Consequences of varied soil hydraulic and meteorological complexity on unsaturated zone time lag estimates

During laboratory assessment of the soil water characteristic curve (SWCC), determining equilibrium at various pressures is challenging. This study establishes a methodological framework to identify appropriate experimental duration at each pressure step for the construction of SWCCs via centrifugation. Three common temporal approaches to equilibrium – 24-, 48- and 72-h – are examined, for a grassland and arable soil. The framework highlights the differences in equilibrium duration between the two soils. For both soils, the 24-h treatment significantly overestimated saturation. For the arable site, no significant difference was observed between the 48- and 72-h treatments. Hence, a 48-h treatment was sufficient to determine ‘effective equilibrium’. For the grassland site, the 48- and 72-h treatments differed significantly. This highlights that a more prolonged duration is necessary for some soils to conclusively determine that effective equilibrium has been reached. This framework can be applied to other soils to determine the optimum centrifuge durations for SWCC construction.

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A methodological framework to determine optimum durations for the construction of soil water characteristic curves using centrifugation

Vero¹,

Healy²,

Henry³

et al. 2016

“…The reliability of PTFs to accurately characterise the properties of field soils has been questioned (Schaap and Leij, 1998;Khodaverdiloo et al, 2011), and increasing the data inputs has been shown to increase their reliability. A demonstration of simple versus complex physical data sources was provided by Vero et al (2014), who found that although higher-quality soil physical data (direct approach) allow better estimation of soil hydraulic parameters, reduced resolution (indirect approach) may be sufficient for some applications, e.g. estimation of unsaturated zone solute travel time (Vero et al, 2014;Fenton et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Application of Dexter’s soil physical quality index: an Irish case study

Fenton

Vero

Schulte

et al. 2017

Self Cite

Historically, due to a lack of measured soil physical data, the quality of Irish soils was relatively unknown. Herein, we investigate the physical quality of the national representative profiles of Co. Waterford. To do this, the soil physical quality (SPQ) S-Index, as described by Dexter (2004a,b,c) using the S-theory (which seeks the inflection point of a soil water retention curve [SWRC]), is used. This can be determined using simple (S-Indirect) or complex (S-Direct) soil physical data streams. Both are achievable using existing data for the County Waterford profiles, but until now, the suitability of this S-Index for Irish soils has never been tested. Indirect-S provides a generic characterisation of SPQ for a particular soil horizon, using simplified and modelled information (e.g. texture and SWRC derived from pedo-transfer functions), whereas Direct-S provides more complex site-specific information (e.g. texture and SWRC measured in the laboratory), which relates to properties measured for that exact soil horizon. Results showed a significant correlation between S-Indirect (S i ) and S-Direct (S d ). Therefore, the S-Index can be used in Irish soils and presents opportunities for the use of S i at the national scale. Outlier horizons contained >6% organic carbon (OC) and bulk density (B d ) values <1 g/cm 3 and were not suitable for S i estimation. In addition, the S-Index did not perform well on excessively drained soils. Overall correlations of S i with B d and of S i with OC% for the dataset were detected. Future work should extend this approach to the national scale dataset in the Irish Soil Information System.

“…It has also been cited in more than 50 scientific publications, for a variety of applications, including farm-scale modelling of grassland productivity and utilisation (Fitzgerald et al, 2008), assessment of agricultural management opportunities such as slurry spreading (Lalor & Schulte, 2008;, understanding spatio-temporal dynamics of water movement through the unsaturated travel zone (e.g. Vero et al, 2014) as well as predicting nutrient emissions to the environment (e.g. Doody et al, 2010;Fenton et al, 2011) and risks of pathogen transfer to water (Samadder et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

A note on the Hybrid Soil Moisture Deficit Model v2.0

Schulte¹,

Simo²,

Creamer³

et al. 2015

The Hybrid Soil Moisture Deficit (HSMD) model has been used for a wide range of applications, including modelling of grassland productivity and utilisation, assessment of agricultural management opportunities such as slurry spreading, predicting nutrient emissions to the environment and risks of pathogen transfer to water. In the decade since its publication, various ad hoc modifications have been developed and the recent publication of the Irish Soil Information System has facilitated improved assessment of the spatial soil moisture dynamics. In this short note, we formally present a new version of the model (HSMD2.0), which includes two new soil drainage classes, as well as an optional module to account for the topographic wetness index at any location. In addition, we present a new Indicative Soil Drainage Map for Ireland, based on the Irish Soil Classification system, developed as part of the Irish Soil Information System. Keywords Areas of natural constraint • drainage • model • soil moisture • trafficability IntroductionIn temperate maritime climates, soil moisture dynamics are drivers of the evolution of agricultural systems. The number of days when soil has excess moisture, known as field capacity (FC) days, determines the type of agricultural system used, with specific influence on herbage growth, herbage utilisation, farm operations and environmental sustainability (Schulte et al., 2012). The European Commission now recognises FC days as a bio-physical criterion that defines a natural constraint for agriculture in Europe (Jones et al., 2013). FC days can be either measured in situ at the field/soil profile scale or modelled as a function of the temporal pattern of soil moisture deficit (SMD), which in turn can be computed from meteorological variables and soil properties. Schulte et al. (2005) combined existing Teagasc and MetÉireann SMD models into the 'hybrid soil moisture deficit' or HSMD model, which is a simple mass-balance calculation to predict SMD from precipitation, evapotranspiration and drainage. Precipitation and evapotranspiration were taken and computed, respectively, from observed weather data or numerical weather prediction (NWP) model output using the Penman-Monteith equation (Allen et al., 1998) and drainage was modelled as a function of one of the three drainage classes calibrated using empirical experimental data. These calibrations showed that poorly drained soils are those that remain wetter than FC for multiple days following winter rainfall events, moderately drained soils carry water in excess of FC during winter rainfall events, but return to FC on the first dry day, whilst well-drained soils never carry soil water in excess of FC. This calibration of drainage is described in detail by Schulte et al. (2005). In recent evaluations of the HSDM model to test its suitability for operational deployment, demonstrated strong relationships between HSMD output and field observations of topsoil (to 30 cm depth) volumetric water content, whilst Doody et al. (2010) concluded that...