REGIONALIZATION OF SOIL-WATER RETENTION CURVES IN A HIGHLY VARIABLE SOILSCAPE .1. DEVELOPING A NEW PEDOTRANSFER FUNCTION

Citation
Ac. Scheinost et al., REGIONALIZATION OF SOIL-WATER RETENTION CURVES IN A HIGHLY VARIABLE SOILSCAPE .1. DEVELOPING A NEW PEDOTRANSFER FUNCTION, Geoderma, 78(3-4), 1997, pp. 129-143
Citations number
23
Categorie Soggetti
Agriculture Soil Science
Journal title
ISSN journal
00167061
Volume
78
Issue
3-4
Year of publication
1997
Pages
129 - 143
Database
ISI
SICI code
0016-7061(1997)78:3-4<129:ROSRCI>2.0.ZU;2-W
Abstract
Geostatistically interpolated soil properties were combined with a ped otransfer function (PTF) to predict the three-dimensional variability of water retention curves (WRCs) in a highly variable soilscape. A new PTF had to be developed to account for the extreme variation in soil parameters: texture varying between gravel and clay, organic C content up to 81 g kg(-1), and bulk density from 0.80 to 1.85 Mg m(-3). A com mon procedure to generate such a PTF is first to parameterize the WRCs with a function, and then to calculate regression equations, linking the function's parameters with soil properties. This procedure could n ot be used, however, because of the overparametrization of possible fu nctions with respect to the eight measured data points of the WRCs, Th erefore, the parameters of a Van Genuchten-type function, theta(s), th eta(r), alpha, and n, were substituted by Linear equations relating th ese parameters with soil properties in a physically meaningful way: th eta(s) = f (porosity, clay), theta(f) = f (clay, organic C), alpha = f (d(g)), and n = f (1/sigma(g)). That is, the particle-size distributio n parameters d(g) and sigma(g), were assumed to be related to the pore -size distribution parameters alpha and n. The substituted Van Genucht en function was then fitted to all WRC data to estimate the slopes and intercepts of these relations. More than 99% of the WRCs' variation c ould be explained by this model, The suitability of the model as a PTF was tested with two additional data sets. It produced reliable predic tions within the study area as well as when transferred to other soils . Compared with another PTF, the new PTF improved the prediction of WR Cs by 60% within the study area. This improvement was mainly caused by accounting for skeletal soils and soils with low density and high org anic matter content. Due to its wide range of validity and its inclusi on of physically meaningful relations, this new PTF may be reliably ap plied to other soilscapes. Future efforts to improve the prediction of WRCs should concentrate on developing simple methods to measure the p ore-size distribution. (C) 1997 Elsevier Science B.V.