Deriving physical and unique bimodal soil Kosugi hydraulic parameters from inverse modelling

被引:18
作者
Fernandez-Galvez, J. [1 ,2 ]
Pollacco, J. A. P. [2 ]
Lilburne, L. [2 ]
McNeill, S. [2 ]
Carrick, S. [2 ]
Lassabatere, L. [3 ]
Angulo-Jaramillo, R. [3 ]
机构
[1] Univ Granada, Dept Reg Geog Anal & Phys Geog, Granada, Spain
[2] Manaaki Whenua Landcare Res, Lincoln, New Zealand
[3] Univ Lyon 1, ENTPE, CNRS, Ecol Hydrosyst Nat & Anthropises UMR5023, Bouguenais, France
关键词
Kosugi hydraulic model; Dual porosity; Hydraulic parameters; Inverse modelling; Non-uniqueness; LOGNORMAL-DISTRIBUTION MODEL; WATER-RETENTION; NEW-ZEALAND; LINKING TEST; CONDUCTIVITY; CURVES; ALGORITHM; MOISTURE; FLOW;
D O I
10.1016/j.advwatres.2021.103933
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
Hydraulic parameters define the water retention, theta( psi), and the unsaturated hydraulic conductivity, K(theta), functions. These functions are usually obtained by fitting experimental data using inverse modelling. The drawback of inverting the hydraulic parameters is that they suffer from non-uniqueness and the optimal hydraulic parameters may not be physical. To reduce the non-uniqueness, it is necessary to invert the hydraulic parameters simultaneously from observations of theta( psi) and K(theta), and ensure the measurements cover the full range of theta from saturated to oven dry. The challenge of using bimodal theta(psi) and K(theta) compared to unimodal functions is that it requires double the number of parameters, one set for the matrix and another set for the macropore domain. The objective of this paper is to address this shortcoming by deriving a procedure to reduce the number of parameters to be optimized to obtain a unique physical set of bimodal soil Kosugi hydraulic parameters from inverse modelling. To achieve this, we (1) derive residual volumetric soil water content from the Kosugi standard deviation parameter of the soil matrix, (2) derive macropore hydraulic parameters from the water pressure head threshold between macropore and matrix flow, and (3) dynamically constrain the Kosugi hydraulic parameters of the soil matrix. The procedure successfully reduces the number of optimized hydraulic parameters and dynamically constrains the hydraulic parameters without compromising the fit of the theta(psi) and K(theta) functions, and the derived hydraulic parameters are more physical. The robustness of the methodology is demonstrated by deriving the hydraulic parameters exclusively from theta(psi) and Ks data, enabling satisfactory prediction of K(theta) even when no additional K(theta) data are available.
引用
收藏
页数:8
相关论文
共 47 条
[21]   Comparison of the Instantaneous Profile Method and inverse modelling for the prediction of effective soil hydraulic properties [J].
Dikinya, O .
AUSTRALIAN JOURNAL OF SOIL RESEARCH, 2005, 43 (05) :599-606
[22]   Estimating soil hydraulic properties from oven-dry to full saturation using shortwave infrared imaging and inverse modeling [J].
Bandai, Toshiyuki ;
Sadeghi, Morteza ;
Babaeian, Ebrahim ;
Jones, Scott B. ;
Tuller, Markus ;
Ghezzehei, Teamrat A. .
JOURNAL OF HYDROLOGY, 2024, 635
[23]   Obtaining soil hydraulic parameters from soil water content data assimilation under different climatic/soil conditions [J].
Valdes-Abellan, Javier ;
Pachepsky, Yakov ;
Martinez, Gonzalo .
CATENA, 2018, 163 :311-320
[24]   Estimation of Hydraulic Parameters from the Soil Water Characteristic Curve [J].
Angelaki, Anastasia ;
Bota, Vasiliki ;
Chalkidis, Iraklis .
SUSTAINABILITY, 2023, 15 (08)
[25]   Effect of Stoniness on the Hydraulic Properties of a Soil from an Evaporation Experiment Using the Wind and Inverse Estimation Methods [J].
Arias, Nerea ;
Virto, Inigo ;
Enrique, Alberto ;
Bescansa, Paloma ;
Walton, Riley ;
Wendroth, Ole .
WATER, 2019, 11 (03)
[26]   Estimation of the soil hydraulic properties from field data by solving an inverse problem [J].
Guellouz, Lamia ;
Askri, Brahim ;
Jaffre, Jerome ;
Bouhlila, Rachida .
SCIENTIFIC REPORTS, 2020, 10 (01)
[27]   Monte Carlo analysis of field water flow comparing uni- and bimodal effective hydraulic parameters for structured soil [J].
Coppola, A. ;
Basile, A. ;
Comegna, A. ;
Lamaddalena, N. .
JOURNAL OF CONTAMINANT HYDROLOGY, 2009, 104 (1-4) :153-165
[28]   Local and global inverse modelling strategies to estimate parameters for pesticide leaching from lysimeter studies [J].
Kahl, Gunnar M. ;
Sidorenko, Yury ;
Gottesbueren, Bernhard .
PEST MANAGEMENT SCIENCE, 2015, 71 (04) :616-631
[29]   Deriving historical equilibrium-line altitudes from a glacier length record by linear inverse modelling [J].
Klok, EJ ;
Oerlemans, J .
HOLOCENE, 2003, 13 (03) :343-351
[30]   Soil Hydraulic Parameters of Bare Soil Plots with Different Soil Structure Inversely Derived from L-Band Brightness Temperatures [J].
Dimitrov, M. ;
Vanderborght, J. ;
Kostov, K. G. ;
Debecker, B. ;
Lammers, P. Schulze ;
Damerow, L. ;
Vereecken, H. .
VADOSE ZONE JOURNAL, 2015, 14 (08)