Solum depth spatial prediction comparing conventional with knowledge-based digital soil mapping approaches

Michele Duarte De Menezes,Phillip Ray Owens,Carlos Rogério De Mello,Sérgio Henrique Godinho Silva,Nilton Curi

doi:10.1590/0103-9016-2013-0416

Michele Duarte De Menezes, Phillip Ray Owens + Show 3 more

Open Access

https://doi.org/10.1590/0103-9016-2013-0416

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Abstract

Solum depth and its spatial distribution play an important role in different types of environmental studies. Several approaches have been used for fitting quantitative relationships between soil properties and their environment in order to predict them spatially. This work aimed to present the steps required for solum depth spatial prediction from knowledge-based digital soil mapping, comparing the prediction to the conventional soil mapping approach through field validation, in a watershed located at Mantiqueira Range region, in the state of Minas Gerais, Brazil. Conventional soil mapping had aerial photo-interpretation as a basis. The knowledge-based digital soil mapping applied fuzzy logic and similarity vectors in an expert system. The knowledge-based digital soil mapping approach showed the advantages over the conventional soil mapping approach by applying the field expert-knowledge in order to enhance the quality of final results, predicting solum depth with suited accuracy in a continuous way, making the soil-landscape relationship explicit.

Highlights

Solum depth (A+B horizon) has been applied in distributed hydro-ecological models to simulate watershed processes as net photosynthesis and stream flow (Quinn et al, 2005; Zhu and McKay, 2001), affecting the soil storage capacity (Follain et al, 2007) or the soil drainage condition (Odeh et al, 1995)
This work aimed to present the steps required for solum depth spatial prediction from knowledge-based digital soil mapping, comparing the prediction to the conventional soil mapping approach through field validation, in a watershed located at Mantiqueira Range region, in the state of Minas Gerais, Brazil
The knowledge-based digital soil mapping approach showed the advantages over the conventional soil mapping approach by applying the field expert-knowledge in order to enhance the quality of final results, predicting solum depth with suited accuracy in a continuous way, making the soillandscape relationship explicit

Summary

Introduction

Solum depth (A+B horizon) has been applied in distributed hydro-ecological models to simulate watershed processes as net photosynthesis and stream flow (Quinn et al, 2005; Zhu and McKay, 2001), affecting the soil storage capacity (Follain et al, 2007) or the soil drainage condition (Odeh et al, 1995). Possessing the maps that represent soil forming factors (environmental variables), the knowledge of pedologists can be incorporated into spatial prediction, whereby the qualitative soil-landscape model is converted into quantitative predictions using relationships between soils and, more frequently, terrain attributes, such as slope, topographic wetness index, and profile curvature. It overcomes a limitation of the conventional soil mapping approach, as raised by Hudson (1992), which fails to highlight the soil surveyor mental model. Because this approach requires an understanding from a soil scientist’s perspective of the repeating soil patterns on the landscape, as does the conventional mapping approach, it is considered to be a knowledge-driven digital soil mapping approach and it has been regarded as efficient and economical (Hudson, 1992; MacMillan et al, 2007)

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