By Ayobami Okerinde

As Nigeria continues to face recurring floods and infrastructure failures in its northern regions, a U.S.-based mathematician, Dr. Hayman Thabet is calling for the urgent integration of scientific modeling and machine learning into the country’s infrastructure planning systems.

Thabet, a postdoctoral researcher at the University of Southern Maine and a widely published expert in applied mathematics and scientific machine learning, has emphasized that traditional design practices are insufficient in the face of increasing climate volatility, population growth, and urban sprawl.

“There’s a need for governments and engineering consultants in Nigeria to begin leveraging data-driven, conformable mathematical models,” he said. “These tools offer highly accurate predictions about environmental stress points, and can radically improve the resilience of our roads, drainage systems, and urban layouts.”

Dr. Thabet made these remarks in a recent technical briefing on climate-responsive urban systems, where he outlined how advanced mathematical modeling has transformed planning practices in countries vulnerable to environmental risk. He argues that northern Nigerian states, such as Adamawa, Borno, and Sokoto, all of which have suffered deadly floods in recent years, are ideal candidates for predictive, cost-efficient planning tools.

“Flooding isn’t just a weather problem, it’s a systems modeling problem,” he noted. “You have to model the topography, hydrology, runoff, drainage pathways, and the performance of infrastructure under pressure. Mathematical models, when coupled with real-time data and satellite imagery, can simulate these conditions far more effectively than conventional methods.”

Dr. Thabet’s academic work spans over two dozen publications focused on nonlinear partial differential equations, space-time fractional modeling, and scientific machine learning. While originally designed to address challenges in pandemic modeling and energy systems, his mathematical techniques have found new relevance in climate resilience, particularly in sub-Saharan African contexts.

In the case of Nigeria, he believes his approach could be applied to urban planning through modular, scalable simulations. For instance, city engineers in Maiduguri or Yola could use real-time rainfall, soil, and population density data to simulate how floodwaters might move through neighborhoods or damage critical infrastructure, and then optimize the layout of culverts, roads, and buffer zones before construction even begins.

“This isn’t science fiction,” he said. “It’s already being used to model disease spread, reservoir behavior, and disaster response in other countries. The question is whether Nigerian institutions are ready to adopt it.”

Nigeria has long grappled with challenges stemming from reactive infrastructure policies, responding to disasters rather than preventing them through planning. According to the Nigerian Hydrological Services Agency, 2022 alone saw over 300 deaths and 1.4 million displaced due to floods, with the brunt of the damage recorded in the north. Experts have pointed to inadequate drainage design, poor urban planning, and weak climate risk assessments as key contributing factors.

Dr. Thabet believes that this cycle of damage and repair can be broken, if planners and policymakers invest in simulation tools and academic partnerships.

“Nigeria has brilliant civil engineers and urban planners. What’s missing is the modeling infrastructure, the ability to simulate 50-year floods, optimize infrastructure resilience under uncertainty, and make data-driven trade-offs,” he said.

He proposes a collaboration model where mathematicians, software developers, and infrastructure specialists co-design digital platforms tailored to northern Nigeria’s terrain and demographic realities. Such platforms could guide ministries of works, housing, and environment in state governments to redesign vulnerable districts more effectively, while staying within budget constraints.

“The math is not the hard part,” he added. “The hard part is political will and institutional uptake. But if the right pilot program is launched in just one city, the results will be obvious and scalable.”

His approach draws inspiration from the same mathematical models used in controlling viral outbreaks during the COVID-19 pandemic. The same class of differential systems, which predicted viral load progression and regional transmission, can also simulate hydrological stress, structural performance, and optimal infrastructure spacing under varied rainfall scenarios.

Infrastructure analysts and academics have welcomed the call for deeper modeling integration.

Engr. Abubakar Ahmed Wali, a Nigerian civil engineer and researcher, agrees: “What Dr. Thabet is proposing is well within reach. It’s not only feasible, it’s necessary. Data-driven planning should be the new normal, not the exception.”

In closing, Dr. Thabet stressed that countries that fail to adapt their planning systems to climate era demands will face repeated economic losses and rising social inequality.

“Floods may not discriminate, but poor infrastructure does. And when it fails, it fails the most vulnerable first,” he said.