Evaluation of Biochar Applications and Irrigation as Climate Change Adaptation Options for Agricultural Systems

The Environmental Policy Integrated Climate (EPIC) model was updated with algorithms to determine the effects of biochar applications on crop yields and selected soil properties. EPIC was validated using the results of a 4-yr field experiment performed on an Amazonian Oxisol amended with biochar. Simulations were conducted for 20-yr into the future and predicted increased values of soil cation exchange capacity, pH, soil C content, and decreased soil bulk density values after biochar applications. EPIC was then used to evaluate climate change impacts and effectiveness of annual biochar applications and irrigation as adaptation options on yields of C3 and C4 crops from representative farms in 10 Southeastern US states. Simulations were conducted for 1979- 2009 historical baseline climate data and 2038-2068 time periods using four regional climate models (RCM). Future corn (Zea mays L.) yields initially increased, but corn and soybean (Glycine max L.) yields had decreased by 2068. Future C4 crops generally produced higher yields compared to the historical yields of C4 crops. Historical baseline yields of C3 crops and future C3 crop yields were not significantly different. Biochar amendments had no effects on yields and in some cases resulted in significant yield decreases. Irrigation caused increases in corn yields, but not for soybean yields. Irrigation did result in increased C3 and C4 crop yields for some farms that were typically in drier areas. Further EPIC simulations were conducted to estimate the effects of climate change impacts and adaptations on microbial respiration, soil C content, and nitrate losses in runoff and leachate. Microbial respiration was higher under C4 crops than under C3 crops. Biochar amendments increased microbial respiration, although the relative relationship of C4>C3 microbial respiration was maintained. Nitrate losses were significantly higher in the future and followed a C3>C4 pattern. The greatest nitrate losses were observed under C3 crops with even greater losses due to irrigation. Biochar amendments resulted in reduced losses for nitrate in leachate, but not in runoff. C sequestration increased under C4 crops and biochar applications. Under some RCM weather scenarios, biochar applications and irrigation are promising adaptation strategies for agriculture in the Southeastern US

Analysis of the Russian Market for Building Energy Efficiency

This report provides analysis of the Russian energy efficiency market for the building sector from the perspective of U.S. businesses interested in exporting relevant technologies, products and experience to Russia. We aim to help U.S. energy efficiency and environmental technologies businesses to better understand the Russian building market to plan their market strategy

Analysis of the Russian Market for Building Energy Efficiency

This report provides analysis of the Russian energy efficiency market for the building sector from the perspective of U.S. businesses interested in exporting relevant technologies, products and experience to Russia. We aim to help U.S. energy efficiency and environmental technologies businesses to better understand the Russian building market to plan their market strategy

Evaluation of the Environmental Policy Integrated Climate (EPIC) Model on Predicting Crop Yield in the Canadian Prairies, a Case Study

The Environmental Policy Integrated Climate (EPIC) model was updated with relevant weather, tillage, and crop management operations from the 1994-2013 Alternative Cropping Systems (ACS) study to assess simulations of annual and long-term yield of wheat, barley, and canola. Linear regression and coefficients of determination (R2), root mean square error of prediction (RMSE), the d index and paired sample t-test were used to assess the relationship between simulated and experimental values. Simulations indicated that the model captured long-term yield trends, but was less accurate at predicting annual variations. These variations were due to variability of soil properties at the research field, terrain attributes, extreme weather events, and the modelâ s overestimation of available nitrogen (N) under low-N input systems. The R2, RMSE, and the d index values on long-term yield were R2 = 0.74, RMSE = 205 kg ha-1, d = 0.75 for wheat; R2 = 0.90, RMSE = 226 kg ha-1, d = 0.73 for barley; R2 = 0.98, RMSE = 238 kg ha-1, d = 0.76 for canola, indicating good model performance. The EPIC model effectively simulated crop yields affected by agricultural inputs and cropping diversity, and may be used to assess future cropping decisions and agronomic management.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Climate Change, Agricultural Inputs, Cropping Diversity, and Environmental Covariates in Multivariate Analysis of Future Wheat, Barley, and Canola Yield in Canadian Prairies, a Case Study

Canadaâ s grain and oilseed production in the Canadian Prairies may be affected by climate change, but the impact of input and diversity has not been assessed relative to projected variability in precipitation and temperature. This study assessed wheat, canola, and barley yield simulated with the Environmental Policy Integrated Climate model for historical weather and future climate scenarios in the context of agricultural inputs and cropping diversity at Scott, Saskatchewan, Canada. Variation of future yield was explored with recursive partitioning in multivariate analyses of inputs, cropping diversity, future growing season precipitation (GSP) and growing degree days (GDD). Agricultural inputs significantly affected wheat yield, but not barley or canola. Wheat yield was highest under reduced and lowest under organic inputs. The combination of input and diversity accounted for about one third of variation in future wheat yield and about 10 % for barley. Most of the variability in yield was correlated with GSP in May-July and GDD in April-June and August-September. Future growing season maximum and minimum temperatures increased by 1.06 and 2.03°C, respectively, and 11% in future GSP. This study showed how input management and reduced tillage maintained or improved yield, in the context of increased temperature due to climate change.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author