No description available.

Hydrogeological hazards are quite diffuse rainfall-induced phenomena that affect mountain regions and can severely impact these territories, producing damages and sometimes casualties. For this reason, hydrogeological risk reduction is crucial. Mitigation strategies aim to reduce hydrogeological risk to an acceptable level and can be classified into structural and non-structural measures. This work focuses on enhancing some non-structural risk mitigation measures for mountain areas: debris-flow rainfall thresholds, as a part of an Early Warning System (EWS), multivariate rainfall scenarios with multi-hazard mapping purpose and public awareness. Regarding debris-flow rainfall thresholds, an innovative calibration method, a suitable uncertainty analysis and a proper validation process are developed. The Backward Dynamical Approach (BDA), a physical-based calibration method, is introduced and a threshold is obtained for a study area. The BDA robustness is then tested by assessing the uncertainty in the threshold estimate. Finally, the calibrated threshold's reliability and its possible forecast use are assessed using a proper validation process. The findings set the stage for using the BDA approach to calibrate debris-flow rainfall thresholds usable in operational EWS. Regarding hazard mapping, a multivariate statistical model is developed to construct multivariate rainfall scenarios with a multi-hazards mapping purpose. A confluence between a debris-flow-prone creek and a flood-prone river is considered. The multivariate statistical model is built by combining the Simplified Metastatistical Extreme Value approach and a copula approach. The obtained rainfall scenarios are promising to be used to build multi-hazard maps. Finally, the public awareness within the LIFE FRANCA (Flood Risk ANticipation and Communication in the Alps) European project is briefly considered. The project action considered in this work focuses on training and communication activities aimed at providing a multidisciplinary view of hydrogeological risk through the holding of courses and seminars.

No description available.

Flood forecasting maps are essential for rapid disaster response and risk management, yet the computational complexity of physically-based simulations hinders their application for efficient high-resolution spatial flood forecasting. To address the problems of high computational cost and long prediction time, this thesis proposes to develop deep learning neural networks based on a flood simulation dataset, and explore their potential use for flood prediction without learning hydrological modelling knowledge from scratch.  A Fully Convolutional Network (FCN), FCN with multiple outputs (Multioutput FCN), UNet, Graph-based model and their Recurrent Neural Network (RNN) variants are trained on a catchment area with twelve rainfall events, and evaluated on two cases of a specific rainfall event both quantitatively and qualitatively. Among them, Convolution-based models (FCN, Multioutput FCN and UNet) are commonly used to solve problems related to spatial data but do not encode the position and orientation of objects, and Graph-based models can capture the structure of the problem but require higher time and space complexity. RNN-based models are effective for modelling time-series data, however, the computation is slow due to its recurrent nature. The results show that Multioutput FCN and the Graph-based model have significant advantages in predicting deep water depths (>50 cm), and the application of recurrent training greatly improves the long-term flood prediction accuracy of the base deep learning models. In addition, the proposed recurrent training FCN model performs the best and can provide flood predictions with high accuracy.

Current research shows that water-related disasters are the most common natural disaster worldwide and these disasters are increasing in numbers. Water-related disasters cause negative consequences through damage to infrastructure and human health.  This thesis aims to provide an overview of the water-related disasters, floods, and landslides in Sweden by displaying the spatial distribution. Furthermore, the purpose is to analyze the consequences of occurred water-related disasters. By answering the following research questions:  How has landslides and floods been spatially distributed over time in Sweden?  How severe has the consequences of floods and landslides been in Sweden?  To answer these research questions a data study was conducted in ArcGIS and Excel to analyze the spatial distribution and the consequences of landslides and floods. The result shows that the three counties in Sweden with the highest number of affected areas by floods are: Västerbotten, Västernorrland and Örebro. These counties constitute 36% of the affected areas. These affected areas have occurred periodically with an increase since 1970. A detailed study over the years 2011–2017 showed that most floods in Sweden lead to consequences with a small extent and limited damages.  Furthermore, the counties Västra Götaland, Västernorrland and Värmland had the highest number of occurred landslides. In total, 83.7% of all landslides have occurred within these three counties. This means that the distribution of floods is more evenly distributed between different counties compared to landslides. Within these counties, the areas that have had notable high numbers of landslides are Ångermanälven, Norsälven, Klarälven and the areas nearby Göta älv. Overall, it has been most common that landslides have an extent in the range between 1000–10000 m2 and that an extent over 100000 m2 are rare. / Aktuell forskning visar att vattenrelaterade naturkatastrofer är de vanligaste naturkatastroferna över hela världen samt att dessa ökar i antal. Vattenrelaterade naturkatastrofer orsakar till negativa konsekvenser till följd av skador på infrastruktur och människors hälsa. Denna kandidatuppsats syftar till att ge en översikt av den geografiska utbredningen av inträffade vattenrelaterade naturkatastroferna skred och översvämningar i Sverige. Vidare, är syftet att analysera konsekvenserna av inträffade vattenrelaterade naturkatastrofer, genom att svara på följande frågeställningar:  Hur har skred och översvämningar varit utspridda över tid i Sverige? Hur allvarliga har konsekvenserna av översvämningar och jordskred varit i Sverige? För att besvara dessa frågeställningar utfördes en analys i ArcGIS och Excel för att undersöka den geografiska utbredningen och konsekvenserna av skred och översvämningar. Resultatet visar att de tre län med flest områden som blivit påverkade av översvämningar är: Västerbotten, Västernorrland and Örebro. Dessa län utgör 36% av de drabbade områdena. Antalet påverkade områden av översvämningar har inträffat periodvis med en ökning sedan 1970. En detaljerad analys över åren 2011–2017 visade att de flesta översvämningar i Sverige resulterade i konsekvenser med liten utbredning och små skador.  Vidare, hade Västra Götaland, Västernorrland och Värmlands län högst antal inträffade skred. Totalt har 83.7% av alla skred inträffat inom dessa tre län. Detta innebär att fördelningen av områden påverkade av översvämningar har varit jämnare fördelade mellan olika län jämfört med skred. Inom dessa län är de områden som har haft anmärkningsvärt högt antal skred: Ångermanälven, Norsälven, Klarälven och områdena i närheten av Göta älv. Överlag har det varit vanligast att jordskred har en utbredning mellan 1000–10000 m2 och att en utbredning över 100000 m2 är ovanlig.

Hälsosamma ekosystem försörjer oss med livsviktiga resurser och tjänster – ekosystemtjänster så som skydd mot översvämning. I Norra Östersjöns vattendistrikt, som Mälaren tillhör, är statusen på den ekosystemtjänsten dålig. Detta beror till stor del på en omfattande dikning och brist på svämplan i området. Under perioder med skyfall riskerar därför området runt Mälaren och dess tillrinnande vattendrag att drabbas av översvämningar som skadar matproduktion, infrastruktur och miljö. Övergödning är redan ett problem i området och stora tillskott av fosfor till följd av översvämmade jordbruksmarker kan orsaka stora algblomningar och försämrad livsmiljö för vattenlevande organismer. Under augusti och september 2023 föll ovanligt stora mängder regn över mellersta Sverige vilket ökade vattenföringen i vattendragen runt Mälaren och översvämmade vissa av dem. Högfrekventa turbiditetsmätningar från in-situ sensorer installerade i Sagån, Hågaån och Fyrisån, tre vattendrag i Mälarens avrinningsområde, har använts för att undersöka skyfallens effekter på deras vattenföring och beräknad fosfortransport. Resultaten visade en signifikant korrelation mellan ökad vattenföring och ökad fosfortransport, en signifikant ökning under 2023 jämfört med 2018–2022 och signifikanta skillnader mellan vattendragen. Översvämmade Sagån hade extremt höga toppar i beräknad fosfortransport. Resultaten indikerar att övergödningsproblemen i Mälaren kan förvärras i ett framtida klimat med mer intensiva skyfall om inte åtgärder tas för att stärka avrinningsområdets förmåga att hantera stora mängder nederbörd. / Healthy ecosystems provide us with vital resources and services – ecosystem services such as flood protection. In the North Baltic Sea Water District, to which Lake Mälaren belongs, the status of that ecosystem service is poor, largely as a result of extensive draining in the area leading to a lack of floodplains. During periods of torrential rain, the area around Lake Mälaren and its tributaries is therefore at risk to be affected by floods that cause damage to food production, infrastructure and the environment. Eutrophication is already a problem in the area and large additions of phosphorus as a result of flooded agricultural land can cause large algal blooms and degraded habitat for aquatic organisms. During August and September 2023, unusually large amounts of rain fell over central Sweden, which increased the flow of water in Lake Mälarens tributaries and flooded some of them. High frequency turbidity data from in-situ sensors installed in Sagån, Hågaån and Fyrisån, three tributaries to Lake Mälaren, was used to study the effects of the heavy rains on their waterflow and estimated phosphorus transport. The results showed a significant correlation between increased water flow and increased phosphorus transport, a significant increase in 2023 compared to 2018-2022 and significant differences between the tributaries. Flooded Sagån had extremely high peaks in estimated phosphorus transport. The results indicate that the eutrophication problems in Lake Mälaren may worsen in a future climate with more intense downpours unless measures are taken to strengthen the catchment's ability to handle large amounts of rainfall.

Extreme rainfall statistics are important for the design and management of the water resource infrastructure. The standard approach for extreme rainfall event severity assessment is the Intensity-Duration-Frequency (IDF) method. However, this approach does not consider the spatial context of rainfall and consequently does not properly describe rainfall storm severity, nor rarity. This study provides a critical account of the current standard practice and presents an approach that takes into consideration both the spatial context of rainfall storms, and indirectly incorporates runoff to produce a representative approach to assessing urban rainfall storm severity in terms of flood potential. A stepwise regression analysis was performed on a dataset of individual rainfall storm characteristics to best represent documented basement floodings in the City of Edmonton. Finally, the urban rainfall storm flood severity index was shown to be most representative of the documented basement floodings' severity when compared to that of the IDF method.

Extreme rainfall statistics are important for the design and management of the water resource infrastructure. The standard approach for extreme rainfall event severity assessment is the Intensity-Duration-Frequency (IDF) method. However, this approach does not consider the spatial context of rainfall and consequently does not properly describe rainfall storm severity, nor rarity. This study provides a critical account of the current standard practice and presents an approach that takes into consideration both the spatial context of rainfall storms, and indirectly incorporates runoff to produce a representative approach to assessing urban rainfall storm severity in terms of flood potential. A stepwise regression analysis was performed on a dataset of individual rainfall storm characteristics to best represent documented basement floodings in the City of Edmonton. Finally, the urban rainfall storm flood severity index was shown to be most representative of the documented basement floodings' severity when compared to that of the IDF method.

Pluvial floods are formed directly from surface runoff after extreme rain events. Urban areas are prone to suffer from these floods due to large portions of hardened surfaces and limited capacity in the stormwater infrastructure. Previous research has shown that catchment response is influenced by the spatio-temporal behaviour of the rainstorm. A rainstorm moving in the same direction as the surface flow can amplify the runoff peak and temporal variability of rainfall intensity generally results in greater peak discharge compared to constant rainfall. This research attempted to relate the effect of storm movement on flood propagation in urban pluvial flooding to the effect from different distributions of rainfall intensity. An additional objective was to investigate the flood response from recent findings on the temporal variability in Swedish rain events and compare it to the flood depths produced by a CDS-rain (Chicago Design Storm), where the latter is the design practice in flood modelling today. A 2D surface model of an urban catchment was coupled with a 1D model of the drainage network and forced by six different hyetographs. Among them were five empirical hyetographs developed by Olsson et al. (2017) and one a CDS-rain. The rainstorms were simulated to move in different directions: along and against the surface flow direction, perpendicular to it and with no movement. Maximum flood depth was evaluated at ten locations and the model results show that storm movement had negligible effect on the flood depths. The impact from the movement was likely limited by the big difference in speed between the rainstorm and the surface flow. All evaluated locations showed a considerable sensitivity to changes in the hyetograph. The maximum flood depth increased at most with a factor of 1.9 depending on the hyetograph that was used as model input. The CDS-rain produced higher flood depths compared to the empirical hyetographs, although one of the empirical hyetographs produced a similar result. Based on the results from this case study, it was concluded that storm movement was not as critical as the temporal variability of rainfall when evaluating maximum flood depth. / Pluviala översvämningar skapas från ytavrinning vid intensiva nederbördstillfällen. De uppstår ofta i urbana miljöer till följd av den höga andelen hårdgjorda ytor och ledningsnätets begränsade kapacitet. Forskning har visat att ett regnmolns rörelseriktning och hastighet påverkar avrinningsförloppet. Om molnet rör sig längs med flödesriktningen i terrängen kan en ökning i vattenlödet nedströms ett avrinningsområde uppstå. Denna effekt har visat sig vara störst om hastigheten hos regnmolnet och vattenflödet är likvärdiga. Ytterliggare en faktor som påverkar avrinningsförloppet är hur regnintensiteten är fördelad över tid. Olsson et al. (2017) har tagit fram fem empiriska regntyper som speglar tidsfördelning inom ett Svenskt regntillfälle. Inom översvämningsmodellering är det vanligt att använda ett så kallat CDS-regn (Chicago Design Storm), vilken har en given tidsfördelning. Med anledning av detta är det intressant att jämföra översvämningar genererade av ett CDS-regn och av de empiriska regntyperna. Syftet med denna studie var att utreda hur regnmolns rörelse påverkar urbana pluviala översvämningar med avseende på vattendjup, samt att jämföra denna påverkan med effekten från olika tidsfördelningar av regnintensiteter. En kombinerad dagvattenmodell (1D) och markavrinningsmodell (2D) av en mindre svensk tätort användes för att simulera olika regnscenarier. De fem empiriska regntyperna och ett CDS-regn simulerades med en rörelseriktning längs med, emot och vinkelrätt i förhållande till flödesriktningen. Även scenarier med stationära regnmoln simulerades. Maximala översvämningsdjup utvärderades i tio punkter spridda över hela modellområdet. Resultatet från simuleringarna visade att regnmolnets rörelse hade försumbar påverkan på översvämningsdjupen. De olika tidsfördelningarna av regnintensitet hade däremot betydande påverkan på de maximala översvämningsdjupen. Som mest var det det maximala översvämningsdjupet 1.9 gånger större beroende vilken regntyp som användes som indata. CDS-regnet genererade i regel de största översvämningsdjupen, även om utfallet från en av de fem empiriska regntyperna var förhållandevis likvärdigt. Regnintensitetens tidsfördelning var därmed en kritisk parameter vid den hydrauliska modelleringen av urbana pluviala översävmningar, till skillnad från molnrörelse som hade försumbar påverkan.

The economic and social losses of environmental disasters are increasingly higher. Floods are a main concern in many locations around the world. Preventive actions are urgent and necessary. This doctoral thesis addresses topics related to hydro-meteorological risks and water resources management. Its aim is to cope with hydrological risks and water resources management through a flooding risk index, complex watershed modeling, different calibration techniques, and ensemble streamflow forecasting. Specific assumptions and research questions are defined in each chapter of the thesis, and are mostly related to the 12,600 km2 Piracicaba watershed, in Southeast, Brazil. Chapter one has general introductions and explains how the thesis is organized. Chapter two brings an assessment and mapping of flooding risks. Chapter three reviews the watershed modelling topic, through applications of a selected watershed model (the Soil and Water Assessment Tool - SWAT) in Brazil. Chapter four proposes a good practice methodology for calibration of watershed models for different time-steps with available data, having hydrology as main focus. Chapter five explores different methodologies for calibrating hydrological models, using two optimization algorithms and with a multi-site and single site approaches to evaluate related changes in performance. Chapter six has complex watershed modeling for sub-daily time-step, with an automatic hourly calibration module that was included in SWAT-CUP and the application of these models to forecast ensemble streamflow and with a data assimilation approach with optimization to improve the quality of the forecasts. Chapter seven has overall conclusions and chapter eight has a summarized list of other activities developed during the doctoral process. Overall we believe the methodologies and results for the Piracicaba watershed are very good. And that they can be replicated in other watersheds in Brazil and around the world. The proposed mapping assessments of flooding vulnerability and risks can be applied for the entire Brazil, and could be used as a tool in water resources management and planning. The watershed model (SWAT) used on this doctoral thesis also proved to be a versatile and robust model, with several good example applications in Brazil, and in particular for the Piracicaba case study. The step by step calibration methodology, as well as the different calibrations performed can help other modelers on choosing where and how to calibrate their own models. For hourly application, this work is pioneer, in area scale and model used. The results for ensemble flow forecasting and data assimilation show a little of what can be performed with this kind of application, and that it can be a potential tool for real time applications in streamflow forecasting and early warning systems. We believe the lessons learnt in this thesis can improve and aid modeler and water resources managers worldwide. / Os prejuízos econômicos e sociais de desastres ambientais têm sido maiores. Inundações são uma das principais preocupações ao redor do mundo. Ações preventivas são urgentes e necessárias. Esta tese de doutorado aborda temas relacionados à gestão dos recursos hídricos e de riscos hidro-meteorológicos. Possui o objetivo de lidar com riscos hidrológicos através de índices de risco a inundações, modelagem complexa de bacias hidrográficas, diferentes técnicas de calibração, e previsão de vazões por conjunto. Pressupostos e objetivos específicos são definidos em cada capítulo da tese, e são na sua maioria relacionados à bacia hidrográfica do Rio Piracicaba (12.600 km2), Sudeste do Brasil. O Capítulo um traz as introduções gerais e explica a organização da tese. O capítulo dois desenvolve mapeamento de riscos a inundações. O capítulo três revisa o tópico de modelagem de bacias hidrográficas, através de aplicações de um modelo selecionado (Soil and Water Assessment Tool - SWAT) no Brasil. O quarto capítulo propõe uma metodologia de boas práticas para a calibração de modelos de bacias hidrográficas utilizando dados disponíveis, com foco principal na hidrologia. O capítulo cinco explora diferentes metodologias de calibração, utilizando dois algoritmos de otimização e abordagens de calibração em um local e demais locais para avaliar alterações relacionadas ao desempenho da modelagem. O capítulo seis trabalha com modelagem sub-diária, com um módulo de calibração horária automática, que foi incluído no SWAT-CUP, e aplicação destes modelos para previsão de vazões por conjunto e assimilação de dados com otimização, para melhorar a qualidade das previsões. O sétimo capítulo traz as conclusões gerais da tese e oitavo capítulo apresenta uma lista resumida de outras atividades desenvolvidas durante o doutorado. Acreditamos que as metodologias e resultados para a bacia hidrográfica Piracicaba são muito bons. E que podem ser replicados em outras bacias hidrográficas no Brasil e ao redor do mundo. O mapeamento de vulnerabilidade e riscos de inundação propostos pode ser aplicados para todo o Brasil, além de possuir potencial como uma ferramenta de planejamento. O modelo utilizado (SWAT) também provou ser versátil e robusto, com vários bons exemplos de aplicações no Brasil, e em especial para a Bacia do Piracicaba. A metodologia sistemática para calibração, bem como as diferentes calibrações executadas podem auxiliar outros modeladores a escolherem como calibrar seus próprios modelos. Este trabalho é pioneiro no tipo de aplicação horária apresentada. Os resultados de previsão por conjunto de vazões e de assimilação de dados mostram o potencial da metodologia para sistemas de previsão de vazões em tempo real e em sistemas de alerta antecipado. Nós acreditamos que as lições aprendidas nesta tese podem auxiliar modeladores e gestores de recursos hídricos ao redor do mundo.