ROSETTA: a computer program for estimating soil hydraulic parameters with hierarchical pedotransfer functions

被引:1890
作者
Schaap, MG [1 ]
Leij, FJ [1 ]
van Genuchten, MT [1 ]
机构
[1] USDA ARS, George E Brown Jr Salin Lab, Riverside, CA 92507 USA
基金
美国国家科学基金会; 美国国家航空航天局;
关键词
soils; hydraulic conductivity; retention; neural networks; computer programs;
D O I
10.1016/S0022-1694(01)00466-8
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Soil hydraulic properties are necessary for many studies of water and solute transport but often cannot be measured because of practical and/or financial constraints. We describe a computer program, ROSETTA, which implements five hierarchical pedotransfer functions (PTFs) for the estimation of water retention, and the saturated and unsaturated hydraulic conductivity. The hierarchy in PTFs allows the estimation of van Genuchten water retention parameters and the saturated hydraulic conductivity using limited (textural classes only) to more extended (texture, bulk density, and one or two water retention points) input data. ROSETTA is based on neural network analyses combined with the bootstrap method, thus allowing the program to provide uncertainty estimates of the predicted hydraulic parameters. The general performance Of ROSETTA was characterized with coefficients of determination, and root mean square errors (RMSEs). The RMSE values decreased from 0.078 to 0.044 cm(3) cm(-3) for water retention when more predictors were used. The RMSE for the saturated conductivity similarly decreased from 0.739 to 0.647 (dimensionless log(10) units). The RMSE values for unsaturated conductivity ranged between 0.79 and 1.06, depending on whether measured or estimated retention parameters were used as predictors. Calculated mean errors showed that the PTFs underestimated water retention and the unsaturated hydraulic conductivity at relatively high suctions. ROSETTA's uncertainty estimates can be used as an indication of model reliability when no hydraulic data are available. The ROSETTA program comes with a graphical user interface that allows user-friendly access to the PTFs, and can be downloaded from the US Salinity Laboratory website: http://www.ussl.ars.usda.gov/. (C) 2001 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:163 / 176
页数:14
相关论文
共 35 条
[1]   EVALUATION OF SPATIAL-DISTRIBUTION OF HYDRAULIC CONDUCTIVITY USING EFFECTIVE POROSITY DATA [J].
AHUJA, LR ;
CASSEL, DK ;
BRUCE, RR ;
BARNES, BB .
SOIL SCIENCE, 1989, 148 (06) :404-411
[2]  
[Anonymous], 1999, P INT WORKSHOP CHARA
[3]   Relationship between the hydraulic conductivity function and the particle-size distribution [J].
Arya, LM ;
Leij, FJ ;
Shouse, PJ ;
van Genuchten, MT .
SOIL SCIENCE SOCIETY OF AMERICA JOURNAL, 1999, 63 (05) :1063-1070
[4]   Scaling parameter to predict the soil water characteristic from particle-size distribution data [J].
Arya, LM ;
Leij, FJ ;
van Genuchten, MT ;
Shouse, PJ .
SOIL SCIENCE SOCIETY OF AMERICA JOURNAL, 1999, 63 (03) :510-519
[5]  
ARYA LM, 1981, SOIL SCI SOC AM J, V45, P1218
[6]  
Bouma J., 1987, Quantified Land Evaluation, Proceedings of Workshop in ISSS and SSSA, Washington, DC, 27 April-2 May 1986, P106
[7]  
BURDINE NT, 1953, T AM I MIN MET ENG, V198, P71
[8]   DEVELOPING JOINT PROBABILITY-DISTRIBUTIONS OF SOIL-WATER RETENTION CHARACTERISTICS [J].
CARSEL, RF ;
PARRISH, RS .
WATER RESOURCES RESEARCH, 1988, 24 (05) :755-769
[9]  
Efron B, 1993, INTRO BOOTSTRAP MONO
[10]   PREDICTING THE WATER-RETENTION CURVE FROM PARTICLE-SIZE DISTRIBUTION .1. SANDY SOILS WITHOUT ORGANIC-MATTER [J].
HAVERKAMP, R ;
PARLANGE, JY .
SOIL SCIENCE, 1986, 142 (06) :325-339