Recipient Organization
TEXAS A&M UNIVERSITY
750 AGRONOMY RD STE 2701
COLLEGE STATION,TX 77843-0001
Performing Department
(N/A)
Non Technical Summary
In the United States,agriculture is a major consumer of water resources for irrigation, especially during droughts, as it often relies on inefficient irrigation techniques. Some of these irrigation methods can also significantly increase greenhouse gas (GHG) emissions, by excessively stimulating the soil microbiota. Adoption of more efficient methods holds the promise of simultaneously increasing water use efficiency and reducing soil GHG emissions, hence contributing to a "climate-smart agriculture". However, high installation costs of efficient irrigation methods often create financial barriers for producers. The overarching goal of this project is to quantify the reduction in GHG emissions with efficientirrigation techniques, toprovide more informed climate-smart irrigation solutions andencourage their adoption by boosting profits through carbon credits. Inparticular, theproject willexperimentally assess the impact of various irrigation methods on GHG emissions in corn and cotton production systems and develop mathematical models able to predict the emissions reduction for different climate, soil, crop and irrigation systems.The project will estimate emission factors for common agricultural scenarios?in Texas, thus providing important insights intotheclimate-smart potential of irrigated crop production systems. This project is expected to increase sustainability of U.S. agriculture by promoting adoption of irrigation techniques that reduce water use and GHG emissions.
Animal Health Component
20%
Research Effort Categories
Basic
80%
Applied
20%
Developmental
(N/A)
Goals / Objectives
The overarching goal of this project is to develop a predictive understanding of the holistic impact of irrigation strategies on water use, soil carbon, and GHG emissions.Specifically, we will pursuefourresearch objectives. In the first objective, we will assess the impact of various irrigation systems and frequency of irrigation on GHG emissions in corn and cotton productionsystems.In the second objective, we will modelthe interaction between soil moisture regime and GHG emissionsto improve the soil module of the Environmental Policy Integrated Climate (EPIC) model. In the third objective, we will use the modified modelto predict GHG emissions under different climate, crop, and irrigation scenarios and develop specific emissions factors.In the fourth objective, we will develop aCrop Climate Impact Index to estimate the climate-smart potential ofirrigation methods.In addition, we will leverage our existing collaborations with the Texas Water Resources Institute to connect with stakeholders and ensure the effective dissemination of the project's findings.
Project Methods
Our methodology aims to assess the climate-smart potential of irrigation strategies to reducetheenvironmental footprint of both water use and GHG emissions, paving the way for additional compensation through emerging carbon markets. We propose to tackle this through a hybrid experimental-modeling approach.We propose establishing field experiments at the Texas A&M Research Farm near College Station to investigateGHG emissions from various irrigation practicesin corn and cotton production systems. We will collect high temporal resolution GHG emissions data, along with soil moisture, temperature,and soil and plant data, to assess the cropping system's performance.To analyze our experimental data, we will employ a range of statistical methods, including ANOVA, t-tests, and regression analysis,for interpreting the climate-smart potential of irrigation systems, yield performance of crops, and soil properties.We will extend the soil module of Environmental Policy Integrated Climate (EPIC) modelbased on a recently developed integrated soil model by PI Calabrese. Data collected from the experiments will be instrumental in developing the new module and testing the extended EPIC model.The extended EPIC model will be used to investigate what-if scenarios across management (M) and environmental (E) conditions and project the impact on greenhouse gas emissions and soil carbon sequestration. In particular, by management we refer to a combination of climate-smart practices (no till, cover crops) and irrigation techniques, so as to quantify how their combination affects GHG emissions and soil carbon sequestration.The results of this numerical experiment will be summarized into a set of emission factors for the combination of climate-smart practices, irrigation schemes/strategies, and climate and soil types.We will then develop appropriatequantitative measures or indexes to summarize the impact of management choices on crop productivity, water use, and carbon budget/intensity and choose strategies that "optimize" irrigation to reduce GHG emissions and increase soil carbon storage while guaranteeing desired crop/plant productivity levels or combine conservation/regeneration practices and optimal irrigation to increase resilience to climate variability.Lastly, we will collaborate with the Texas Water Resources Institute (collaboratorDr. Allen Berthold) to engage with relevant stakeholders, e.g., through focus group discussions, meetings, and consultations. To broaden our reach, we will also develop outreach material, including fact sheets and presentations, to summarize our key findings.