Climate change has clearly intensified the frequency and intensity of weather extremes. As a result, more and more floods with devastating consequences are being recorded around the world. To better cope with them, we need accurate and precise forecasts and warning systems. According to hydrologists, the most important prevention tool in the coming years will be artificial intelligence. How can AI help? Practical solutions are already being implemented, with considerable success.

Artificial intelligence in flood risk management

The process of climate change cannot be easily stopped – even consistent reductions in emissions will not work like a magic wand and will not save us from the effects of further cataclysms in the coming decades. The key issue, therefore, is to prepare adequately for extreme weather events and effectively mitigate their effects.

In the field of flood risk management, artificial intelligence offers unprecedented advantages – it can quickly process huge amounts of data and formulate the most likely forecasts and models based on it. Satellite images and hydrological measurements are used for analysis, on the basis of which it is possible to try to understand how floods occur and what determines their scale. Due to the volume and complexity of this data, only computer technology has a chance to make calculations fast and accurate enough.

Artificial intelligence as a flood risk management tool makes it possible to formulate forecasts well in advance and with a precision that humans cannot match. They form the basis for spatial planning and, above all, the preparation of infrastructure and rapid response systems for disasters. The benefits cannot be overestimated, both in terms of protecting human life and health and preserving property assets.

Technologies used by AI

The great potential of artificial intelligence in forecasting meteorological and hydrological phenomena lies in the so-called “artificial intelligence”. machine learning(from machine learning). We are talking about processes resulting from the software used in AI, and enabling actual learning based on the information input. The more data we provide to artificial intelligence, the easier it will be for it to draw complex conclusions about the processes taking place on Earth.

From the point of view of flood control, the so-called “flood prevention” is particularly important. Deep learning, which involves the creation of multilayer neural networks. Artificial intelligence uses the data given to it to predict future events based on past experience – this can be done in a supervised way, with the exact type of data tagged, or unsupervised, when AI tries to find order in the information on its own, without human intervention.

Self-developed algorithms allow the machines to observe the course of the flood using images acquired from Sentinel-2 and Landsat satellites and information from the MODIS sensor. The result is very fast and accurate forecasts with much higher probabilities than the traditional models used for decades to predict hydrological phenomena. An excellent example of technology development in this area is the Sen1Floods11 project, which used 4831 chips to monitor flooding on six continents. The result was the acquisition of a dataset on surface water, on the basis of which it is possible to train, verify and test convolutional neural networks capable of in-depth image analysis based on various filters.

Unfortunately, as experts point out, machine learning – despite all its advantages – also has its overt limitations. One of the more serious is the selection of the right algorithms, closely related to the quality of the systems used to train artificial intelligence.

Artificial intelligence versus flooding – what it looks like in practice

Flood control using AI is not at all a vision straight out of science fiction movies, but an actual practice already being implemented successfully in many places around the world. We’re talking about both global initiatives to assess trends in climate change and local efforts seeking to reduce flood losses in the here and now.

An interesting example is a project carried out by scientists at Texas A&M University with financial support from the National Oceanic and Atmospheric Administration (NOAA). As part of it, users send via the BluPix application photos of road signs partially submerged by rising water levels. Artificial intelligence analyzes the photos and compares them with the actual height of the poles, while assessing the depth of flooding and the extent and speed of the spreading floods. The initiative was created in response to the disaster caused by Hurricane Harvey in 2017, which resulted in the loss of more than 100 lives and property damage of 125 billion dollars.

The Irish city of Cork, on the other hand, is using an innovative model developed by researchers at the CeADAR AI Applications Center, based at the University of Dublin. In its framework, artificial intelligence takes historical data from satellites and creates maps from which it is possible to predict future floods with surprising precision.

At the University of New Orleans, researchers are combining images acquired from military drones with sensory data and using them to monitor the integrity and stability of flood control systems. The project, in which artificial intelligence and its analytical capabilities play a key role, is of tremendous importance in a region that regularly experiences flooding from hurricanes, heavy rainfall and flooding of the Mississippi River.

AI algorithms are also used in a global tool developed by Google to forecast floods around the world. Google’s Flood Forecasting System is a hydrological model that predicts how water levels in rivers and streams will rise, while forecasting the scale and scope of floods. Based on in-depth analysis, warnings are prepared and can be distributed as early as 5 days before an expected disaster. Another publicly available tool, FloodHub, monitors river levels in 180 countries around the world and provides forecasts of expected floods in 1,800 locations with 450 million people, including Poland.

How does the future look?

Report published in 2023. by the Stockholm International Peace Research Institute (SIPRI), however, warns of the limitations of using AI to enhance climate security.

The quality and availability of data, without which artificial intelligence cannot create realistic models, is cited as a major problem. Experts stress that it is necessary to develop new technologies and data sources that will enable a more interdisciplinary approach to forecasting.

Further progress will help develop more efficient and stable solutions to better manage water resources and respond more quickly to flood risks. In SIPRI’s view, artificial intelligence is crucial to the development of strategies for adaptation and climate change mitigation efforts, which translates into building more resilient communities and better protection of natural ecosystems. Technological advances appear to be the way forward for more efficient and effective flood risk management in a world increasingly hard-hit by a capricious climate.

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