| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
a USDA-ARS Hydrology and Remote Sensing Lab., 10300 Baltimore Ave. Bldg. 007 Rm. 124, BARC-WEST, Beltsville, MD 20705-2350, USA
b USDA-ARS, George E. Brown Jr. Salinity Lab., 450 W. Big Springs Road, Riverside, CA 92507
c ALTERRA Green World Res., P.O. Box 47, 6700 AA Wageningen, The Netherlands
* Corresponding author (anemes{at}hydrolab.arsusda.gov)
Estimation of soil hydraulic properties by pedotransfer functions (PTFs) can be an alternative to troublesome and expensive measurements. New approaches to develop PTFs are continuously being introduced, however, PTF applicability in locations other than those of data collection has been rarely reported. We used three databases were used to develop PTFs using artificial neural networks (NNs). Data from Hungary were used to derive national scale soil hydraulic PTFs. The HYPRES database was used to develop continental scale PTFs. Finally, a database containing mostly American and European data was used to develop intercontinental scale PTFs. For each database, 11 PTFs were developed that differed in detail of input data. Accuracy of the estimations was tested using independent Hungarian data. First, soil water retention at nine values of matric potential were estimated. Root mean squared residuals (RMSRs) using different inputs ranged from 0.02 to 0.06 m3 m-3 for national scale PTFs, while international scale PTFs had RMSRs from 0.025 to 0.088 m3 m-3. Estimated water retention curves (WRCs) were then used to simulate soil moisture time series of seven Hungarian soils. Root mean squared residuals during a growing season ranged from 0.065 to 0.07 m3 m-3, using different PTF estimates. Simulations using laboratory-measured WRCs had RMSR of 0.061 m3 m-3. Such small differences in the accuracy of simulations make international PTFs an alternative to national PTFs and measurements. However, testing of the international PTFs with a specific model for specific soil and land use remains desirable because of uncertainty in soil representation in such databases.
Abbreviations: Db, bulk density • OM, organic matter • NN, neural network • PTF, pedotransfer function • MR, mean residual • RMSR, root mean squared residual • WRC, water retention curve
This article has been cited by other articles:
|
|
 |
|
  R. B. Jana, B. P. Mohanty, and E. P. Springer Multiscale Pedotransfer Functions for Soil Water Retention Vadose Zone J., November 20, 2007; 6(4): 868 - 878. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. Zacharias and G. Wessolek Excluding Organic Matter Content from Pedotransfer Predictors of Soil Water Retention Soil Sci. Soc. Am. J., January 1, 2007; 71(1): 43 - 50. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. Nemes, W. J. Rawls, Ya. A. Pachepsky, and M. Th. van Genuchten Sensitivity Analysis of the Nonparametric Nearest Neighbor Technique to Estimate Soil Water Retention Vadose Zone J., November 20, 2006; 5(4): 1222 - 1235. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
K. Parasuraman, A. Elshorbagy, and B. C. Si Estimating Saturated Hydraulic Conductivity In Spatially Variable Fields Using Neural Network Ensembles Soil Sci. Soc. Am. J., September 20, 2006; 70(6): 1851 - 1859. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. Nemes, W. J. Rawls, and Y. A. Pachepsky Use of the Nonparametric Nearest Neighbor Approach to Estimate Soil Hydraulic Properties Soil Sci. Soc. Am. J., February 2, 2006; 70(2): 327 - 336. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
G. Crescimanno and P. Garofalo Application and Evaluation of the SWAP Model for Simulating Water and Solute Transport in a Cracking Clay Soil Soil Sci. Soc. Am. J., October 27, 2005; 69(6): 1943 - 1954. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. Somaratne, G. Seneviratne, and U. Coomaraswamy Prediction of Soil Organic Carbon across Different Land-use Patterns: A Neural Network Approach Soil Sci. Soc. Am. J., August 25, 2005; 69(5): 1580 - 1589. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
F. Gerard, M. Tinsley, and K. U. Mayer Preferential Flow Revealed by Hydrologic Modeling Based on Predicted Hydraulic Properties Soil Sci. Soc. Am. J., September 1, 2004; 68(5): 1526 - 1538. [Abstract] [Full Text] [PDF]
|
|
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| The SCI Journals | Agronomy Journal | Crop Science | |||
| Journal of Natural Resources and Life Sciences Education |
Vadose Zone Journal | ||||
| Journal of Plant Registrations | Journal of Environmental Quality |
The Plant Genome | |||
