Disaster risk Reduction (DRR) is well known and practiced in many nations. Community Based Disaster Risk Reduction (CBDRR) is a sub-component of DRR which is slowly being practiced in most at risk communities. However, there are still gaps regarding the principles and guidelines that guide the process of CBDRR. This study stipulates numerous guiding principles that govern the processes of CBDRR activities. These are: traditional knowledge, understanding of community members, capacity of community members, community participation, political will and training of community members. Furthermore the study used the guidelines to evaluate which activities by the Oshakati community members relate to the principles and guidelines of CBDRR as a way of reducing the risk of recurring floods in the community. Through focus group discussions and semi-structured individual interviews, it was found that the community members in Oshakati adhere to most principles of CBDRR such as the use of traditional knowledge, community members having the capacity to work together to solve common societal problems and to understand community structures. However, guidelines such as community participation, political will and training of community members were not adhered to due to various challenges such as the lack of institutional capacity and limited resources. The findings further stipulate that those guidelines were not adhered to due to inadequate knowledge on DRR and lack of support from the local government due to limited availability of resources. The study recommends that in order for the local government to reduce the risk of recurring floods in the community, the local government need to build capacity of its personnel working directly with DRR aspects. These can be achieved through a shift in the approach of responding to flooding to being proactive, creating awareness regarding the hazard and ensuring genuine participation of community members into local government CBDRR activities. / M Development and Management, North-West University, Potchefstroom Campus, 2015

Disaster risk Reduction (DRR) is well known and practiced in many nations. Community Based Disaster Risk Reduction (CBDRR) is a sub-component of DRR which is slowly being practiced in most at risk communities. However, there are still gaps regarding the principles and guidelines that guide the process of CBDRR. This study stipulates numerous guiding principles that govern the processes of CBDRR activities. These are: traditional knowledge, understanding of community members, capacity of community members, community participation, political will and training of community members. Furthermore the study used the guidelines to evaluate which activities by the Oshakati community members relate to the principles and guidelines of CBDRR as a way of reducing the risk of recurring floods in the community. Through focus group discussions and semi-structured individual interviews, it was found that the community members in Oshakati adhere to most principles of CBDRR such as the use of traditional knowledge, community members having the capacity to work together to solve common societal problems and to understand community structures. However, guidelines such as community participation, political will and training of community members were not adhered to due to various challenges such as the lack of institutional capacity and limited resources. The findings further stipulate that those guidelines were not adhered to due to inadequate knowledge on DRR and lack of support from the local government due to limited availability of resources. The study recommends that in order for the local government to reduce the risk of recurring floods in the community, the local government need to build capacity of its personnel working directly with DRR aspects. These can be achieved through a shift in the approach of responding to flooding to being proactive, creating awareness regarding the hazard and ensuring genuine participation of community members into local government CBDRR activities. / M Development and Management, North-West University, Potchefstroom Campus, 2015

<p>The main objective of this study is to understand and asses flood risk perception among people living in Msimbazi Valley in Das es Salaam, Tanzania. Many of the people I have interviewed are experiencing flooding every year but it is rarely considered disastrous. Looked at individually they may not be disasters but cumulatively they may be. The rapid urbanisation, in this part of the world, forces people to live on hazardous but central land because of the livelihood opportunities available there. The government and the local communities are well aware of the risk of floods in the area and are considered as a serious threat to the families. People are still living in these areas because they find the benefits big enough to make up the risks.</p>

Traditional flood-frequency techniques are based on the assumption that the observed flood record represents a sample that has been drawn from a single climatically homogeneous population of floods. A hydroclimatic approach was used to evaluate this assumption by identifying the circulation patterns and atmospheric flood-generating mechanisms which control the temporal and spatial variability of flooding. Mean monthly discharges and instantaneous peak flows of the partial duration series were analyzed for thirty gaging stations in the climatically sensitive, semiarid, Gila River basin for the period 1950 to 1980. Correlation fields and composite maps were constructed to define the relationship between 700 mb height circulation anomalies and mean monthly streamflow. Individual flood events were linked to climate by analyzing daily synoptic weather maps and classifying each flood event into one of eight hydroclimatic categories on the basis of the atmospheric mechanisms which generated each flow. The analysis demonstrated that floods and anomalously high streamflow in the Gila River basin originate from a variety of atmospheric processes which vary spatially, seasonally, and from year-to-year. The mechanisms most important for generating floods included winter fronts, cutoff lows, tropical storms, snowmelt, and widespread and localized summer monsoon-related circulation patterns. When flood discharges were grouped into hydroclimatically homogeneous categories, histogram plots of their frequency distributions exhibited means and variances that differed from those of the overall frequency distribution of the entire flood series. The means of the discharges generated by frontal precipitation and tropical storms tended to plot above the mean of the overall series, while the means of floods generated by snowmelt tended to plot below the overall mean. Flood estimates computed from a series containing mixed distributions were not the same as flood estimates computed from climatically homogeneous subsets of the same series. These results have implications for traditional flood-frequency analysis and other stochastic methods of analyzing hydrologic time series. The hydroclimatically-defined subgroups in the flood series of the Gila River basin indicate that nonhomogeneity and nonstationarity can be imparted to a hydrologic time series by differing atmospheric mechanisms alone.

The aim of this research project was to estimate parameters for the distribution of annual maximum flood levels for the Zambezi River at Katima Mulilo. The estimation of parameters was done by using the maximum likelihood method. The study aimed to explore data of the Zambezi's annual maximum flood heights at Katima Mulilo by means of fitting the Gumbel, Weibull and the generalized extreme value distributions and evaluated their goodness of fit.

The objective of this thesis was to design a canister for the disposal of spent nuclear fuel and other high-level waste in deep borehole repositories using currently available and proven oil, gas, and geothermal drilling technology. The canister is suitable for disposal of various waste forms, such as fuel assemblies and vitrified waste. The design addresses real and perceived hazards of transporting and placing high-level waste, in the form of spent reactor fuel, into a deep igneous rock environment with particular emphasis on thermal performance. The proposed boreholes are 3 to 5 km deep, in igneous rock such as granite. The rock must be in a geologically stable area from a volcanic and tectonic standpoint, and it should have low permeability, as shown in recent data taken from a Russian deep borehole. Although deep granite should remain dry, water in flooded boreholes is expected to be reducing, but potentially corrosive to steel. However, the granite and plug are the containment barrier, not the canister itself. The canisters use standard oil drilling casings. The inner diameter is 315.32mm in order to accommodate a PWR assembly with a width of 214mm. At five meters tall, each canister holds one PWR assembly. The canister thickness is 12.19mm, with an outer diameter of 339.7mm. A liner can extend to the bottom of the emplacement zone to aid in retrievability. The liner has an outer diameter of 406.4mm and a thickness of 9.52mm. The standard drill bit used with a liner of this size has an outer diameter of 444.5mm. / Contract number: N62271-97-6-0026. / US Navy (USN) author.

Dans les régions méditerranéennes françaises, des épisodes pluvieux diluviens se produisent régulièrement et provoquent des crues très rapides et volumineuses que l'on appelle crues éclair. Elles font fréquemment de nombreuses victimes et peuvent, sur un seul évènement, coûter plus d'un milliard d'euros. Face à cette problématique, les pouvoirs publics mettent en place des parades parmi lesquelles la prévision hydrologique tient une place essentielle.C'est dans ce contexte que le projet BVNE (Bassin Versant Numérique Expérimental) a été initié par le SCHAPI (Service Central d'Hydrométéorologie et d'Appui à la Prévision des Inondations) dans le but d'améliorer la prévision des crues rapides. Ces travaux s'inscrivent dans le cadre de ce projet et ont trois objectifs principaux : réaliser des prévisions sur des bassins capables de ces réactions qu'ils soient correctement jaugés, mal jaugés ou non jaugés.La zone d'étude choisie, le massif des Cévennes, concentre la majorité de ces épisodes hydrométéorologiques intenses en France. Ce mémoire la présente en détails, mettant en avant ses caractéristiques les plus influentes sur l'hydrologie de surface. Au regard de la complexité de la relation entre pluie et débit dans les bassins concernés et de la difficulté éprouvée par les modèles à base physique à fournir des informations précises en mode prédictif sans prévision de pluie, l'utilisation de l'apprentissage statistique par réseaux de neurones s'est imposée dans la recherche d'une solution opérationnelle.C'est ainsi que des modèles à réseaux de neurones ont été synthétisés et appliqués à un bassin de la zone cévenole, dans des contextes bien et mal jaugés. Les bons résultats obtenus ont été le point de départ de la généralisation à 15 bassins de la zone d'étude. A cette fin, une méthode de généralisation est développée à partir du modèle élaboré sur le bassin jaugé et de corrections estimées en fonction des caractéristiques physiques des bassins. Les résultats de l'application de cette méthode sont de bonne qualité et ouvrent la porte à de nombreux axes de recherche pour l'avenir, tout en démontrant encore que l'utilisation de l'apprentissage statistique pour l'hydrologie peut constituer une solution pertinente. / In the French Mediterranean regions, heavy rainfall episodes regularly occur and induce very rapid and voluminous floods called flash floods. They frequently cause fatalities and can cost more than one billion euros during only one event. In order to cope with this issue, the public authorities' implemented countermeasures in which hydrological forecasting plays an essential role.In this contexte, the French Flood Forecasting Service (called SCHAPI for Service Central d'Hydrométéorologie et d'Appui à la Prévision des Inondations) initiated the BVNE (Digital Experimental Basin, for Bassin Versant Numérique Expérimental) project in order to enhance flash flood forecasts. The present work is a part of this project and aim at three main purposes: providing flash flood forecasts on well-gauged basins, poorly gauged basins and ungauged basins.The study area chosen, the Cévennes range, concentrates the major part of these intense hydrometeorological events in France. This dissertation presents it precisely, highlighting its most hydrological-influent characteristics.With regard to the complexity of the rainfall-discharge relation in the focused basins and the difficulty experienced by the physically based models to provide precise information in forecast mode without rainfall forecasts, the use of neural networks statistical learning imposed itself in the research of operational solutions.Thus, the neural networks models were designed and applied to a basin of the Cévennes range, in the well-gauged and poorly gauged contexts. The good results obtained have been the start point of a generalization to 15 basins of the study area.For this purpose, a generalization method was developed from the model created on the gauged basin and from corrections estimated as a function of basin characteristics.The results of this method application are of good quality and open the door to numerous pats of inquiry for the future, while demonstrating again that the use of statistical learning for hydrology can be a relevant solution.

The thesis focuses on how floods were covered in Czech newspapers. The approach taken by two periodicals, Mladá Fronta (MF DNES) and Rudé Právo (Právo), was compared on five examples of actual floods that took place in the Czech Republic and Czechoslovakia between 1954 - 2002. Examined was how the manner in informing about natural disasters differs between the period prior to 1989 and after, and how developments in technology contributed to the visual aspects of reporting on these events.

This thesis applies the runoff process in ostrovská Bystřice river catchment in Ore Mountains. For this purpose we used runoff precipitation model HEC-HMS. Our specific goal is to model the soil runoff, which is observed on eleven runoff precipitation events in the period 2009 - 2013. We analyzed basic physical characteristics of soils, which occur in observed river basin. The results were afterwards used to set up parameters of studied methods. We found out, that the moisture from antecedent precipitation influences modeling of soil runoff. The antecedent precipitation conditions the change of basic physical characteristic. We disregarded the influence of evapotranspiration and effect of vegetation on soil runoff. For the parameterization we have chosen two methods, which describe soil runoff. It was SCS CN and Green Ampt methods. These two methods have been compared on sample of resulting events. The methods were manually and automatically calibrating. The results showed on the insignificant difference between both observed methods. No better significant predicative capacity was manifested for one or other methods. Key worlds: soil runoff modeling, SCS CN, Green Ampt, HEC-HMS, infiltration

This work deals with the modelling of runoff processes in the experimental Bystřice river catchment in the Krušné Mountains. Rainfall-runoff model WaSiM (Topmodel version) was used for this purpose.Objective of this study was modelling snow accumulation and snowmelt in winter periods 2009/2010 and 2010/2011. Sensitivity analysis of TOPMODEL parameters was performed using Monte Carlo and GLUE methodology. Wasim was calibrated manually for 25 and 250 m grid scales and daily timestep. Results of simulations in both spatial scales different spatial scales differed significantly. Better performance of modelling in finer scale wasn't proved in validation of the model. Results of the simulations pointed out uncertainty in model calibration. Rasters of modeled snow water equivalent were also analyzed in selected days representing periods of snow accumulation and snowmelt. The goal was to examine the functioning of used snow model (combination of temperature index method and energy balance method) within the WaSiM frame. Finer scale raster proved to be practical for this purpose It was found that the spatial heterogeneity in the distribution of snow is determined by evapotranspiration and also by effect of radiation correction (in the case of rainfall).Influence of interception and vegetation effects on...