Industrial agriculture disproportionately affects minority, low-income, and Tribal communities, propagating environmental injustice. Concentrated Animal Feeding Operations (CAFOs) apply massive amounts of untreated waste to nearby farmlands. Even though the environmental health impacts of CAFOs are well documented, most studies rely almost exclusively on known CAFO locations from public records, which are incomplete.
We integrated analyzing time-series of satellite and hydro-climatic data to quantify flooding, surface water, and their drivers of change and vegetation response to flooding across Australia’s breadbasket, the Murray-Darling Basin (MDB), a large (1 million km2) dryland basin the size of the U.S. 4 corner states from 1986 to 2011. The three decades investigated represented a period of extreme hydroclimatic variability, including the Millennium Drought (1999-2009), the worst drought recorded for southeastern Australia, followed by some of the wettest years on record (2010-11 La Niña years).
Located in the southwest of Western Australia, the Swan Coastal Plain (SCP) is a global biodiversity hotspot with over 1,500 wetlands. More than 70% of the wetlands have been lost since European settlement. The SCP is located in an area affected by recent climate change that also experiences rapid urban development, as the city of Perth has been expanding over time, so has ground water abstraction for urban consumption. We used Landsat TM and ETM+ imagery from 1999 to 2011 to automatically derive a spatially and temporally explicit time-series of surface water body extent on the SCP based on decision trees. We provided the first spatio-temporally dynamic map of the water bodies of the SCP.
Climate and land use change act synergistically to affect scarce water resources, already under enormous pressure in Australia. This cross-disciplinary project aimed to quantify the climate-driven variability and impact of climate and land use change on surface water dynamics and connectivity. This research took a holistic approach integrating remote sensing and climate data, land use science, graph theory, and spatial statistics. The project focused on one of largest dryland basins in the world (the size of the four corner states), Australia’s Murray-Darling Basin (MDB).