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Water 2016, 8(3), 96; doi:10.3390/w8030096

Predicting Soil Infiltration and Horizon Thickness for a Large-Scale Water Balance Model in an Arid Environment

1
Faculty of Agriculture, Tottori University, 4-101 Koyama-Minami, Tottori 680-8553, Japan
2
Arid Land Research Center, Tottori University, 1390 Hamasaka, Tottori 680-0001, Japan
3
Department of Materials and Life Science, Seikei University, 3-3-1, Kichijoji-kitamachi, Musashino, Tokyo 180-8633, Japan
4
School of Veterinary and Life Sciences, Murdoch University, 90 South Street, Murdoch 6150 WA, Australia
5
University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
Professor Emeritus.
*
Author to whom correspondence should be addressed.
Academic Editors: Magaly Koch and Thomas M. Missimer
Received: 16 January 2016 / Revised: 1 March 2016 / Accepted: 3 March 2016 / Published: 10 March 2016
(This article belongs to the Special Issue Water Resources Assessment and Management in Drylands)
View Full-Text   |   Download PDF [2983 KB, uploaded 10 March 2016]   |  

Abstract

Prediction of soil characteristics over large areas is desirable for environmental modeling. In arid environments, soil characteristics often show strong ecological connectivity with natural vegetation, specifically biomass and/or canopy cover, suggesting that the soil characteristics may be predicted from vegetation data. The objective of this study was to predict soil infiltration characteristics and horizon (soil layer) thickness using vegetation data for a large-scale water balance model in an arid region. Double-ring infiltrometer tests (at 23 sites), horizon thickness measurements (58 sites) and vegetation surveys (35 sites) were conducted in a 30 km × 50 km area in Western Australia during 1999 to 2003. The relationships between soil parameters and vegetation data were evaluated quantitatively by simple linear regression. The parameters for initial-term infiltration had strong and positive correlations with biomass and canopy coverage (R2 = 0.64 − 0.81). The horizon thickness also had strong positive correlations with vegetation properties (R2 = 0.53 − 0.67). These results suggest that the soil infiltration parameters and horizon thickness can be spatially predicted by properties of vegetation using their linear regression based equations and vegetation maps. The background and reasons of the strong ecological connectivity between soil and vegetation in this region were also considered. View Full-Text
Keywords: soil permeability; land cover; Acacia aneura; Eucalyptus camaldulensis; remote sensing; hydraulic conductivity; spatial variability; arid land soil permeability; land cover; Acacia aneura; Eucalyptus camaldulensis; remote sensing; hydraulic conductivity; spatial variability; arid land
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Saito, T.; Yasuda, H.; Suganuma, H.; Inosako, K.; Abe, Y.; Kojima, T. Predicting Soil Infiltration and Horizon Thickness for a Large-Scale Water Balance Model in an Arid Environment. Water 2016, 8, 96.

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