Gabriela May Lagunes

Youth Perspectives: Building Climate Change Resilience Through Data Science


In order to tackle climate change, we need to use all the available resources humanity has, and data is one of the most important assets humanity can count on. Therefore, it is imperative that every effort to build resilience is rooted in appropriate data-driven decision making. In this article I share two cases of cities that have failed to do this and give three broad but fundamental recommendations to change this for the better: 1) to invest in digital infrastructure that allows governments to collect and leverage data from its human and natural systems, 2) to make data professionals part of the efforts for climate resilience building, 3) and for all of us to become data champions who bring attention to the importance of data practices for the achievement of climate resilience.


Climate change is possibly the biggest challenge humanity has ever faced, and in order to survive, we need to use all the resources we have. Today, one of the biggest assets humanity has is data. For instance, it is estimated that every day we generate 2.5 quintillion (i.e. 10 to the 18th) bytes of data, that by 2025 there will be 75 billion devices connected to the Internet of Things, and that by 2030 90% of people over 7 years of age will be digitally active [1]. Artificial Intelligence alone is projected to add 15.7 trillion USD to the global economy by 2030 [2]. There is a plethora of statistics that can prove the importance of Data Science. Nevertheless, the efforts made to integrate the leveraging of data into building resilience to climate change are very limited in comparison to other fields.

In this article I will present two non-success stories of cities that have failed to integrate data into their efforts to mitigate the effects and adapt to the challenges brought by climate change. After these cautionary tales, I will give some examples of already available technology that can be used in order to build climate change resilience in the short and long term. This is not meant to be a comprehensive, academic study of the implications that the absence or presence of data governance can have in efforts for climate resilience. Instead, this article is meant to share my own experiences and observations as a student, researcher and young data professional with the hope of bringing a different perspective to the discussion.

A Tales of Two Cities: Freetown and Monterrey

Urban Water Resilience in Freetown, Sierra Leona

Four years ago I was a graduate student in the Engineering Faculty of University College London, and as part of a Master’s degree I wrote a dissertation titled “Climate Change Resilience of The Urban Water System in Freetown” [3]. For this project I was granted funding and support from the university and its industrial partners to go to Freetown and develop a framework to assess the level of resilience to climate change and other natural hazards of the precarious water network of the capital.

The objective of the project was to bring together different dimensions and aspects of resilience and to develop a methodology to help the people in charge of the water systems to assess how resilient the system could be to different climate scenarios. The idea was that, with the help of this self-assessment tool, the relevant organisations could adapt to new climate conditions and address already existing challenges. Based on previous research and literature reviews I made beforehand, during my time in the city I conducted several interviews with different NGOs and grassroots organisations, talked to national and local authorities, had stakeholders and beneficiary workshops, visited water treatment plants, tested pipes, tracked water leaks and even learned the basics of water dam designs from a group of international engineers that at the time were working on renovating the water network. Back in London, I brought all of those learnings together into a very comprehensive evaluation framework for urban water systems called ResUrb [3].

At the time I did not know it, but the most important encounter I had in Freetown was with Mr Clifford Coomber. Mr Coomber had worked for the Guma Valley Water Company for over 18 years by the time we met. The Guma Valley Water Company was the government body in charge of keeping the water network that served Freetown and its citizens. Mr Coomber was the main carer of the already worn-down Guma Valley water dam, the main water source of Freetown. He showed me the dam and the outdated working conditions in which its infrastructure was kept at the time. And the most remarkable thing he showed me was a notebook (see Figure 1).

Figure 1. Last and first entry of Mr. Coomber’s notebook in June 2018.

In this notebook Mr Coomber had meticulously recorded by hand the volume of rainfall and the water reservoir levels that the dam had every single day between January 2001 and June 2018. In an urban setting with zero digital infrastructure for the tracking of any human activity or basic services like water and energy supply, Mr. Coomber had created a small but priceless, almost 20-year-old database with information that could serve as a proxy for the demand, use and availability of water in the whole city. He kept this record by his own initiative and without any clear objective. In his own reasoning, he just thought it was interesting to see the changes brought by time. This almost miraculous data wrangler made it possible for myself and the international team of engineers working on the water network to get insights like the following (see Figure 2).

Figure 2. Total days of rain per year at the Guma Dam and Reservoir levels of the Guma Dam per day per year (feet)

With the registry of rainfall, we could see that there was a gradual and constant decreasing of the length of the rain season over the Guma Valley dam. This meant that the dam had about 15% less water available at the end of that 18-year period. We could also see that this had a visible effect on the way the water dam replenished itself every year. The yearly reservoir levels showed that the dam lowered its levels consistently during the first half of the year, and then filled again during the rainy season. This pattern alone could have made us think that the amount of water available for the population stayed consistent, but interviews with the Guma Valley Company staff revealed that the reason why the 2017 line is so similar to 2001 was because they started having a set number of hours every day in which the dam was closed starting from 2008. In order to be able to reach maximum capacity in the dam after the rainy season, the city was left without water starting with a couple of hours every day. This daily closure became longer and longer with time, and by the time I was there in 2018 the city had water only around 9 hours a day. It took me a long time to understand this because, of course, I was staying in a privileged area of the city full of hotels with the infrastructure to sustain private water reservoirs.

In the end this framework achieved two things: First, it helped me gain my second Master of Science degree with a distinction. Second, and I believe more importantly, it became a nice, thick addition to the pile of forgotten books, papers and reports that no one ever reads on a shelf of Freetown’s Guma Valley Water Company office. It may have helped someone to kill a mosquito or two, but I can neither confirm nor deny that assumption.

According to my professors’ feedback, the framework I proposed in this project was a sound piece of academic work in the fields of Engineering and Climate Sciences. But in the end it amounted to nothing because, in order to be applied, it required the people in charge of the city’s water to have a crucial and completely absent resource: data. Data about the changing levels of precipitation that fell into the main water dams. Data about the effect of erosion around the water dams due to deforestation and illegal human activities in protected areas. Data about the growing demand of water due to a growing population and migration. Data on the effects of fast spreading waterborne diseases. Data about loss of both water and active income due to leakages, illegal interventions to the pipes and missing payments of many users.

The data I was able to get from Mr. Coomber’s notebook helped the engineers working in the renovation of the water system to better plan their work. It gave them insights to the water volumes available in different moments of the year and how these were changing with time. Nevertheless, to my knowledge, there were no subsequent efforts to keep data collections beyond Mr. Coomber’s notebook. This means that whatever achievements in water infrastructure the international organisations working in Freetown could have, were doomed to have an ephemeral impact. This was because the changing weather conditions were going to increase the system’s vulnerability with time and the authorities lacked the information in order to adapt to these conditions.

Today, water access continues to be an overbearing challenge in Sierra Leone, where 60% of the population has no access to clean water and the level of vulnerability of the poorest keeps increasing with the changing weather conditions and the aftermath of the Covid-19 global pandemic [4].

Droughts in Monterrey, Mexico

Fast forward to the summer of 2022. Due to the Covid-19 pandemic I left London in 2020 and moved back to Mexico, my home country. My husband and I made this difficult decision so that our then-newborn son could interact with his family (and not only with his mother and father) during the long months and years we needed to isolate without knowing when or how we could have access to vaccines. It was only in June this year, 2 years and 3 months after the first lockdown was announced in the U.K., that the CDC approved the application of Covid-19 vaccines in kids of his age group (from 6 months to 5 years), and we still have to wait some months for our second baby to be able to be vaccinated [5].

We live in Monterrey, an industrial and prosperous city, home to one of the most important universities of Latin America [6], and the wealthiest borough in the country. Even though Monterrey’s society is proud of its achievements, conservative values and work ethic, a couple of months ago life in Monterrey became a bit closer to what life in Freetown has been for decades. During the past 6 years our region has seen consistently lower levels of rainfall every year, and now we are in the middle of the worst drought ever recorded with the highest temperatures in the region registered since 2015. The 3 reservoirs that serve the city are at 45%, 8% and 2% capacity. Right now, the whole city only has running water from 4 a.m. to 10 a.m. every day, with some random days having shorter time windows, and with the most marginalised areas of the city getting no water at all [7].

Figure 3. Images of the diminishing levels of water in La Boca dam and of people waiting for water trucks in Monterrey. Photos by Reuters [8]

Climate change has brought the hardest drought recorded, but the effects that this natural hazard is having on the population of my city could have been prevented if its authorities had had an appropriate, data-driven water management system in place. For instance, in the 1980s Mr. Alfonso Martinez, the then governor of the city, predicted that the city should not go beyond 4 million people in population to avoid extreme stresses in the water system [9]. Monterrey’s population, however, is more than 5.5 million people today, and no major updates have been done to the urban water network since his time. In addition, the water system has been exploited without regulation by private companies and industries that, theoretically, had agreed on respecting pre-established limits in their water consumption [7]. Major plans for the update and restructuring of the city have been in place since 2016 [10] but these lack clear pathways of data governance that would make their tracking and implementation transparent and, eventually, successful. There have even been talks of starting a smart monitoring of water usage in the city to achieve these objectives since 2017, [11] but these have not had any tangible results so far.

Lack of water has already made it harder to keep the hygiene measures necessary to keep Covid-19 at bay in the region. In the month of June alone, the weekly average for new cases in the state of Monterrey grew from 30 to over 850, meaning that we are well into the 5th wave of the pandemic for the city [12]. Moreover, water-borne diseases are at a rise, with a recent and severe spread of norovirus in the state [13]. I lack access to statistics for the number of cases that Monterrey has seen of norovirus in the past couple of months, but I can tell you that I had to take my 2-year-old toddler to the emergency room 3 times within the same week due to this public health issue, that for him meant sudden and unstoppable vomiting, diarrhoea and fever. It took him almost a month to fully recover. Now he is well and thriving, but again, not everyone has the same blessings and resources we do.

Data Science for Climate Resilience, Everywhere

I presented the antithesis of success stories of the use of Data Science to tackle the climate crisis because I wanted to illustrate how dangerous and neglectful it is to govern without insights brought by data nowadays. I still have not seen a fully successful case of a city or region taking data-driven decisions for the good of its people. Nevertheless, I believe it is possible. This is why my current work and education is aimed so I can be part of the new wave of data practitioners making this dream a reality. But action is needed now, more than ever. Therefore, I leave with you some recommendations on how to integrate data into our resilience building efforts.

The Internet of Things

The internet of things (IoT) is the network of devices producing and collecting data from a great variety of systems. It can be used to have smart and efficient water, energy and waste management in urban settings, to monitor and control air quality, and to track live networks like transportation and supply chains [14]. There are already successful companies developing accessible devices for different and specific objectives which could help governments achieve their resilience building goals [15]. It is imperative that cities and countries invest in IoT infrastructure in order to be able to build resilience for the human and natural systems they are responsible for.

Figure 4. Sustainable IoT for Sustainable Smart Cities. Image taken from Ram et al. 2020.[16]

Complex Solutions for Complex Problems

Data Science could be thought of as a collection of methodologies to generate valuable insights from large and complex sets of data. The building of resilience to climate change is a multidisciplinary, multidimensional problem, and Data Science has a great but still under-used potential for it. Deep Learning is a prominent area of Data Science where data is processed by neural networks and high processing computing, algorithms and computational resources that mimic the way the human brain functions. Deep Learning makes it possible to achieve relevant capabilities for resilience building like predicting extreme weather events, localising and visualising climate distressed areas via satellite images, discovering new and more efficient materials, and designing and monitoring more efficient human and natural systems, like forestry, agricultural lands and buildings [17]. It is imperative that data professionals become part of the efforts of resilience building so this kind of knowledge and insights become assets for data-driven decision making of governments and public institutions.

Data Champions

As you can probably tell from my tales, it all boils down to free will. We can take all the data and technology of the world, and it will not be enough to solve the climate crisis if authorities, institutions and people are not willing to use them for the greater good. We need to have data champions in all levels and kinds of organisations and institutions that bring attention to the need for collecting and leveraging appropriate data to make smart decisions for resilience building.

Concluding Thoughts

The effects of climate change are already upon us. The most privileged will be able to adapt and maybe even thrive. But that will not be the case for the majority if climate action remains secondary in the world’s leaders’ agendas. We have to act now so our work does not end up in a pile of unread publications full of unheard cautionary tales of an imminent, bleak future for our already born children. Please help me clean up this world so that our kids can have a happy, joyful and peaceful life worth living.


[1] Infographic: How much data is produced today? CloudTweaks.

[2] 32 Crucial Technology Industry Statistics to Know in 2022. Ana Djurovic. February 16, 2021. GoRemotely

[3] Climate Change Resilience of The Urban Water System in Freetown. Gabriela May Lagunes. University College London Department of Civil, Environmental & Geomatic Engineering. Submitted on September 12, 2018 as part of the requirements of the MSc Engineering for International Development program. 

[4] Sierra Leone. Water Aid. WASH Matters, Policy and Practice. 

[5] CDC Recommends COVID-19 Vaccines for Young Children. CDC Media Statement. Saturday, June 18th, 2022.

[6] Tecnolgico de Monterrey. Best Universities Global Ranking. U.S. News. 

[7] Monterrey suffers weeks-long water cutoff amid drought. Marcos Martínez Chacón. The Washington Post. June 21, 2022. 

[8] La peor sequía en Monterrey. Fotos. Milenio Noticias. July 2, 2022. 

[9] El ex-gobernador Alfonso Martínez lo predijo hace 40 años. YouTube video shared by Samuel García, current governor of Nuevo Leon. Published on June 21, 2022. 

[10] PLAN HÍDRICO NUEVO LEÓN 2050. Fondo de Agua Metropolitano de Monterrey. Rodrigo Crespo Elizondo et al. 2016. 

[11] Monterrey: Manejo climáticamente inteligente del agua, December 20, 2017, por Svante Persson. 

[12] Covid-19 Statistics for Mexico. Google Visualisation consulted on July 2, 2022. 

[13] ¿Qué es el norovirus, el virus con presencia en Nuevo León? Expansión Política. April 13th, 2022. 

[14] IoT and Sustainability: 7 Applications for a Greener Planet. BehrTech Blog 2022. 

[15] 13 Examples of IoT in Environmental Sustainability You Should Know. Mike Thomas. Built In. June 29, 2022. 

[16] Ram, Saswat & Sahoo, Sauvagya & Das, Banee & Mahapatra, Kamalakanta & Mohanty, Saraju. (2020). Eternal-Thing: A Secure Aging-Aware Solar-Energy Harvester Thing for Sustainable IoT. IEEE Transactions on Sustainable Computing. PP. 1-1. 10.1109/TSUSC.2020.2987616. 

[17] Fighting the Climate Crisis: 6 Future Game-Changers Made Possible by Deep Learning. Daniel Fleury. Towards Data Science. Jun 30, 2019.