A Data-intensive Approach for Evaluating Water-Energy-Land-Food Nexus at
Multiple Scales
Abstract
Satisfying global food demand places a significant burden on finite
resources like water, energy, and land across the world. Ensuring
sustainable food production requires an understanding of water, energy,
and land at local scales, which is often hampered by the lack of
detailed data. Taking advantage of several large datasets, this study
focused on the interactions between groundwater, energy, land, and food
(WELF) at multiple spatial scales in the Indian state of Andhra Pradesh.
Using FAO’s CROPWAT model, MODIS evapotranspiration data, and a detailed
multiscale agricultural database, we estimated the irrigation water
requirements at multiple spatial scales. A detailed estimate of
groundwater and energy consumption was obtained, which was used to infer
the interactions between WELF. The results from our study allow us to
identify local and regional hotspots of groundwater and energy
consumption. Our results indicate that regional estimates of groundwater
or energy consumption, while indicative of local conditions, are unable
to capture the variations at finer scales. The interactions between WELF
at multiple scales also indicate that the efficiency of groundwater and
energy consumption for various crops varies widely across and within
regions. Our study highlights the need to more effectively manage the
cultivation of water-intensive crops such as paddy and sugarcane to
optimize groundwater consumption. Policy-makers must focus on
transitioning towards sustainable agriculture that prioritizes food and
water security. Future research must take advantage of extensive
datasets to better evaluate the adverse effects on water and energy
resources to ensure sustainable food production.