Skip to main content
ARS Home » Research » Publications at this Location » Publication #95195

Title: USE OF SOIL PENETRATION RESISTANCE AND GMDH TO IMPROVE SOIL WATER RETENTION ESTIMATES

Author
item PACHEPSKY, YAKOV - DUKE UNIVERSITY
item Rawls, Walter
item GIMENEZ, DANIEL - RUTGERS UNIVERSITY
item WATT, JAMES - WHENUA LANDCARE NZ

Submitted to: Soil Technology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/2/1998
Publication Date: N/A
Citation: N/A

Interpretive Summary: The soil controls the downward movement and storage of water which is critical to crops, flood prediction, and engineering design of conservation practices. Laboratory and field methods for determining soil hydraulic properties are time consuming and expensive especially on a regional scale, thus, new simple field techniques are needed to describe soil effects on the water storage and movement in soils. The usefulness of a simple shear and penetration field measurements were found to be useful in describing soil effects on the water storage and movement. The customers of such research are federal agencies such as EPA, NRC, DOD, DOE, USGS, NASA, NRCS, NOAA, state agencies and consulting and private firms doing environmental work.

Technical Abstract: The accuracy of pedotransfer functions can be improved using more flexible equations and additional input variables. Penetration resistance as parameter related to soil structure can be a useful additional input to pedotransfer functions. Our objectives were to see whether using penetration resistance can improve the accuracy of estimating were retention from soil composition and bulk density. To develop pedotranfer functions, we applied ground method of data handling (GMDH) resulting in hierarchical polynomial regression networks or abductive networks. The advantage of GMDH is that it automates finding essential input variables to be included in pedotransfer functions and, unlike the artificial neural networks, presents an explicit form of the equations. We developed pedotransfer functions from data on texture, bulk density, penetration resistance, and water content at 0, -5, -10, -20, -100, -1500 kPa in 180 samples of New Zealand soils. Abductive networks were used to estimate water contents at particular matrix potentials. The water contents at -1500 kPa and the penetration resistance were the essential variables to include in pedotranfer functions along with bulk density and texture. The pore volume fractal dimensions could be reliably estimated from the water content at -1500 kPa and penetration resistance. The variation coefficient rather than average value of penetration resistance was found to be a good predictor in some cases.