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ARS Home » Plains Area » El Reno, Oklahoma » Grazinglands Research Laboratory » Agroclimate and Natural Resources Research » Research » Research Project #422669

Research Project: ADAPTING SOIL AND WATER CONSERVATION TO MEET THE CHALLENGES OF A CHANGING CLIMATE

Location: Agroclimate and Natural Resources Research

2017 Annual Report


Objectives
The long-term objective is to develop soil and water conservation decision support information for policy makers, land managers, and producers to identify conservation measures to mitigate the impacts of climate change. The Fort Cobb Reservoir(FCR)watershed, Oklahoma, was selected as the project watershed. Obj 1: Quantify the effects of past climate variations on runoff, soil erosion, sediment transport and nutrient movement for the FCR watershed, using available data records, reconstructed chronology of reservoir sedimentation, and computer modeling. 1A: Identify past climate variations and determine impacts on watershed runoff, sediment yield, and reservoir sedimentation. 1B: Reconstruct chronology of watershed sediment yield from reservoir sedimentation profiles; identify sediment sources; estimate sediment yield of major erosive storm-runoff events. 1C: Identify baseline land use, conservation, and climate conditions for impact assessment of climate change scenarios; calibrate/validate hydrologic and erosion models. Obj 2: Determine the potential impacts of 3 selected climate change scenarios on the hydrologic system and soil and water resources of the FCR watershed. 2A: Determine trends in annual precipitation and temperature for 3 greenhouse gas (GHG) emission scenarios; identify changes in seasonal precipitation and temperature distribution, estimate monthly precipitation and temperature statistics expected to prevail around the half century mark. 2B: Develop/evaluate spatio-temporal downscaling methods that integrate changed climate statistics into a synthetic weather generator; generate daily weather outcomes for each GHG emission scenario that reflect the statistical characteristics of projected climate change. Obj 3: Identify soil and water conservation strategies and options that are adapted to and mitigate the impacts of climate change, and test their effectiveness at enhancing the resilience of agricultural landscapes under climatic changes. 3A: Estimate extent of soil erosion/sedimentation under 3 GHG emission scenarios; identify soil conservation options/practices/coverage that mitigate soil erosion and sedimentation attributable to climate change; determine risk of exceeding current soil erosion and sedimentation rates. 3B: Develop communication tools that synthesize information across combinations of conservation practices, conservation coverage, climate change scenario, and conservation effectiveness. Obj 4: Develop science-based, region-specific information and technologies for agricultural and natural resource managers that enable climate-smart decision-making and where possible provide assistance to enable land managers to implement those decisions. The work will be conducted at the USDA Southern Plains Climate Change Hub and will be coordinated with NRCS, FS, and other USDA and non-USDA organizations in accordance with guidance found in the USDA Climate Change Hubs Charter and Terms of Reference.


Approach
The effects of past climate variations on runoff, soil erosion, sediment transport and fate, and nutrient movement for the Fort Cobb Reservoir (FCR) watershed are quantified based on available climate, hydrology, and environmental data records, reconstructed chronology of reservoir sedimentation, and computer modeling of watershed processes. Published climate data from Global Climate Models (GCM) are used to determine trends in annual precipitation and air temperature for three greenhouse gas (GHG) emission scenarios, identify changes in seasonal and monthly precipitation and temperature distribution within a year, and estimate monthly precipitation and temperature statistics that are expected to prevail around the half century mark. Synthetic weather generation models are used to generate daily weather outcomes that reflect the statistical characteristics of the projected climate change. Soil and water conservation strategies and options that are adapted to and mitigate the detrimental impacts of climate change are identified based on simulated soil erosion and sedimentation. Selected soil conservation options, practices, and coverage are tested with regard to their effectiveness at enhancing the resilience of agricultural landscapes under anticipated climatic changes. Risk of exceeding predefined soil erosion and sedimentation rates under climate change are determined. Information across combinations of conservation practices, conservation coverage, climate change scenario, and conservation effectiveness is synthesized and communicated in a format relevant to land managers, conservationists, and producers, as well as other practitioners. Climate smart agricultural management and decision making potential is determined based on the latest available climate information of long term historical climate records, the 5th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), and climate projections of Global Circulation Models (GCM). Based on the insight gained, a demonstration crop production application is developed to illustrate producer's benefits and risks of including climate variations and change as an agricultural management criterion. The effects and implications of GCM climate projection lead time and uncertainties on the climate-based decision making in agricultural production and natural resources conservation is made clear.


Progress Report
This research project had a term date of 10 Mar 2017. Progress reported here is a brief summary over the life of the project from 11 Mar 2012 through 10 Mar 2017. In the Southern Great Plains, anticipated changes in climate include an increase in drought frequency and a disproportionate increase in intensity of severe storm events. Special concerns arise that current conservation efforts, based largely on climate observations and agronomic practices of the last century, may not keep pace with these climatic changes. Intensified storm activity will lead to more runoff, increased soil erosion, enhanced nutrient movement, and higher risk of flooding, which in turn affect the agricultural productivity potential and downstream water quality. This interdisciplinary research project addressed key relationships needed to integrate climate, water, soil erosion, sedimentation, soil conservation, crop production, and sustainability of the agricultural production system into a climate change impact assessment tool. A statistical method to downscale climate change projections to daily weather outcomes at the field scale was developed and incorporated into a weather generator. This included an empirical procedure to mimic the anticipated increase in storm intensity. Soil erosion was simulated with an ARS soil erosion model. Land use was winter wheat and conservation practices were conventional tillage, conservation tillage and no-till. The integrated model was applied to assess the response of the climate-erosion-conservation-cropping system for two climate change scenarios, ten climate change projections, and two storm intensification alternatives. The interplay of climate change scenarios/projections and soil erosion and conservation for winter wheat fields were quantified. Conservation strategies and options were investigated, and the effectiveness and risk of various conservation options at reducing or offsetting climate change impacts on soil erosion on winter wheat fields were discussed. Knowledge of spatially distributed soil erosion and sediment source was expanded to rigorously calibrate erosion models and identify the most vulnerable erosion areas in the landscape that would benefit from additional conservation practices. Relations of reservoir sediment chronology, sedimentation rates, and sediment sources to land use, climate variations, and timing of major erosive storm-runoff events were also investigated and quantified using isotopes. This project demonstrated that effective soil conservation practices for winter wheat recommended by today’s conservation programs are more than adequate, in most cases to address anticipated increases in soil erosion due to climate change in spite of the large uncertainties of projected soil erosion. The findings inform a broader effort to support resilient agriculture in the Southern Great Plains, in the face of an increasingly varied and changing climate, through science translation and synthesis, technology transfer and tool development, and stakeholder outreach and education, an effort facilitated in large measure by the Southern Plains Climate Hub. In particular, this project’s results can be applied to planning for and implementation of additional conservation practices that can lead to a more stable and productive regional agricultural landscape. The progress for the period of 11 Mar 2017 through 31 Sep 2017 is reported under the new research project #3070-11130-006-00D “Uncertainty of Future Water Availability Due to Climate Change and Impacts on the Long Term Sustainability and Resilience of Agricultural Lands in the Southern Great Plains.”


Accomplishments
1. Southern Plains agricultural vulnerability to climate change. Agricultural activity in the Southern Plains contributes significantly to the Nation’s wheat and beef production. This region is subject to numerous climate-related hazards and vulnerabilities, including: longer, warmer growing seasons with increased vulnerability to late season frost; increased extreme weather events (e.g., downpours, droughts, heatwaves) and continued violent storm events (ice, hail, wind, tornadic activity); greater frequency, duration, and intensity of drought; increasing wildfire conditions; declining groundwater aquifer levels; increasing pest, disease, and weed pressure; increasing heat stress on plants and livestock; and vegetation shifts that may impact species of concern such as pollinators. ARS scientists in El Reno, Oklahoma worked with regional agricultural professionals and producers to identify key adaptation and mitigation strategies to these climate extremes, including: increasing soil health through conversion to no-till production; incorporation of cover crops and enhancement of soil and residue management; implementation of adaptive grazing management and improved health of pasture and grazing lands soils; development of heat, frost, and drought resistant cultivars and heat tolerant livestock; increased irrigation efficiency; and improved energy and water efficiency of agriculture systems and rural communities. The findings are captured in the 2015 vulnerability assessment and 2017 Climatic Change manuscript which are being used to shape strategic priorities for technology transfer and stakeholder outreach, including: engaging with partners on soil health demonstration plots and producer field days; facilitation of research on benefits of adaption and mitigation strategies and the methods to encourage the adoption of these strategies.

2. Real-time tactical agronomic management benefit little from climate change information. Opportunities for climate-smart real-time management of agricultural production systems and conservation of soil resources in the Southern Great Plains are somewhat limited by highly variable and unpredictable year-to-year climate swings. As a result, predictions of impacts of climate change on soil erosion are often shrouded in sizable uncertainties due to the unknown pathway along which green-house gases might evolve, and differences in predictions of global warming and climate change by different Global Circulation Models. Also, special concerns arise in that current soil and water conservation efforts, based largely on climate observations and agronomic practices of the past century, will not keep pace with climatic changes. Soil erosion is expected to increase under climate change primarily because of the anticipated increase in intensity of heavy storms. ARS researchers in El Reno, Oklahoma, evaluated the effectiveness of various tillage operations to control soil erosion from winter wheat crops in central Oklahoma. Researchers found that wide implementation of conservation tillage could offset a large portion of the anticipated increase in sediment yield. To overcome even the largest uncertainties in projected climate, more effective conservation measures such as terraces or no-till may be necessary. They also confirmed that the large uncertainties and the relative short lead-time of agronomic and conservation decisions limit the use of climate change projections for real-time tactical management of crops and soil and water resources. However, exploratory investigations, strategic positioning, and long range planning applications may benefit from climate projections as they approximate the trend, magnitude, and direction of anticipated change and provide valuable information on the sustainability of crop production systems.

3. Improved methods for soil redistribution, sediment provenance, and reservoir sedimentation. Radioactive tracers such as Cesium (137Cs) have been widely used to estimate point soil redistribution rates. ARS researchers at El Reno, Oklahoma, found that the conventional method rests on the assumption that initial Cesium tracer is spatially uniform. However, field measurements and a computer simulation showed that the tracer is spatially variable. A new concept was developed to use the mean Cesium values to remove the spatial variability, and the new method improves the accuracy of estimated soil loss rates. The new Cesium tracer approach will be useful to soil erosion scientists and agricultural engineers who are interested in spatial distribution of soil erosion and precision soil conservation in agricultural landscapes. The knowledge of sediment provenance (e.g., gully vs. overland) is critical for soil conservation planning and calibrating/validating spatially distributed erosion prediction models. ARS researchers in El Reno, Oklahoma, developed a new multiple composite fingerprint method for estimating sediment source contributions in watersheds. The new approach takes advantage of all tracers that have source discrimination power and pass the statistical significance test. The average source contributions from multiple composite fingerprints improved the sediment provenance estimation substantially. The new approach provides more reliable sediment provenance to erosion modelers and soil conservationists to validate erosion models and implement precision conservation practices. Knowledge of sediment chronology is essential for calculating sedimentation rates and characterizing the impacts of historical climate variations and land use changes on erosion and sedimentation. ARS researchers in El Reno, Oklahoma evaluated a number of sediment dating models, and found that a composite method that combines two radionuclides provides a better means for sediment age dating.

4. Downscaled General Circulation Model (GCM) climate projections. Climate change scenarios simulated by GCMs are at a spatial and temporal scale that is too large for direct application in soil, water and agricultural productivity investigations. Increases in daily extreme storm events that affect soil erosion and nutrient movement in a watershed are also not captured by the large scale of GCMs. This significantly limits capabilities of modeling impacts of climate change scenarios in agricultural and watersheds. ARS scientists at El Reno, Oklahoma, developed a statistical downscaling method based on a weather generator to explicitly simulate both spatial and temporal climate variations during downscaling. In addition, a model that accounts for the intensification of extreme storm events was developed. Climate change projections for diverse physiographic regions across the continental United States were determined and multi-decadal climate trends were identified. Results showed that the downscaling method and the storm intensification model were capable of generating daily precipitation that possess desirable characteristics of precipitation amounts, frequency, and duration of dry and wet spells. The methodologies are available to hydrologists, agronomists, and agricultural modelers to assess impacts of climate change on crop production and water resources.

5. Rainfall disaggregation enables high resolution hydrologic and agricultural simulations. Crop growth and soil moisture dynamics are generally simulated at daily or sub-daily time scales. While daily rainfall projections are increasingly available for climate change analyses, the projections sometimes display an unusually large number of rainy days with very low daily rainfall amounts and unrealistic sequences of rainy days. This leads to higher infiltration amounts and lower surface runoff volumes than expected. ARS scientist in El Reno, Oklahoma, examined the performance of two rainfall disaggregation models. Average hourly rainfall characteristics of the observed rainfall data were, in most cases, adequately replicated by the disaggregated rainfall. However, both models had difficulties reproducing hourly rainfall sequence characteristics for large storm events of short duration and high precipitation intensity. Alternatively, statistical downscaling methods that are based on stochastic rainfall generation are more likely to succeed at downscaling rainfall because rainfall generation parameters explicitly contain information on rainfall distribution and sequencing characteristics. Scientists and agricultural consultants who depend on downscaled climate data are the primary benefitters of disaggregation methods and capabilities.

6. Southern Plains Climate Hub: Partnerships, communication, and education. Activities associated with the Southern Plains Climate Hub in El Reno, Oklahoma have been organized within seven priority themes: facilitating research translation; delivering adaptation demonstrations; developing tools and products; conducting assessments; building regional partnerships; providing regional communications; and enhancing education and outreach. Key accomplishments include organizing soil health and cover crop field days; facilitating four state and regional workshops and developing an agroforestry component in support of the USDA Building Blocks for Climate-Smart Agriculture initiative; initiating a regional soil health management field study; publishing a Bundled Benefits report on water quality and climate change for soil health practices in targeted Oklahoma watersheds; and co-sponsoring the 2016 Great Plains Grazing Coordinated Agricultural Project (CAP) Research Symposium and the 2016 North American Drought, Wildfire, and Climate Services Forum, the latter of which led to a partnership with the National Drought Mitigation Center to provide drought early warning and impact assessment information. Key accomplishments related to partnership development, regional communications, and education and outreach include the establishment of four new cooperative agreements; training of USDA, Extension, and stakeholder audiences on climate change information; and development of K-12 and Extension agent climate curricula.


Review Publications
Steiner, J.L., Brown, D.P., Briske, D.D., Rottler, C.M. 2017. Vulnerability of southern plains agriculture to climate change. Climatic Change. 146(1):201-218. https://doi.org/10.1007/s10584-017-1965-5.
Garbrecht, J.D., Nearing, M.A., Shields, D., Tomer, M.D., Sadler, E.J., Bonta, J.V., Baffaut, C. 2014. Impact of weather and climate scenarios on conservation assessment outcomes. Journal of Soil and Water Conservation. 69(5):374.
Garbrecht, J.D., Zhang, X.J. 2015. Soil erosion from winter wheat cropland under climate change in central Oklahoma. Applied Engineering in Agriculture. 31(3):439-454.
Garbrecht, J.D., Starks, P.J. 2009. Watershed sediment yield reduction through soil conservation in a west-central Oklahoma watershed. Journal of Ecohydrology. 2(3):313-320.
Zhang, X.J. 2013. Verifying a temporal disaggregation method for generating daily precipitation of potentially non-stationary climate change for site-specific impact assessment. International Journal of Climatology. 33(2):326-342.