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1. Modeling the Impacts of Climate Change on Crop Yield and Irrigation in the Monocacy River Watershed, USA

   https://doi.org/10.3390/cli8120139  

   Paul, Manashi; Dangol, Sijal; Kholodovsky, Vitaly; Sapkota, Amy R.; Negahban-Azar, Masoud; Lansing, Stephanie (December 2020, Climate)

   null (Ed.)

   Crop yield depends on multiple factors, including climate conditions, soil characteristics, and available water. The objective of this study was to evaluate the impact of projected temperature and precipitation changes on crop yields in the Monocacy River Watershed in the Mid-Atlantic United States based on climate change scenarios. The Soil and Water Assessment Tool (SWAT) was applied to simulate watershed hydrology and crop yield. To evaluate the effect of future climate projections, four global climate models (GCMs) and three representative concentration pathways (RCP 4.5, 6, and 8.5) were used in the SWAT model. According to all GCMs and RCPs, a warmer climate with a wetter Autumn and Spring and a drier late Summer season is anticipated by mid and late century in this region. To evaluate future management strategies, water budget and crop yields were assessed for two scenarios: current rainfed and adaptive irrigated conditions. Irrigation would improve corn yields during mid-century across all scenarios. However, prolonged irrigation would have a negative impact due to nutrients runoff on both corn and soybean yields compared to rainfed condition. Decision tree analysis indicated that corn and soybean yields are most influenced by soil moisture, temperature, and precipitation as well as the water management practice used (i.e., rainfed or irrigated). The computed values from the SWAT modeling can be used as guidelines for water resource managers in this watershed to plan for projected water shortages and manage crop yields based on projected climate change conditions. 

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2. The greenhouse gas cost of agricultural intensification with groundwater irrigation in a Midwest U.S. row cropping system

   https://doi.org/10.1111/gcb.14472  

   McGill, Bonnie M.; Hamilton, Stephen K.; Millar, Neville; Robertson, G. Philip (October 2018, Global Change Biology)

   Abstract Groundwater irrigation of cropland is expanding worldwide with poorly known implications for climate change. This study compares experimental measurements of the net global warming impact of a rainfed versus a groundwater‐irrigated corn (maize)–soybean–wheat, no‐till cropping system in the Midwest US, the region that produces the majority of U.S. corn and soybean. Irrigation significantly increased soil organic carbon (C) storage in the upper 25 cm, but not by enough to make up for the CO₂‐equivalent (CO₂e) costs of fossil fuel power, soil emissions of nitrous oxide (N₂O), and degassing of supersaturated CO₂and N₂O from the groundwater. A rainfed reference system had a net mitigating effect of −13.9 (±31) g CO₂e m⁻² year⁻¹, but with irrigation at an average rate for the region, the irrigated system contributed to global warming with net greenhouse gas (GHG) emissions of 27.1 (±32) g CO₂e m⁻² year⁻¹. Compared to the rainfed system, the irrigated system had 45% more GHG emissions and 7% more C sequestration. The irrigation‐associated increase in soil N₂O and fossil fuel emissions contributed 18% and 9%, respectively, to the system's total emissions in an average irrigation year. Groundwater degassing of CO₂and N₂O are missing components of previous assessments of the GHG cost of groundwater irrigation; together they were 4% of the irrigated system's total emissions. The irrigated system's net impact normalized by crop yield (GHG intensity) was +0.04 (±0.006) kg CO₂e kg⁻¹yield, close to that of the rainfed system, which was −0.03 (±0.002) kg CO₂e kg⁻¹yield. Thus, the increased crop yield resulting from irrigation can ameliorate overall GHG emissions if intensification by irrigation prevents land conversion emissions elsewhere, although the expansion of irrigation risks depletion of local water resources. 

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3. Life cycle greenhouse gas emissions for irrigated corn production in the U.S. great plains

   https://doi.org/10.1016/j.envc.2023.100750  

   Koushki, Raana; Sharma, Sumit; Warren, Jason; Foltz, Mary E. (December 2023, Environmental Challenges)

   Agricultural management practices improve crop yields to satisfy food demand of the growing population. However, these activities can have negative consequences, including the release of greenhouse gas (GHG) emissions that contribute to global climate change. To mitigate this global environmental problem, the management practices that contribute the most to system GHG emissions should be identified and targeted to mitigate emissions. Accordingly, we estimated the cradle-to-product GHG emissions of irrigated corn production under various farmer-selected scenarios at an experimental testing field in the semi-arid U.S. Great Plains. We applied a carbon footprint approach to quantify life cycle GHG emissions associated with pre-field (e.g., energy production, fertilizer production) and in-field (e.g., groundwater pumping, fertilizer application) activities within fourteen scenarios in the 2020 Oklahoma Testing Ag Performance Solutions (TAPS) sprinkler corn competition. We determined that 63% of the total GHG emission from corn production was associated with in- field activities and that agricultural soil emissions were the overall driving factor. Soil biochemical processes within agricultural soils were expected to contribute an average of 89 ± 18 g CO2-eq kg− 1 corn of the total 271 ± 46 g CO2-eq kg− 1 corn estimated from these systems. On-site natural gas combustion for agricultural groundwater pumping, pre-field fertilizer production, and pre-field energy production for groundwater pumping were the next most influential parameters on total GHG emissions. Diesel fuel, seed, and herbicide production had insignificant contributions to total GHG emissions from corn production. The model was most sensitive to the modeled GHG emissions from agricultural soil, which had significant uncertainty in the emission factor. Therefore, future efforts should target field measurements to better predict the contribution of direct soil emissions to total GHG emissions, particularly under different managements. In addition, identifying the optimal application rate of irrigation water and fertilizer will help to decrease GHG emissions from groundwater irrigated crops. 

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4. Quantifying the Natural Climate Solution Potential of Agricultural Systems by Combining Eddy Covariance and Remote Sensing

   https://doi.org/10.1029/2022JG006895  

   Wiesner, Susanne; Desai, Ankur R.; Duff, Alison J.; Metzger, Stefan; Stoy, Paul C. (September 2022, Journal of Geophysical Research: Biogeosciences)

   Abstract Livestock agriculture accounts for ∼15% of global anthropogenic greenhouse gas (GHG) emissions. Recently, natural climate solutions (NCS) have been identified to mitigate farm‐scale GHG emissions. Nevertheless, their impacts are difficult to quantify due to farm spatial heterogeneity and effort required to measure changes in carbon stocks. Remote sensing (RS) models are difficult to parameterize for heterogeneous agricultural landscapes. Eddy covariance (EC) in combination with novel techniques that quantitatively match source area variations could help update such vegetation‐specific parameters while accounting for pronounced heterogeneity. We evaluate a plant physiological parameter, the maximum quantum yield (MQY), which is commonly used to calculate gross and net primary productivity in RS applications. RS models often rely on spatially invariable MQY, which leads to inconsistencies between RS and EC models. We evaluate if EC data improve RS models by updating crop specific MQYs to quantify agricultural GHG mitigation potentials. We assessed how farm harvest compared to annual sums of (a) RS without improvements, (b) EC results, and (c) EC‐RS models. We then estimated emissions to calculate the annual GHG balance, including mitigation through plant carbon uptake. Our results indicate that EC‐RS models significantly improved the prediction of crop yields. The EC model captures diurnal variations in carbon dynamics in contrast to RS models based on input limitations. A net zero GHG balance indicated that perennial vegetation mitigated over 60% of emissions while comprising 40% of the landscape. We conclude that the combination of RS and EC can improve the quantification of NCS in agroecosystems. 

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5. Sustainability of lettuce production: A comparison of local and centralized food production

   https://doi.org/10.1016/j.jclepro.2023.139224  

   Maynard, Reid; Burkhardt, Jesse; Quinn, Jason C (November 2023, Journal of Cleaner Production)

   Communities are considering local food production in response to the pressing need to reduce food system greenhouse gas (GHG) emissions. However, local food systems can vary considerably in design and operation, including controlled environment agriculture (CEA), which refers to agricultural production that takes place within an enclosed space where environmental conditions, such as temperature, humidity, and light, are precisely controlled. Such systems require a considerable amount of energy and thus emissions; therefore, this study seeks to quantify these environmental impacts to determine how local CEA systems compare to alternative systems. For this study’s methods, we apply life cycle assessment methodology to quantify the cradle-to-storeshelf GHG emissions and water consumption of four lettuce production systems: local indoor plant factory, local greenhouse, local seasonal soil, and conventional centralized production in California with transportation. Using geographically specific inputs, the study estimates the environmental impact of the different production systems including geospatially resolved growth modeling, emissions intensity, and transportation distances. The results include the major finding that baseline CEA systems always have higher GHG emissions (2.6–7.7 kg CO2e kg−1) than centralized production (0.3–1.0 kg CO2e kg−1), though water consumption is significantly less owing to hydroponic efficiency. In contrast, local seasonal soil production generally has a lower GHG impact than centralized production, though water consumption varies by crop yield and local precipitation during growing seasons. Scenario analyses indicate CEA facilities would need to electrify all systems and utilize low-carbon electricity sources to have equivalent or lower GHG impacts than California centralized production plus transportation. We conclude that these results can inform consumers and policy makers that local seasonal production and conventional supply chains are more sustainable than local CEA production in near-term food-energy-water sustainability nexus decision making. 

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