Climate variability and trends affect global crop yields and are characterized as highly dependent on location, crop type, and irrigation. U.S. Great Plains, due to its significance in national food production, evident climate variability, and extensive irrigation is an ideal region of investigation for climate impacts on food production. This paper evaluates climate impacts on maize, sorghum, and soybean yields and effect of irrigation for individual counties in this region by employing extensive crop yield and climate datasets from 1968–2013. Variability in crop yields was a quarter of the regional average yields, with a quarter of this variability explained by climate variability, and temperature and precipitation explained these in singularity or combination at different locations. Observed temperature trend was beneficial for maize yields, but detrimental for sorghum and soybean yields, whereas observed precipitation trend was beneficial for all three crops. Irrigated yields demonstrated increased robustness and an effective mitigation strategy against climate impacts than their non-irrigated counterparts by a considerable fraction. The information, data, and maps provided can serve as an assessment guide for planners, managers, and policy- and decision makers to prioritize agricultural resilience efforts and resource allocation or re-allocation in the regions that exhibit risk from climate variability.

Significant air temperature changes have occurred globally during the 20^th century, which are spatially variable to a considerable degree and these changes can have substantial implications in agroecosystem productivity. The agroclimate indicators that are responsible in these contexts are first fall frost (FFF), last spring frost (LSF), climatological growing season (CGS) length, and heat accumulation (growing degree days, GDD). We explore spatial and temporal trends associated with these indices across the continental U.S. (CONUS) during 1900–2014 using datasets collected at 1218 sites. On average, FFF has been occurring later (by 5.4 days century⁻¹), and LSF has been occurring earlier (by 6.9 days century⁻¹), resulting in the average lengthening of the CGS (by 12.7 days century⁻¹). Annual GDD has been increasing by 50 °C century⁻¹. We also report trends for agricultural belts and climate regions. We developed relationships between county-level crop yields vs. agroclimate changes and found that all crops (maize, soybean, sorghum, spring wheat, winter wheat, and cotton) responded positively to a lengthened CGS, while responding negatively to increase in GDD, except cotton. Overall, we find that the observed changes in agroclimate, were beneficial for crop yields in the CONUS, albeit some crop and region specific exceptions.

Soil moisture sensors can be effective and promising decision-making tools for diverse applications and audiences, including agricultural managers, irrigation practitioners, and researchers. Nevertheless, there exists immense adoption potential in the United States, with only 1.2 in 10 farms nationally using soil moisture sensors to decide when to irrigate. This number is much lower in the global scale. Increased adoption is likely hindered by lack of scientific support in need assessment, selection, suitability and use of these sensors. Here, through extensive field research, we address the operational feasibility of soil moisture sensors, an aspect which has been overlooked in the past, and integrate it with their performance accuracy, in order to develop a quantitative framework to guide users in the selection of best-suited sensors for varying applications. These evaluations were conducted for nine commercially available sensors under silt loam and loamy sand soils in irrigated cropland and rainfed grassland for two different installation orientations [sensing component parallel (horizontal) and perpendicular (vertical) to the ground surface] typically used. All the sensors were assessed for their aptness in terms of cost, ease of operation, convenience of telemetry, and performance accuracy. Best sensors under each soil condition, sensor orientation, and user applications (research versus agricultural production) were identified. The step-by-step guide presented here will serve as an unprecedented and holistic adoption-assisting resource and can be extended to other sensors as well.