Marshall Moutenot
Apr 23, 2018 · 3 min read

Quick experiment: Look down from your screen. I’d wager you just glanced at a hefty amount of cotton. Reading this post in bed? Sounds comfortable! I guarantee you are swaddled in kilograms of spun, woven, washed and dyed cotton. But what happens before the mass processing of the most abundantly produced textile in the world remains largely unknown to the majority of consumers.

Cotton production itself is water-intensive, requiring 20,000 liters of water to produce one kilogram (a little more than the average pair of jeans). For reference, that’s equivalent in water usage to a pruney 35-hour long shower. Don’t try it!

When examined at a global scale, cotton is one of the top agricultural consumers of water. Increasing uncertainty around water supply due to climate change threatens supply chains dependent on cotton, as well as the ecosystems in the river basins where cotton is cultivated. Thankfully, companies are becoming well aware of these risks, and are investing heavily in a more sustainable, more efficiently produced cotton.

Okay, but how?

There are two means by which cotton’s water-use efficiency can be improved:

  1. Increasing the share of irrigated water that plants are able to use
  2. Producing more crop per unit of water

Sounds obvious, but how does one go about implementing these improvements? Since the cultivation of cotton is so widespread, so too is the suite of management practices. From high-tech, industrial-scale farm fields in the Rio Grande River Basin, to small, family-owned farm fields in the Indus River Basin, management practices vary, as do the climates. Through extensive research through pilot programs, a number of “Better Management Practices” (BMPs) have been identified for the various regions in which cotton is grown and, for those of you in the audience waiting to hear where on earth (and off of earth — ha ha) Upstream comes into the picture. Many BMPs can be identified using our satellite technology. Hence the following announcement:

Kennedy Space Center, FL (April 23, 2018) — The Center for the Advancement of Science in Space (CASIS) today announced the selection of three projects from its Cotton Sustainability Challenge. The challenge, sponsored by Target Corporation, provided researchers and innovators the ability to propose solutions to improve crop production on Earth by sending their concepts to the International Space Station (ISS) U.S. National Laboratory. The challenge sought potential solutions to benefit cotton production by improving water sustainability. Through this collaboration, CASIS and NASA will facilitate hardware implementation and in-orbit access to the ISS National Lab, while Target will provide grant funding for selected proposals. CASIS is the organization tasked by NASA with managing the ISS National Lab.

Field Scale, Aggregated Best Management Practice Verification and Monitoring. Marshall Moutenot, Upstream

Upstream is a public benefit corporation with the mission to create economic forces that drive environmental conservation. To do so, Upstream has created a customizable and scalable machine learning platform that utilizes data from Earth-observation satellites to inform and empower public, corporate, and nonprofit sectors to make evidence-based decisions related to water use, management, and conservation. Upstream proposes to leverage ISS remote sensing imagery to expand the capabilities of its “Best Management Practice Assessment and Real-time Monitoring” platform to enable the automated monitoring and analysis of cotton agriculture and inform Target’s production-related water use goals for sustainable cotton production.

Extremely not to scale

And this is just the beginning: Upstream will power Verifiable Sustainability Plans globally for organizations dependent on water-intensive crops. Setting baseline efficiencies, and monitoring progress towards sustainability goals, ensures that investments in infrastructure and management practices are made, well, better.

Upstream Tech

Quantified environmental decision making with machine learning and satellite imagery.

Marshall Moutenot

Written by

Working to conserve freshwater @upstream_tech.

Upstream Tech

Quantified environmental decision making with machine learning and satellite imagery.

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