Mapping the Soil Texture in the Heihe River Basin Based on Fuzzy Logic and Data Fusion

Ling Lu,Youhua Ran,Chao Liu,Xin Li

doi:10.3390/su9071246

Abstract

Mapping soil texture in a river basin is critically important for eco-hydrological studies and water resource management at the watershed scale. However, due to the scarcity of in situ observation of soil texture, it is very difficult to map the soil texture in high resolution using traditional methods. Here, we used an integrated method based on fuzzy logic theory and data fusion to map the soil texture in the Heihe River basin in an arid region of Northwest China, by combining in situ soil texture measurement data, environmental factors, a previous soil texture map, and other thematic maps. Considering the different landscape characteristics over the whole Heihe River basin, different mapping schemes have been used to extract the soil texture in the upstream, middle, and downstream areas of the Heihe River basin, respectively. The validation results indicate that the soil texture map achieved an accuracy of 69% for test data from the midstream area of the Heihe River basin, which represents a much higher accuracy than that of another existing soil map in the Heihe River basin. In addition, compared with the time-consuming and expensive traditional soil mapping method, this new method could ensure greater efficiency and a better representation of the explicitly spatial distribution of soil texture and can, therefore, satisfy the requirements of regional modeling.

Highlights

Soil texture is one of the most basic physical properties of soils
The soil of the artificial oasis in the midstream area of the Heihe River basin (HRB) is dominated by loam and sandy loam, and other areas are dominated by silt loam and loamy sand
This indicates that by combining the large number of soil profile data with environmental factors, we can obtain relatively good soil texture prediction results by applying the method based on the combination of a decision tree and fuzzy logic

Summary

Introduction

Different soil textures that vary in their composition and contents of specific particles have very different soil hydraulic characteristics, such as water retention and hydraulic conductivity, and soil thermal parameters, such as thermal conductivity and heat capacity [1]. The soil texture type, which has an important influence on the simulation of water cycle and surface fluxes, is a critical parameter in land surface process models, hydrological models, and land surface process-coupled atmospheric models. These models always require soil properties as inputs according to the soil texture classification scheme of the United States Department of Agriculture (USDA). The exploration of digital soil mapping methods that can directly generate accurate Chinese soil texture maps using existing soil environmental data and soil survey data would be of great value and necessity

Methods

Results

Conclusion