DISASTER ALERTSCuts to Early Warning Systems Are Leaving the U.S. Unprepared for Summer Floods
The extreme costs and death toll of recent floodings across Texas, New Mexico, and the Northeast have put into question the future of the United States’ emergency preparedness amid major budget and staffing cuts to critical risk-reduction agencies and programs.
Flash floods in Texas Hill Country killed at least 130 people earlier this month, while New Mexico, New York, and New Jersey experienced flooded transit systems, blocked roads, and even swept away homes in the past several weeks.
The United States has seen intense rainfalls this summer—at least four that are thought to have a roughly 0.1 percent chance of happening in a given year. As temperatures rise, the atmosphere can hold more water vapor: for every 1°F of warming, the air can hold 4 percent more moisture. This added moisture can make rain fall heavier and faster, leading to increased flooding.
Partially to blame for the vast devastation and damages across the country is the lack of effective warning systems, despite efforts from state officials to seek state funding to bolster preparedness. Early warning systems save lives, livelihoods, and property during and after disasters by allowing people to seek shelter and take action to protect property. That may mean evacuation or sheltering in place, boarding up windows, moving animals and vehicles to higher ground, or protecting critical infrastructure like the electric grid. However, the Trump administration’s cuts to the necessary agencies that assess the risk of emergencies, develop weather forecasts to inform early warning systems, and provide disaster relief threaten the safety of Americans in the face of increasingly extreme weather events.
How do early warning systems work?
Early warning systems alert people to imminent threats in their immediate area. Typically issued by government agencies, an early warning gives individuals, communities, and organizations time—anywhere from minutes in the case of an earthquake to days in the case of a hurricane—to reduce risk of harm before disaster strikes.
The first step is identifying the risks posed to a particular region or sector. Historical disaster data can provide insights as to how future hazards may unfold. However, climate change is rapidly altering the intensity and/or frequency of certain hazards—including wildfires, extreme rainfall, storms, and drought. That means that the worst flood that happened in the past may no longer be a good guide for estimating the scale of flooding in the future.
Once authorities identify potential risks, experts monitor those risks by analyzing data for signs of changing conditions and to detect imminent threats. Data sources include rain and wind gauges, seismic sensors, buoys, and satellite observations. Artificial intelligence (AI) has also been increasingly assisting in the data analysis process.
