Salt of the Earth

Abstract

Salinity in surface waters is on the rise throughout much of the world. Many factors contribute to this change including increased water extraction, poor irrigation management, and sea-level rise. To date no study has attempted to quantify impacts on global food production. In this paper we develop a plausibly causal model to test the sensitivity of global and regional agricultural productivity to changes in water salinity. To do so, we utilize several local and global datasets on water quality and agricultural productivity and a model which isolates the impact of exogenous changes in water salinity on yields. We then train a machine learning model to predict salinity globally in order to simulate average global food losses from 2000-2013. These losses are found to be high, in the range of the equivalent of 124 trillion kilocalories, or enough to feed over 170 million people every day, each year. Global maps building on these results show that pockets of high losses occur on all continents but can be expected to be particularly problematic in regions already experiencing malnutrition challenges.