“MIT is a place where dreams come true,” says César Terrer, an assistant professor in the Department of Civil and Environmental Engineering. Here at MIT, Terrer says he’s been given the resources to explore the ideas he finds most exciting, and at the top of his list is climate science. In particular, he is interested in plant-soil interactions and how both can mitigate the impacts of climate change. In 2022, Terrer received a seed grant from the Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) to produce drought monitoring systems for farmers. The project is leveraging a new generation of remote sensing devices to provide high-resolution plant water stress on a regional and global scale.
Growing up in Granada, Spain, Terrer always had an aptitude for and a passion for science. He studied Environmental Sciences at the University of Murcia, where he did an internship in the Department of Ecology. Using computational analysis tools, he worked on modeling the distribution of species in response to human development. Early in his college experience, Terrer says he viewed his professors as “superheroes” with some kind of academic prowess. He knew that he wanted to follow in his footsteps by one day working as a faculty member at the academy. Of course, there would be many steps along the way before achieving that dream.
Upon completing his undergraduate studies, Terrer set his sights on exciting and adventurous research roles. He thought that maybe he would do field work in the Amazon, interacting with the native communities. But when the opportunity arose to work in Australia on a state-of-the-art climate change experiment that simulates future carbon dioxide levels, he headed south to study how plants react to CO.2 in an Australian native eucalyptus biome. It was during this experience that Terrer became very interested in the carbon cycle and the ability of ecosystems to buffer rising levels of CO2 caused by human activity.
Around 2014, he began to delve into the carbon cycle when he began his PhD studies at Imperial College London. The main question that Terrer tried to answer during his PhD was “will plants be able to absorb the expected future levels of CO2 In the atmosphere?” To answer the question, Terrer became an early adopter of artificial intelligence, machine learning, and remote sensing to analyze data from real-life global climate change experiments. His findings from these “basic truth” values and observations resulted in an article in the journal Science. In it, he claimed that climate models likely overestimated the amount of carbon that plants will be able to absorb by the end of the century, by a factor of three.
After postdoctoral positions at Stanford University and the Universitat Autónoma de Barcelona, followed by a prestigious Lawrence Fellowship, Terrer says he had “too many ideas and not enough time to carry out all those ideas.” He knew it was time to lead his own group. Not long after applying for teaching positions, he landed at MIT.
New ways to monitor drought
Terrer is employing methods similar to those he used during his PhD to analyze data from around the world for his J-WAFS project. He and postdoc Wenzhe Jiao collect data from remote-sensing satellites and field experiments and use machine learning to find new ways to monitor drought. Terrer says Jiao is a “remote sensing wizard,” fusing data from different satellite products to understand the water cycle. With Jiao’s hydrology background and Terrer’s knowledge of plants, soil and the carbon cycle, the duo are a formidable team to tackle this project.
According to the United Nations World Meteorological Organization, the number and duration of droughts has increased by 29% since 2000, compared to the previous two decades. From the Horn of Africa to the western United States, drought is devastating vegetation and severely stressing water supplies, compromising food production and increasing food insecurity. Drought monitoring can provide critical information about the location, frequency, and severity of drought, but assessing the impact of drought on vegetation is extremely challenging. This is because the sensitivity of plants to water deficits varies between species and ecosystems.
Terrer and Jiao can get a clearer picture of how the drought is affecting plants using the latest generation of remote sensing observations, which provide images of the planet with incredible spatial and temporal resolution. Satellite products such as Sentinel, Landsat, and Planet can provide daily images from space with resolution so high that individual trees can be distinguished. Along with the images and data sets from the satellites, the team is using ground-based observations of weather data. They are also using the MIT Supercloud at the MIT Lincoln Laboratory to process and analyze all data sets. The J-WAFS project is one of the first to harness high-resolution data to quantitatively measure the impacts of drought on plants in the United States with the hope of expanding to a global assessment in the future.
Help farmers and resource managers
Each week, the US Drought Monitor provides a map of drought conditions in the United States. The map has zero resolution and is more of a summary or summary of the drought, unable to predict future drought scenarios. The lack of a comprehensive spatiotemporal assessment of the historical and future impacts of drought on global vegetation productivity is detrimental to farmers both in the United States and around the world.
Terrer and Jiao plan to generate metrics for plant water stress with unprecedented resolution of 10 to 30 meters. This means they will be able to provide drought tracking maps at the scale of a typical US farm, giving farmers more accurate and useful data every day or two. The team will use the information from the satellites to monitor plant growth and soil moisture, as well as the time lag in the response of plant growth to soil moisture. In this way, Terrer and Jiao say they will eventually be able to create a kind of “plant water stress forecast” that could predict the adverse impacts of drought four weeks in advance. “Based on the current soil moisture and delayed response time, we hope to predict future plant water stress,” Jiao says.
The expected results of this project will provide farmers, land and water resource managers, and decision makers with more accurate data at the specific farm level, enabling better drought preparedness, mitigation, and adaptation. “We hope that our data will be open access online once we finish the project, so that farmers and other stakeholders can use the maps as tools,” Jiao says.
Terrer adds that the project “has the potential to help us better understand future states of climate systems and also to identify regional hotspots most likely to experience water crises at the national, state, local and tribal government scales.” He also hopes the project will improve our understanding of the global carbon-water-energy cycle responses to drought, with applications to determine the impacts of climate change on natural ecosystems as a whole.
