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Remote Sensing-Based Assessment of the Crop, Energy and Water Nexus in the Central Valley, California

S. Alam,M. Gebremichael,Ruopu Li

Published 2019 in Remote Sensing

ABSTRACT

An integrated assessment of crop-energy-water (CEW) nexus is critical to understand the tradeoffs and synergies for better management of sustainable agricultural systems. In this study, we evaluate the historic evolution of CEW interactions in the Central Valley, California, a critical agricultural region that produces approximately 50% of US fruits, nuts and vegetables. Specifically, we consider three nexus elements, including water use for irrigation (blue water), energy use for groundwater pumping, and crop yield (for all crops aggregated, almond and cotton). To quantify the interactions between CEW elements, we estimate the water use for cropping (water footprint) and energy use for cropping (energy footprint). We conduct the analyses for four historical periods, i.e., 2007–2009 (Drought 1), 2010–2011 (Post-drought 1), 2012–2015 (Drought 2) and 2016–2018 (Post-drought 2). We find that the southern regions (San Joaquin and Tulare) are susceptible to greater stress on energy and water, especially during droughts. The groundwater footprint (GWF) has been continuously increasing due to greater crop water use and a shift from row crops to profitable water-intensive tree crops. The GWF in Tulare during Drought 2 was around 60% higher than Drought 1, where the GWF in Tulare was almost twice that of Sacramento. The energy and water uses for almond production have increased during the recent periods, whereas their uses have mostly decreased for cotton. On average, energy and water footprints under almond crop scenario are around 3–3.5 times as much as the footprints under all crops scenario.

PUBLICATION RECORD

  • Publication year

    2019

  • Venue

    Remote Sensing

  • Publication date

    2019-07-18

  • Fields of study

    Agricultural and Food Sciences, Geology, Computer Science, Environmental Science

  • Identifiers
    DOI 10.3390/RS11141701
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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