Multi-model projections of trade-offs between irrigated and rainfed maize yields under changing climate and future emission scenarios

Highlights

• 18 GCMs were investigated for impacts of future climate on irrigated and rainfed maize yield.

• Up to 17% declines in decadal rainfed yields with RCP 4.5 emission scenarios were revealed.

• Up to 21.5% declines in decadal rainfed yields with RCP 8.5 emission scenarios were revealed.

• Rainfed yield variability was 533% (RCP 4.5) and 200% (RCP 8.5) > irrigated yield variability.

• Precipitation change explained 46% (RCP 4.5) and 50% (RCP 8.5) variability in rainfed yield.

Abstract

Eighteen global circulation models (GCMs) were evaluated to determine the potential impacts of future climate change on irrigated and rainfed maize yields using the FAO AquaCrop model on an inter-annual and decadal basis (2020 s until 2090 s). Prior to deemed fit for future simulations, AquaCrop model was subject to comprehensive calibration and validation using extensive field-measured long-term datasets. We observed declines in (decadal) rainfed maize yields, ranging from 2.2% (0.2 t/ha) to 17% (1.4 t/ha) and from 8.1% (0.6 t/ha) to 21.5% (1.7 t/ha) under Representative Concentration Pathways (RCPs) RCP 4.5 and RCP 8.5, respectively. The range of declines was lower for irrigated yields [3.7% (0.5 t/ha) to 6.7% (1.0 t/ha) and 4.3% (0.6 t/ha) to 15.6% (2.2 t/ha) under RCP 4.5 and RCP 8.5, respectively]. Near maximal yield declines were distributed uniformly across the century and almost all decades exhibited > 10% yield declines under at least one emission scenario. Both economic (grain yield) advantage associated with irrigation (difference in irrigated and rainfed yields) and yield stabilizing benefit of irrigation (difference in rainfed and irrigated yield variability) are projected to decrease significantly (p < 0.05) under RCP 8.5. Rainfed maize yield variability was 533% and 200% greater than irrigated yield variability under RCP 4.5 and RCP 8.5, respectively. For RCP 4.5, the long-term mean inter-GCM (2020–2099) standard deviation in rainfed yields (4.6 t/ha) was 460% greater than that in irrigated yields (0.8 t/ha), while for RCP 8.5, this difference was 271% (4.6 t/ha vs. 1.2 t/ha). T_max and T_min were able to explain more variability in irrigated than rainfed maize yields, the difference being 229% and 126%, respectively. Precipitation change explained 46% and 50% of the variability in rainfed yield change under RCP 4.5 and RCP 8.5, respectively, and was 100% and 733% greater than what was explained for irrigated yield variability. The research findings hold significance for water allocation considering how dynamics of grain yields vs. availability of irrigation may manifest in the future.

Introduction

Global climate is very likely to warm by 1.2–1.9 °C in the near term (2021–2040) (IPCC, 2021). The global mean surface temperature was 0.99 °C higher during 2001–2020 than during the pre-industrial period of 1850–1900 (IPCC, 2021). Climate change has already impacted crop productivity of major agricultural crops across global agro-ecosystems (Lobell et al., 2011, Kukal and Irmak, 2018a, Skaggs and Irmak, 2012, Lobell and Asner, 2003, Leng, 2017, Ray et al., 2015, Ray et al., 2019). These changes in climate characteristics are projected to manifest as increased mean air temperatures in most land and ocean regions, hot extremes, heavy precipitation and increased probability of drought and precipitation deficits. Such climate shocks and shifts will impact crop yield, cultivation area and food supply, thereby, having major implications on sustainable agricultural development and poverty eradication goals. Climatic variability has been reported to explain more than 60% of the maize, rice, wheat and soybean yield variations in the global primary breadbasket areas (Ray et al., 2015). Thus, assessment of the impacts of magnitude and variations in historical and future climate on crop yield is critical to ensuring food security for rapidly growing world population.

The intensity and direction of climate change impacts on crop production are complex, uncertain and may result in net positive or negative outcomes. The reductions in crop yields, as a result of climate change, are reported to be more common than crop yield benefits (Porter et al., 2014). Crop production is negatively affected by climate change due to increase in climate extremes that include changes in rainfall extremes, increases in hot nights, extremely high daytime temperatures, drought events, heat stress, flooding, chilling damage, spread of pests and diseases. Studies have reported that maize and wheat yields start declining with 1–2 °C of local warming and under nitrogen stress conditions at low latitude areas (Porter et al., 2014). Overall, a significant reduction in crop yield of four major commodity crops including wheat (by 6%), rice (by 3.2%), maize (by 7.4%) and soybean (by 3.1%) has been projected for each degree Celsius rise in global mean temperature (Zhao et al., 2017). On the other hand, warming may benefit crop production in higher latitude areas with more fertile soils, favoring crops and grassland production in contrast to the areas at low latitudes. Climate variations have also been reported to cause lengthening of the growing season due to earlier start and later end of the growing season (Qian et al., 2010, Skaggs and Irmak, 2012). While some reports indicate that increase in atmospheric CO₂ concentrations increased yields by improving radiation and water use efficiencies, the effects of CO₂ fertilization on crops are still uncertain and vary within C₃ and C₄ crop species. This implies that the climate change impacts cannot be generalized as they vary with crop type and site, thus, it is very important to conduct crop and site-specific impact assessments while carrying out future projections to better understand potential dynamics between climate change and agricultural productivity.

This research was conducted to quantify and analyze the impacts of climate variability on South-Central Nebraska maize productivity. Maize is the largest crop grown in the U.S.A., accounting for approximately 31.3% of the world maize production (USDA-FAS, 2020). Nebraska is ranked as the third state contributing the most to the total U.S. maize production (13.0%). Environmental conditions in Nebraska, and the High Plains region is highly variable as indicated by recent droughts (1983, 2002, 2005, 2012, 2017), heat waves (2000, 2002, 2006, 2010, 2011), and floods (2001, 2007, 2008, 2011, 2019). Changes in the observed frequency and intensity of extreme weather events are major concerns for agriculture and will most likely negatively impact agricultural productivity in the U.S. Great Plains states and around the world. The warming of 1.5 ^oC has been reported for the global scale in the last century (IPCC, 2021) and, as many other regions, Nebraska has experienced warming since the beginning of 20th century, mostly during winter and spring months (Irmak et al., 2012, Irmak, 2018; Kukal and Irmak, 2017). The length of frost-free season has increased by 5–25 days across Nebraska and is projected to increase in future decades (Skaggs and Irmak et al., 2012; Kukal and Irmak, 2018b). The percentage of average annual precipitation in the form of heavy rainfall events has increased for portions of northern Great Plains states, including eastern Nebraska, and the Midwest and this trend is projected to continue in future decades increasing the flood magnitudes (Irmak et al., 2012, Irmak, 2018). Climate change impacts many agricultural practices, including hydrologic variables (precipitation, runoff, deep percolation, etc.), crop irrigation requirements, evapotranspiration, etc. Irrigation is one of the major reasons for consistent and high yields of maize in Nebraska and other Great Plains states. Nebraska has higher irrigated acres under maize than any other U.S. state and state’s crop production is highly dependent on surface and groundwater resources (and precipitation) both of which are subject to consequences from climate change and variability. Thus, identifying the climate change impacts under both rainfed and irrigated maize production is crucial to assess and quantify changes in maize yield for future policy and decision-making and developing best agricultural production and management practices and adoption to such changes.

The complex and multi-way interactions among climatic elements and crop parameters require a multifaceted, mechanistic and comprehensive assessments. Process-based crop simulation models are valuable tools to evaluate crop response to climate variations. The FAO AquaCrop model was developed to predict attainable crop growth, water use and yield parameters for various crops under water-limiting conditions. AquaCrop model was chosen to study the impact of climate changes on maize yield because: (1) it has been calibrated and validated for the study region (Sandhu and Irmak, 2019b). (2) it performs well for simulating maize crop’s responses under a wide array of environmental conditions and nutrient management scenarios (Dale et al., 2017; Foster et al., 2017; Heng et al., 2009; Abedinpour et al., 2012; Hsiao et al., 2009; Ahmadi et al., 2015); and (3) it has been used in crop impact projection studies globally and is often intended for policy outcomes (Bouras et. al, 2019; Stevens and Madani, 2016; Dale et al., 2017). The detailed theoretical background and concepts of AquaCrop are provided by Steduto et al. (2009) and Raes et al. (2009). The particular features that distinguishes AquaCrop from other crop models include: (1) its focus solely on water; (2) the use of canopy cover (CC) for simulating crop growth and development and water use instead of leaf area index as CC is more readily available and known to users other than researchers; (3) the use of water productivity that allows extended application of model to diverse climates, locations and seasons; (4) the relatively low number of input parameters and most of which are explicit and mostly intuitive as compared with other models; (5) a well-developed user interface and availability of open source code with appropriate documentation; and (6) its considerable balance between accuracy, simplicity and robustness. Therefore, AquaCrop model was selected for this study to determine and evaluate long-term future (and past) irrigated and rainfed maize productivity relationships with climate.

Irrigation is often discussed as a mitigation tool for decoupling of crop production and climate variability impacts. Although the role of irrigation on historical crop yields is adequately addressed (Kukal and Irmak, 2019, Kukal and Irmak, 2020, Troy et al., 2015, Li and Troy, 2018), limited knowledge exists on how these benefits will sustain in the future, especially with respect to rainfed crop production. It is critical to understand the evolution of crop yield tradeoffs that result from conversion of irrigated to rainfed cropland due to lack of freshwater resources. Limited knowledge exists on how climate change and variability will impact maize yield in the most-intensely irrigated conditions of the U.S. This is especially critical to quantify to be able to better analyze, project and plan groundwater depletion vs. agricultural water requirements and crop productivity relationships. With the potential groundwater resources limitations in the future, the region may experience conversion of irrigated to rainfed farmland (Deines et al., 2020). In this context, it is important to develop irrigated and rainfed yield projections under different emission scenarios to help understand the economic tradeoff among more stable and higher yields and irrigation capital, which currently constitute significant knowledge gaps. The objective of this study is to assess the impacts of climate parameters projected (by 18 GCMs) during the remainder of the 21st century (2020–2099) on irrigated and rainfed maize yields under two different emission scenarios (RCP 4.5 and RCP 8.5). Ultimately, the relative performance of irrigated maize is evaluated against that of rainfed maize to project the sensitivity of the two different crop management regimes against climate change and variability.