Abstract
Rainwater harvesting (RWH) has been used globally to address water scarcity for various ecosystem uses, including crop irrigation requirements, and to meet the water resource needs of a growing world population. However, the costs, benefits and impacts of alternative crop types and irrigation practices is challenging to evaluate comprehensively. We present an assessment methodology to evaluate the sustainability of agricultural systems as applied to a southeastern U.S. river basin. We utilized detailed, crop-level cultivation information to calculate sustainability indicators (relative to well-water irrigation) at the basin scale (6-digit Hydrologic Unit Codes). 40 design configurations comprising crop types and irrigation practices were evaluated to demonstrate the methodology's robustness. Four RWH designs and four major crops (pasture-grass, soybeans, corn, and cotton) resembling current practices were evaluated, as well as six combined systems (combined RWH and well-water systems) with four globally representative crops (corn, soybeans, wheat, and quinoa). Sustainability scores were calculated by integrating seven life cycle impact indicators (cumulative energy demand, CO2 emission, blue water use, ecotoxicity, eutrophication, human health-cancer, and life cycle costs). At a basin-wide RWH adoption rate of 25%, the benefits, relative to 100% well-water, of the RWH systems irrigating soybeans and supported with well-water (0.4 well-water: 0.6 RWH) provided cumulative energy savings of 39 Peta Joule and reductions in CO2 emission, blue water use, ecotoxicity, eutrophication, and human health-cancer at 1.9 Mt CO2 eq., 6.9 Gm3, 5.7 MCTU, 6.6 kt N eq., and 0.07 CTU, respectively. These benefits increased linearly with RWH scaling variables including the adoption rates, system service life, crop area, and water needs. Our methodology integrates the three pillars of agricultural sustainability specific to rainwater harvesting into a single score. It is applicable to other locations worldwide facing water scarcity by modifying the RWH system design, selecting other crop types, and obtaining appropriate data.