%0 Journal Article
%T Using Reflectance Spectroscopy and Artificial Neural Network to Assess Water Infiltration Rate into the Soil Profile
%A Naftali Goldshleger
%A Alexandra Chudnovsky
%A Eyal Ben-Dor
%J Applied and Environmental Soil Science
%D 2012
%I Hindawi Publishing Corporation
%R 10.1155/2012/439567
%X We explored the effect of raindrop energy on both water infiltration into soil and the soil's NIR-SWIR spectral reflectance (1200¨C2400£¿nm). Seven soils with different physical and morphological properties from Israel and the US were subjected to an artificial rainstorm. The spectral properties of the crust formed on the soil surface were analyzed using an artificial neural network (ANN). Results were compared to a study with the same population in which partial least-squares (PLS) regression was applied. It was concluded that both models (PLS regression and ANN) are generic as they are based on properties that correlate with the physical crust, such as clay content, water content and organic matter. Nonetheless, better results for the connection between infiltration rate and spectral properties were achieved with the non-linear ANN technique in terms of statistical values (RMSE of 17.3% for PLS regression and 10% for ANN). Furthermore, although both models were run at the selected wavelengths and their accuracy was assessed with an independent external group of samples, no pre-processing procedure was applied to the reflectance data when using ANN. As the relationship between infiltration rate and soil reflectance is not linear, ANN methods have the advantage for examining this relationship when many soils are being analyzed. 1. Introduction 1.1. Physical Crust and Infiltration Rate The main cause of runoff from rain and overhead irrigation is the generation of a structural soil crust [1, 2]. Crust formation results from a combination of the kinetic energy impact of raindrops and the level of stability of the soil aggregates [1, 2]. The structural crust is generated within minutes and significantly reduces soil infiltration rate (IR). Assessment of this IR is vital for sustainable land management, especially in semiarid and arid regions where harsh climatic conditions cause soil degradation and damage to agricultural areas. Thus, monitoring of soil crust conditions is essential for the proper management of soils, from both an agricultural and land-degradation perspective. 1.2. Reflectance Spectroscopy Previous research has shown that reflectance spectroscopy can provide a valuable means of assessing the condition of the soil crust and estimating related problems. The spectral reflectance provides information about the chemical and physical conditions of bulk matter (in the laboratory) and of the surface (in the field), which can then be used to assess the condition of the soil crust and estimate the related problem (e.g., infiltration rate, runoff
%U http://www.hindawi.com/journals/aess/2012/439567/