The application of biochar as an environmentally friendly additive for agricultural soils has recently gained significant attention. However, the influence of biochar addition on unsaturated hydraulic behavior at high suction ranges (i.e., exceeding 100 kPa) remains largely understudied. This study investigates the impact of biochar addition on the unsaturated hydraulic properties of biochar amended soil (BAS). The effects of biochar content, particle size, and soil compaction on the unsaturated hydraulic properties of BAS were also considered. Peanut shell biochar was utilized in this investigation and was amended into a compacted silty sand with distinct particle size groups. Soil water retention curves and unsaturated permeability were measured through a series of evaporation tests. Results demonstrate that the impact of soil compaction on the unsaturated hydraulic properties of BAS diminishes at high suction range, regardless of biochar particle size and content. A high degree of compaction reduces the saturated permeability of BAS by minimising soil macropores. On the other hand, incorporating high biochar contents with fine particles into the soil enhances the reduction of unsaturated permeability and the improvement of water holding capacity, thereby making biochar an effective application in soil for sustainability of the agroecological environment.

Image edge detection in virtual reality scenes is one of the most important technologies in the field of image processing and computer vision. It occupies an important position in the image processing system and is a key factor that affects the performance of the entire system. The quality of the algorithm directly affects the performance of the computer’s visual system. This paper briefly describes the basic theoretical methods of image edge detection. The basic theory and processing flow of image edge detection are analyzed, and several commonly used edge detection preprocessing methods and their basic principles are elaborated in detail. The existing traditional edge detection methods are briefly introduced, and the traditional edge detection methods are compared. This paper studies the adaptive multi-scale edge detection method based on Canny algorithm, and through theoretical analysis, compares the advantages and disadvantages of various algorithms in image edge detection. In the process of acquiring image edges, the local maximum value of the modulus is calculated along the gradient direction and the threshold is adaptively selected based on the image blocking principle. Comparing with the traditional modulus maximum edge detection method, this algorithm overcomes the contradiction that can suppress the interference of noise and obtain better edge detection effect to a certain extent. Experiments show that the method in this paper not only suppresses the interference of impulsive noise to the image edge detection, but also greatly reduces the possibility of false edges, and obtains a satisfactory accurate binary edge image.