Improvements on Flood Alleviation in Germany: Lessons Learned from the Elbe Flood in August 2002

The increase in damage due to natural disasters is directly related to the number of people who live and work in hazardous areas and continuously accumulate assets. Therefore, land use planning authorities have to manage effectively the establishment and development of settlements in flood-prone areas in order to avoid the further increase of vulnerable assets. Germany faced major destruction during the flood in August 2002 in the Elbe and Danube catchments, and many changes have been suggested in the existing German water and planning regulations. This article presents some findings of a “Lessons Learned” study that was carried out in the aftermath of the flood and discusses the following topics: 1) the establishment of comprehensive hazard maps and flood protection concepts, 2) the harmonization of regulations of flood protection at the federal level, 3) the communication of the flood hazard and awareness strategies, and 4) how damage potential can be minimized through measures of area precaution such as resettlement and risk-adapted land use. Although attempts towards a coordinated and harmonized creation of flood hazard maps and concepts have been made, there is still no uniform strategy at all planning levels and for all states (Lae nder) of the Federal Republic of Germany. The development and communication of possible mitigation strategies for “unthinkable extreme events” beyond the common safety level of a 100-year flood are needed. In order to establish a sustainable and integrated flood risk management, interdisciplinary and catchment-based approaches are needed.     

Wayfinding with a GPS-based mobile navigation system: A comparison with maps and direct experience

This study examined the effectiveness of a Global Positioning System (GPS)-based mobile navigation system in comparison to paper maps and direct experience of routes, by focusing on the user's wayfinding behavior and acquired spatial knowledge. Based on information received from one of these three media, participants walked six routes finding the way to goals. Results showed that GPS users traveled longer distances and made more stops during the walk than map users and direct-experience participants. Also, GPS users traveled more slowly, made larger direction errors, drew sketch maps with poorer topological accuracy, and rated wayfinding tasks as more difficult than direct-experience participants. Characteristics of navigation with these three learning media and possible reasons for the ineffectiveness of the GPS-based navigation system are discussed.     

基于SOM-SVM组合分类器的涂层防护性能研究

目的为避免EIS,EN技术可能出现的问题,建立一个准确、高效的评价模型,以探究现役军用有机涂层防护性能。方法利用电化学阻抗谱(EIS)、电化学噪声(EN)技术分析了两种军车有机涂层在循环暴露试验中的腐蚀行为,提取低频阻抗模值|Z|_(0.1 Hz)与涂层噪声电阻R_n两种电化学评价参数作为自组织神经网络(SOM)的输入训练样本,同时结合支持向量机(SVM)方法建立涂层防护性能组合分类器。结果将涂层失效过程自适应地分为涂层防护性能良好、防护性能下降、基本失效三个阶段。结论所建立的SOM-SVM组合分类器对于辅助分析涂层防护性能具有可行性。     

Community response to hazard information

The impact of flood hazard information on public acceptance of a selected flood mitigation strategy was assessed by an analysis of the content of newspaper reports of community reaction and letters to the editor. The impact of personal delivery of a flood hazard map on individual perception of risk and attitude to such information was assessed using personal interviews. The results indicated that media coverage of the flood hazard information reduced public criticism of the works. This result must be partially attributable to the dramatic style of media coverage and the fact that the media only emphasized the positive value of the works. The interview demonstrated that personal delivery of the information raised perception of risk, improved comprehension of flood risk, had no impact on acceptability of risk but discouraged some respondents from seeking such information in the future. Factors to explain the last negative change were identified to be the format of the map sheet and low salience of flood hazard. On the basis of all results, methods to improve community response to hazard information are provided.     

QUALITY OF HYDROMETEOROLOGICAL DATA IN COLD REGIONS1

ABSTRACT: Many users of hydrometeorological records are not aware of the number of inconsistencies and biases that occur in hydrometeorological records. Examples are presented illustrating how the exposures of sites for measurement of precipitation, wind, snow on the ground, and evaporation determine to a large extent how useful the records are for estimating areal conditions. For areas where precipitation in the form of snow produces a significant portion of the runoff, a smaller number of quality records may be more valuable for modeling than a much larger number of records of lower quality. Information is presented to show that the overall value of an operational hydrometeorological network is dependent upon how consistent and representative of average conditions the collected records are, especially for mountainous areas in cold regions.     

Probabilistic Flood Inundation Forecasting Using Rating Curve Libraries

One approach for performing uncertainty assessment in flood inundation modeling is to use an ensemble of models with different conceptualizations, parameters, and initial and boundary conditions that capture the factors contributing to uncertainty. However, the high computational expense of many hydraulic models renders their use impractical for ensemble forecasting. To address this challenge, we developed a rating curve library method for flood inundation forecasting. This method involves pre‐running a hydraulic model using multiple inflows and extracting rating curves, which prescribe a relation between streamflow and stage at various cross sections along a river reach. For a given streamflow, flood stage at each cross section is interpolated from the pre‐computed rating curve library to delineate flood inundation depths and extents at a lower computational cost. In this article, we describe the workflow for our rating curve library method and the Rating Curve based Automatic Flood Forecasting (RCAFF) software that automates this workflow. We also investigate the feasibility of using this method to transform ensemble streamflow forecasts into local, probabilistic flood inundation delineations for the Onion and Shoal Creeks in Austin, Texas. While our results show water surface elevations from RCAFF are comparable to those from the hydraulic models, the ensemble streamflow forecasts used as inputs to RCAFF are the largest source of uncertainty in predicting observed floods.     

Effects of publication bias on conservation planning

Conservation planners need reliable information on spatial patterns of biodiversity. However, existing data sets are skewed because some ecosystems, taxa, and locations are underrepresented. We determined how many articles have been published in recent decades on the biodiversity of different countries and their constituent provinces. We searched the Web of Science catalogues Science Citation Index (SCI) and Social Science Citation Index (SSCI) for biodiversity-related articles published from 1993 to 2016 that included country and province names. We combined data on research publication frequency with other provincial-scale factors hypothesized to affect the likelihood of research activity (i.e., economic development, human presence, infrastructure, and remoteness). Areas that appeared understudied relative to the biodiversity expected based on site climate likely have been inaccessible to researchers for reasons, notably armed conflict. Geographic publication bias is of most concern in the most remote areas of sub-Saharan Africa and South America. Our provincial-scale model may help compensate for publication biases in conservation planning by revealing the spatial extent of research needs and the low cost of redoing this analysis annually.     

Seasonal and spatial variability of Po,U and Pu levels in the river catchment area assessed by application of neural-network based classification

The present study deals with the application of self-organizing maps (SOM) in order to model, classify and interpret seasonal and spatial variability of ²¹⁰Po, ²³⁸U and ^239+240Pu levels in the Vistula river basin. The data set represents concentration values for 3 alpha emitters (²¹⁰Po, ²³⁸U and ^239+240Pu) measured in surface water samples collected at 19 different sampling locations (8 in major Vistula stream while 11 in right or left Vistula tributaries) during four seasons (winter, spring, summer and autumn) in the framework of a one-year quality monitoring study. The advantages of an SOM algorithm, its classification and visualization ability for environmental data sets, are stressed. The neural-network based classification made it possible to reveal specific patterns related to both seasonal and spatial variability. In the middle and upper part of Vistula catchment as well as in the right-shore tributaries, concentrations of ²¹⁰Po and ²³⁸U during summer and winter are the lowest. Concentrations of ²¹⁰Po and ²³⁸U increase significantly during spring and autumn in the Vistula river catchment, especially in the delta of Vistula river. High concentration of anthropogenic originated ^239+240Pu indicates “site-specific” character of pollution in two large left-shore tributaries located in the middle part of the Vistula drainage area. Efficient classification of sampling locations could lead to an optimization of river radiochemical sampling networks and to a better tracing of natural and anthropogenic changes along Vistula river stream.     

Application of fuzzy sets and cognitive maps to incorporate social science scenarios in integrated assessment modelsA case study of urbanization in Ujung Pandang, Indonesia

Decision–support systems in the field of integrated water management could benefit considerably from social science knowledge, as many environmental changes are human-induced. Unfortunately the adequate incorporation of qualitative social science concepts in a quantitative modeling framework is not straightforward. The applicability of fuzzy set theory and fuzzy cognitive maps for the integration of qualitative scenarios in a decision–support system was examined for the urbanization of the coastal city of Ujung Pandang, Indonesia. The results indicate that both techniques are useful tools for the design of integrated models based on a combination of concepts from the natural and social sciences. This revised version was published online in July 2006 with corrections to the Cover Date.     

Soil contamination of heavy metals in the Katedan Industrial Development Area, Hyderabad, India

Studies on quantitative soil contamination due to heavy metals were carried out in Katedan Industrial Development Area (KIDA), south of Hyderabad, Andhra Pradesh, India under the Indo-Norwegian Institutional Cooperation Programme. The study area falls under a semi-arid type of climate and consists of granites and pegmatite of igneous origin belonging to the Archaean age. There are about 300 industries dealing with dyeing, edible oil production, battery manufacturing, metal plating, chemicals, etc. Most of the industries discharge their untreated effluents either on open land or into ditches. Solid waste from industries is randomly dumped along roads and open grounds. Soil samples were collected throughout the industrial area and from downstream residential areas and were analysed by X-ray Fluorescence Spectrometer for fourteen trace metals and ten major oxides. The analytical data shows very high concentrations of lead, chromium, nickel, zinc, arsenic and cadmium through out the industrial area. The random dumping of hazardous waste in the industrial area could be the main cause of the soil contamination spreading by rainwater and wind. In the residential areas the local dumping is expected to be the main source as it is difficult to foresee that rain and wind can transport the contaminants from the industrial area. If emission to air by the smokestacks is significant, this may contribute to considerable spreading of contaminants like As, Cd and Pb throughout the area. A comparison of the results with the Canadian Soil Quality Guidelines (SQGL) show that most of the industrial area is heavily contaminated by As, Pb and Zn and local areas by Cr, Cu and Ni. The residential area is also contaminated by As and some small areas by Cr, Cu, Pb and Zn. The Cd contamination is detected over large area but it is not exceeding the SQGL value. Natural background values of As and Cr exceed the SQGL values and contribute significantly to the contamination in the residential area. However, the availability is considerably less than anthropogenic contaminants and must therefore be assessed differently. The pre- and post-monsoon sampling over two hydrological cycles in 2002 and 2003 indicate that the As, Cd and Pb contaminants are more mobile and may expect to reach the groundwater. The other contaminants seem to be much more stable. The contamination is especially serious in the industrial area as it is housing a large permanent residing population. The study not only aims at determining the natural background levels of trace elements as a guide for future pollution monitoring but also focuses on the pollution vulnerability of the watershed. A plan of action for remediation is recommended.