Some Considerations For Drought Monitoring Systems – A Spatial Perspective

from Australia

Some Considerations For Drought Monitoring Systems – A Spatial Perspective

from Australia

Associate Professor Kevin McDougallProgram Leader, GIS/Remote Sensing

Australian Centre for Sustainable Catchments

Overview of PresentationOverview of Presentation

• Australian Overview – Key Australian Agencies• Information in Australia Supporting Drought Monitoring• Australian Water Availability Project (AWAP)• Spatial Information Challenges in Early Warning Systems• The Concept of Spatial Data Infrastructure and its Role in

Building Comprehensive Systems• Citizen Volunteered Geographic or Spatial Information• Conclusions

Australian OverviewAustralian Overview

• Australian continent has one of the most variable rainfall climates in the world

• Australian Bureau of Meteorology (BoM) has a Drought Watch service since 1965

• Agriculture suffers first and most severely• BoM provides regular Drought Statements

Sources of Spatial Data in AustraliaSources of Spatial Data in Australia

• Bureau of Meteorology – primary meteorological data including location of recording stations – rainfall, temperature and river gauges, climate and climate models

• Soil and Geology – Geosciences Australia compiled from state level

• Hydrology – Geosciences Australia and State mapping agencies• Digital Elevation Models (DEM) • Satellite Imagery – USA, Japan and European Sensors

Crop Yield Crop Yield Prediction Prediction and Forecastingand ForecastingMODISMODIS

LandsatLandsat

Australian Water Availability Project (AWAP)Australian Water Availability Project (AWAP)

• Monitors the state and trend of terrestrial water balance of Australian Continent

• Joint effort by CSIRO Marine and Atmospheric Research, Bureau of Meteorology and Bureau of Rural Science

• Project has run since 2005• Uses past history (climatologies) and present state of soil

moisture and water• Gridded mapping system with spatial resolution of 5km• Data provided through a web interface• Weekly (near real time), historical monthly (1900 to

present) and 3 monthly climatologies

AWAP Data and ModelsAWAP Data and Models• Utilises a water balance model using data fusion• Examines change in state of precipitation, transpiration, soil

evaporation, surface runoff, deep drainage and leaching• Gridded data from BoM precipitation, solar irradiance, air

temperatures• Soil properties from Australian Soils Atlas (over 700 soil types)• Vegetation Fraction cover from satellite• Observed hydrological outflows from unimpaired catchments• Land Surface Temperature – from NOAA- AVHRR and AATSR• Enables understanding of trends in water balance

AWAP OutputsAWAP Outputs

• Relative soil moisture in upper (typically 0.2m)• Relative soil moisture in lower layer (typically 0.2m to 1.5m)• Rainfall maximum daily temperature• Evaporation• Transpiration

AWAP PortalAWAP Portal

Soil Moisture (Upper Layer)Soil Moisture (Upper Layer)

Jan 2011 July 2011

Soil Moisture (Lower Layer)Soil Moisture (Lower Layer)

Jan 2011 July 2011

PrecipitationPrecipitation

Jan 2011 July 2011

Local DischargeLocal Discharge

Soil EvaporationSoil Evaporation

Maximum TemperatureMaximum Temperature

Spatial Data InputsSpatial Data Inputs

Spatial Data Challenges in Continental ModellingSpatial Data Challenges in Continental Modelling

• Data Paucity – no data, poor spatial distribution and gaps• Data Heterogeneity – multiple sources, multiple scales, multiple

standards, differing systems and formats• Data Quality – lack of quality assured data• Data Access – lack of sharing or capacity to share existing data• People and Institutional Systems

So what are the possible solutions?

Utilise Multiple Sensors and SourcesUtilise Multiple Sensors and Sources

• Remotes Sensors with Global or Continental coverage– MODIS (or Moderate Resolution Imaging Spectro-

radiometer) revisits every 1-2 days– NOAA – Advanced Very High Resolution Radiometer

(AVHRR) – twice daily coverage– Advanced Along-Track Scanning Radiometer (AATSR)

Spatial Data Infrastructure (SDI) Trends and Importance for Early Warning Systems

Spatial Data Infrastructure (SDI) Trends and Importance for Early Warning Systems

• Spatial Data is now becoming a essential component of our lives – key spatial data such as transport, hydrology, elevation, vegetation are now integrated into our lives eg GPS guidance, Google maps

• Mapping agencies now treat as an infrastructure similar to roads, electricity etc

• Established by governments, primarily at national and state levels and Global initiatives

• Global Spatial Data Infrastructure – bringing spatial data together from local to global

Digital Maps SDI Ver 1

1980 1990 2000

Internet

Information & Communication Age

Digital MappingSeamless / Scalable / Multi-dimensional

2010

SDI Ver 3SDI Ver 2

Spatial Data Now UbiquitousSpatial Data Now Ubiquitous

• Since 2005/6 – access to user-friendly web based spatial information portals has increased dramatically

• Google Earth and Google Maps is probably the most significant development in access to spatial information for the public

• Yahoo maps

Technology Driving ChangeTechnology Driving Change

• In 2000 developing countries accounted for around one-quarter of the world’s 700 million mobile phones by the beginning of 2009 that share had grown to three-quarters but the number had risen to over 4 billion.

• MySpace, YouTube and Facebook had over 400 million visits in the last 2 months – 6 years ago they didn’t exist

• 5 years ago we were talking about convergence – it’s here plus more• Average American teenager sends over 2,200 text message a month• iTunes Apps Store opened in July 2008 there are now over 350,000

Apps available

Citizen or User Volunteered Spatial InformationCitizen or User Volunteered Spatial Information

• Coined Volunteered Geographic Information (VGI) by Mike Goodchild and others

• Examples include – Wikimapia– Open Streetmaps– GeoCommons

• Ordinary people become spatial sensors or reporters• Millions of potential sensors• Meteorological volunteers have leading the way

OpenStreetMapOpenStreetMap

WikimapiaWikimapia

Crowd Mapping and Social NetworkingCrowd Mapping and Social Networking

Crowd Map of Queensland Floods

Tweets on #qldfloods

Some Issues in Volunteered or Citizen Geographic Information

Some Issues in Volunteered or Citizen Geographic Information

• Non-geographic/spatial users supplying data• Large variations in quality• Greater level of subjectivity• Multiple entries• Possible IP issues and legal issues• Existing data standards not designed for ad-hoc users• Metadata variable

Conclusions and Challenges Conclusions and Challenges

• Spatial information and digital mapping is now more accessible than ever before

• Data integration and quality issues remain a significant challenge

• Greater use of mobile technologies and positioning systems to improve the currency and positional quality

• Citizens and users will increasingly have an important role to play in information collection and/or validation