scholarly journals The effect of soil hydraulic properties vs. soil texture in land surface models

2005 ◽  
Vol 32 (2) ◽  
Author(s):  
E. D. Gutmann
Keyword(s):  
Soil Texture ◽  
Land Surface ◽  
Hydraulic Properties ◽  
Land Surface Models ◽  
Soil Hydraulic Properties ◽  
Surface Models ◽  
Soil Hydraulic

scholarly journals Geophysical mapping of soil texture variability in the root zone to improve modelling of the water and nutrient flow.

2020 ◽  
Author(s):  
Kim Schwartz Madsen ◽  
Bo Vangsø Iversen ◽  
Christen Duus Børgesen
Keyword(s):  
Soil Texture ◽  
Hydraulic Properties ◽  
Root Zone ◽  
Clay Fraction ◽  
Clay Content ◽  
Auxiliary Variable ◽  
Pedotransfer Functions ◽  
Soil Hydraulic Properties ◽  
Sampling Density ◽  
Soil Hydraulic

<p>Modelling is often used to acquire information on water and nutrient fluxes within and out of the root zone. The models require detailed information on the spatial variability of soil hydraulic properties derived from soil texture and other soil characteristics using pedotransfer functions (PTFs). Soil texture can vary considerably within a field and is cumbersome and expensive to map in details using traditionally measurements in the laboratory. The electrical conductivity (EC) of the soil have shown to correlate with its textural composition.</p><p>This study investigates the ability of electromagnetic induction (EMI) methods to predict clay content in three soil layers of the root zone. As the clay fraction often is a main predictor in PTFs predicting soil hydraulic properties this parameter is of high interest. EMI and soil textural surveys on four Danish agricultural fields with varying textural composition were used. Sampling density varied between 0.5 and 38 points per hectare. The EMI data was gathered with a Dualem21 instrument with a sampling density 200-3000 points per hectare. The EC values were used together with the measured values of the clay content creating a statistical relationship between the two variables. Co-kriging of the clay content from the textural sampling points with the EC as auxiliary variable produces clay content maps of the fields. Unused (80%) texture points were used for validation. EMI-predicted clay content maps and clay content maps based on the survey were compared. The two sets of soil texture maps are used as predictors for PTF models to predict soil hydraulic properties as input in field-scale root zone modelling.</p><p>The comparisons between EC and clay content show some degree of correlation with an R<sup>2</sup> in the range of 0.55 to 0.80 for the four fields. The field with the highest average clay content showed the best relationship between the two parameters. Co-kriging with EC decreased mean error by 0.016 to 0.52 and RMSE by 0.04 to 1.80 between observed and predicted clay maps.</p>

scholarly journals Spatial Variability of Soil Physical and Hydraulic Properties in a Durum Wheat Field: An Assessment by the BEST-Procedure

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1434 ◽  
Author(s):  
Mirko Castellini ◽  
Anna Maria Stellacci ◽  
Matteo Tomaiuolo ◽  
Emanuele Barca
Keyword(s):  
Spatial Variability ◽  
Crop Yield ◽  
Soil Texture ◽  
Hydraulic Properties ◽  
Wheat Yield ◽  
Structure Stability ◽  
Soil Hydraulic Properties ◽  
Field Scale ◽  
Cross Correlation Analysis ◽  
Soil Hydraulic

Spatial variability of soil properties at the field scale can determine the extent of agricultural yields and specific research in this area is needed. The general objective of this study was to investigate the relationships between soil physical and hydraulic properties and wheat yield at the field scale and test the BEST-procedure for the spatialization of soil hydraulic properties. A simplified version of the BEST-procedure, to estimate some capacitive indicators from the soil water retention curve (air capacity, ACe, relative field capacity, RFCe, plant available water capacity, PAWCe), was applied and coupled to estimates of structure stability index (SSI), determinations of soil texture and measurements of bulk density (BD), soil organic carbon (TOC) and saturated hydraulic conductivity (Ks). Variables under study were spatialized to investigate correlations with observed medium-high levels of wheat yields. Soil physical quality assessment and correlations analysis highlighted some inconsistencies (i.e., a negative correlation between PAWCe and crop yield), and only five variables (i.e., clay + silt fraction, BD, TOC, SSI and PAWCe) were spatially structured. Therefore, for the soil–crop system studied, application of the simplified BEST-procedure did not return completely reliable results. Results highlighted that (i) BD was the only variable selected by stepwise analysis as a function of crop yield, (ii) BD showed a spatial distribution in agreement with that detected for crop yield, and (iii) the cross-correlation analysis showed a significant positive relationship between BD and wheat yield up to a distance of approximately 25 m. Such results have implications for Mediterranean agro-environments management. In any case, the reliability of simplified measurement methods for estimating soil hydraulic properties needs to be further verified by adopting denser measurements grids in order to better capture the soil spatial variability. In addition, the temporal stability of observed spatial relationships, i.e., between BD or soil texture and crop yields, needs to be investigated along a larger time interval in order to properly use this information for improving agronomic management.

scholarly journals Evaluating the value of a network of cosmic-ray probes for improving land surface modelling

2016 ◽  
Author(s):  
R. Baatz ◽  
Harrie-Jan Hendricks Franssen ◽  
Xujun Han ◽  
Tim Hoar ◽  
Heye R. Bogena ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Cosmic Ray ◽  
Land Surface Models ◽  
Lower Boundary Condition ◽  
Soil Map ◽  
Community Land Model ◽  
Verification Period ◽  
Surface Models ◽  
Soil Hydraulic

Abstract. Land surface models can model matter and energy fluxes between the land surface and atmosphere, and provide a lower boundary condition to atmospheric circulation models. For these applications, accurate soil moisture quantification is highly desirable but not always possible given limited observations and limited subsurface data accuracy. Cosmic-ray probes (CRPs) offer an interesting alternative to indirectly measure soil moisture and provide an observation that can be assimilated into land surface models for improved soil moisture prediction. Synthetic studies have shown the potential to estimate subsurface parameters of land surface models with the assimilation of CRP observations. In this study, the potential of a network of CRPs for estimating subsurface parameters and improved soil moisture states is tested in a real-world case scenario using the local ensemble transform Kalman filter with the Community Land Model. The potential of the CRP network was tested by assimilating CRP-data for the years 2011 and 2012 (with or without soil hydraulic parameter estimation), followed by the verification year 2013. This was done using (i) the regional soil map as input information for the simulations, and (ii) an erroneous, biased soil map. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the biased soil map, soil moisture characterization improved in both periods strongly from a ERMS of 0.11 cm3/cm3 to 0.03 cm3/cm3 (assimilation period) and from 0.12 cm3/cm3 to 0.05 cm3/cm3 (verification period) and the estimated soil hydraulic parameters were after assimilation closer to the ones of the regional soil map. Finally, the value of the CRP network was also evaluated with jackknifing data assimilation experiments. It was found that the CRP network is able to improve soil moisture estimates at locations between the assimilation sites from a ERMS of 0.12 cm3/cm3 to 0.06 cm3/cm3 (verification period), but again only if the initial soil map was biased.

scholarly journals High-resolution hydraulic parameter maps for surface soils in tropical South America

2013 ◽  
Vol 6 (4) ◽  
pp. 6741-6774 ◽  
Author(s):  
T. R. Marthews ◽  
C. A. Quesada ◽  
D. R. Galbraith ◽  
Y. Malhi ◽  
C. E. Mullins ◽  
...  
Keyword(s):  
High Resolution ◽  
South America ◽  
Soil Profile ◽  
Land Surface ◽  
Water Movement ◽  
Land Surface Models ◽  
Hydraulic Parameter ◽  
Surface Models ◽  
Soil Hydraulic ◽  
Tropical South America

Abstract. Modern land surface model simulations capture soil profile water movement through the use of soil hydraulics sub-models, but good hydraulic parameterisations are often lacking, especially in the tropics. We present much-improved gridded datasets of hydraulic parameters for surface soil for the critical area of tropical South America, describing soil profile water movement across the region to 30 cm depth. Optimal hydraulic parameter values are given for the Brooks and Corey, Campbell, van Genuchten–Mualem and van Genuchten–Burdine soil hydraulic models, which are widely-used hydraulic sub-models in Land Surface Models. This has been possible through interpolating soil measurements from several sources through the SOTERLAC soil and terrain database and using the most recent pedotransfer functions (PTFs) derived for South American soils. All soil parameter data layers are provided at 15 arcsec resolution and available for download, this being 20 × higher resolution than the best comparable parameter maps available to date. Specific examples are given of the use of PTFs and the importance highlighted of using PTFs that have been locally-parameterised and that are not just based on soil texture. Details are provided specifically on how to assemble the ancillary data files required for grid-based vegetation simulation using the Joint UK Land Environment Simulator (JULES). We discuss current developments in soil hydraulic modelling and how high-resolution parameter maps such as these can improve the simulation of vegetation development and productivity in land surface models.

scholarly journals High-resolution hydraulic parameter maps for surface soils in tropical South America

2014 ◽  
Vol 7 (3) ◽  
pp. 711-723 ◽  
Author(s):  
T. R. Marthews ◽  
C. A. Quesada ◽  
D. R. Galbraith ◽  
Y. Malhi ◽  
C. E. Mullins ◽  
...  
Keyword(s):  
High Resolution ◽  
South America ◽  
Soil Profile ◽  
Land Surface ◽  
Water Movement ◽  
Land Surface Models ◽  
Hydraulic Parameter ◽  
Surface Models ◽  
Soil Hydraulic ◽  
Tropical South America

Abstract. Modern land surface model simulations capture soil profile water movement through the use of soil hydraulics sub-models, but good hydraulic parameterisations are often lacking, especially in the tropics. We present much-improved gridded data sets of hydraulic parameters for surface soil for the critical area of tropical South America, describing soil profile water movement across the region to 30 cm depth. Optimal hydraulic parameter values are given for the Brooks and Corey, Campbell, van Genuchten–Mualem and van Genuchten–Burdine soil hydraulic models, which are widely used hydraulic sub-models in land surface models. This has been possible through interpolating soil measurements from several sources through the SOTERLAC soil and terrain data base and using the most recent pedotransfer functions (PTFs) derived for South American soils. All soil parameter data layers are provided at 15 arcsec resolution and available for download, this being 20x higher resolution than the best comparable parameter maps available to date. Specific examples are given of the use of PTFs and the importance highlighted of using PTFs that have been locally parameterised and that are not just based on soil texture. We discuss current developments in soil hydraulic modelling and how high-resolution parameter maps such as these can improve the simulation of vegetation development and productivity in land surface models.

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