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Lab Leader: Anthony Acciavatti
Sarthak Arora ❍ Markley Boyer ❍ Ariel Chamberlain ❍ Nikhil Raj Deep ❍ James Smoot ❍ Michael Warner ❍

Naalas are one of the most ubiquitous features of the Ganga River Basin. A stem, watercourse, sewer, drain, or conduit are but a few of the many functions of naalas. Indeed, naalas are critical hydrological infrastructures for farms and cities alike. This applied research project will focus on how the restructuring of naalas within the Ganga River basin can abate pollution and rejuvenate River Ganga with new forms of civic infrastructure and ecological services. In a manner like other major river basins across the world, from the Mississippi to the Yangtze, the Ganga River basin confronts many of the challenges that result with industrialization and urbanization in terms of pollution and environmental degradation. While these challenges are not exclusive to Indian rivers, there are three factors that make the Ganga Basin particularly challenging and unique: population density, agriculture, and monsoons. Not only is the basin one of the most densely populated basins in the world, with over 500 million people dwelling within it, but it remains agriculturally productive and undergoes dramatic changes every year due to immense amounts of precipitation during the southwest monsoon. Rather than attempt to take on the basin in its entirety, this project looks at the ways in which the naala interfaces with these three factors and is a major point source of pollution within the basin today.

This multi-disciplinary project takes a two-prong approach. First, developing new methods of measuring and mapping naalas is crucial. This will involve mapping and categorizing the spectrum of morphologies of naalas across the basin, but also documenting adjoining land parcels and mapping larger catchment areas. From this mapping we will compile a taxonomy of naala types in the states of Uttarakhand and Uttar Pradesh. From this taxonomy we will identify five naalas that confront many of the issues facing the Ganga basin in terms of pollution abatement and rejuvenation. Second, building on the mapping techniques and the categories, we will then develop new prototypes for how and where to develop new forms of civic infrastructure along a naala. These infrastructures must incorporate the dynamism of the monsoons and development pressures facing second and third tier cities across the basin. They might include, but are not limited to, new parks and bioswales or incorporating agriculture and bioremediation. For this project, we will need participants with expertise in hydraulic engineering, soil science, GIS (particularly with experience in riparian systems), permaculturalists with familiarity with bioswales and wetlands, anthropologists, and machine learning engineers.

Anthony Acciavatti is the inaugural Diana Balmori Assistant Professor at Yale University. He is the author of Ganges Water Machine: Designing New India’s Ancient River (2015), which is the first comprehensive mapping and environmental history of the Ganges River Basin in over half a century. Begun at a moment in time when detailed satellite imagery of the Ganges was difficult to obtain, Acciavatti spent nearly a decade crisscrossing the basin by foot, boat, and car. He designed new instruments to map soils and document the choreography of temporary cities and the periodicity of the monsoons.

Coastal Wetland Forests
Elliott White Jr

The goal of our lab is to create a high-spatial resolution map of coastal forested wetlands at global scale. If we know precisely where these ecologically critical but fragile forests are located, we can manage freshwater flows to counteract saltwater introgression due to rising sea levels, and we can assist in their migration inland, preserving their critical function in protecting coastlines and sequestering carbon.

Jason Baldes
Gisel Booman

Across the continent, a number of first nations are in the process of reintroducing bison to the grasslands in which they were once the primary grazer and an ecologically vital species. Initial experiences and evolutionary considerations suggest that this may be ecologically beneficial in terms of grassland biodiversity, carbon cycle, and resilience to climate change. However, these questions have not yet been studied at scale. In this lab, we will leverage remote sensing to scale up from ground measurements, establishing the large-scale patterns of bison impact.

Riparian Ecosystems
Forrest Pound

Beaver dams are known to result in greener, more drought-resilient waterways in semi-arid environments. We are using computer vision to spot dams in satellite imagery, generating a large dataset that we can use to train models that will tell us what the ecological effects of a dam will be at any point on a waterway. The goal is to create a tool to guide efficient restoration through the introduction of small dams.

Bundled Ecological NFT
Philip Taylor

Markets in voluntary carbon credits are increasingly providing a flow of capital for regenerating ecosystems. The problem is, thriving and resilient ecosystems are not just carbon. We need to find ways to structure credits to incentivize the diverse and functional ecosystems we want, not merely high-concentrations of carbon. We will design the technological tools to support a market in bundled ecological credits.

Global Forests
Aron Boettcher

We are building an accurate and global model for predicting potential rates of reforestation and resulting carbon sequestration. Such a model could have a transformational impact on global reforestation efforts by opening new streams of financing in the form of carbon credit futures.

Impact & Risk
Aaron Hirsh
Valérie Lechêne

Leveraging The Earthshot Institute’s broad scientific and technical expertise, the Impact and Risk Lab helps investors and governments who earnestly want to forecast, measure, and address the socio-ecological risks to and/or impacts from their work. For a given system, we build simple process-based models to identify key socio-ecological risks and outcomes. We then draw on big data to improve and train our models, generating quantitative predictions and developing measurement systems for verification.

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