GIS-based multiple criteria evaluation for spatial mine management Micaela Grigorescu (Geological Survey of Queensland)

Transcription

1 GIS-based multiple criteria evaluation for spatial mine management Micaela Grigorescu (Geological Survey of Queensland) ACARP Project C21041 (Jane H Hodgkinson, Micaela Preda-Grigorescu, Claire Côte, Habib Alehossein) 11 April 2014 ADVANCED COAL PORTFOLIO/ CLIMATE ADAPTATION FLAGSHIP

2 ACARP Project C21041 CRATER Climate Related Adaptation from Terrain Evaluation Results (Climate adaptation assessment with special regard to flooding) 1. Spatial data processing GIS layers GIS modelling hot-spots of vulnerability 2. Fault tree analysis: factors leading to failure targets adaption options 3. 5-capitals analysis assessment of: financial human social physical natural factors for each adaptation option

3 1 Multiple criteria evaluation (MCE) - definitions structured framework for investigating, analysing and resolving decision problems constrained by multiple objectives used to appraise a discrete number of alternatives against a set of multiple criteria and conflicting objectives framework = GIS = georeferenced datasets decision = management of environmental issues that have a spatial representation alternatives = infrastructure within the mining site criteria = terrain characteristics (elevation and slope), soil characteristics (drainage, runoff, infiltration, erodability, etc), proximity to creeks, density of drainage lines and vegetation cover

4 Multiple criteria evaluation (MCE) - process define the issue to be modelled (e.g. flooding) choose/gather criteria (c) (e.g. terrain and soil characteristics, drainage) assess how the criteria influence the issue => ranking schemes establish weights (w) importance of each criterion outcome = map/model (hot-spots where flooding can impact infrastructure) w 1 * c 1 + w 2 * c w n * c n where w 1 + w w n = 1 (100%)

5 Input data - terrain Tile-based point Lidar data => elevation slope

6 Resulting datasets => Ranked datasets Legend 3m DEM Value High : Low : class ranking concept - The higher the class index, the better the location 1

7 Resulting datasets => Ranked datasets Legend degrees class ranking concept - The higher the class index, the better the location 1

8 Resulting datasets => Ranked datasets Input data - drainage Legend Creeks Concetric buffers (100m) Legend Creeks 7 class ranking concept - The higher the class index, the better the location 1

9 Legend L5 + L4 datasets Soil types Ac Ad Bb Bd Bn Bu Bz Cc Cw Fx FxLp Gm Hf Mi Mw Pr Rn Rp Rt Ss Wm Ww L4 L5 Input data - soil L4 Australian Soil Resource Information System (ASRIS) Level 4 Tracts and Land Unit Attribution, 1:250,000 or broader L5 ASRIS Level 5 Tracts, 1:50,000 1:250,000 (other colours) localised high resolution pedological study Subdatasets Drainage: most wet to least wet Permeability: slow infiltration to rapid infiltration Surface condition: more overland runoff to less runoff Water availability: wetter to drier Water erosion: most unstable to most stable

10 Ranked datasets Legend L5 + L4 datasets Surface condition (runoff) Legend L5 + L4 datasets Water erosion (stability)

11 Input data - vegetation Ranked dataset Legend Vegetation RE Native vegetation Cleared land Legend 2 5

12 Multiple criteria evaluation - solution MCE solution = MCE Veg * w5 + Creeks * w4 + Soil * w3 + Slope * w2 + Elevation * w1 Sum of weights = 100%

13 MCE solutions: Elevation + Slope + Soils (5 parameters) + + Drainage density + Proximity to creeks + Vegetation cover The higher the score, the better the location weighted equally weighted

14 Examples of vulnerability assessment: MCE solution in relation to infrastructure Legend Conveyor Railway MCE MCE score Legend buildings_all MCE MCE score

15 Examples of vulnerability assessment: MCE solution in relation to infrastructure and hot-spots

16 Conclusions Gathered and analysed terrain, soil and drainage datasets in a raster format Produced an essential GIS platform Easy to establish, update and maintain Highly flexible MCE modelling Provided infrastructure targets for optimisation and/or adaptation Necessary before and after mine establishment

17 Hotspot Cause 2 Sudden extreme downpour Fault tree analysis Flooding of exit route Flooding of critical exit route Sudden extreme downpour Prolonged extreme wet season Prolongue d extreme wet season TARGETS FOR POSSIBLE ADAPTATION OPTIONS Event not forecast Factors leading to failure Event forecast with low probability Event misforecast as low rainfall event Long term forecast uncertain and too late to act Total seasonal rainfall expected to have been lower Event forecast but exit route not known to flood

18 3 5-capitals analysis for each adaptation option FINANCIAL HUMAN Available capital for adaptation option SOCIAL Required capital for adaptation option 0 PHYSICAL NATURAL

19 Project achievements = provide a spatial management tool Reduce downtime, associated costs and risks Protect reputation Perform due diligence Shareholder and client confidence Staff safety and security

20 Future directions What if scenarios Automated MCE Multiple mine-site evaluation Non-mine environment