Fluvial flooding has long been recognized as one of the most frequently occurring natural disasters worldwide, with consequences as large economic losses from damages on infrastructure and agriculture, as well as severe impacts on human health. A less known and explored type of flooding is groundwater flooding. A flood type that for instance can arise in river-connected floodplains when groundwater levels rise to the ground surface due to increased river stages in the watercourse. Although groundwater flooding in general is a poorly understood phenomenon, it has become more recognized since its inclusion in the European Floods Directive (2007/60/EC) in 2007. Sweden has however excluded pure groundwater flooding as a separate flood type in its interpretation of the directive, but recognizes groundwater as a component which together with soil water and river water can influence the appearance of a flood event. One of the difficulties regarding groundwater floods that occur in connection to a river is that they typically are hard to differentiate from inundations of fluvial or pluvial origin. It is however important to address the role of groundwater in the inundation of these settings, since traditional flood protection strategies like levees might be circumvented by flows through the subsurface. The aim of this study has been to investigate the role of groundwater in the flooding of a river-connected floodplain by setting up a groundwater model in the integrated hydrological modeling tool MIKE SHE and couple it to an existing MIKE 11 river model, developed by DHI. The study area is a floodplain located along the river Silverån, a tributary to the river Emån, located in the south eastern part of Sweden. By running the model using four different sub-scenarios, regarding initial groundwater level and amount of precipitation, flood extent and contribution of groundwater to the inundation, in relation to other flood sources, has been investigated for different river discharges. A scenario with artificial levees constructed along parts of the river was also examined as levees have been found to have little effect on groundwater floods. As the model provides a simplified and generalized representation of reality it possesses several uncertainties, and so does the results. In summary, the results are in line with what is stated in the Swedish interpretation of the European Floods directive. It has not been possible to demonstrate pure groundwater flooding, but the results suggest that an elevated groundwater level in the beginning of a flood event will increase the extent of the inundation and result in a larger contribution of groundwater to the total amount of flood water. This suggests that there, in some cases, might be a value in integrating groundwater processes in flood risk mapping. Something that is not included in the conventional hydraulic 1D and 2D models, which traditionally are used in flood mapping. As could be expected, the results indicate that groundwater only accounts for a minor part of the flood water added to the total floodplain, while the major sources are river water and surface runoff. A delimited floodplain section that was investigated more in detail, as an increased flow from groundwater to overland water was detected along it, did however show larger contributions from groundwater. This river reach was less vulnerable to fluvial flooding, which in total resulted in a less severe flood, but also enabled a larger amount of groundwater to seep up to the floodplain surface. These conditions did also result in that the river section experienced a worsened inundation at the sub-scenario of high precipitation and high initial groundwater level, as levees were constructed along the river. Most likely because a lot of surface runoff, otherwise able to drain to the river along this section, got trapped outside the levees since it was unable to drain both to the river and to the saturated ground. These results support the theory that levees have little impact on groundwater flooding and stresses the importance 0f surveying and understanding the governing processes in the inundation of a floodplain when planning which type of flood protection scheme to use. / Översvämning utmed vattendrag, så kallad fluvial översvämning, har länge varit känd som en av de vanligast förekommande naturkatastroftyperna världen över, med konsekvenser i form av stora ekonomiska förluster, skador på infrastruktur och jordbruk samt allvarlig påverkan på människors hälsa. En mindre känd och utforskad översvämningstyp är grundvattenöversvämning. En typ av översvämning som kan uppstå i svämplanet längs ett vattendrag då grundvattennivån går upp i markytan till följd av förhöjda nivåer i vattendraget. Trots att grundvattenöversvämning generellt sett är ett outforskat fenomen har det blivit mer uppmärksammat sedan det inkluderades i det europeiska översvämningsdirektivet (2007/60/EG) som antogs 2007. I Sverige har man dock valt att exkludera renodlade grundvattenöversvämningar ur sin tolkning av direktivet och sagt att sådana inte förekommer i Sverige. Istället ser man grundvattnet som en av delarna i ett samverkande system, där det tillsammans med markvatten och ytvatten kan ha påverkan då ett vattendrag översvämmas. En svårighet med grundvattenöversvämningar som inträffar i anslutning till vattendrag är att de kan vara svåra att skilja från översvämningar med fluvialt eller pluvialt ursprung. Det är dock viktigt att uppmärksamma grundvattnets roll i den här typen av översvämningar då traditionella åtgärder som sätts in mot översvämningar, såsom invallningar, kan kringgås av flöden genom marken. Syftet med den här studien har varit att undersöka grundvattnets roll vid en översvämning utmed ett vattendrag genom att konstruera en grundvattenmodell i det integrerade hydrologiska modellverktyget MIKE SHE och koppla denna till en befintlig MIKE 11 vattendragsmodell, utvecklad av DHI. Modellområdet som studerats är beläget längs Silverån, ett av biflödena till Emån i sydöstra Sverige. Genom att undersöka fyra olika delscenarion, avseende initial grundvattenyta och nederbördsmängd, har översvämningsutbredning samt grundvattnets bidrag till översvämningen utvärderats för olika vattenflöden. Ett scenario där invallningar konstruerats längs delar av vattendraget har också undersökts, eftersom invallningar visat sig ha begränsad effekt på grundvattenöversvämningar. Eftersom modellen utgör en förenklad och generaliserad representation av verkligheten har den flertalet osäkerheter, något som även gäller för modellresultaten. Sammanfattningsvis kan sägas att resultaten är i linje med den svenska tolkningen av det europeiska översvämningsdirektivet. Det har inte varit möjligt att påvisa renodlade grundvattenöversvämningar. Däremot pekar resultaten på att en förhöjd grundvattennivå under inledningen av ett översvämningstillfälle kommer att bidra till en ökad översvämningsutbredning, samt ett större bidrag av grundvatten till den totala mängden översvämningsvatten. Detta indikerar att det i vissa fall skulle kunna finnas en mening i att inkludera grundvattenprocesser vid översvämningskartering. Något som inte finns med i de konventionella hydrauliska 1D- och 2D-modeller som traditionellt används vid översvämningskarteringen. Som väntat visar resultaten på att grundvattnet står för en mycket liten del av det vatten som totalt översvämmar det undersökta svämplanet, och att de främsta källorna är vatten från vattendraget tillsammans med ytavrinning. Längs en avgränsad sträcka av svämplanet som undersöktes mer i detalj, då ett ökat flöde från grundvatten till vatten på markytan påträffades längs denna, återfanns dock ett större bidrag från grundvattnet. Denna del av svämplanet var mindre känsligt för fluvial översvämning, något som på det hela taget resulterade i en mindre allvarlig översvämning, men också tillät en större mängd grundvatten att tränga upp på markytan. Dessa förhållanden ledda också till att den aktuella delen av svämplanet kom att få en förvärrad översvämning då vallar konstruerades för delscenariot med hög nederbörd och initialt hög grundvattenyta. Detta till följd av att en stor mängd ytavrinning, som tidigare kunnat dräneras till den här delen av vattendraget, fastnade utanför vallarna istället för att avledas till vattendraget eller infiltrera den mättade marken. Dessa resultat kan sägas stödja teorin kring att invallningar har liten påverkan på grundvattenöversvämningar och visar på vikten av att undersöka och förstå styrande processer kring översvämningen av ett svämplan då åtgärder mot översvämning planeras.

Accessible flood modeling for low-resource, data-scarce communities currently does not exist. This paper proposes using drone imagery to compensate for the lack of other flood modeling data (i.e. streamflow measurements). Three flood models were run for Dzaleka Refugee Camp, located in Dowa, Malawi. Two of the models (the Soil and Water Assessment Tool (SWAT) and the Hydrologic Engineering Center River Analysis System (HEC-RAS)) are commonly used hydrological-hydraulic based models. The third model, the Water Caused Erosion Patterns (WCEP) model, was proposed by the author to capitalize on the high-resolution drone imagery using geological-geomorphological information. The drone imagery used in this study has a resolution of 3.5cm and shows erosion patterns throughout the refugee camp. By comparing the erosion patterns to flow direction of the surface, the erosion patterns were determined to be water caused or not water caused, the erosion patterns considered water caused were defined as high-risk flood areas, creating the WCEP model. The three models were compared using locations of collapsed houses throughout the camp. It was found that the WCEP model represents the location of collapsed houses significantly better (misclassification rate below 17%) than the SWAT or HEC-RAS models (misclassification rate below 54%, and 67% respectively). The WCEP model was combined with the best hydrological-hydraulic model (SWAT) to create a hydrogeomorphological model which capitalizes on both the drone imagery and the hydrological process. / Master of Science / The negative impact flooding has on communities can be reduced through flood modeling. But commonly used flood models are not accessible to data-scarce communities because of the historical data the models require. This paper explores using aerial imagery taken by a drone to make-up for the lack of historical data at Dzaleka Refugee Camp located in Dowa, Malawi. Drone imagery has a very high spatial resolution (3.5cm), so it is able to provide a lot of details, including marks that show an increase of flooding in certain areas and elevation information. The flood model presented in this paper is created using the found flood marks in drone imagery. The presented model is then compared to two commonly used flood models, and all three flood models are compared to locations of houses that collapsed from flooding throughout the refugee camp. The model created using drone imagery did the best job predicting high-risk locations with misclassification rates below 17%. The drone imagery model was then combined with a commonly used model to create a more comprehensive flood model, capitalizing on all available data.

Distributed models of the land surface are essential for global climate models because of the importance of land-atmosphere exchanges of water, energy, momentum. They are also used for high resolution hydrologic simulation because of the need to capture non-linear responses to spatially variable inputs. Continued improvements to these models, and the data which they use, is especially important given ongoing changes in climate and land cover. In hydrologic models, important aspects are sometimes neglected due to the need to simplify the models for operational simulation. For example, operational flash flood models do not consider the role of snow and are often lumped (i.e. do not discretize a watershed into multiple units, and so do not fully consider the effect of intense, localized rainstorms). To address this deficiency, an overland flow model is coupled with a subsurface flow model to create a distributed flash flood forecasting system that can simulate flash floods that involve rain on snow. The model is intended for operational use, and there are extensive algorithms to incorporate high-resolution hydrometeorologic data, to assist in the calibration of the models, and to run the model in real time. A second study, which is designed to improve snow simulation in forested environments, demonstrates the importance of explicitly representing a near canopy environment in snow models, instead of only representing open and canopy covered areas (i.e. with % canopy fraction), as is often done. Our modeling, which uses canopy structure information from Aerial Laser Survey Mapping at 1 meter resolution, suggests that areas near trees have more net snow water input than surrounding areas because of the lack of snow interception, shading by the trees, and the effects of wind. In addition, the greatest discrepancy between our model simulations that explicitly represent forest structure and those that do not occur in areas with more canopy edges. In addition, two value-added Land Cover products (land cover type and maximum green vegetation fraction; MGVF) are developed and evaluated. The new products are good successors to current generation land cover products that are used in global models (many of which rely on 20 year old AVHRR land cover data from a single year) because they are based on 10 years of recent MODIS data. There is substantial spurious interannual variability in the MODIS land cover type data, and the MGVF product can vary substantially from year to year depending on climate conditions, suggesting the importance of using climatologies for land cover data. The new land cover type climatology also agrees better with validation sites, and the MGVF climatology is more consistent with other measures of vegetation (e.g. Leaf Area Index) than the older land cover data.

Selon le Rapport mondial des risques publié par l'Institut universitaire des Nations Unies pour l'environnement et la sécurité humaine, le Mexique a une vulnérabilité de 46% et un manque de capacité d'adaptation de 76% en termes de risques de catastrophe. Un de ceux est les risques d'inondation en cas de catastrophe qui pose un sérieux défi pour le développement et la vie des habitants du Mexique. Mexico est confronté à des problèmes d'inondation dans certaines zones à l'ONU certaines périodes de l'année, causant des pertes et des dommages importants sur les propriétés et les résidents dont certains blessés. En conséquence, il est important de procéder à une évaluation des risques d'inondation dans le bassin de Mexico et d'estimer les dommages des inondations probables. Cependant, les données limitées de débits observés et des profondeurs d'eau dans les principaux cours d'eau de la ville sont disponibles, et esta distributeur d'un obstacle à la compréhension des inondations dans la ville de Mexico. Pour la raison d'origine, plusieurs études doivent être effectuées intérêt dans le but d'avoir une compréhension claire disponibles du bassin versant, qui impliquent, études hydrauliques, météorologiques et hydrologiques, la répartition des précipitations, l'analyse des eaux de ruissellement, les risques d'inondation et de la vulnérabilité, et des études de esta permettent l'estimation de dommages directs et indirects à l'économie, aux actifs et à la vie humaine / According to the World Risk Report released by the United Nations University Institute for Environment and Human Security, Mexico has a vulnerability of 46% and a lack of coping capacity of 76% in terms of disaster risk. One of those disaster risks is flooding which poses a serious challenge to the development and the lives of the inhabitants of Mexico. Mexico City is facing problems of flooding in some areas at certain times of the year, causing important losses and damages on properties and residents including some casualties. Therefore, it is important to carry out a flood risk assessment in the catchment of Mexico City and estimate damages of probable flood events. However, limited data of observed discharges and water depths in the main rivers of the city are available, and this represents an obstacle for the understanding of flooding in Mexico City. For these reason, several studies have to be carried out in order to have a clear understanding of the catchment, which involve, meteorological and hydrological/hidraulic studies, rainfall distribution, runoff analysis, flood risk and vulnerability, and this studies allow the estimation of direct and indirect damages to the economy, to assets and to human life. The premise of this study is that with the limited data and resources available, the catchment can be represented to an acceptable degree by the construction of a deterministic hydrological model of the Mexico City basin. The objective of the developed tool is to provide an efficient support to management of the flood processes by predicting the behavior of the catchment for different rainfall events and flood scenarios

No description available.

<p>  </p> <p>Floods all over the world are one of the most common and devastating natural disasters for human society, and the flood risk is increasing recently due to more and more extreme climatic events. In the United States, one of the key resources that provide the flood risk information to the public is the Flood Insurance Rate Map (FIRM) administrated by the Federal Emergency Management Agency (FEMA) and the digitalized FIRMs have covered over 90% of the United States population so far. However, the uncertainty in the modeling process of FIRMs is rarely investigated. In this study, we use two of the widely used multi-model methods, the Bayesian Model Averaging (BMA) and the generalized likelihood uncertainty estimation (GLUE), to evaluate and reduce the impacts of various uncertainties with respect to modeling settings, evaluation metrics, and algorithm parameters on the flood modeling of FIRMs. Accordingly, three objectives of this study are to: (1) quantify the uncertainty in FEMA FIRMs by using BMA and Hierarchical BMA approaches; (2) investigate the inherent limitations and uncertainty in existing evaluation metrics of flood models; and (3) estimate the BMA parameters (weights and variances) using the Metropolis-Hastings (M-H) algorithm with multiple Markov Chains Monte Carlo (MCMC).</p> <p><br></p> <p>In the first objective, both the BMA and hierarchical BMA (HBMA) approaches are employed to quantify the uncertainty within the detailed FEMA models of the Deep River and the Saint Marys River in the State of Indiana based on water stage predictions from 150 HEC-RAS 1D unsteady flow model configurations that incorporate four uncertainty sources including bridges, channel roughness, floodplain roughness, and upstream flow input. Given the ensemble predictions and the observed water stage data in the training period, the BMA weight and the variance for each model member are obtained, and then the BMA prediction ability is validated for the observed data from the later period. The results indicate that the BMA prediction is more robust than both the original FEMA model and the ensemble mean. Furthermore, the HBMA framework explicitly shows the propagation of various uncertainty sources, and both the channel roughness and the upstream flow input have a larger impact on prediction variance than bridges. Hence, it provides insights for modelers into the relative impact of individual uncertainty sources in the flood modeling process. The results show that the probabilistic flood maps developed based on the BMA analysis could provide more reliable predictions than the deterministic FIRMs.</p> <p><br></p> <p>In the second objective, the inherent limitations and sampling uncertainty in several commonly used model evaluation metrics, namely, the Nash Sutcliffe efficiency (<em>NSE</em>), the Kling Gupta efficiency (<em>KGE</em>), and the coefficient of determination (<em>R</em>2), are investigated systematically, and hence the overall performance of flood models can be evaluated in a comprehensive way. These evaluation metrics are then applied to the 1D HEC-RAS models of six reaches located in the states of Indiana and Texas of the United States to quantify the uncertainty associated with the channel roughness and upstream flow input. The results show that the model performances based on the uniform and normal priors are comparable. The distributions of these evaluation metrics are significantly different for the flood model under different high-flow scenarios, and it further indicates that the metrics should be treated as random statistical variables given both aleatory and epistemic uncertainties in the modeling process. Additionally, the white-noise error in observations has the least impact on the evaluation metrics.</p> <p><br></p> <p>In the third objective, the Metropolis-Hastings (M-H) algorithm, which is one of the most widely used algorithms in the MCMC method, is proposed to estimate the BMA parameters (weights and variances), since the reliability of BMA parameters determines the accuracy of BMA predictions. However, the uncertainty in the BMA parameters with fixed values, which are usually obtained from the Expectation-Maximization (EM) algorithm, has not been adequately investigated in BMA-related applications over the past few decades. Both numerical experiments and two practical 1D HEC-RAS models in the states of Indiana and Texas of the United States are employed to examine the applicability of the M-H algorithm with multiple independent Markov chains. The results show that the BMA weights estimated from both algorithms are comparable, while the BMA variances obtained from the M-H MCMC algorithm are closer to the given variances in the numerical experiment. Overall, the MCMC approach with multiple chains can provide more information associated with the uncertainty of BMA parameters and its performance of water stage predictions is better than the default EM algorithm in terms of multiple evaluation metrics as well as algorithm flexibility.</p>

The creation of reliable flood extent maps is becoming an increasingly important question as the  damage  caused by  natural  disasters  is  becoming  more  severe and the frequency of these events is increasing.  By limiting the uncertainty in flood modelling and simplifying the creation of flood extent maps, a more iterative process is made possible. This iterative process could potentially facilitate the development of more reliable emergency plans. The purpose of this report is to describe how water levels, simulated with a hydraulic model in an efficient way, can be processed in ArcGIS to produce flood extent maps. Focus has been placed on the inclusion of flooded areas occurring on the side of the river and the improvement of handling of tributaries. Inundated areas close to a flooded river can occur due to ground water interactions and increased surface runoff being trapped in low-lying points in the terrain. By analysing flood extent maps derived by various methods, a new model was developed in ArcGIS’s ModelBuilder. By viewing the entire river as a coherent unit the model produces flood extent maps with more reliable descriptions regarding connecting tributaries. This new model drastically decreases the need for manual adjustments and the creation of extra polygon shapefiles to constrain the interpolation area.  At the same time, it decreases the computation time due to the fact that it is a “cleaner” model. When applying the model on areas previously mapped using a tool developed at WSP (the KOG-tool) and MIKE 11’s built in tool for mapping of flood extent, it showed a high degree of accuracy. Concerning differences in water levels, the majority of raster values lay within a 0-1-millimetre range. These results imply a high credibility for the developed model. When evaluating the model against empirical flooding data, it showed satisfactory agreement, especially considering   the limited water level data available and the fact that the developed model does not take into consideration interaction with urban infrastructure or potential river blockages. / Efterfrågan av pålitliga översvämningskartor ökar med den ökade frekvensen av översvämningar med betydande negativ påverkan. Genom att minska osäkerheter i översvämningsmodellering och effektivisera genereringen av vattenutbredningskartor tillåts en mer iterativ process som medför mer pålitliga kartor. Syftet med denna rapport har varit att beskriva hur vattennivåer simulerade med hydrauliska modeller effektivt kan bearbetas i ArcGIS för att åstadkomma kartor över översvämningars vattenutbredning. Förbättrad hantering av översvämningsöar och anslutande biflöden har varit fokusområden. Genom att utvärdera och analysera vattenutbredningar genererade med olika verktyg har en modell, SÖK-modellen, utvecklats i ArcGIS:s ModelBuilder. Genom att hantera hela vattendraget som en sammanhängande enhet hanteras anslutande biflöden på ett sätt som leder till mer korrekt beskrivning av vattenutbredning i biflöden. Den framtagna modellen minskar drastiskt behovet av manuella justeringar och skapande av polygoner med syfte att begränsa interpolationsområden samtidigt som beräkningstiden minskas. Användning av modellen på områden karterade med ett av WSP utvecklat verktyg samt med MIKE 11s inbyggda modul för översvämningskartering visar på god överensstämmelse av interpolerade vattennivåer mellan de olika verktygen, de flesta skillnader är i storleksordningen 0-1 millimeter. Detta kombinerat med stora likheter i vattenutbredning mellan de utvärderade verktygen medför att den framtagna modellen anses lika pålitlig som övriga utvärderade verktyg. Vid utvärdering av modellen på en faktisk översvämning påvisades god överensstämmelse med observerad vattenutbredning, speciellt med hänsyn till den begränsade datamängd som funnits tillgänglig samt att den framtagna modellen inte tar hänsyn till interaktioner med urban infrastruktur eller eventuella blockader i vattendraget.

<p>Topography is one of the primary drivers of physical processes in the rivers and floodplains. Advances in remote-sensing and survey techniques have provided high-resolution representation of the floodplains but information regarding the 3D representation of river channels (commonly known as river bathymetry) is sparsely available. Field surveys along an entire river network in a watershed remains infeasible and algorithms for estimating simple but effective characterization of river channel geometry are hindered by an incomplete understanding of the role of river bathymetry in surface and subsurface processes. </p> <p> The first objective of this dissertation develops an automated framework – System for Producing RIver Network Geometry (SPRING) for improving the geospatial descriptors of a river network. The tool takes as input the DEM and erroneous river centerline to produce spatially consistent river centerlines, banks, and an improved representation of river channel geometry. SPRING can process entire river networks and is not limited single reach applications. The proposed framework is flexible in terms of data requirements, resolution of output datasets and user preferences. It has a user-friendly graphic user interface (GUI) and is appropriate for large-scale applications since it requires minimal user input.</p> <p> A better understanding of the role of bathymetric characteristics in surface-subsurface hydrology and hydrodynamics can facilitate an efficient incorporation of river bathymetry in large river networks. The second objective explores the level of bathymetric detail required for accurately simulating surface and subsurface processes by developing four bathymetric representations using SPRING with reducing level of detail. These bathymetric configurations are simulated using a physically based tightly coupled hydrologic and hydrodynamic model to estimate surface and subsurface fluxes in the floodplains. Comparison of fluxes for the four bathymetric configurations show that the impact of river bathymetry extends beyond surface routing to surface water – groundwater interactions. Channel conveyance capacity and thalweg elevation are the most important characteristics controlling these interactions followed by channel side slope and channel asymmetry. </p> <p> The final objective aims to develop benchmarks for bathymetric characteristics for accurately simulating flooding related physical processes. The sensitivity of surface and subsurface fluxes to error in channel conveyance capacity is investigated across reaches with varying geomorphological characteristics. SPRING is used to create six bathymetric configurations with varying range of error in channel conveyance capacity (ranging from 25% to 300%). They are simulated using a tightly coupled physically distributed model for a flood event and the estimates of water surface elevation, infiltration and lateral seepage are compared. Results show that incorporating channel conveyance capacity with an error of within 25% significantly improves the estimates of surface and subsurface fluxes as compared to those not having any bathymetric correction. For certain reaches, such as those with high drainage area (>1000km²) or low sinuosity (< 1.25), errors of up to 100% in channel conveyance capacity can still improve H&H modeling.</p>

<div>With increasing focus on large scale planning and allocation of resources for protection against future flood risk, it is necessary to analyze and improve the deficiencies in the conventional flood modeling approach through a better understanding of the interactions between river hydrodynamics and subsurface processes. Recent studies have shown that it is possible to improve the flood inundation modeling and mapping using physically-based integrated models that incorporate observable data through assimilation and simulate hydrologic fluxes using the fundamental laws of conservation of mass at multiple spatiotemporal scales. However, despite the significance of integrated modeling in hydrology, it has received relatively less attention within the context of flood hazard. The overall aim of this dissertation is to study the heterogeneity in complex physical processes that govern the watershed response during flooding and incorporate these effects in integrated models across large scales for improved flood risk estimation. Specifically, this dissertation addresses the following questions: (1) Can physical process incorporation using integrated models improve the characterization of antecedent conditions and increase the accuracy of the watershed response to flood events? (2) What factors need to be considered for characterizing scale-dependent physical processes in integrated models across large watersheds? (3) How can the computational efficiency and process representation be improved for modeling flood events at large scales? (4) Can the applicability of integrated models be improved for capturing the hydrodynamics of unprecedented flood events in complex urban systems?</div><div><br></div><div>To understand the combined effect of surface-subsurface hydrology and hydrodynamics on streamflow generation and subsequent inundation during floods, the first objective incorporates an integrated surface water-groundwater (SW-GW) modeling approach for simulating flood conditions. The results suggest that an integrated model provides a more realistic simulation of flood hydrodynamics for different antecedent soil conditions. Overall, the findings suggest that the current practice of simulating floods which assumes an impervious surface may not be providing realistic estimates of flood inundation, and that an integrated approach incorporating all the hydrologic and hydraulic processes in the river system must be adopted.</div><div><br></div><div>The second objective focuses on providing solutions to better characterize scale-dependent processes in integrated models by comparing two model structures across two spatial scales and analyzing the changes in flood responses. The results indicate that since the characteristic length scales of GW processes are larger than SW processes, the intrinsic scale (or resolution) of GW in integrated models should be coarser when compared to SW. The results also highlight the degradation of streamflow prediction using a single channel roughness when the stream length scales are increased. A distributed channel roughness variable along the stream length improves the modeled basin response. Further, the results highlight the ability of a dimensionless parameter 𝜂1, representing the ratio of the reach length in the study region to maximum length of the single stream draining at that point, for identifying which streams may require a distributed channel roughness.</div><div><br></div><div>The third objective presents a hybrid flood modeling approach that incorporates the advantages of both loosely-coupled (‘downward’) and integrated (‘upward’) modeling approaches by coupling empirically-based and physically-based approaches within a watershed. The computational efficiency and accuracy of the proposed hybrid modeling approach is tested across three watersheds in Indiana using multiple flood events and comparing the results with fully- integrated models. Overall, the hybrid modeling approach results in a performance comparable to a fully-integrated approach but at a much higher computational efficiency, while at the same time, providing objective-oriented flexibility to the modeler.</div><div><br></div><div>The fourth objective presents a physically-based but computationally-efficient approach for modeling unprecedented flood events at large scales in complex urban systems. The application of the proposed approach results in accurate simulation of large scale flood hydrodynamics which is shown using Hurricane Harvey as the test case. The results also suggest that the ability to control the mesh development using the proposed flexible model structure for incorporating important physical and hydraulic features is as important as integration of distributed hydrology and hydrodynamics.</div>

No description available.