In this talk, we will present results from a series of microeconomic case studies that quantify the societal benefits of using environmental satellite information in a range of decisions, including flood hazard notices, drought disaster assistance, post-wildfire response actions, endangered species conservation, harmful algal bloom management, and air quality regulation. We will focus in particular on the flooding, drought, and wildfire case studies. The first study estimates the value of using terrestrial water storage information from the GRACE satellites to improve National Weather Service flood and river flow forecasts; it finds that Valley City, ND could have saved $1.7 million in flood mitigation costs during a 2011 event had GRACE data been incorporated into these forecasts. The second study estimates the value of using the same GRACE-based terrestrial water storage information to inform drought forecasts that can reduce uncertainty in corn and soybean futures markets. The third study demonstrates the cost-effectiveness of using Landsat imagery (instead of commercial satellite imagery or aerial surveys) to map burned land after a wildfire and prioritize post-fire response activities. It finds that federal agencies save up to $7.7 million per year in post-fire costs by using Landsat imagery to input burn severity information into the Burn Area Emergency Response (BAER) program.
The case studies we describe above were conducted by experts from the VALUABLES Consortium, a cooperative agreement between energy and environmental economics think tank Resources for the Future and NASA. These studies employ a microeconomic framework that the consortium is developing as a resource that scientific communities like the American Meteorological Society can use to measure the socioeconomic benefits of using environmental satellite information in decisionmaking. The VALUABLES framework employs a rigorous, quantitative approach known as the value of information, or VOI. The VOI method quantifies the changes that can be attributed to using improved information in decisionmaking. It does this by comparing outcomes in two different states of the world: a state in which action is taken based on currently-available information and a different state in which action is taken using improved information (typically the environmental satellite information whose value we wish to measure). The difference in socioeconomically-meaningful outcomes between the two states represents the value of this information.