Estimating particle-size distribution from limited soil texture data
By Todd H. Skaggs, L. Arya, P. Shouse, B. Mohanty. 2001
134 citations recorded by the source corpus.
Subfields: Civil and Structural Engineering, Environmental Engineering, Management, Monitoring, Policy and Law
View Paper: https://www.semanticscholar.org/paper/e4074bb54157b7250709e05bb46ef038a51aa1c6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Civil and Structural Engineering
- Jirka Šimůnek
- Navin Twarakavi
- Tomislav Hengl
- M. G. Schaap
- Parveen Sihag
- Wim Cornelis
- M. T. V. Genuchten
- Amir Haghverdi
In Environmental Engineering
- Jirka Šimůnek
- Navin Twarakavi
- Tomislav Hengl
- M. G. Schaap
- Parveen Sihag
- Wim Cornelis
- M. T. V. Genuchten
- Amir Haghverdi
In Management, Monitoring, Policy and Law
Citations in the corpus
- A Practical Guide to Geostatistical Mapping (2009, methodology): “The literature (Skaggs et al., 2001) reports that the this technique can be used to determine the content of soil earth fractions only to an accuracy of ±5–10%.”
- Prediction of unsaturated hydraulic conductivity using fuzzy logic and artificial neural network (2018, background): “2017b) However, predictive approaches of the soil hydraulic conductivity have obtain consideration by researchers and attempts have been made to raise the accuracy of predictability (Skaggs et al. 2001; AlSulaiman and Aboukarima 2015).”
- Can texture‐based classification optimally classify soils with respect to soil hydraulics? (2010, background): “Skaggs et al. [2001] seem to suggest that four instead of three particle size fractions are needed to adequately characterize a particle size distribution.”