Estimation of Soil Hydraulic Parameters Using Inverse Method Based on Specific Liquid-Vapor Interfacial Area Around the Soil Particles

Document Type : Research Paper

Authors

1 Former Graduate Student, Water Engineering Department, School of Agriculture Shiraz University.

2 Corresponding Author, Professor of Water Engineering Department, School of Agriculture, Shiraz University

3 Assistant Professor of Water Engineering and Science Department, Agricultural College, Jahrom University .

Abstract

For the simulation of soil water flux, the relationships between the soil hydraulic conductivity, water content and pressure head are required. The relationship between soil water content ( with soil pressure head [h( ] and hydraulic conductivity [K( )]  are usually obtained by fitting experimental equations. Describing these relationships, the experimental equations such as van Genuchten (van Genuchten, 1980) have been used. Zand-Parsa and Sepaskhah, (2004) proposed a new method for prediction of the soil hydraulic conductivity function [K( ) based on specific liquid-vapor interfacial area around the soil particles and  Zand-Parsa (2006) improved this method for a more straightforward and efficient numerical technique for prediction of function.
The different equations of h (  and K ( ) have three to five soil hydraulic parameters, which  vary considerably in different soil groups. For measurements of the soil hydraulic parameters, laboratory and field methods are time consuming and require excessive financial costs; hence, inverse methods have been used by many researchers. Estimation of the soil hydraulic parameters with using the inverse method is usually less costly and time-consuming than the direct methods, especially for in situ characterization of large sites. Soil hydraulic parameters can be predicted using the inverse method, which are the combination of the numerical model with an iteration algorithm, and genetic algorithm for parameter estimation values (Kamali and Zand-Parsa (2016); Mahbod and Zand-Parsa (2010). For a given initial and boundary conditions and soil hydrauic parameters, Richards’ equation can be solved with numerical methods.
In this study, soil hydraulic parameters were estimated by inverse method based on the soil-water characteristic curve of van Genuchten (1980) method, the function of soil hydraulic conductivity- water content obtained by the method of liquid- vapor interfacial area around the soil particles (Zand-Parsa, 2006).

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Main Subjects


1-    زندپارسا، ش.، محمودیان شوشتری، م. و ا. مجنونی هریس، 1394. اندازه­گیری تبخیر- تعرق استاندارد ذرت با روش بیلان آب و اعماق متغیر ریشه در یک منطقه خشک و نیمه خشک. مجله دانش آب خاک، 25(4/1): 180-169.
 
2-    مجنونی هریس، ا. ارزیابی مدل شبیه سازی رشد ذرت (MSM) در مقادیر مختلف آب و کود نیتروژنه برای آبیاری جویچه‌ای. پایان نامه‌ی کارشناسی ارشد، رشته مهندسی آبیاری و زهکشی، دانشکده کشاورزی، بخش مهندسی آب، دانشگاه شیراز. 271 صفحه.
 
3-    مهبد، م. 1386. تخمین توابع هیدرولیکی خاک به روش معکوس با استفاده از الگوریتم ژنتیک در شرایط مزرعه و آزمایشگاه. پایان نامه کارشناسی ارشد، رشته مهندسی آبیاری و زهکشی، دانشکده کشاورزی، بخش مهندسی آب، دانشگاه شیراز. 188 صفحه.
 
4-    نهضتی پاقلعه، ع. 1387 . اصلاح و ارزیابی مدل شبیه سازی رشد گیاه ذرت(MSM) نسبت به تراکم های مخلف گیاه در مقادیر متفاوت کود نیتروژن. نهمین سمینار سراسری آبیاری و کاهش تبخیر، 9 صفحه.
 
5-     Campbell, GS. 1985. Soil physics with basic (transport models for soil plant systems). Book.
 
6-    Campbell, GS. 1991. Simulation of water uptake by plant roots. In: Hanks J, Ritchie JT, editors. Modelling plant and soil system. Agronomy No. 31. Madison (WI): ASA-SSSA. P: 273-285.
 
7-    Hillel, D. 1998. Environmental soil physics. NewYork: Academic Press. Inc. 771 p.
 
8-    Kamali, H.R., Sh. Zand-Parsa. 2016. Optimization of a new inverse method for estimation of individual soil hydraulic parameters under field condition. Transactions of the ASABE, 95:1-10.
 
9-    Mahbod, M. and Sh. Zand-parsa. 2010. Prediction of soil hydraulic parameters by inverse method using genetic algorithm under field conditions. Archives of Agronomy and Soil Science, 56(1): 13-28.
 
10- Minasny, B., Hopmans. JW., Harter. T., Eching. SO, Tuli. A., and MA. Denton. 2004. Neutral networks prediction of soil hydraulic functions for alluvial soils using multistep outflow data. Soil Science Society of American Journal, 68:417-429.
 
11- Richards, L.A. 1931. Capillary conduction of liquids through porous medium. Ph.D Thesis, Cornell University.
12- Ritter, R., Mun˜oz-Carpena Regalado, C.M., Vanclooster, M and S. Lambot. 2004. Analysis of alternative measurement strategies for the inverse optimization of the hydraulic properties of a volcanic soil. Journal of Hydrology, 295 : 124-139.
 
13- Schelle, H. Iden, SC. Fank, J and W. Durner.  2013. Simultaneous estimation of soil hydraulic and root distribution parameters from lysimeter data by inverse modeling. Procedia Environmental Sciences, 19: 564 – 573.
 
14- van Genuchten, M.Th. 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soil. Soil Science Society of American Journal, 44: 892-898.
 
15- Wöhling, T, Vrugt, JA. and GF. Barkle. 2008. Comparison of Three Multiobjective Optimization Algorithms for Inverse Modeling of Vadose Zone Hydraulic Properties. Soil Science Society of American Journal, 72: 305-319.
 
16- Zand-Parsa, Sh. 2001. A simulation model for prediction of water and nitrogen effects on corn yield. Ph.D. Thesis, Irrigation Department, Agricultural College, Shiraz University, Shiraz, Iran.
 
17- Zand-Parsa, Sh., and A.R. Sepaskhah. 2004. Soil hydraulic conductivity function based on specific liquid–vapour interfacial area around the soil particles. Geoderma, 119: 143–157.
 
18- Zand-Parsa, Sh. 2006. Improved soil hydraulic conductivity function based on specific liquid-vapour interfacial area around the soil particles. Geoderma, 132: 20-30.
Volume 40, Issue 4
February 2018
Pages 1-15
  • Receive Date: 13 December 2015
  • Revise Date: 06 February 2018
  • Accept Date: 19 April 2016
  • Publish Date: 21 January 2018