智利大西洋鲑养殖业的成功经验及启示

智利作为海水养殖大国,海水养殖总量一直位于世界前列,其中大西洋鲑养殖业是智利渔业的支柱产业,其成功发展离不开政府的支持、健全的法律体系保障、成熟的产业体系和先进的养殖技术等。文章主要采用描述性统计分析和对比分析的方法,在总结智利大西洋鲑养殖经验的基础上,针对我国海水养殖业存在的问题提出提高苗种质量、完善法律制度保障、提高组织化程度以及重视技术创新等一系列建议,以期促进我国海水养殖业的发展。     

Spatially distributed rainfall information and its potential for regional landslide early warning systems

Hydrological extreme events pose an imminent risk to society and economics. In this paper, various aspects of hydrological hazards in Russia are analysed at different scales of risk assessment. It is shown that the number of hydrological and meteorological hazards in Russia has been growing every year. The frequency of economic losses associated with extreme low flow in this century has increased by factor five compared to the last decade of the previous century. With regard to floods, an interesting spatial patter can be observed. On the one hand, the number of floods in the Asian part of the country has increased, whereas on the other hand, the number and intensity of floods in estuarine areas in the European part of Russia have significantly reduced since the middle of the twentieth century, especially in the 2000s. This decrease can be attributed to runoff flooding in the mouths of regulated rivers, with an effective system of flood and ice jam protection. The analysis shows that there is an 8–12-year periodicity in the number of flood occurrences and that flood surges have intensified over the last 110 years, especially on the European territory of Russia. An integrated index that accounts for flood hazards and socio-economic vulnerability was calculated for each region of Russia. A classification of flood risk was also developed, taking into account more than 20 hydrological and social–economic characteristics. Based on these characteristics, hazard and vulnerability maps for entire Russia were generated which can be used for water management and the development of future water resources plans.     

Spatially distributed rainfall information and its potential for regional landslide early warning systems

Crucial to most landslide early warning system (EWS) is the precise prediction of rainfall in space and time. Researchers are aware of the importance of the spatial variability of rainfall in landslide studies. Commonly, however, it is neglected by implementing simplified approaches (e.g. representative rain gauges for an entire area). With spatially differentiated rainfall information, real-time comparison with rainfall thresholds or the implementation in process-based approaches might form the basis for improved landslide warnings. This study suggests an automated workflow from the hourly, web-based collection of rain gauge data to the generation of spatially differentiated rainfall predictions based on deterministic and geostatistical methods. With kriging usually being a labour-intensive, manual task, a simplified variogram modelling routine was applied for the automated processing of up-to-date point information data. Validation showed quite satisfactory results, yet it also revealed the drawbacks that are associated with univariate geostatistical interpolation techniques which solely rely on rain gauges (e.g. smoothing of data, difficulties in resolving small-scale, highly intermittent rainfall). In the perspective, the potential use of citizen scientific data is highlighted for the improvement of studies on landslide EWS.