Predicting soil moisture conditions for arable free draining soils in Ireland under spring cereal crop production

peer-reviewedTemporal prediction of soil moisture and evapotranspiration has a crucial role in agricultural and environmental management. A lack of Irish models for predicting evapotranspiration and soil moisture conditions for arable soils still represents a knowledge gap in this particular area of Irish agro-climatic modelling. The soil moisture deficit (SMD) crop model presented in this paper is based on the SMD hybrid model for Irish grassland (Schulte et al., 2005). Crop and site specific components (free-draining soil) have been integrated in the new model, which was calibrated and tested using soil tension measurements from two experimental sites located on a well-drained soil under spring barley cultivation in south-eastern Ireland. Calibration of the model gave an R2 of 0.71 for the relationship between predicted SMD and measured soil tension, while model testing yielded R2 values of 0.67 and 0.65 (two sites). The crop model presented here is designed to predict soil moisture conditions and effective drainage (i.e., leaching events). The model provided reasonable predictions of soil moisture conditions and effective drainage within its boundaries, i.e., free-draining land used for spring cereal production under Irish conditions. In general, the model is simple and practical due to the small number of required input parameters, and due to model outputs that have good practical applicability, such as for computing the cumulative amount of watersoluble nutrients leached from arable land under spring cereals in free-draining soils

Mustard catch crop enhances denitrification in shallow groundwater beneath a spring barley field

The study was funded by Department of Agriculture and Food through the Research Stimulus Fund Programme (Grant RSF 06383) in collaboration with the Department of Civil, Structural & Environmental Engineering, Trinity College Dublin, Ireland.peer-reviewedOver-winter green cover crops have been reported to increase dissolved organic carbon (DOC) concentrations in groundwater, which can be used as an energy source for denitrifiers. This study investigates the impact of a mustard catch crop on in situ denitrification and nitrous oxide (N2O) emissions from an aquifer overlain by arable land. Denitrification rates and N2O-N/(N2O-N + N2-N) mole fractions were measured in situ with a push–pull method in shallow groundwater under a spring barley system in experimental plots with and without a mustard cover crop. The results suggest that a mustard cover crop could substantially enhance reduction of groundwater nitrate NO3--N via denitrification without significantly increasing N2O emissions. Mean total denitrification (TDN) rates below mustard cover crop and no cover crop were 7.61 and 0.002 μg kg−1 d−1, respectively. Estimated N2O-N/(N2O-N + N2-N) ratios, being 0.001 and 1.0 below mustard cover crop and no cover crop respectively, indicate that denitrification below mustard cover crop reduces N2O to N2, unlike the plot with no cover crop. The observed enhanced denitrification under the mustard cover crop may result from the higher groundwater DOC under mustard cover crop (1.53 mg L−1) than no cover crop (0.90 mg L−1) being added by the root exudates and root masses of mustard. This study gives insights into the missing piece in agricultural nitrogen (N) balance and groundwater derived N2O emissions under arable land and thus helps minimise the uncertainty in agricultural N and N2O-N balances

Soil organic carbon stocks by soil group for afforested soils in Ireland

Forest ecosystems are recognised as Natural Climate Solutions because forest soils are such important carbon stores, containing almost half of the total soil organic carbon of terrestrial ecosystems. Here we present the results of a synthesis of soil carbon stocks by World Reference Base soil group, and forest litter carbon stocks for afforested soils in the Republic of Ireland. We report soil carbon stocks of mineral soils separately from organo-mineral soils. We estimated mean soil carbon stocks in a 100 cm deep mineral soil to be between 162 ± 87 t C/ha (Gleysols) and 416 ± 0 t C/ha (Umbrisols, n = 1), and between 173 ± 65 t C/ha (Phaeozems) and 602 ± 226 t C/ha (Regosols) in a 100 cm deep organo-mineral soil; both less than the estimated soil carbon stocks in organic soils (Histosols): 645 ± 222 t C/ha. The entire soil carbon stocks in mineral Leptosols (100 ± 0 t C/ha, n = 1), Stagnosols (144 ± 39 t C/ha), Luvisols (159 ± 52 t C/ha) and Fluvisols (231 ± 0 t C/ha, n = 1) was contained in the upper 50 cm of soil. Based on a 100 cm deep soil, Histosols hold 1.6–4 times the amount of soil C than mineral soils and 1.1–3.7 times the amount in organo-mineral soils for the same profile depth. Certain mineral (e.g. Umbrisols) and organo-mineral soils (e.g Gleysols, Regosols) contain substantial soil carbon stocks relative to Histosols. We found considerable soil carbon stocks below 30 cm depth, which highlights the importance of depth extent for cumulative soil carbon stocks estimates. The upper third of the 100 cm profile contained 33% (Histosols) to 70% (Luvisols) of the soil carbon stocks and the upper half of a 100 cm profile contained the entire soil carbon stocks for Leptosols, Stagnosols, Luvisols and Fluvisols and organo-mineral Leptosols. Unfortunately, there were few samples available for mineral Leptosols, Umbrisols, Luvisols and Fluvisols, and the organo-mineral Stagnosols and Regosols, which precludes the drawing of conclusions for these groups. Relative to the soil carbon stocks, we found low mean forest litter stocks: 4.1 ± 5.5 t C/ha, 4.8 ± 3.3 t C/ha and 2.7 ± 2.9 t C/ha for broadleaf, coniferous and mixed forests respectively. Few exceptions existed for individual sites: 22.7 and 131.3 t C/ha for broadleaf forests. Our results are evidence that soil carbon stocks in mineral, organo-mineral and organic soils need to be protected, appropriately managed, and enhanced to be beneficial for greenhouse gas mitigation. Assessments are needed to identify which soil-site-management practice combinations risk soil carbon stock depletion. The large range observed in soil and litter carbon stocks stresses the importance of adequately accounting for soil group differences when GHG inventories are compiled. The synthesised dataset will contribute to improved SCS estimation for afforested lands in Ireland

Variations in travel time for N loading to groundwaters in four case studies in Ireland:Implications for policy makers and regulators

Peer-reviewedMitigation measures to protect waterbodies must be implemented by 2012 to meet the requirements of the EU Water Framework Directive. The efficacy of these measures will be assessed in 2015. Whilst diffuse N pathways between source and receptor are generally long and complex, EU legislation does not account for differences in hydrological travel time distributions that may result in different water quality response times. The “lag time” between introducing mitigation measures and first improvements in water quality is likely to be different in different catchments; a process that should be considered by policy makers and catchment managers. Many examples of travel time variations have been quoted in the literature but no Irish specific examples are available. Lag times based on initial nutrient breakthrough at four contrasting sites were estimated to a receptor 500 m away from a source. Vertical travel times were estimated using a combination of depth of infiltration calculations based on effective rainfall and subsoil physical parameters and existing hydrological tracer data. Horizontal travel times were estimated using a combination of Darcian linear velocity calculations and existing tracer migration data. Total travel times, assuming no biogeochemical processes, ranged from months to decades between the contrasting sites; the shortest times occurred under thin soil/subsoil on karst limestone and the longest times through thick low permeability soils/subsoils over poorly productive aquifers. Policy makers should consider hydrological lag times when assessing the efficacy of mitigation measures introduced under the Water Framework Directive. This lag time reflects complete flushing of a particular nutrient from source to receptor. Further research is required to assess the potential mitigation of nitrate through denitrification along the pathway from source to receptor

Insights into CO2 simulations from the Irish Blackwater peatland using ECOSSE model

The EGU General Assembly 2020, Vienna, Austria (events to be held online due to coronavirus outbreak), 4-8 May 2020Non-degraded peatlands are known to be important carbon sink; however, if they are exposed to anthropogenic changes they can act as carbon source. This study forms a part of the larger AUGER project (http://www.ucd.ie/auger). It uses the ECOSSE process-based model to predict CO2 emissions [heterotrophic respiration (Rh)] associated with different peatland management (Smith et al., 2010). The work aims to provide preliminary insights into CO2 modelling procedures for drained and rewetted sites from Blackwater, the former Irish raised bog. After drainage in 1950’s (due to peat-extraction) and cessation of draining in 1999, the landscape developed drained ‘Bare Peat’ (BP), and rewetted ‘Reeds’ (R) and ‘Sedges’ (S) sites (Renou-Wilson et al., 2019). Modelling of CO2 from these sites was done using ECOSSE-v.6.2b model (‘site-specific’ mode) with water-table (WT) module (Smith et al., 2010), and default peatland vegetation parameters. The other model-input parameters (including soil respiration, WT and other soil parameters) were obtained from measurements reported in Renou-Wilson et al. (2019). Simulations on drained BP site were run starting from 1950 and on rewetted R and S sites starting from 1999 (which is the year of cessation of drainage). The climate data inputs (2010-2017) were obtained from ICHEC (EPA_Climate-WRF, 2019). The long-term average climate data for model spin-up were obtained from Met Éireann (2012) with potential evapotranspiration estimated by Thornthwaite (1948) method. Daily ecosystem respiration (Reco) data for May/June 2011 to Aug 2011 obtained from raw CO2 flux measurements (Renou-Wilson et al., 2019) were used. For vegetated sites Rh was estimated from Reco using method explained in Abdalla et al. (2014). Daily CO2 simulations were compared to Reco for BP site (r2 =0.20) and to Rh for R site (r2 = 0.35) and S site (r2 = 0.55). The preliminary results showed some underestimation of simulated CO2 indicating the need for further modelling refinements for satisfactory results. The results from BP site further indicated on the importance of including long-term drainage period (i.e. from 1950 on) because avoiding this step resulted in a large overestimation of predicted CO2.Environmental Protection Agenc

Peatland Properties Influencing Greenhouse Gas Emissions and Removal

A nationwide peatland survey was conducted across 50 ombrotrophic peatlands (bogs) in Ireland to ascertain a wide range of peat properties. In addition to natural (relatively intact) sites, we surveyed the most prevalent peatland land use categories (LUCs): grassland, forestry and peat extraction (both industrial and domestic), as well as management options (deep drained; shallow drained; rewetting). Furthermore, the entirety of the peat profile (down to the sub-peat mineral soil/bedrock) was sampled. Our results demonstrate that Irish bogs have been drastically altered by human activities and that the sampled peat properties reflect the nature and magnitude of the impact of the land use and management.Environmental Protection Agency2022-07-25 JG: full report added at author's reques

Soil organic carbon stocks by soil group for afforested soils in Ireland

Forest ecosystems are recognised as Natural Climate Solutions because forest soils are such important carbon stores, containing almost half of the total soil organic carbon of terrestrial ecosystems. Here we present the results of a synthesis of soil carbon stocks by World Reference Base soil group, and forest litter carbon stocks for afforested soils in the Republic of Ireland. We report soil carbon stocks of mineral soils separately from organomineral soils. We estimated mean soil carbon stocks in a 100 cm deep mineral soil to be between 162 ± 87 t C/ha (Gleysols) and 416 ± 0 t C/ha (Umbrisols, n = 1), and between 173 ± 65 t C/ha (Phaeozems) and 602 ± 226 t C/ ha (Regosols) in a 100 cm deep organo-mineral soil; both less than the estimated soil carbon stocks in organic soils (Histosols): 645 ± 222 t C/ha. The entire soil carbon stocks in mineral Leptosols (100 ± 0 t C/ha, n = 1), Stagnosols (144 ± 39 t C/ha), Luvisols (159 ± 52 t C/ha) and Fluvisols (231 ± 0 t C/ha, n = 1) was contained in the upper 50 cm of soil. Based on a 100 cm deep soil, Histosols hold 1.6–4 times the amount of soil C than mineral soils and 1.1–3.7 times the amount in organo-mineral soils for the same profile depth. Certain mineral (e. g. Umbrisols) and organo-mineral soils (e.g Gleysols, Regosols) contain substantial soil carbon stocks relative to Histosols. We found considerable soil carbon stocks below 30 cm depth, which highlights the importance of depth extent for cumulative soil carbon stocks estimates. The upper third of the 100 cm profile contained 33% (Histosols) to 70% (Luvisols) of the soil carbon stocks and the upper half of a 100 cm profile contained the entire soil carbon stocks for Leptosols, Stagnosols, Luvisols and Fluvisols and organo-mineral Leptosols. Unfortunately, there were few samples available for mineral Leptosols, Umbrisols, Luvisols and Fluvisols, and the organomineral Stagnosols and Regosols, which precludes the drawing of conclusions for these groups. Relative to the soil carbon stocks, we found low mean forest litter stocks: 4.1 ± 5.5 t C/ha, 4.8 ± 3.3 t C/ha and 2.7 ± 2.9 t C/ha for broadleaf, coniferous and mixed forests respectively. Few exceptions existed for individual sites: 22.7 and 131.3 t C/ha for broadleaf forests. Our results are evidence that soil carbon stocks in mineral, organo-mineral and organic soils need to be protected, appropriately managed, and enhanced to be beneficial for greenhouse gas mitigation. Assessments are needed to identify which soil-site-management practice combinations risk soil carbon stock depletion. The large range observed in soil and litter carbon stocks stresses the importance of adequately accounting for soil group differences when GHG inventories are compiled. The synthesised dataset will contribute to improved SCS estimation for afforested lands in Ireland.</p