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Large scale ecosystem restoration is an important societal issue because significant risks, costs, and benefits can accrue on large landscapes. It is important to understand baseline ecosystem conditions, existing condition, and to the extent possible estimate ecosystem response to alternative management scenarios. Incorporating ecosystem process and function into restoration planning and implementation will make ecosystem restoration projects sustainable. The Upper Mississippi River System is an excellent case study for such issues because it is an important, multiple-use ecosystem with significant ongoing investment in ecosystem, agri-system, and navigation system management. Large-scale geomorphology, hydrology, and land cover information was compared among presettlement, contemporary, and potential future reference conditions to examine ecosystem state and evaluate mechanisms responsible for ecosystem condition. The UMRS was scaled by physiographically similar characteristics into large floodplain reaches several hundred river miles in length, geomorphic reaches 50 to several hundred miles, and a mile-by-mile segmentation of the river floodplain extent. Ecologically relevant geomorphic classes were devised from existing data and evaluated by river reach to characterize presettlement geomorphology, and dams and levees were superimposed to reflect the altered hydrogeomorphology of the contemporary ecosystem. A pre- and post-impact Indicators of Hydrologic Alteration river stage analysis evaluated dam impacts, and pre-dam and post-dam aquatic habitat class distribution was compared. A floodplain inundation simulation analysis provided new information on the potential spatial distribution of frequent floods. Land cover data available for presettlement and modern reference periods were compared at several spatial scales. Multivariate analyses evaluated land cover characteristics among geomorphic reaches, as well as to assess the influence of hydrogeomorphic drivers on land cover for presettlement and contemporary reference periods. The objective of this research was to clearly delineate the divergence of environmental conditions among reference periods to evaluate which drivers need to be, and can be, altered to change ecosystem state. Hydrogeomorphic response to development indicates several restoration objectives that are appropriate system-wide and others that are best suited to specific river reaches. Similar data sources are available for much of the rest of the United States through the Public Land Survey and engineering surveys of any significant civil works projects.

Floods are caused by extreme meteorological and hydrological changes that are influenced directly or indirectly by human activities within the environment. The flood trends show that floods will reoccur and shall continue to affect the livelihoods, property, agriculture and the surrounding environment. This research has analyzed the riverine flood by integrating remote sensing, Geographical Information Systems (GIS), and hydraulic and/or hydrological modeling, to develop informed flood mapping for flood risk management. The application of Hydrological Engineering Center River Analysis System (HEC RAS) and HEC HMS models, developed by the USA Hydrologic Engineering Center of the Army Corps of Engineers in a data-poor environment of a developing country were successful, as a flood modeling tools in early warning systems and land use planning. The methodology involved data collection, preparation, and model simulation using 30m Shuttle Radar Topographic Mission (SRTM) Digital Elevation Model (DEM) as a critical data input of HEC RAS model. The findings showed that modeling using HEC-RAS and HEC HMS models in a data-poor environment requires intensive data enhancements and adjustments; multiple utilization of open sources data; carrying out multiple model computation iterations and calibration; multiple field observation, which may be constrained with time and resources to get reasonable output.

Floods are the most impactful natural disasters on earth, and reliable flood warning systems are critical for disaster preparation, mitigation, and response. The GEOGloWS ECMWF Streamflow Services (GESS) provide forecasted streamflow throughout the world. While forecasted discharge is essential to flood warning, forecasted inundation extents are required to understand and predict flood impact. In this research, I sought to expand GESS flood warning potential by generating inundation extents from streamflow forecasts. I compared Height Above Nearest Drainage (HAND), a method beneficial for flood mapping on a watershed scale, to a 2D hydrodynamic model, specifically Sedimentation and River Hydraulics – Two Dimension (SRH-2D), a method localized to specific areas of high importance. In three study areas in the Amazon basin, I validated HAND and SRH-2D flood maps against water maps derived from satellite SAR imagery. Specifically, I analyzed what features of an SRH-2D model were required to generate more accurate flood extents than HAND. I also analyzed the practicality of using SRH-2D for forecasting by comparing flood extents generated from simulating a complete forecast hydrograph to flood extents precomputed at predetermined, incremental flowrates. The SRH-2D models outperformed HAND, but their accuracy decreased at flowrates different than those used for calibration, limiting their reliability for forecasting and impact analysis. Based on this study, the key features necessary for a reliable SRH-2D model for forecasting include (1) a high-resolution DEM for an accurate representation of the floodplain, (2) correct representation of channel flow control, and (3) a channel bathymetry approximation and exit boundary rating curve that correctly predict water levels at a range of input flowrates. For forecasting practicality, the precomputed flood extents had accuracies comparable to the complete hydrograph simulations, showing their potential for estimating forecasted inundation extents. Future research should include (1) a more comprehensive analysis using existing SRH-2D models in areas with more bathymetry information and calibration data, (2) further assessment of the reliability of precomputed flood maps for forecasting applications, and (3) quantifying the effect of error in the streamflow forecasts on the accuracy of the resulting flood extents.

No description available.

This dissertation introduces FESM (Flood Event Simulation Model), a Geographic Information System (GIS) tool designed for use on gaged river systems that can be used to guide logistic support during disaster events. FESM rapidly generates flood predictions using elevation data from real-world sensors or generated by other models. Verification and validation data for FESM are provided. In order to construct a visualization system for interacting with FESM outputs, single buffer and dual buffer techniques for moving massive datasets to the GPU for processing using OpenCL were rigorously tested and timed, and an analysis of the costs/benefits of using buffers or images was conducted. Finally, DRO (Dynamic Raster Overlay), a visualization system for analysis of datasets composed of multiple overlapping flood maps is introduced, and expert feedback is provided on the effectiveness of DRO with selected case studies.

Floods are becoming more frequent and the magnitude of direct consequences, relating to destruction of critical infrastructure and loss of life, has highlighted the importance of flood management. This thesis proposes a new methodology to quantify the impact of predicted and historic flooding events on emergency services. The approach moves beyond simple flood inundation mapping by accounting for the relationship between flood depth and vehicular speed. A case study was presented for Calgary Alberta, where the depths of a predicted 100-year flood and an historic 2013 flood event were modelled. The methodology applied geographic information systems (GIS) to flood depth mapping, utilizing digital elevation models (DEMs), flood extents, and hydrological data. Flood depths were then assigned to links comprising the road network, where the maximum vehicle speed was calculated as a function of the standing depth of water on a link. The flooded network was used to derive service areas for several types of emergency services (emergency medical services (EMS), fire, and police), following targeted response times. The results quantified and located the residential and work populations that no longer meet the targeted response times. During both flood scenarios, EMS were found to have the greatest reduction in accessibility, with 23% to 47% of residents and workers, respectively, not served. Fire services were seen to be more resilient with only 3% to 9% of residents and workers, respectively, not served. The results for police services were similar to fire services. However, the former have a greater range of response times, meaning these areas represent those that are completely isolated during both flood events. Overall, the proposed methodology quantified vulnerable populations on a partially degraded network, which can be used to develop evacuation plans and emergency response strategies, minimizing disturbances in the network and the number of people affected. / Thesis / Master of Science (MSc)

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.

Flooding is one of the deadliest natural hazards in the world. Forecasting floods in advance can significantly reduce the socio-economic impacts. An accurate and reliable flood forecasting system is heavily dependent on the input precipitation data. Real-time, spatially, and temporally continuous Radar Quantitative Precipitation Estimates (QPEs) is useful precipitation information source. This research aims to investigate the efficacy of American and Canadian weather radar QPEs on hydrological model calibration and validation for flood forecasting in urban and semi-urban watersheds in Canada. A comprehensive review was conducted on the weather Radar network and its’ hydrological applications, challenges, and potential future research in Canada. First, radar QPEs were evaluated to verify the reliability and accuracy as precipitation input for hydrometeorological models. Then, the radar-gauge merging techniques were assessed to select the best method for urban flood forecasting applications. After that, merged Radar QPEs were used as precipitation input for the hydrological models to assess the impact of radar QPEs on hydrological model calibration and validation. Finally, a framework was developed by integrating hydrological and hydraulic models to produce flood forecasts and inundation maps in urbanized watersheds. Results indicated that dual-polarized radar QPEs could be effectively used as a source of precipitation input to hydrological models. The radar-gauge merging enhances both the accuracy and reliability of Radar QPEs, and therefore, the accuracy of streamflow simulation is also improved. Since flood forecasting agencies usually use hydrological models calibrated and validated using gauge data, it is recommended to use bias-corrected Radar QPEs to run existing hydrological models to simulate streamflow to produce flood extent maps. The hydrological and hydraulic models could be integrated into one framework using bias-corrected Radar QPEs to develop a successful flood forecasting system. / Thesis / Doctor of Science (PhD) / Floods are common and increasing deadly natural hazards in the world. Predicting floods in advance using Flood Early Warning System (FEWS) can facilitate flood mitigation. Radar Quantitative Precipitation Estimates (QPEs) can provide real-time, spatially, and temporally continuous precipitation data. This research focuses on bias-correcting and evaluating radar QPEs for hydrologic forecasting. The corrected QPE are applied into a framework connecting hydrological and hydraulic models for operational flood forecasting in urban watersheds in Canada. The key contributions include: (1) Dual-polarized radar QPEs is a useful precipitation input to calibrate, validate and run hydrological models; (2) Radar-gauge merging enhance accuracy and reliability of radar QPEs; (3) Floods could be more accurately predicted by integrating hydrological and hydraulic models in one framework using bias-corrected Radar QPEs; and (4) Gauge-calibrated hydrological models can be run effectively using the bias-corrected radar QPEs. This research will benefit future applications of real-time radar QPEs in operational FEWS.

Water contamination during urban flood events can have a negative impact on human health and the environment. Prior flood studies lack investigation into how GIS can map and analyze this at a large scale (cadastral) level. This  thesis  focused on how GIS can  help map and analyze water contamination risk in urban  areas  using  LiDAR  elevation  data,  at  a  large-scale  (cadastral)  level,  and  symbology  and  flood classification  intervals  specifically  selected  for  contamination  risk.  This  was  done  by  first  completing a literature review about past research and studies  of similar scope. Based on  the findings, a method to map and analyze water contamination risk during sea-based flood scenarios was tested in the Näringen district of Gävle, Sweden. This study area was investigated and flood contamination risk maps were produced  for two different  flood scenarios which illustrated  which properties are vulnerable to flooding and at what depth, what their contamination risk is, and if they are hydrologically connected to the ocean.  The findings from this investigation  are that this method of examining water contamination risk could be useful to planning officials who are in charge of policies relating to land-use. These findings could help guide landuse  or  hazardous  material  storage  regulations  or  restrictions.  To  further  research  in  this  topic,  it  is recommended  that  similar  studies  are  performed  that  use  a  more  detailed  land-use  map  which  has information  on  what  type  and  quantity  of  possible  contaminants  are  stored  on  individual  properties. Furthermore, flood modeling should be employed in place of the flood mapping which was conducted in this thesis.