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Drought disasters are natural disasters with complex mechanisms and multiple characteristics. The quantitative evaluation of crop drought risk is central to managing drought risk and reducing loss. Therefore, assessing drought loss risk from the perspective of the drought formation process has scientific and prbactical value. In this study, we constructed crop drought loss risk curves to describe the development of drought risk loss. The intensity of drought events was expressed by the occurrence frequency, which was calculated based on long-term precipitation (1955–2012) and the copula function. The possible loss risk caused by drought was expressed as yield loss, which was simulated using the DSSAT-SROPGRO-soybean model. The spatiotemporal distribution characteristics of agricultural drought loss risk in the Huaibei Plain of Anhui Province, China, were represented by risk distribution maps. The main results showed that: 1) Drought events occurred more frequently in northern regions (Huaibei and Suzhou), but the intensity was lower. 2) Without irrigation, Fuyang was the region with the highest potential drought loss risk (more than 80% yield loss rate). 3) Irrigation had a significant effect on reducing drought risk loss, while efficiency was influenced by the spatiotemporal distribution of precipitation. This study has established and implemented a quantitative framework for regional drought risk assessment by creating drought risk curves and risk maps, which have significant value for improving the regional agricultural drought risk management level. [ABSTRACT FROM AUTHOR]

Event evolution analysis which provides an effective approach to capture the main context of a story from explosive increased news texts has become the critical basis for many real applications, such as crisis and emergency management and decision making. Especially, the development of societal risk events which may cause some possible harm to society or individuals has been heavily concerned by both the government and the public. In order to capture the evolution and trends of societal risk events, this paper presents an improved algorithm based on the method of information maps. It contains an event-level cluster generation algorithm and an evaluation algorithm. The main work includes: 1) Word embedding representation is adopted and event-level clusters are chosen as nodes of the events evolution chains which may comprehensively present the underlying structure of events. Meanwhile, clusters that consist of risk-labeled events enable to illustrate how events evolve along the time with transitions of risks. 2) One real-world case, the event of "Chinese Red Cross", is studied and a series of experiments are conducted. 3) An evaluation algorithm is proposed on the basis of indicators of map construction without massive human-annotated dataset. Our approach for event evolution analysis automatically generates a visual evolution of societal risk events, displaying a clear and structural picture of events development. [ABSTRACT FROM AUTHOR]

Wildlife-vehicle collisions are increasing across both Europe and North America, with considerable implications for animal populations themselves, for human safety and in terms of economic cost. Deer are generally the primary species involved in large mammals-vehicle collisions. Classical mitigation measures have however proven to have a limited efficacy. The development of tools aimed at predicting the real-time risk of hitting deer on a particular stretch of road can improve both human and wildlife safety, particularly if such tools can be adopted on a large scale. We analysed data on deer-vehicle collisions (DVCs) occurring on the major roads in England between 2008–2014, collected on behalf of Highways England agency. Using zero-inflated regression models, we analysed the relationships between DVCs and data on environmental, bioclimatic and traffic-related factors, on different spatial scales and for different seasons. Traffic flow, average precipitation, and a combination of suburban areas and broadleaved forest were generally associated with increased frequency of DVCs. We used the results of these models to draw seasonal risk maps, which could potentially be used to target appropriate physical mitigation or measures aimed at increasing driver awareness. [ABSTRACT FROM AUTHOR]

Context: Biological invasions are characterized by dynamic spatiotemporal distribution patterns. Yet landscape scale distribution patterns of invasive species are rarely leveraged to understand invasion in a comprehensive manner. Objectives: Characterize three key stages of invasion from the landscape scale distribution patterns for an invasive insect-Asian citrus psyllid ( Diaphorina citri), and investigate the potential spatial variability in establishment and impact risk. Methods: The study focuses on the recent invasion of D. citri in Southern California's urban landscape. We used a combination of spatiotemporal pattern analyses and species distribution models (SDMs) to characterize the introduction, establishment and impact of D. citri invasion. Results: Diaphorina citri detections in relation to major roadways revealed that initial detections are significantly closer to major roads than later detections, suggesting that transportation corridors serve as introduction pathways. SDMs of D. citri establishment and impact potential using presence-(pseudo)absence and abundance revealed percent impervious surface as the best landscape predictor. Inclusion of prior D. citri detections as a lagged spatiotemporal effect improved both model fit and performance suggesting that small-scale dispersal events do matter. Interestingly, interpolated risk maps based on the predicted occurrence and abundance highlighted substantial spatial variability in D. citri establishment and impact risk. Conclusion: Our study demonstrates how examining spatiotemporal patterns of an invasive species is useful in inferring key stages of the invasion, and how occurrence and abundance information can be leveraged to quantify variability in establishment and impact risk. The study thus provides a useful baseline in formulating effective landscape-level management actions. [ABSTRACT FROM AUTHOR]

In this paper we develop a GIS-based multicriteria flood risk assessment and mapping approach. This approach includes flood risks which are not measured in monetary terms; it shows the spatial distribution of multiple risks, and it is able to deal with uncertainties in criteria values and to show their influence on the overall flood risk assessment. Additionally, the approach can be used to show the spatial allocation of the flood effects if risk reduction measures are implemented. The approach is applied to a pilot study for the River Mulde in Saxony, Germany, heavily affected by the hazardous flood in 2002. Therefore, a GIS database of economic, social and environmental risk criteria was created. Two different multicriteria decision rules, a disjunctive and an additive weighting approach, are utilised for an overall flood risk assessment in the area. For implementation, a software tool (FloodCalc) was developed supporting both, the risk calculation of the single criteria as well as the multicriteria analysis. [ABSTRACT FROM AUTHOR]