiltration  capacity  of  was  limiting  the  amount  of  erosion  on  the  plots.  Bursts  with  rainfall  intensity  in  excess  of  50  mm  h-­‐1  were  required  to  produce  substantial  surface  runoff  and  erosion.  There  are  studies  that  provide  a  longer-­‐term  perspective  on  the  role  of  fire  in  shaping  the  soils  currently  mantling  the  hill  slopes  in  Tasmania  (McIntosh  et  al.  2005;  Fletcher  et  al.  2014).  The  12  studies  indicate  that  post-­‐fire  erosion  is  an  important  landscape  process  leading  to  distinct  spatial-­‐temporal  patterns  of  variability  in  soil  physical  properties  and  their  nutrient  status.      5.3.8  Northern  Territory  Kakadu  region  –  savannah  woodland    High  intensity  rainfall  is  common  in  the  tropical  north  at  the  beginning  of  the  wet  season;  fires  burn  the  landscape  at  high  rates  (almost  annually);  and  the  soils  can  be  highly  erodible.  The  combination  of  these  factors  may  result  in  fire  having  an  important  role  in  soil  erosion,  even  though  the  terrain  is,  in  most  part,  less  rugged  than  the  ranges  in  south  eastern  Australia.  Research  indicates  that  due  to  the  relatively  flat  terrain,  the  effect  of  fires  on  erosion  is  low  compared  to  other  tropical  systems  (Townsend  and  Douglas  2000;  Townsend  and  Douglas  2004).  However,  significant  increases  in  sediment  concentration  and  water  constituents  were  measured  when  catchments  burned  late  in  the  dry  season,  when  intensities  were  higher  than  early  dry  season  fires,  and  when  the  timing  of  fire  impacts  occurred  closer  to  the  onset  of  erosive  rainfall.  For  late  season  bushfire,  the  concentration  of  sediment  and  other  constituents  were  up  by  a  factor  of  10  during  episodic  run-­‐off  early  in  the  wet  season,  while  during  base  flow  later  in  the  wet  season  the  concentrations  were  up  by  a  factor  of  two  to  three.  Managing  fires  and  promoting  fires  early  in  dry  season  is  therefore  recommended  in  terms  of  reducing  erosion  and  limiting  the  chance  of  land  degradation  and  water  quality  impacts  (Russell-­‐Smith  et  al.  2006).        

 

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5.4  Summary  of  research    It  is  difficult  to  determine  exactly  what  causes  variation  in  post-­‐fire  erosion.  However  an  obvious  factor  is  terrain  (slope  and  relief)  and  variable  catchment  attributes  (soil).  Terrain  varies  depending  on  geology  and  history  of  uplift,  denudation  and  incision.  In  the  Hawkesbury  Sandstone  the  geology  seems  to  be  an  important  factor  contributing  to  low  connectivity  between  hill  slopes  and  the  river  network.  In  the  Alpine  region  of  Victoria,  as  well  as  in  Canberra  and  New  South  Wales,  the  high  relief  and  relatively  steep  slopes  seem  to  correspond  with  the  largest  post-­‐fire  erosion  responses.  However,  the  wetter  forest  types  in  this  region  seem  to  have  a  somewhat  muted  response  compared  to  the  drier  systems,  and  this  is  linked  to  differences  in  soil  properties.  Soils  vary  at  small  spatial  scales  and  it  is  difficult  to  determine  how  it  contributes  to  variation  between  regions.  One  pattern  that  is  emerging  from  research  in  central  and  north  eastern  Victoria  is  that  forest  type  (a  proxy  for  water  availability)  is  important  and  is  causing  variation  in  erosion  response  within  the  region.      A  common  theme  to  almost  all  studies  is  that  the  majority  of  erosion  occurs  within  a  very  few  storm  events  during  which  the  rainfall  intensity  is  high.  This  dependency  on  rainstorms  (and  its  randomness)  is  a  critical  factor  to  consider  when  modelling  erosion  and  evaluating  risk.  In  the  Nattai  Catchment  near  Sydney,  the  relatively  low  erosion  rate  following  bushfire  in  2001  was  attributed  to  the  lack  of  intense  rainfall.  And  it  was  argued  that  this  is  likely  to  be  a  general  pattern  because  of  lower  than  average  rainfall  during  the  dry  periods  when  large  bushfires  are  more  common.  It  is  unclear,  however,  if  reduced  annual  rainfall  corresponds  with  reduced  frequency  of  high  intensity  storms.  Catastrophic  bushfires  in  Victoria  in  2009  were  followed  by  two  years  with  annual  rainfall  that  was  higher  than  the  10  preceding  years.      Table  1  summarises  the  impact  of  bushfire  on  erosion  relative  to  unburned  erosion  rates.  The  largest  recorded  responses  include  the  extreme  erosion  in  eastern  uplands  of  Victoria  (2003-­‐2009),  the  Cotter  Catchments  (2003)  and  those  reported  by  Brown  in  the  upper  Tumut  in  1972.  The  most  subdued  impacts  are  probably  those  recorded  in  the  northern  territory.  Literature  on  post-­‐fire  erosion  in  New  Zealand  is  lacking,  possibly  reflecting  the  relatively  low  importance  of  fire  disturbance  on  catchment  processes  in  this  region  (McIntosh  et  al.  2005),  relative  to  the  other  geomorphic  processes  such  as  landslides  and  debris  flows  from  flooding  rainfall  and  snowmelt.          

 

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5.5  Bushfire  CRC  research  in  south  eastern  Australia  –  summary  of  recent  advances      5.5.1  Burned  landscapes  and  erosion:  aridity  as  a  predictor  Crowning  bushfires  typically  act  as  a  homogenising  agent  whereby  landscape  variability  due  to  vegetation  diminishes.  The  landscape  is  reset  and  hill  slopes  are  smooth,  un-­‐vegetated  and  covered  with  non-­‐cohesive  and  easily  erodible  material  (Nyman  et  al.  2013b).  This  means  that  the  main  control  on  variation  in  erosion  is  infiltration  capacity.  High  infiltration  capacity  reduces  surface  run-­‐off,  which  is  the  main  agent  of  erosion  and  sediment  transport.  In  wet  Eucalypt  forests  of  Victoria,  for  instance,  the  macro-­‐porous  soils  and  high  infiltration  capacity  (>  100  m  h-­‐1)  seems  to  limit  the  amount  of  erosion  from  burned  hill  slopes.  Dry  forests  in  nearby  foothills,  however,  have  lower  infiltration  capacities  (<50  mm  h-­‐1)  resulting  in  much  higher  erosion  rates.  In  Victoria,  this  climatic  driven  variation  in  soil  infiltration  capacity  seems  to  be  driving  landscape-­‐scale  variability  in  erosion.  This  effect  can  be  seen  in  data  from  Aberfeldy  fire  near  the  Thompson  Reservoir,  where  post-­‐fire  run-­‐off  rates  where  measured  on  hill  slopes  across  different  levels  of  aridity  (Figure  3).  Aridity  is  the  balance  between  potential  evapotranspiration  and  rainfall  (i.e.  water  availability)  and  has  been  quantified  for  a  large  area  using  measures  of  net  radiation  and  rainfall  that  represent  regional  variation  as  well  as  local  topographic  effects  (Nyman  et  al.  2014).        

   Figure  3.  Relationship  between  peak  discharge  (m3  h-­‐1),  rainfall  intensity  (mm  h-­‐1)  and  aridity  (-­‐)  in  forests  near  the  Thompson  Catchment  in  Victoria.  A  simple  2-­‐parameter  function  accounts  for  85%  of  variation.  The  runoff  data  was  collected  for  1  year  post-­‐fire,  at  3  min  intervals  from  8  m  plots,  on  hill  slopes  burned  by  crowning  fire  during  the  Aberfeldy  fire  in  February  2013.  Data  (unpublished)  from  Rene  van  der  Sant,  PhD  student  with  the  Bushfire  CRC/University  of  Melbourne.  

 

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The  relationship  in  Figure  3  indicates  that  the  aridity  index  (or  long  term  ratio  between  potential  evapotranspiration  and  rainfall)  can  be  a  very  strong  predictor  of  erosion  potential  in  landscapes  where  aridity  (or  dryness)  results  in  climatic-­‐related  variation  in  soil  properties.  In  the  eastern  uplands  of  Victoria,  where  the  role  of  aridity  is  beginning  to  be  quantified,  the  aridity  index  varies  from  ~0.8  to  4.5.  This  range  includes  biomes  ranging  from  rainforest  to  open  woodland.  Surface  run-­‐off  is  very  sensitive  to  changes  in  aridity  between  1  and  2.  It  remains  unknown  how  important  aridity  is  as  predictor  for  drier  landscapes  (e.g.  South  Australia)  where  aridity  is  generally  higher  than~  3.    5.5.2  Fire  severity:  Bushfire  versus  planned  fire  In  mixed  severity  and  understory  burns,  fire  severity  can  have  large  effects  on  erosion  from  burned  areas,  because  of  i)  patchiness  in  the  fire  footprint,  and  ii)  less  combustion  and    soil  heating  within  burned  patches.  Burn  patchiness  and  its  effects  on  hydrological  processes  is  difficult  to  model  and  quantity.  In  a  bushfire  setting,  the  fire  severity  is  typically  classified  into  categories;  understory  burn  (>3),  crown  scorch  (2)  and  crown  burn  (1).  These  categories  are  usually  obtained  from  some  continuous  metric  such  as  normalized  burn  ratio  (dNBR)  from  remotely  sensed  data  (e.g.  spot  or  Landsat  imagery)  which  quantifies  the  amount  of  biomass  lost  in  the  burn.  These  continuous  metrics  are  more  suited  to  hydrological  modelling  because  of  the  representation  of  spatial  pattern  in  gridded  data.  For  mixed  severity  and  understorey  burns  (particularly  planned  fire)  it  seems  that  runoff  and  erosion  processes  can  be  insensitive  to  subtle  variations  in  fire  severity  and  that  it  is  the  patchiness  in  burns  that  are  important  (Moody  et  al.  2008;  Cawson  et  al.  2013).  In  quantifying  the  effects  of  fire  severity  on  erosion,  the  fire  severity  metric  is  therefore  better  represented  as  a  continuous  grid-­‐based  metric  (e.g.  dNBR  or  NDVI)  (Chafer  2008)  rather  than  polygons  with  fire  severity  categories.        The  synthesis  of  literature  in  Section  4.2  considers  the  effects  of  bushfire  on  erosion.  Bushfires  represent  a  very  different  type  of  impact  compared  to  planned  (or  prescribed)  fire,  particularly  in  high  rainfall  regions  where  background  fuel  loads  are  high  and  where  bushfires  burn  with  very  high  intensity  (Cawson  et  al.  2012).  Differences  in  erosion  after  bushfire  versus  planned  fire  can  be  attributed  to  i)  the  degree  of  soil  heating  (DeBano  2000),  ii)  the  degree  of  patchiness  of  vegetation  after  burning  (Cawson  et  al.  2013)  ,  and  iii)  the  timing  of  the  burn  in  relation  to  seasonal  rainfall  patterns  (Russell-­‐Smith  et  al.  2006).  In  a  review  of  surface  runoff  and  erosion  after  prescribed  burning  Cawson  et  al.  (2012)  found  that  the  impacts  on  catchment  scale  erosion  were  usually  minimal,  but  that  very  large  erosion  events  do  occur  in  instances  when  burns  are  followed  by  high  intensity  rainfall.  Factors  contributing  to  the  relatively  subdued  erosion  response  of  planned  fires  include  i)  low  fire  severity,  ii)  burn  patchiness,  iii)  intact  riparian  vegetation  and  dilution  as  a  result  of  small  burned  areas  relative  to  the  overall  catchment  area.    In  a  study  on  the  effects  of  burn  patchiness  on  sediment  flux  on  100  m  long  hill  slopes  (~  25  degrees)    near  the  Upper  Yarra  catchment  (Cawson  et  al.  2013)  found  that  in  the  first  16-­‐months  after  fire,  a  uniform  prescribed  burn  increased  the  annual  sediment  flux  by  up  to  3  order  of  magnitude  (from  1.3  g  m-­‐1  yr-­‐1  for  unburnt  hill  slopes  to  ~1300  g  m-­‐1  yr-­‐1  for  burned  hill  slopes),  although  they  found  that  this  response  was  very  sensitive  to:    Post-­‐fire  rainfall:  A  single  event  (I15  ~54  mm  h-­‐1)  produced  80%  of  the  total  sediment  flux.  The  I15  had  an  average  return  interval  of  ~  4  years,  while  the  I30  had  a  return  interval  of  8-­‐10  years.  It  is  unclear  which  is  the  right  temporal  scale  for  causing  the  hill  slope  erosion  response  although  usually  it  is  the  short  rainfall  bursts  within  the  storm  that  cause  most  of  the  erosion.  The  degree  of  patchiness  in  the  burn.  Unburnt  buffers  (or  patches)  of  widths  1,  5,  and  10  m  resulted  in  a  reduction  on  sediment  flux  of  1.3,  98.1  and  99.9%,  respectively.          

 

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A  recent  study  with  the  Bushfire  CRC  into  the  effects  of  planned  fires  versus  bushfire  near  Myrtleford  in  north  east  Victoria  indicates  that  erosion  processes  in  small  headwater  catchments  (~  0.3  ha)  can  be  strongly  affected  by  prescribed  fire,  but  that  the  effects  are  substantially  lower  the  when  compared  to  the  response  after  the  catastrophic  2009  bushfires  (Figure  4).  For  bushfire  affected  headwater  (crown  burn),  the  run-­‐off  increased  non-­‐linearly  with  a  sharp  increase  for  rainfall  intensities  10  mm  h-­‐1,  whereas  in  lower  severity  planned  burns  (scorch  height  of  1-­‐8  m),  there  seems  to  be  a  threshold  rainfall  intensity  around  30-­‐40  mm  h-­‐1  below  which  the  runoff  response  is  unlikely  to  cause  much  erosion.  This  threshold  intensity  seems  consistent  with  the  results  from  Cawson  et  al.  (2013).    

 Figure  4.  Peak  discharge  for  bushfire  and  planned  fire  as  a  function  of  rainfall  intensity.  This  metric  of  peak  discharge  is  directly  related  to  the  capacity  of  the  catchment  to  erode  and  transport  sediment.    The  data  (unpublished)  was  collected  as  part  of  a  research  project  partially  funded  by  the  Bushfire  CRC.  Result  from  this  work  is  being  prepared  for  publication  and  is  yet  to  undergo  peer-­‐review.      The  peak  discharge  per  unit  area  varied  predictably  with  rainfall  intensity,  but  the  relation  was  dependent  on  the  type  of  disturbance.  As  expected,  the  unburnt  catchment  produced  very  little  runoff,  even  for  rainfall  intensities  of  ~  40  mm  h-­‐1.  The  bushfire-­‐affected  catchment  produced  largest  peak  discharge.  Extrapolating  the  curve  to  obtain  the  peak  discharge  for  debris  flow  producing  storms  in  this  region  (I15  ≈  40  mm  h-­‐1:  return  interval  of  <  1  year)    (see:  Nyman  2013)  indicates  that  debris  flow  events  correspond  with  peak  discharge  of  ~    350  m3  ha-­‐1  hr-­‐1.  The  trends  for  the  planned  burn  in  Figure  5  indicate  that  an  I15  of  ~60  mm  h-­‐1  (return  interval  of  ~  3  years  in  this  region)  would  be  required  to  produce  the  same  runoff  response  from  a  planned  burn.  Whether  or  not  such  an  event  would  result  in  large  debris  flow  depends  on  the  burn  pattern  more  broadly  across  the  catchment;  a  single  headwater  of  this  size  (<1  ha)  is  unlikely  to  be  sufficient  for  sustaining  debris  flow  processes  at  larger  scales.  The  picture  in  Figure  5  b  shows  how  the  transport  of  sediment  and  organic  matter  resulted  in  equipment  failure  in  the  instrumented  planned  burn  following  a  moderately  intense  rainfall  event  (I15  =  20  mm  h-­‐1).  

 

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   Figure  5.  Instrumented  headwater  catchments  in  north-­‐east  Victoria.  a)  The  sediment  trap  and  tipping  bucket  after  installation  in  a  prescribed  burn.  b)  The  first  storm  event  after  the  burn  (I15  =  20  mm  h-­‐1;  Average  return  interval  =1)  resulted  in  450  kg  (2.5  t  ha-­‐1)  of  erosion.  This  event  carried  a  lot  of  large  organic  debris  which  exceeded  the  measurement  capacity  of  the  equipment.                                

 

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5.5.3  Rainfall,  bushfire  regimes  and  episodic  patches  of  erosion      Almost  all  catchments  are  likely  to  respond  with  some  increase  in  erosion  as  a  result  of  vegetation  removal  by  fire.  A  recurring  theme,  however,  in  the  Australian  and  international  literature  on  post-­‐fire  erosion  is  that  most  of  the  erosion  occurs  as  a  result  of  a  few  large  (or  extreme)  erosion  responses  (Brown  1972;  Miller  et  al.  2003;  White  et  al.  2006;Nyman  et  al.  2011).  The  magnitude  of  the  threat  to  water  supply  or  other  water  resources  assets  (e.g.  biodiversity  or  recreation)  is  therefore  not  embedded  within  the  average  erosion  response  from  burned  areas.  Instead  it  is  a  function  of  the  likelihood  (or  probability)  of  erosion  response  exceeding  some  threshold.  Thresholds  may  be  the  treatment  capacity  of  a  water  supply  system,  tolerable  sediment  concentration  for  a  fish  species  or  a  phosphorous  threshold  for  blue-­‐green  algae  blooms.    This  likelihood  of  erosion  exceeding  a  tolerable  threshold  is  determined  by  the  terrain,  soil  and  the  spatial-­‐temporal  pattern  of  fire  events  and  rainstorms  which  prime  the  landscape  for  a  response  (Nyman  et  al.  2013a).    The  role  of  fire  and  rainfall  in  cause  variation  in  risk  was  modelled  by  Jones  et  al.  (2014)  using  a  spatial-­‐temporal  model  (Figure  6)  which  represents  the  frequency  and  the  area  of  overlapping  burned  areas  and  rain  storms.  This  type  of  modelling  approach  can  be  coupled  with  information  on  landscape  properties  (soil  and  terrain)  to  quantify  the  likelihood  of  fires  and  rainfall  resulting  in  adverse  impacts  on  water  quality.    

   Figure  6.  A  single  realisation  of  rain  storms  and  burn  impacts  in  space  (1000  km  x  1000  km)  and  time  (50  years).  For  burn  impacts  in  this  hypothetical  scenario  the  mean  radius  of  the  disc  shaped  burn  areas  is  100  km,  the  duration  of  impact  is  2  years  and  the  average  return  interval  for  bushfires  is  20  years.  The  corresponding  values  for  rain  storms  are  1  km,  30  minutes  and  2  years.  The  risk  set,  where  rain  storm  and  burn  impacts  overlap,  is  where  erosion  events  may  occur  (reproduced  from  Jones  et  al,  2014)  

 

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6  Fire  and  rainfall  regimes  as  drivers    –  a  regional  analysis  This  section  describes  an  approach  for  regional  assessment  of  risk  associated  with  fire  and  rain  storms  in  catchments.  The  assessment  uses  fire  history  and  design  storms  to  obtain  a  measure  of  the  degree  to  which  a  landscape  is  primed  by  fire  and  intense  rainfall  (see  section  1.5.3  and  Figure  6).  The  analysis  builds  on  the  methods  developed  in  Jones  et  al.  (2014)  and  defines  the  following  parameters  to  describe  the  fire  and  rainfall  regime  of  a  region:    

� λ  =  fire  event  rate  (km-­‐2  year-­‐1)  � μ  =  storm  event  rate  (km-­‐2  year-­‐1)  � α  =  E||fire  event||  (km2  ×  years)  � β  =  E||rainfall  event||  (km2  ×  years)  

 These  parameters  are  used  to  obtain  𝐸‖𝐴,  which  is  the  average  annual  rate  of  intersection  between  storms  and  rainfall  (or  the  index  of  fire  and  storm  overlap).  This  is  the  rate  at  which  the  landscape  is  primed  by  fire  events  and  rain  storms;  in  each  of  the  major  capitals  of  Australia.  Auckland,  New  Zealand,  was  initially  included  in  the  analysis,  but  with  no  fires  between  1991  and  2007  on  the  North  Island  exceeding  150  ha  in  size  (Anderson  et  al.  2008),  the  importance  of  burning  on  catchment  processes  was  assumed  negligible.  Fire  history  was  obtained  from  different  sources  (Table  2).  For  some  jurisdictions,  fire  history  was  provided  by  local  agencies.  In  other  cases,  data  was  located  through  online  databases.    

   Topographic  effects  on  erosion  potential  for  headwaters  (areas  <  250  ha)  was  calculated  across  Australia  and  New  Zealand  using  a  90  m  DEM  available  from  the  Shuttle  Radar  Topography  Mission  SRTM  (http://www.cgiarcsi.org/data/srtm-­‐90m-­‐digital-­‐elevation-­‐database-­‐v4-­‐1).  The  equation  is  based  on  the  LS  factor  (known  as  the  topographic  erosion  potential)  in  the  RUSLE  model  (Renard  et  al.  1991)  but  modified  (see:  Desmet  and  Govers  1996)  to  incorporate  information  on  convergent  hill  slopes  in  its  representation  of  erosion  risk:    

   A  is  the  contributing  area  (m2),  S  is  the  slope  (degrees)  and  m  and  n  are  parameters  (0.5  and  1.3,  respectively)  that  describes  the  relative  importance  of  slope  gradient  versus  contributing  area.      

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Table 2. Some high-value catchment and the cities they supply. Catchment are partially of fully forested.

City Water supply catchments Reservoirs Capacity (GL)

AEP % I30 = 35 mm h-1

Mean LS

Duration of fire record

Forest area

km2

Mean fire size km2

Fire frequency

year-1 km-2 E||A||

Sydney

Shoalhaven Lake Yarrunga 8

63 10.8 1962 - 2014 28 106 97 2.16 7.4 Upper Nepean Lake Napean 68

Warragamba Lake Burragorang 2027

Canberra Cotter River Catchment

Corin 71

34 19.3 1938 - 2014 7 640 96 1.76 3.3 - 6.0 Bundoora 11

Cotter 76

Perth Darling Ranges Helena River Reservoir 64

24 3.1 2003 - 2013 9 160 78 1.59 1.7 - 4.4

Canning Reservoir 90

Adelaide Mt Lofty Ranges Mt Bold Reservoir 46

14 4.1 1931 - 2014 6 219 78 1.51 0.9 - 4.2 Kangaroo Ck 19

Melbourne Yarra Ranges Upper Yarra Reservoir 201

24 18.7 1927 - 2012 64 020 95 1.73 2.2 Baw Baw / Thompson Thompson Reservoir 1070

Hobart Mt Wellington Wellington Park n/a 6 22.9 1980 - 2013 47 860 58 0.84 0.17 - 1.7

Darwin Darwin River Darwin River Dam 285 63 0.7 - - - - 622

Brisbane D'Aguilar Range Somerset Dam 378

63 15.3 1986 - 2013 46 217 28 0.22 0.2 Wivenhoe Dam 1165

Auckland Hunua Ranges Mangatangi Dam 35

36 12.3 1991 - 2007 - - - 0 Waitakere Ranges

Lower Huia Dam 6

1The storm frequency is calculated for 30-minute storms with intensities ranging from 20 – 35 mm h-1. The maximum storm frequency is when storms on average occur at least once a year. 2 The fire regime parameters from Darwin were calculated based on the average annual proportion of land burned (~19%) (Russell-Smith et al. 2006).

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The  mean  LS  (eq.  2)  were  calculated  for  individual  catchments  contributing  to  the  water  supply  reservoirs.  In  most  cases  the  LS  were  consistent  for  all  the  catchments  although  the  Warragamba  catchment  near  Sydney  had  very  different  values  in  the  southern  arm  (LS=9)  versus  the  northern  arm  (LS  =  15).  Figure  7  shows  the  how  LS  varies  in  Australia  with  a  clear  tendency  for  higher  values  in  the  Dividing  Ranges  along  the  east  and  south-­‐east  coast.  Maps  of  the  LS  factor  for  different  water  supply  catchments  of  major  cities  in  Table  2  are  shown  Appendix  1.  These  provide  some  examples  that  are  representative  of  some  of  the  different  regions.  However,  there  are  many  other  important  reservoirs  in  cities  and  regional  towns  that  are  not  included.      

   Figure  7   Variation  in  topographic  erosion  potential  (LS)  across  the  Australian  continent.    Terrain  along  the  eastern  and  south-­‐eastern  coast  stands  out  with  the  highest  potential  for  erosion.  The  combined  effects  of  LS  and  𝐸‖𝐴‖  on  erosion  risk  is  shown  in  a  two  dimensional  plot  which  describes  the  regional  exposure  to  risk.  The  y-­‐axis  (storm  and  fire  overlaps)  can  be  interpreted  as  the  likelihood  of  coincidence  of  forcing  variables,  while  the  topographic  erosion  potential  is  the  consequence.  Catchment  near  Darwin  frequently  burn  and  they  experience  intense  thunderstorm  activity,  hence  the  likelihood  of  fire  and  storm  overlaps  is  very  high  (Figure  8).  The  terrain  is  flat  so  the  consequence  of  overlaps  is  low.  In  Hobart,  the  storm  frequency  is  low  and  fires  are  generally  smaller,  so  the  likelihood  of  overlaps  is  low  to  moderate,  depending  on  the  rainfall  intensity  threshold.  The  consequence  is  very  high  due  to  the  steep  slopes  of  Mt  Wellington  which  forms  much  of  the  water  supply  network  in  Wellington  Park.  Canberra  and  Melbourne  are  very  similar  with  moderate  likelihood  but  high  consequence,  which  is  consistent  with  observation.  New  Zealand  did  not  make  it  onto  the  chart  because  the  fire  and  storm  overlap  was  negligible  (~0).  Water  supply  catchments  in  the  Mt  Lofty  Ranges  (Adelaide)  and  those  in  the  Darling  Ranges  (Perth)  form  a  pair  at  the  lower  end  of  the  consequence-­‐axis  (x-­‐axis)  and  with  low  to  moderate  likelihood  (y-­‐axis).      

 

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   Figure  8.  Topographic  erosion  potential      a)  Matrix  for  evaluating  exposure  to  risk  from  bushfire-­‐related  erosion  in  forested  catchments.  In  b)Darwin  is  excluded  because  of  the  distinctiveness  of  the  tropical  region  in  terms  of  fire  and  rainfall  regimes.  The  LS  factor  (x-­‐axis)  represents  the  topographic  erosion  potential  while  the  𝐸  𝐴‖  metric  (y-­‐axis)  represents  the  intensity  of  the  fire  and  storm  processes  leading  to  erosion.  The  y-­‐axis  can  be  interpreted  as  the  likelihood  of  the  landscape  being  primed  by  rainfall  and  burns.  The  x-­‐axis  is  the  potential  erosion  response  (or  consequence)  of  this  priming  process.  𝐸‖𝐴‖  on  the  y-­‐axis  is  displayed  as  a  range  for  some  sites  because  it  incorporates  the  varying  levels  of  overlap  depending  on  the  30-­‐minute  storm  intensity  threshold  used  in  the  model.  The  model  currently  includes  30-­‐minute  intensities  between  20  and  35  mm  h-­‐1.  On  average,  in  the  water  supply  catchments  of  Darwin,  Brisbane  and  Sydney  these  storms  occur  at  least  once  a  year.  The  𝐸‖𝐴‖  in  these  regions  is  therefore  insensitive  to  changes  in  the  storm  threshold;  hence  it  is  a  single  value.  At  the  other  sites  the  35  mm  h-­‐1  storm  had  a  recurrence  interval  of  more  than  a  year  so  reducing  the  threshold  meant  that  𝐸‖𝐴‖  also  increased.  At  20  mm  h-­‐1  the  storms  occur  on  an  annual  basis  everywhere,  and  there  is  no  further  increase  in  𝐸‖𝐴‖.  Low,  moderate  and  high  categories  are  arbitrary  and  were  defined  simply  by  dividing  the  risk  into  three  equally  spaced  categories.  Note  that  the  Sydney  catchments  include  a  very  large  area  and  that  there  are  sections  within  these  areas  that  have  higher  LS  than  the  average  values  in  this  figure.        

 

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7  Guidelines  This  section  of  the  report  describes  guidelines  or  a  set  of  steps  for  assessing  erosion  risk.  The  steps  lead  to  an  estimation  of  risk.  The  framework  is  general,  allowing  for  different  management  settings  which  may  vary  in  terms  of  data  availability,  type  of  assets,  potential  consequences  and  the  available  options  for  mitigating  the  risk.  The  steps  are  similar  whether  risk  assessment  is  part  of  planned  fire  operations,  strategic  planning  (pre-­‐fire)  or  a  rapid  post-­‐fire  response  operation.    7.1  Six  generic  steps  for  risk  assessment  1.  Identify  relevant  assets.  Assets  vary  depending  on  location  and  management  setting,  but  are  typically  associated  with  off-­‐site  (i.e.  downstream)  impacts,  although  they  can  also  be  local  (e.g.  when  the  concerns  relate  to  impacts  on  soil  resources).  Assets  include:    

� Water  reservoirs  and  water  off-­‐take  points.  � Culverts,  roads  and  other  infrastructure  that  may  be  impacted  by  flash  floods  or  debris  flows.  � Biodiversity  (fish,  invertebrates,  ecosystem  function).  � Recreational  assets  (picnic  grounds,  campsites,  swimming  holes.).  � Soil  resources  (nutrient  status,  organic  matter).  

 2.  Locate  relevant  assets  and  determine  their  vulnerability  to  impacts  of  erosion.  Vulnerability  may  for  instance  be  a  function  of  treatment  capacity  in  a  water  supply  system  or  the  sensitivity  of  an  invertebrate  to  turbid  water.  Consider  factors  such  as  whether:    

� The  asset  may  be  a  water  off-­‐take  in  a  river,  in  which  case  the  contributing  area  may  be  very  large  catchments.  At  this  scale  the  catchment  may  be  partially  burned  by  bushfire  or  it  may  have  multiple  planned  burns  scheduled  in  it  over  a  fire  season.  

� The  asset  may  be  a  small  population  of  a  threatened  fish  species,  in  which  case  the  contributing  area  may  be  relatively  small  and  embedded  entirely  within  a  burned  area.  

� The  asset’s  vulnerability  to  erosion/water  quality  impacts.  Understanding  the  vulnerability  is  critical  because  it  helps  identity  the  relevant  variables  for  evaluating  risk  and  monitoring  impacts.  For  some  assets,  such  as  water  supply  reservoirs,  the  vulnerability  is  typically  linked  to  peak  concentrations  of  sediment  (or  some  other  constituent).  

� Ecological  assets  may  also  be  vulnerable  to  cumulative  low-­‐level  but  reoccurring  water  quality  impacts,  such  as  the  combined  effects  of  small  planned  burn  areas  within  a  larger  catchment.  

 3.  Determine  the  potential  exposure  to  risk  by  identifying  the  processes  that  are  likely  to  operate.  Both  the  type  and  intensity  of  process  are  relevant.    

� Use  past  observation  or  available  knowledge  from  a  representative  region  to  determine  what  type  of  processes  is  likely  to  operate.  Landslides,  debris  flows,  sheet  erosion,  gully  erosion  are  different  processes  that  should  be  identified  as  separate  sources  of  risk.  

� If  there  is  no  relevant  literature  for  a  particular  catchment  then  work  off  simple  erosion  models  such  as  RUSLE  (e.g.  Rulli  et  al.  2013).  

� Determine  the  potential  erosion  response  (including  the  worst  case  scenario  in  terms  of  impact  on  assets)  given  the  type  of  processes  operating  in  a  particular  setting.  How  do  these  compare  to  background  levels  (i.e.  is  there  a  substantial  change  relative  to  background  exposure).  

 

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� Assets  that  are  located  a  long  distance  downstream  from  a  burned  catchment  may  be  less  exposed  to  impacts  than  assets  located  within  or  nearby  the  burned  catchments.  The  attenuating  of  exposure  with  distance  from  erosion  source  can  be  done  qualitatively  by  weighting  the  importance  of  the  source  area  (burned  catchment)  based  on  its  distance  from  the  asset  (see  equation  3  in  Weidner  and  Todd  2011).  

 4.  Determine  the  consequence  of  erosion  processes.  

� What  is  the  potential  consequence  given  the  erosion  responses  (from  3)  and  vulnerability  of  the  asset  to  erosion  (from  2  above)?  

� The  consequence  can  be  interruptions  to  water  supply  (treatment  capacity  exceeded),  local  loss  of  biodiversity  or  persistent  changes  in  stream  function.  In  engineering  design  and  water  supply  systems,  the  consequences  can  be  easily  determined  by  examining  the  vulnerability  of  the  systems  to  erosion.  

 5.  Determine  likelihood  of  erosion  process.  Allocate  some  probabilities  to  these  (qualitative  or  quantitative).  

� Given  the  storm  regime,  the  fire  size,  its  severity  and  the  terrain  what  is  the  likelihood  of  responses  in  3.  

� Qualitative  categories  may  be  very  unlikely  (1:  10  000  chance),  possible  (1:1000  chance),  highly  probable  (1:100)  and  almost  certain  (more  than  1:10  chance).  Use  a  risk  framework  which  is  consistent  with  other  decision-­‐making  processes  within  the  agency.  

� Quantitative  approaches  may  be  used  when  detailed  information  on  post-­‐fire  erosion  responses  is  available.  

� The  assessment  can  be  made  using  just  terrain  attributes  (eq.  2;  data  at  90  m  resolution  made  available  through  this  project),  or  more  ideally  it  can  made  using  a  combination  of  local  data  and  erosion  modelling.  For  planning  fuel  reduction  burns  the  metric  of  erosion  potential  (eq  .2)  can  be  used  to  determine  the  relative  risks  within  a  catchment  where  planned  burns  are  scheduled.  This  approach  of  datelining  relative  risks  can  also  be  used  in  a  bushfire  setting,  although  the  likelihood  of  erosion  events  also  depends  on  fire  severity.  If  there  is  information  available  on  the  impact  of  fire  severity  on  erosion,  the  LS  factor  can  be  adjusted  based  on  fire  severity  mapped  from  satellite  (e.g.  Sheridan  et  al.  2009  or  it  can  be  incorporated  into  the  RUSLE  framework  by  adjusting  the  soil  and  cover  factors  in  the  equation  (e.g.  Rulli  et  al.  2013).  

 6.  Plot  in  risk  matrix  and  determine  risk  level.  

� Terminology  for  likelihood,  consequence  and  risk  should  be  consistent  with  that  used  elsewhere  in  the  decision-­‐making  processes.  

� The  information  used  to  inform  the  risk  assessment  should  be  continuously  updated  with  new  knowledge  and  modelling  capabilities.  

                       

 

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Strategies  for  risk  mitigation  are  split  into  two  sections:  i)  before  planned  fire;  and  ii)  after  bushfire    7.1.1  Prescribed  fire  Risk  mitigation  –  fire  operations  

� Schedule  burns  in  high  risk  areas  in  high  value  catchments  over  multiple  years.  � Promote  patchy  burns  in  steep  terrain.  Unburnt  patches  should  be  in  the  order  of  10-­‐100  

metres.  Patchiness  is  most  effective  when  distributed  throughout  the  source  areas.  Regular  patches  are  more  effective  than  a  single  buffer.  

� Avoid  burning  in  steep  converging  headwaters  (1st-­‐order  basins,  usually  <200  ha)  above  high  value  assets.  These  parts  of  the  landscape  are  prone  to  threshold  driven  shifts  in  erosion  (i.e.  channel  initiation  and  evacuation  of  stored  sediment  in  convergent  headwaters).  

� Unburnt  buffers  along  drainage  lines  can  be  effective  for  most  rainfall  events,  although  their  capacity  to  reduce  sediment  delivery  to  streams  is  likely  to  be  exceeded  during  intense  rainfall.  

 Monitoring  and  evaluation  

� Post  fire  evaluation  of  hill  slope  erosion  (e.g.  Morris  et  al.  2013)  can  be  used  to  build  database  to  help  inform  future  risk  assessments.  These  qualitative  assessments  can  be  carried  out  opportunistically  after  rainfall  events  or  as  routine  evaluation  (e.g.  one  year  after  the  burn).  Qualitative  erosion  assessment  can  be  quick  and  they  can  be  carried  out  alongside  other  post-­‐fire  monitoring  and  evaluation  protocol  (fire  severity,  fauna  and  vegetation).  

� More  critically,  a  change  in  the  rate  of  application  of  planned  burns  (recently  set  to  5%)  should  be  accompanied  with  rigorous  monitoring  schemes  for  detecting  trends  in  soil  physical  and  chemical  properties  over  time,  in  a  similar  way  that  fauna  and  flora  are  being  monitored.  Organic  matter,  nutrient  levels,  seed  banks  and  soil  microbial  activity  are  critical  components  of  forest  ecosystems.  Soil  monitoring  in  areas  of  different  erosion  potential  help  capture  the  overall  effect  of  fire  regimes  on  forest  ecosystems.  

� High  value  catchments  could  be  used  as  more  intensive  experiment  for  determining  the  long  term  effects  of  burning  on  sediment  transport  and  water  quality,  although  this  would  require  significant  investments  in  infrastructure  for  sampling  and  measuring  sediment  concentration  and  discharge  in  streams  or  rivers.  

 7.1.2  Bushfire  Post-­‐bushfire  response  

� Information  on  topography  (DEM)  and  fire  severity  are  nearly  always  available  following  bushfire.  These  can  be  used  to  evaluate  erosion  risk  by  following  the  steps  outlined  in  section  7.1  using  general  approaches  for  modelling  erosion  (Rulli  et  al.  2013)  or  specific  models  developed  for  local  conditions  (Sheridan  et  al.  2009).  

� These  risk  assessments  should  inform  decisions  regarding  mitigation.  � Examples  of  post-­‐fire  mitigation  includes  hill  slope  erosion  control,  preparing  alternative  

water  supplies  and  limiting  access  to  recreational  areas  and  roads  at  risk  of  flash  flooding  or  debris  flows.  

   

 

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8  Recommendation  for  future  research  priorities  Landscapes  are  highly  variable  in  terms  of  fire  impacts  on  erosion.  Some  regional  trends  have  emerged  from  the  analysis  presented  in  this  report.  Regions  of  ACT,  Victoria  and  NSW  fall  into  some  of  the  highest  risk  categories  in  terms  of  the  fire,  storm  and  topographic  controls  (Figure  8).  These  regions  also  have  the  strongest  knowledge  base.  There  is  considerable  potential  for  fire  to  cause  erosion  in  catchments  near  Hobart,  yet  very  little  is  known  about  fire  and  erosion  processes  in  this  region.  Local  variation  within  regions  can  be  large  and  site  specific  research  on  erosion  is  required  to  improve  the  knowledge  base  for  quantitative  risk  assessments  in  various  regions.  Studies  on  post-­‐fire  erosion  should  therefore  be  carried  out  opportunistically  when  bushfire  provides  opportunities  for  obtaining  parameters  and  data  to  improve  modelling  capacity.    Common  to  all  the  fire  prone  regions  is  the  lack  of  an  integrated  modelling  approach  for  determining  the  net  impact  of  a  fire  regime  (including  bushfire  and  planned  fire)  on  the  treatability  of  the  water  that  is  sourced  from  forested  catchments.  Key  questions  are:  

� How  can  fire/land  managers  work  with  water  supply  agencies  to  develop  plans  that  optimise  prescribed  burns  (scheduling  and  operations)  to  achieve  reduced  risk  of  bushfire  while  also  minimising  the  risk  to  water  supply?  Regular  application  of  prescribed  fire  in  water  supply  catchments  means  that  there  is  some  increased  risk  of  water  contamination  in  the  short-­‐term,  but  this  increase  in  risk  may  be  offset  by  the  reduced  risk  of  bushfire-­‐related  impacts  in  the  future.    

� What  is  the  landscape  scale  effect  of  having  large  areas  consistently  exposed  to  higher  erosion  rates?  For  large  catchment  areas  the  increased  application  of  planned  burns  means  that  some  proportion  of  the  catchment  is  in  some  state  of  elevated  erosion  potential.  It  is  unclear  how  these  impacts  play  out  in  terms  of  water  quality  and  sediment  transport  at  larger  scales  where  patchiness  within  burns,  their  frequency,  size  and  density  (burns  per  area  per  time)  become  important.  

� How  does  the  size  of  burned  areas,  their  severity  and  their  frequency  influence  water  quality  and  sediment  transport  to  reservoirs?  

   Developing  tools  for  optimizing  burns  in  high  value  water  catchments  is  high  priority  goal  that  would  enable  fire/land  managers  to  carry  out  prescribed  burns  with  the  long-­‐term  strategy  to  reduce  bushfire  risk  while  maintaining  the  capacity  of  catchments  to  deliver  drinking  water  at  minimal  cost  to  the  water  supply  agencies.    The  development  of  such  tools  is  currently  constrained  by  a  major  gap  in  research  in  which  there  are  currently  no  spatially  explicit  erosion  models  that  evaluate  the  impact  of  fire  regimes  on  water  quality.  Recent  developments  in  fire  modelling,  however,  demonstrate  that  it  is  becoming  increasingly  feasible  to  explore  what  fire  regimes  emerge  under  different  climate  and  management  scenarios  and  what  the  implications  may  be  for  land  managers  (Bradstock  et  al.  2012;  Collins  et  al.  2015).  When  applied  to  erosion  processes  in  a  water  supply  catchment,  this  type  of  modelling  approach  would  enable  land  and  water  managers  to  evaluate  the  cost  and  benefits  of  different  fire  management  scenarios,  taking  into  account  both  the  operational  and  strategic  elements  of  the  fire  management.              

 

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Operations  may  be  optimised  so  that  highly  sensitive  (steep  and  erodible)  areas  of  a  water  supply  catchment  are  given  special  consideration  during  prescribed  burns  in  terms  of  the  overall  area  that  is  treated  or  the  manner  in  which  it  is  treated.  For  example,  it  may  be  important  to  know  if  there  is  some  benefit  in  scheduling  burns  as  multiple  smaller  burns  every  year,    rather  than  a  single  large  burn  every  second  year.  Additionally,  where  do  land/fire  managers  have  the  most  leverage  in  terms  of  minimising  impacts?  Is  it  by  modifying  the  size  and  frequency  of  burns  within  a  catchment  or  is  it  by  modifying  the  lighting  pattern  within  burns?  What  are  the  cost  and  benefit  of  different  management  scenarios  in  terms  of  water  quality  impacts,  the  resources  needed  to  carry  out  the  burns,  and  the  overall  reduction  in  bushfire  risk  (the  high  level  objective  of  planned  burning)?    A  model  that  incorporates  planned  and  unplanned  fire  as  two  processes  that  combine  to  produce  water  quality  risk  requires  parameters  that  describe  the  fire  regime  itself,  as  well  as  the  erosion  processes  that  emerge  as  a  result  of  different  burn  outcomes  (severity  and  patchiness).  In  most  catchments,  the  parameters  required  to  drive  such  a  model  are  lacking.  However,  by  focusing  the  model  development  around  regions  where  the  parameters  and  modelling  capacity  are  available,  it  is  possible  to  begin  to  explore  how  fire  management  can  be  optimised  to  minimise  water  quality  impacts  using  the  most  cost-­‐effective  (or  efficient)  solutions.  The  result  from  this  type  of  modelling  approach  is  site  specific  in  terms  of  the  absolute  values  that  the  model  produces.  The  trends  and  patterns  that  emerge  however  can  be  generalised  more  broadly  and  used  to  guide  management  activities  outside  the  exact  conditions  for  which  the  model  was  parameterised.  Once  the  modelling  framework  is  in  place,  there  will  be  opportunities  to  apply  the  model  to  new  regions  by  incorporating  more  site  specific  information  on  local  erosion  processes.    Another  important  gap  is  the  lack  of  knowledge  on  how  landscapes  vary  in  terms  of  their  susceptibility  to  soil  degradation  as  a  result  of  frequent  fire.  Most  studies  on  soil  carbon  and  nutrients  in  fire-­‐prone  forests  have  been  carried  out  in  flat  terrain  where  there  is  little  potential  for  erosion.  In  mountainous  terrain,  there  may  be  considerable  variation  in  how  soils  (and  hence  vegetation)  respond  to  changes  in  fire  regimes.  Developing  robust  monitoring  systems  for  quantifying  these  potential  effects  is  important  when  arguing  for  a  marked  shift  in  the  sale  of  land  management  interventions,  such  as  the  5%  target  currently  being  rolled  out  across  the  south  and  east  coast  of  Australia.    The  soil  is  a  critical  component  of  the  ecosystem  and  the  effects  of  burning  on  the  soil  should  be  quantified  over  time  as  part  of  routine-­‐based  monitoring,  alongside  the  monitoring  of  flora  and  fauna  which  is  already  taking  place  in  most  jurisdictions.  

 

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Appendix  1  

     

 

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 Figure 5. LS factor for some water supply catchments near Perth (Helena and Canning Reservoirs)        

 

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