The standardized precipitation index is one of the most widely used indices for characterizing and monitoring drought in various regions. SPI's applicability has regional and time-scale constraints when it observes in several homogeneous climatic regions with similar characteristics. It also does not provide sufficient knowledge about precipitation deficits and the spatiotemporal evolution of drought. Therefore, a new method, the regional spatially agglomerative continuous drought probability monitoring system, is proposed to obtain spatiotemporal information and monitor drought characteristics more expeditiously. The proposed (...) framework uses spatially agglomerative precipitation and copulas’ functions to continuously monitor the drought probability in the homogenous region. The RSACDPMS is validated in the region of the Northern area of Pakistan. The outcomes of the current study provide a better quantitative way to obtain appropriate information about precipitation deficits and the spatiotemporal evolution of drought. (shrink)

Nowadays, higher education worldwide is affected by the COVID-19 pandemic. It has affected students’ attendance in the universities and causes universities to close down in more than 190 countries. On the other hand, novice engineers studied only a few lectures related to highway engineering. Their lectures have included very little knowledge about asphalt pavement construction as highway engineering consists of many areas that are not studied in detail during their studying years subject to their traditional education. Due to all mentioned, (...) a new drive to promote online learning paves the way to evaluate our future approach to curriculum development and delivery of educational materials for engineering courses. However, experts can offer solutions to these problems using their past experience. Hence, a system that allows experts to share their experience with other engineers after completing a project is needed. Nevertheless, the web-based expert system for maintaining flexible pavement problems in tropical regions designed in this study is a novel concept. Prior to developing this system, the need for such a system was determined through literature review and validated through a questionnaire survey. Experts were interviewed, and a questionnaire survey was conducted to construct the knowledge base of the system. Knowledge was presented as rules and coded in software through PHP programming. Web pages that support the user interface were designed using a framework that consists of CSS, HTML, and J-Query. Furthermore, the system was tested by an array of users engaged in highway engineering, namely, experts, teaching experts, novice engineers, and students. The mean values of the overall system evaluation performed by 20 users using a five-point Likert scale were 4, 4.5, 3.75, 4.25, 5, 4, and 3.5. Expert and user satisfaction prove the effectiveness of the proposed system. (shrink)

Flooding is one of the most damaging natural hazards globally. During the past three years, floods have claimed hundreds of lives and millions of dollars of damage in Iran. In this study, we detected flood locations and mapped areas susceptible to floods using time series satellite data analysis as well as a new model of bagging ensemble-based alternating decision trees, namely, bag-ADTree. We used Sentinel-1 data for flood detection and time series analysis. We employed twelve conditioning parameters of elevation, normalized (...) difference’s vegetation index, slope, topographic wetness index, aspect, curvature, stream power index, lithology, drainage density, proximities to river, soil type, and rainfall for mapping areas susceptible to floods. ADTree and bag-ADTree models were used for flood susceptibility mapping. We used software of Sentinel application platform, Waikato Environment for Knowledge Analysis, ArcGIS, and Statistical Package for the Social Sciences for preprocessing, processing, and postprocessing of the data. We extracted 199 locations as flooded areas, which were tested using a global positioning system to ensure that flooded areas were detected correctly. Root mean square error, accuracy, and the area under the ROC curve were used to validate the models. Findings showed that root mean square error was 0.31 and 0.3 for ADTree and bag-ADTree techniques, respectively. More findings illustrated that accuracy was obtained as 86.61 for bag-ADTree model, while it was 85.44 for ADTree method. Based on AUC, success and prediction rates were 0.736 and 0.786 for bag-ADTree algorithm, in order, while these proportions were 0.714 and 0.784 for ADTree. This study can be a good source of information for crisis management in the study area. (shrink)