Predicting of soil water characteristics curve with modified Van Genuchten model by particle size distribution data
Paper Details
Predicting of soil water characteristics curve with modified Van Genuchten model by particle size distribution data
Abstract
Direct measurement of soil moisture characteristics curve (SMC) due to spatial and temporal variation is labor and expensive. So, prediction of SMC from basic soil properties which can be measured easily would be satisfactory. In this study, we use a dataset containing 18 UNSODA soil samples to evaluate the performance of modified Van Genuchten (VG) model. We make a comparison between the results obtained from modified VG model and ROSETTA software showing that the modification of VG model increases the accuracy of SMC. The model bias was related to particles size and particles surface energy. We concluded that modified VG model improve predictions of SMC more accurate for large scale hydrological management.
Abbasi Y, Ghanbarian-Alavijeh BE, Liaghat AM, Shorafa ME. 2011. Evaluation of pedotransfer functions for estimating soil water retention curve of saline and saline-alkali soils of Iran. Pedosphere 21, 230-237.
Antinoro C, Bagarello V, Ferro V, Giordano G, Iovino M. 2014. A simplified approach to estimate water retention for Sicilian soils by the Arya–Paris model. Geoderma 213, 226-234.
Arya LM, Paris JF. 1981. A physicoempirical model to predict the soil moisture characteristic from particle-size distribution and bulk density data. Soil Science Society of America Journal 45, 1023-1030.
Chan TP, Govindaraju RS. 2004. Estimating soil water retention curve from particle-size distribution data based on poly disperse sphere systems. Vadose Zone Journal 3, 1443-1454.
Christiaens K, Feyen J. 2001. Analysis of uncertainties associated with different methods to determine soil hydraulic properties and their propagation in the distributed hydrological MIKE SHE model. Journal of Hydrology 246, 63-81.
Dashtaki S, Homaee M, Khodaverdiloo H. 2010. Derivation and validation of pedotransfer functions for estimating soil water retention curve using a variety of soil data. Soil Use Manage 26, 68-74.
Ghanbarian-Alavijeh B, Liaghat A, Huang Guan-Hua, Van Genuchten M Th. 2010. Estimation of the van Genuchten soil water retention properties from soil textural data 20, 456-465.
Harter T, Hopmans J. 2004. Role of vadose zone flow processes in regional scale hydrology: Review, opportunities and challenges. Kluwer Pubp 179.
Hunt AG, Ghanbarian B, Saville KC. 2013. Unsaturated hydraulic conductivity modeling for porous media with two fractal regimes.Geoderma 207, 268-278.
Hwang SI, Choi SI. 2006. Use of a lognormal distribution model for estimating soil water retention curves from particle-size distribution data. Journal of Hydrology 323, 325-334.
Islam N, Wallender W, Mitchell JP, Wicks S, Howitt RE. 2006. Performance evaluation of methods for the estimation of soil hydraulic parameters and their suitability in a hydrologic model.Geoderma1 341, 135-151.
Mc Bratney B. 2002. The Neuro-m Method for Fitting Neural Network Parametric Pedotransfer Functions. Budiman Minasny and Alex. Soil Science Society of America Journal 66, 352-361.
Meskini-Vishkaee F, Mohammadi MH, Vancl-ooster M. 2014. Predicting the soil moisture retention curve, from soil particle size distribution and bulk density data using a packing density scaling factor. Hydrology and Earth System Sciences 18, 4053-4063.
Mohammadi MH, Meskini-Vishkaee F. 2013. Predicting soil moisture characteristic curves from continuous particle-size distribution data. Pedosp-here 23, 70-80.
Mohammadi MH, Vanclooster M. 2011. Predicting the soil moisture characteristic curve from particle size distribution with a simple conceptual model. Vadose Zone Journal 10, 594-602.
Nemes A, Schaap MG, Leij FJ, Wösten JHM. 2001. Description of the unsaturated soil hydraulic database UNSODA version 2.0. Journal of Hydrology 251, 151-162.
Nimmo JR, Herkelrath WN, Laguna Luna AM. 2007. Physically based estimation of soil water retention from textural data: General framework, new models, and streamlined existing models. Vadose Zone Journal 6, 766-773.
Schaap MG, Leij FJ. 1998. Using neural networks to predict soil water retention and soil hydraulic conductivity. Soil and Tillage Research 47, 37-42.
Schaap MG, Leij FJ, van Genuchten MT. 2001. ROSETTA: a computer program for estimating soil hydraulic parameters with hierarchical pedotransfer functions. Journal of hydrology 251, 163-176.
Van Genuchten MT. 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil science society of America journal 44, 892-898.
Vereecken H, Weynants M, Javaux M, Pachepsky Y, Schaap MG, Genuchten MT. 2010. Using pedotransfer functions to estimate the van Genuchten–Mualem soil hydraulic properties: A review. Vadose zone Journal 9, 795-820.
Samaneh Amanabadi, Mohammad Hossien Mohammadi, Mohammad Hassan Masihabadi (2016), Predicting of soil water characteristics curve with modified Van Genuchten model by particle size distribution data; JBES, V9, N1, July, P33-39
https://innspub.net/predicting-of-soil-water-characteristics-curve-with-modified-van-genuchten-model-by-particle-size-distribution-data/
Copyright © 2016
By Authors and International
Network for Natural Sciences
(INNSPUB) https://innspub.net
This article is published under the terms of the
Creative Commons Attribution License 4.0