Soil and water conservation and ecological restoration in watershed and implications to energy implications and policies

This study aims to address the limitation of traditional soil and water conservation measures that rely on empirical judgement. By integrating Geographic Information System (GIS) technology with deep learning, the study constructs an intelligent decision support system for watershed soil and water conservation and ecological restoration. This study first develops a GIS-based automatic water environment monitoring system. It integrates multi-source geographic data to realise real-time monitoring and early warning of water quality. Further, it constructs a multi-scale soil and water environmental quality evaluation model. By using principal component analysis (PCA), one-way analysis of variance (ANOVA) and pollution index evaluation method, the study comprehensively evaluates the soil and water environmental quality and reveals the key driving factors at different spatial scales. In the field of deep learning, the study optimises the backbone model of Convolutional Neural Network (CNN). This study innovatively integrates GIS and deep learning technologies.