Application of artificial intelligence in three aspects of landslide risk assessment: A comprehensive review

Landslides are one of the geological disasters with wide distribution,high impact and serious damage around the world.Landslide risk assessment can help us know the risk of landslides occurring,which is an effective way to prevent landslide disasters in advance.In recent decades,artificial intelligence(AI)has developed rapidly and has been used in a wide range of applications,especially for natural hazards.Based on the published literatures,this paper presents a detailed review of AI applications in landslide risk assessment.Three key areas where the application of AI is prominent are identified,including landslide detection,landslide susceptibility assessment,and prediction of landslide displacement.Machine learning(ML)containing deep learning(DL)has emerged as the primary technology which has been considered successfully due to its ability to quantify complex nonlinear relationships of soil structures and landslide predisposing factors.Among the algorithms,convolutional neural networks(CNNs)and recurrent neural networks(RNNs)are two models that are most widely used with satisfactory results in landslide risk assessment.The generalization ability,sampling training strategies,and hyperparameters optimization of these models are crucial and should be carefully considered.The challenges and opportunities of AI applications are also fully discussed to provide suggestions for future research in landslide risk assessment.

Evolution of drought and flood events on the Qinghai-Tibet Plateau and key issues for response

The Qinghai-Tibet Plateau is a climate-sensitive region.The characteristics of drought and flood events in this region are significantly different as compared to other areas in the country,which could potentially induce a series of water security,ecological and environmental problems.It is urgent that innovative theories and methods for estimation of drought and flood disasters as well as their adaptive regulations are required.Based on extensive literature review,this paper identifies new situations of the evolution of drought and flood events on the Qinghai-Tibet Plateau,and analyzes the research progress in terms of monitoring and simulation,forecasting and early warning,risk prevention and emergency response.The study found that there were problems such as insufficient integration of multi-source data,low accuracy of forecasting and early warning,unclear driving mechanisms of drought and flood disaster chains,and lack of targeted risk prevention and regulation measures.On this basis,future research priorities are proposed,and the possible research and development paths are elaborated,including the evolution law of drought and flood on the Qinghai-Tibet Plateau,the coincidence characteristics of drought and flood from the perspective of a water resources system,prediction and early warning of drought and flood coupled with numerical simulation and knowledge mining,identification of risk blocking points of drought and flood disaster chain and the adaptive regulations.Hopefully,the paper will provide technical support for preventing flood and drought disasters,water resources protection,ecological restoration and climate change adaptation on the Qinghai-Tibet Plateau.