The main aim of this study was to compare the performances of the hybrid approaches of traditional bivariate weights of evidence (WoE) with multivariate logistic regression (WoE-LR) and machine learning-based random forest (WoE-RF) for landslide susceptibility mapping. The performance of the three landslide models was validated with receiver operating characteristic (ROC) curves and area under the curve (AUC). The results showed that the areas under the curve obtained using the WoE, WoE-LR, and WoE-RF methods were 0.720, 0.773, and 0.802 for the training dataset, and were 0.695, 0.763, and 0.782 for the validation dataset, respectively. The results demonstrate the superiority of hybrid models and that the resultant maps would be useful for land use planning in landslide-prone areas.

Purpose The purpose of this paper is to facilitate understanding of how to mitigate the privacy concerns of users who have experienced privacy invasions. Design/methodology/approach Drawing on the communication privacy management theory, the authors developed a model suggesting that privacy concerns form through a cognitive process involving threat-coping appraisals, institutional privacy assurances and privacy experiences. The model was tested using data from an empirical survey with 913 randomly selected social media users. Findings Privacy concerns are jointly determined by perceived privacy risks and privacy self-efficacy. The perceived effectiveness of institutional privacy assurances in terms of established privacy policies and privacy protection technology influences the perceptions of privacy risks and privacy self-efficacy. More specifically, privacy invasion experiences are negatively associated with the perceived effectiveness of institutional privacy assurances. Research limitations/implications Privacy concerns are conceptualized as general concerns that reflect an individual’s worry about the possible loss of private information. The specific types of private information were not differentiated. Originality/value This paper is among the first to clarify the specific mechanisms through which privacy invasion experiences influence privacy concerns. Privacy concerns have long been viewed as resulting from individual actions. The study contributes to literature by linking privacy concerns with institutional privacy practice.

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Soil water is a link between different water bodies. The study of soil water evaporation is of great significance to understand the regional hydrological process, promote environmental remediation in arid areas, and rationalize ecological water use. On the basis of soil water δ2H and δ18O data from April to October 2017 in the Xiying River basin in the upper reaches of the Qilian mountains, the lc-excess and Craig-Gordon model were applied to reflect the evaporating fractionation of soil water. The results show that the change in evaporation loss drives the enrichment of soil water isotopes. The signal of evaporative fractionation of soil water isotopes at different elevations has spatiotemporal heterogeneity. From the perspective of time dynamics, the evaporation loss of the whole region during the observation period was affected by temperature before July, while after July, it was controlled jointly by temperature and humidity, evaporation was weakened. Soil salt content and vegetation played an important role in evaporation loss. In terms of spatial dynamics, the soil moisture evaporation at the Xiying (2097 m) and Huajian (2390 m) stations in the foothills area is larger than that at the Nichan station (2721 m) on the hillside and Lenglong station (3637 m) on the mountain top. The surface soil water evaporation is strong, and the evaporation becomes weak with the increase of depth. The research has guiding significance for the restoration and protection of vegetation in arid areas and the formulation of reasonable animal husbandry policies.