CO2 soil flux baseline at the technological development plant for CO2 injection at Hontomin (Burgos, Spain)

From the end of 2013 and during the following two years, 20 kt of CO2sc are planned to be injected in a saline reservoir (1500 m depth) at the Hontomín site (NE Spain). The target aquifers are Lower Jurassic limestone formations which are sealed by Lower Cretaceous clay units at the Hontomín site (NE Spain). The injection of CO2 is part of the activities committed in the Technology Development phase of the EC-funded OXYCFB300 project (European Energy Program for Recovery – EEPR, http://www.compostillaproject.eu), which include CO2 injection strategies, risk assessment, and testing and validating monitoring methodologies and techniques. Among the monitoring works, the project is intended to prove that present-day technology is able to monitor the evolution of injected CO2 in the reservoir and to detect potential leakage. One of the techniques is the measurement of CO2 flux at the soil–atmosphere interface, which includes campaigns before, during and after the injection operations. In this work soil CO2 flux measurements in the vicinity of oil borehole, drilled in the eighties and named H-1 to H-4, and injection and monitoring wells were performed using an accumulation chamber equipped with an IR sensor. Seven surveys were carried out from November 2009 to summer 2011. More than 4000 measurements were used to determine the baseline flux of CO2 and its seasonal variations. The measured values were low (from 5 to 13 g m−2 day−1) and few outliers were identified, mainly located close to the H-2 oil well. Nevertheless, these values cannot be associated to a deep source of CO2, being more likely related to biological processes, i.e. soil respiration. No anomalies were recognized close to the deep fault system (Ubierna Fault) detected by geophysical investigations. There, the CO2 flux is indeed as low as other measurement stations. CO2 fluxes appear to be controlled by the biological activity since the lowest values were recorded during autumn-winter seasons and they tend to increase in warm periods. Two reference CO2 flux values (UCL50 of 5 g m−2 d−1 for non-ploughed areas in autumn–winter seasons and 3.5 and 12 g m−2 d−1 for in ploughed and non-ploughed areas, respectively, in spring–summer time, and UCL99 of 26 g m−2 d−1 for autumn–winter in not-ploughed areas and 34 and 42 g m−2 d−1 for spring–summer in ploughed and not-ploughed areas, respectively) were calculated. Fluxes higher than these reference values could be indicative of possible leakage during the operational and post-closure stages of the storage project.

Managing Soil Organic Carbon: A Farm Perspective

Farming practices that lead to declining returns and inputs of carbon to soils pose a threat to key soil functions. The EU FP 7 interdisciplinary project Smart SOIL is using scientific testing and modeling to identify management practices that can optimize soil carbon storage and crop productivity. A consultation with advisors and policymakers in six European case study regions seeks to identify barriers to, and incentives for, uptake of such practices. Results from preliminary interviews are reported. Overall advisor and farmer awareness of management practices specifically directed towards soil carbon. is low. Most production- related decisions are taken in the short term, but managing soil carbon needs a long- term approach. Key barriers to uptake of practices include: perceived scientifi c uncertainty about the effi cacy of practices; lack of real life ?best practice? examples to show farmers; diffi culty in demonstrating the positive effects of soil carbon management practices and economic benefi ts over a long time scale; and advisors being unable to provide suitable advice due to inadequate information or training. Most farmers are unconvinced of the economic benefi ts of practices for managing soil carbon. Incentives are therefore needed, either as subsidies or as evidence of the cost effectiveness of practices. All new measures and advice should be integrated into existing programmes to avoid a fragmented policy approach.

Testing of crop Models for Accurate Predictions of Evapotranspiration and crop Water Use

All crop models, whether site-specific or global-gridded and regardless of crop, simulate daily crop transpiration and soil evaporation during the crop life cycle, resulting in seasonal crop water use. Modelers use several methods for predicting daily potential evapotranspiration (ET), including FAO-56, Penman-Monteith, Priestley-Taylor, Hargreaves, full energy balance, and transpiration water efficiency. They use extinction equations to partition energy to soil evaporation or transpiration, depending on leaf area index. Most models simulate soil water balance and soil-root water supply for transpiration, and limit transpiration if water uptake is insufficient, and thereafter reduce dry matter production. Comparisons among multiple crop and global gridded models in the Agricultural Model Intercomparison and Improvement Project (AgMIP) show surprisingly large differences in simulated ET and crop water use for the same climatic conditions. Model intercomparisons alone are not enough to know which approaches are correct. There is an urgent need to test these models against field-observed data on ET and crop water use. It is important to test various ET modules/equations in a model platform where other aspects such as soil water balance and rooting are held constant, to avoid compensation caused by other parts of models. The CSM-CROPGRO model in DSSAT already has ET equations for Priestley-Taylor, Penman-FAO-24, Penman-Monteith-FAO-56, and an hourly energy balance approach. In this work, we added transpiration-efficiency modules to DSSAT and AgMaize models and tested the various ET equations against available data on ET, soil water balance, and season-long crop water use of soybean, fababean, maize, and other crops where runoff and deep percolation were known or zero. The different ET modules created considerable differences in predicted ET, growth, and yield.