Location: Great Plains Agroclimate and Natural Resources Research
2022 Annual Report
Objectives
Objective 1: Develop new and enhance existing model components and methodologies to better estimate long term trends, variations, and uncertainty in future water availability due to climate change.
Objective 2: Determine the impacts of future variation or change in water availability on soil erosion, crop productivity, and resilience and sustainability of managed agricultural lands.
Objective 3: Develop long-range planning information for policy makers, environmental organizations, and conservation planners on potential future water availability, cropland productivity, and water and soil conservation options that would maintain or increase the resilience and sustainability of agricultural lands.
Objective 4: Develop science-based, region-specific information and technologies for agricultural and natural resource managers that enable climate-smart decision-making and transfer the information and technologies to users.
Approach
The Earth’s climate is warming and will likely continue to warm for the rest of this century. In the Southern Great Plains of the U.S., droughts are expected to increase in frequency, duration, and severity, and storm events to become more intense. Climate change poses a new set of challenges affecting future water availability, agricultural soil resources, and long term sustainability of rainfed crop production systems in the Southern Great Plains. The extent of climate change impacts on agriculture at the end of the century is unclear, and information on management strategies and conservation options to effectively adapt to and mitigate the detrimental effects of climate change is limited. This applied, goal-driven investigation uses available projections of precipitation, air temperature, and carbon dioxide levels through year 2100, and relies on agricultural system models to simulate impacts of climate change scenarios on rainfall-runoff, soil erosion, and sustainability of crop production systems. Long term land management strategies, agronomic options, and conservation measures that enhance future water availability, reduce soil erosion, and improve the sustainability of cropping systems are explored, and uncertainties in projected impacts are estimated. Effectiveness and risk of various strategies and options to reduce or offset climate change impacts are determined by evaluation of probability distributions of climate change impacts. Findings are expected to support national and regional strategic planning of alternative long term adaptive conservation measures that maintain effective, competitive, sustainable, and environmentally responsible agricultural cropping systems under changing and uncertain future climatic conditions.
Progress Report
Researchers at El Reno, Oklahoma, substantially completed all the objectives set forth in the research project. Specifically, scientists developed two software programs (or computer tools), which explicitly take into consideration the storm intensification under climate change during climate downscaling. One program is called SYNthetic weather generaTOR (SYNTOR in short), and another is referred as a Generator for Point Climate Change (GPCC). Both programs were compared and evaluated against the other seven existing climate downscaling methods at four Oklahoma weather recording stations (Weatherford, Idabel, Hooker, Kingfisher) using daily precipitation data from 1949 to 2016 and were found to have slight advantages over the other methods for simulating precipitation frequency, sequency, and extremes. Both programs were used to downscale climate projections of 25 Global Climate Models (GCM)/ Regional Climate Models (RCM) for the two Green House Gases emission scenarios (RCP 8.5 and 2.6) for the period of 2021-2080 for the Weatherford site. The downscaled climate change scenarios were used to drive the Water Erosion Prediction Project (WEPP) model for simulating the impacts of climate change on soil loss, surface runoff, grain yield, available soil moisture, and above-ground biomass in four common tillage systems and 11 cropping systems. Tillage systems included conventional till, conservation till, no-till, and delayed till. Crops included winter wheat, soybean, sorghum, canola, and cotton, which were planted in continuous monoculture or in rotation with alfalfa. Before using the WEPP model, the model was calibrated using average grain yields measured in Oklahoma as well as the soil loss rates measured with H-flumes and Cs-137 tracer in several small research watersheds. The simulated model outputs were presented in the forms of tables and graphs and analyzed statistically for the ranges of variations and the 95% confidence intervals. Compared with the present climate, future precipitation at the study region would decrease by about 3%, and crop yields decline by 10 to 20% except cotton due to decreased precipitation and rising temperature. Despite a decrease in precipitation, surface runoff and soil loss would increase slightly by <7% and <30%, respectively, due to increased occurrence of extreme rainfall events. Results showed that no-till systems are most effective in reducing soil erosion, followed by crop rotations with alfalfa.
Accomplishments
1. Effects of climate change and crop management systems on soil erosion and crop production analyzed. Proper simulation of storm intensification under climate change is critical in projecting crop yield, surface runoff, and soil loss. Such impact assessments are imperative for developing strategic plans for food security and resources conservation. ARS researchers at El Reno, Oklahoma, developed 100 climate scenarios coupled with storm intensification, which were based on 25 downscaled General Circulation Model (GCM) projections under the Representative Concentration Pathways (RCP) 4.5 and 8.5 for the 2021–2080 period. The climate files were used to drive the Water Erosion Prediction Project (WEPP) model to simulate crop yield, runoff, and soil loss under 29 combinations of 11 cropping systems and 4 tillage systems. Results showed that annual precipitation would decline by ~3% in the study region during 2021–2080; but the future extreme storm events would increase, leading to an increase in soil loss. The amounts of surface runoff and soil loss from extreme storms would account for 46% and 64% of the annual totals, respectively. Average runoff and soil losses in crop-alfalfa rotation or double cropping systems would be much less than those in continuous monoculture cropping systems. No-till and crop-alfalfa rotations are the best agricultural management alternatives to mitigate soil erosion. The analysis of variance indicated that the GCM projections and cropping and tillage systems were the major contributors of uncertainty for projecting surface runoff and soil loss. Results also showed that crop yields would generally decrease in the region, simply due to the decline in annual precipitation. This work improved the simulation of surface runoff and soil loss under climate change by integrating storm intensification from multiple GCM ensembles. The results would be useful to NRCS engineers and producers in Oklahoma to develop soil and water conservation plans that mitigate soil loss and surface runoff while enhancing crop productivity under future climate change.
