As a senior pursuing his degree in sustainable development at Columbia, Dylan Dettloff jumped at the opportunity to take a newly offered course in spring 2025: Climate & Sustainable Water Systems taught by Cynthia Paulson, adjunct professor at the Columbia Climate School. Dettloff enjoyed learning about myriad water policy issues, especially how underserved communities can play a distinctive role in addressing water scarcity.
He learned that small communities, especially Indigenous communities, are struggling. Globally, 1 in 4 people do not have access to clean water. Although technology and strategies exist to address the lack of potable resources, spanning water management, distribution, treatment and conservation, the benefits tend not to trickle down. These technologies often remain unimplemented in smaller communities facing dire need.
Dettloff applied to and received the Columbia Climate School Collaborative Research Grant, which gave him the chance to explore this newfound interest and develop something meaningful. Broadly, students apply for funding for two consecutive semesters and participate with a poster in the Climate School Student Research Showcase at the end of April following the application year. Dettloff proposed and executed research on identifying desalination approaches for rural and water-scarce communities through a multi-criteria decision analysis (MCDA) framework with Paulson as his supervisor. MCDA uses structured frameworks to rank and compare alternatives when there are multiple, and often conflicting, objectives. He created a Python-based model that takes inputs of physical and social data from communities and helps policymakers make more informed decisions about which water technologies to implement.
For the project, Dettloff wanted to model one water technology: solar still desalination. This technology uses thermal energy from the sun to evaporate water and leave salts or contaminants behind. The result is pure drinking water. Dettloff’s initial idea involved optimization modeling, or figuring out which technological improvements could maximize freshwater yield while minimizing equipment costs. But after receiving the grant and beginning his research, he realized that a lot of optimization work had already been done. The gap he identified was in the rollout of the technology: the missing piece that determines how communities can best access and use it.
Depending on where communities are located and their composition, different water technologies “can serve them better than others,” he found. Dettloff ultimately created a tool that ranks technologies given a community background. The MCDA framework—introduced to Dettloff by Paulson—takes in social and geophysical data points and ranks water technologies based on how they match up with those data points. This decision science approach allowed Dettloff to take different aspects of the solution (in this case, water technology) and rank them in sequence, showing how different conditions may affect each other in the future. For example, if the price of fossil fuels decreases or solar energy becomes vastly more affordable, technologies might switch rankings, altering what could be a better fit for a certain community. Ideally, the tool is accessible enough that any infrastructure or community planner can use the model independently.
Dettloff included five sample areas: the Navajo Nation, two communities in India, one in Namibia, and one in Madagascar. His goal is for all people who end up using this tool to understand the output of the model; he envisions continuing to work to make the charts and visuals more readable. Going forward, he would also love to go to each of those communities to ensure the social data is accurate by meeting with community leaders.
A highlight of Dettloff’s research process involved a visit to the Massachusetts Institute of Technology (MIT), a trip enabled by the grant funding. He went with Paulson to meet with different mechanical engineers and Ph.D. students who were working on electrodialysis, another membrane-based process in which a direct electric field separates liquid into purified water and a concentrated brine stream. Dettloff spoke with Melissa Brei at MIT, who also did desalination research in coordination with the Navajo Nation in the American Southwest.
Dettloff’s time at MIT shaped how he viewed some of the water solutions he had been analyzing. He understood that sometimes community members must drive more than two hours to get bottled water. Point-of-use solutions, which are installed directly where the water is dispensed, could minimize this need to haul water.
Dettloff remarked that “opportunities like [the Collaborative Research Grant] don’t exist as much as they should.” For other students interested in taking advantage of the grant opportunity, Dettloff offered some advice. In the proposal, he suggested including specifics about skills you might not have fully developed yet and explaining how you are going to advance those skills. Dettloff was “by no means a Python expert” when he started his project, but he knows much more now because he built it into his work. The funding also covered the software he needed for model creation and data analysis.
Dettloff is currently working to get his paper published. He has gone through many rounds of editing with his faculty advisor, and following its possible publication, Dettloff believes there is a lot more he can do and study in this field. If possible, Dettloff would like to collaborate with people who have greater expertise in Python programming to make his model more accurate. He also hopes to continue studying water scarcity through a Ph.D. program in the future.
