Flash floods are known for their unpredictability, making it challenging for meteorologists to issue timely alerts. These floods can form with little notice, often providing forecasters only hours—if not minutes—to predict their specific impact areas. This was tragically illustrated during the recent Independence Day weekend flooding in Texas, where over 100 lives were lost, including many children and families who were unaware of the ongoing emergency.
The ability to issue effective warnings hinges on the availability of detailed weather and hydrological data. Meteorologists face the difficult task of estimating rainfall amounts and understanding how that water will behave after hitting the ground. Compounding these challenges is the impact of climate change. Moreover, cuts made to federal climate research and weather forecasting under the previous administration threaten to exacerbate an already difficult situation.
The National Weather Service (NWS) characterizes a flash flood as flooding that begins within six hours of a significant rainfall event, or from sudden causes such as a dam break. Storms are typically the primary instigators of such flooding. The science of accurately foreseeing precipitation amounts—known as quantitative precipitation forecasting—is still under development, with scientists striving to refine their methods.
“Getting those very precise measurements at those very precise locations is something that we’re still working on”
Various factors affect how much rain falls in specific areas, including the cloud’s shape, moisture levels within the clouds, and atmospheric conditions between the cloud base and the ground. According to Chris Vagasky, a meteorologist at the University of Wisconsin-Madison, raindrop size, along with wind speed and direction, also plays a crucial role. These variables contribute to the inherent uncertainty surrounding rainfall predictions.
“Getting those very precise measurements at those very precise locations is something that we’re still working on, improving that science,” Vagasky noted. Achieving progress depends on enhanced computer models and a more comprehensive understanding of cloud precipitation processes.
In addition to rainfall predictions, accurately forecasting the subsequent water flow on land includes its own set of challenges. The nature of the terrain—be it sandy, rocky, or urban—affects how the water is absorbed or runs off. The geography of the area and the size of the watershed contribute significantly to the flood risk. Regions like Texas’ hill country, known for its topographical variances, can funnel even modest rainfalls into significant flooding events, especially when channels collapse under the water’s weight.
Forecasts must also factor in the timing between peak rainfall and when flooding occurs downstream. Claudio Meier, a water resources engineer at the University of Memphis, explains that smaller and steeper basins tend to respond swiftly to rainfall, providing little time for alerts to be issued.
“That means that from the moment that you’re seeing all this rain falling to the moment you get the big flood, you only get a few tens of minutes to a couple of hours. So that’s very little time to warn people or do anything about it,” Meier stated.
During the recent flooding, water levels along the Guadalupe River rose dramatically; they surged from 8 cubic feet per second at 1:10 AM to a staggering 120,000 cubic feet per second within a matter of hours. This drastic change turned a calm river into a torrent within a short window of time, demonstrating just how quickly conditions can escalate.
In the wake of the disaster, some scientists have maintained that the NWS forecasts were issued appropriately despite claims of inadequate advance notice from local officials. While forecasters are capable of issuing general rainfall warnings days in advance, specific flash flood alerts require current data, resulting in tighter timeframes for accuracy.
“The last hurdle is to get these messages in front of people”
On Thursday, at 1:18 PM, the NWS issued a flood watch alert for several counties in south-central Texas, indicating that conditions for flash flooding were possible. Later, at 1:14 AM, they issued an upgraded warning, stating that life-threatening flash flooding was imminent due to thunderstorms.
The challenge of communicating these urgent warnings was exacerbated by the timing of the flooding, which occurred while many people were asleep. This phenomenon, called the “last mile” problem by experts like Vagasky, highlights the difficulty in ensuring that emergency messages reach those in need.
Further complicating matters, social media platforms have become less reliable as sources of verified information, and the local NWS office responsible for forecasting was notably missing key personnel after budget cuts, hindering their operational capacity.
In response to these criticisms, the NWS stated that all forecasts and warnings were issued promptly and that they provided necessary support to local emergency management agencies.
Experts have emphasized the importance of robust data collection to enhance the accuracy of flash flood predictions. Proposed cuts to the National Weather Service’s funding could jeopardize essential research and operational activities related to flood forecasting. Additionally, a previously funded global Flash Flood Guidance System, which supported international warning systems, has seen a halt in funding, further diminishing resources available for flood prediction and management.
Recent studies have suggested that climate change has worsened the severity of storms, increasing the likelihood of flash floods. The hotter climate leads to higher evaporation rates, ultimately culminating in heavier rainfall during storms, worsening the risk of flooding.
“It’s absolutely important to rethink how we communicate early warning systems,” advocates Mireia Ginesta, a research associate at the University of Oxford. Ginesta emphasizes the need for continued funding for research and the need for the public to take flooding alerts more seriously.
