Stream network analysis and geomorphic flood plain mapping from orbital and suborbital remote sensing imagery application to flood hazard studies in central Texas

The author has identified the following significant results. Development of a quantitative hydrogeomorphic approach to flood hazard evaluation was hindered by (1) problems of resolution and definition of the morphometric parameters which have hydrologic significance, and (2) mechanical difficulties in creating the necessary volume of data for meaningful analysis. Measures of network resolution such as drainage density and basin Shreve magnitude indicated that large scale topographic maps offered greater resolution than small scale suborbital imagery and orbital imagery. The disparity in network resolution capabilities between orbital and suborbital imagery formats depends on factors such as rock type, vegetation, and land use. The problem of morphometric data analysis was approached by developing a computer-assisted method for network analysis. The system allows rapid identification of network properties which can then be related to measures of flood response

Large scale flood risk mapping in data scarce environments: An application for Romania

Large-scale flood risk assessment is essential in supporting national and global policies, emergency operations and land-use management. The present study proposes a cost-efficient method for the large-scale mapping of direct economic flood damage in data-scarce environments. The proposed framework consists of three main stages: (i) deriving a water depth map through a geomorphic method based on a supervised linear binary classification; (ii) generating an exposure land-use map developed from multi-spectral Landsat 8 satellite images using a machine-learning classification algorithm; and (iii) performing a flood damage assessment using a GIS tool, based on the vulnerability (depth-damage) curves method. The proposed integrated method was applied over the entire country of Romania (including minor order basins) for a 100-year return time at 30-m resolution. The results showed how the description of flood risk may especially benefit from the ability of the proposed cost-efficient model to carry out large-scale analyses in data-scarce environments. This approach may help in performing and updating risk assessments and management, taking into account the temporal and spatial changes in hazard, exposure, and vulnerability

Assessment of flood hazard over large geographical areas using data-driven approaches

The mapping of flood hazard can be time and resource consuming, but it is essential for assessing flood risk and for designing strategies to avoid consequences and recover faster in the event of flooding. This generally involves setting up complex numerical hydrologic/hydrodynamic models to simulate the flow of water in river channels and over the floodplains. Although such approach is considered standard, it is not always feasible. For example, it is challenging to simulate floods over large areas, produce a number of scenarios, represent flood mechanisms in a detailed way, and make use of all the data that is increasingly available in the field of water resources. Clearly, flood managers could use more options. Machine learning (i.e., algorithms that learn from data, in contrast to physically-based equations) has been seldomly used until now, but is a good candidate because of simplicity, typically faster runtimes and ability to handle large amounts of data. In combination with geographic information systems attractive tools can potentially be created. The combination of nearly instantaneous results with a web-GIS provides the possibility of near-real time analysis using any modern web browser. This thesis seek for additional clues that can help in the answering of the following questions: can data-driven models live to their expectations in flood hazard assessment? to what extent they offer viable alternatives to standard approaches and what are the concrete advantages and limitations? Several aspects of flood hazard assessment are addressed by developing and employing different state-of-the-art data-driven approaches, namely for the estimation and mapping of areas that may be subject to flooding across geographic scales, their downscaling, their extrapolation and regionalisation, or the transfer between catchments based on physical similarity. In each part of the thesis, the viability of selected methods are demonstrated and possible ways to overcome limitations are highlight

Improving regional flood risk assessment using flood frequency and dendrogeomorphic analyses in mountain catchments impacted by tropical cyclones

River floods frequently occur when tropical cyclones hit land. Nonetheless, systematic, long-term discharge data remain rather scarce in many tropical countries, which prevent proper analysis of peak discharges occurring during floods. The Térraba catchment is the biggest and most dynamic catchment in Costa Rica. In this study, we developed regional flood-frequency analyses combining tree-ring based estimation and measurement of peak discharge at monitoring stations during tropical cyclones to derive flood quartiles. Flood quartiles were combined with the Topographic Wetness Index (TWI) to determine regional flood hazards along floodplains. The flood risk assessment was based on a high-resolution mapping of infrastructure, population density (as a measure of exposure), and a social development index (to represent vulnerability). We show that peak discharge of cycloneinduced floods can be assessed accurately with flood-frequency analyses including dendrogeomorphic reconstructions and systematic discharge measurements. We also show that regional flood risk assessments can be performed in large-scale catchments if both coarse and detailed inputs are used. The results of this study will be useful for the development of flood risk schemes promoting resilience of local populations.Swiss Federal Commission for Scholarships/[ESKAS-Nr 2017.1072]//SuizaMinisterio de Ciencia, Innovación, Tecnología y Telecomunicaciones/[No MICITT-PINN-CON-2-1-4-17-1-002]/MICITT/Costa RicaUniversidad de Costa Rica/[OAICE-187-2017]/UCR/Costa RicaUCR::Vicerrectoría de Docencia::Ciencias Sociales::Facultad de Ciencias Sociales::Escuela de Geografí

Assessing and managing urban riverscapes: integrating physical processes and social-ecological values

2022 Summer.Includes bibliographical references.In the age of the Anthropocene, human influence has spread far and wide across our planet affecting the physical, chemical, and biological condition of the rivers, streams, and floodplains in the urban environment, our "urban riverscapes." The human connection to urban riverscapes includes both the built environment created and accessed by people and the intangible community values that humans place upon flowing water. The value of these benefits encourages stewardship of our waterways by integrating experiential, aesthetic, and cultural attributes that foster appreciation for streams as natural systems in the built environment. However, when poorly managed, human activities adversely impact our natural ecosystems, resulting in less resilient stream systems, poor aesthetics, and unsafe conditions. The research presented in this dissertation asks the following overarching research question: How can managers and practitioners apply multi-scale social-ecological, hydrologic, geomorphologic, and riparian ecological remote sensing and field data to advance urban riverscape management? Four chapters follow from this hypothesis: urban riverscape problems lie on a spectrum of complexity where solutions are often conceivable but difficult to implement. Integrating diverse perspectives and knowledge extends the scope of stakeholder perspectives so that social-ecological context is considered alongside the physical processes that typically characterize riverscapes. This approach entails leveraging existing and new methods to create frameworks that integrate the multi-scale assessment of physical conditions and social-ecological qualities underlying applied riverscape management. I explore the integration of diverse knowledge to enhance management outcomes through the concept of "wicked problems." I analyze the connections between diverse types of knowledge and practices through numerous case studies. My analysis shows how systematically characterizing project attributes, such as the prominence of local government and technical knowledge or the weakness of academia and indigenous knowledge, requires an approach that builds capacity and collaboration within transdisciplinary stakeholder groups. I find that the importance of integrating communities, including under-represented knowledge bases, into urban riverscape management can generate equitable and incremental solutions. To evaluate connections between social values, ecological conditions, and hydrogeomorphic processes, I outline a framework for urban riverscape assessment that advances the practice of managing urban riverscapes facing complex problems. The framework is based upon evaluation across four foundational categories, or facets, critical to the management of urban riverscapes: (1) human connections and values, (2) hydrologic processes and hydraulic characteristics, (3) geomorphic forms and processes, and (4) ecological structure and processes. I structure the framework around three tiers of actionable steps, which tackle the questions: Why are we assessing this riverscape (Tier 1)? What do we need to understand in and along this riverscape (Tier 2)? How will we assess the riverscape to develop that understanding (Tier 3)? I find that the answer to the first question is context-based and dependent upon integrating diverse types of knowledge, while the response to the second question involves examining the functions and values of urban riverscapes through the lens of the four facets and their inter-related processes. Answering the third question requires developing and testing a novel assessment method – the "Urban Riverscape conditions-Based Assessment for management Needs" (URBAN). I base URBAN on riverscape context and on integrating the assessment of facets at multiple scales. I apply the method to a test data set of publicly available and site-specific data across a study area in the Denver metropolitan region to illustrate its overall performance, including its ability to evaluate specific riverscape physical conditions and social-ecological qualities. I find reach typologies combined with urban riverscape characteristics provide tangible management strategies that managers can use to inform planning and decision making. The overarching conclusion of this dissertation is that managing urban riverscapes requires assessment methods that consider scale (spatial, temporal, and topical) and context (both physical and social characteristics), and the use of indicators and metrics that directly support decision-making among interdisciplinary stakeholders. It is possible to move toward this vision by using remote-sensed and field data that provides both social and physical information, to assess the relationship between physical condition and social-ecological values, and to use that information to determine where and how to prioritize management strategies for urban riverscapes

Enhancing Operational Flood Detection Solutions through an Integrated Use of Satellite Earth Observations and Numerical Models

Among natural disasters floods are the most common and widespread hazards worldwide (CRED and UNISDR, 2018). Thus, making communities more resilient to flood is a priority, particularly in large flood-prone areas located in emerging countries, because the effects of extreme events severely setback the development process (Wright, 2013). In this context, operational flood preparedness requires novel modeling approaches for a fast delineation of flooding in riverine environments. Starting from a review of advances in the flood modeling domain and a selection of the more suitable open toolsets available in the literature, a new method for the Rapid Estimation of FLood EXtent (REFLEX) at multiple scales (Arcorace et al., 2019) is proposed. The simplified hydraulic modeling adopted in this method consists of a hydro-geomorphological approach based on the Height Above the Nearest Drainage (HAND) model (Nobre et al., 2015). The hydraulic component of this method employs a simplified version of fluid mechanic equations for natural river channels. The input runoff volume is distributed from channel to hillslope cells of the DEM by using an iterative flood volume optimization based on Manning\u2019s equation. The model also includes a GIS-based method to expand HAND contours across neighbor watersheds in flat areas, particularly useful in flood modeling expansion over coastal zones. REFLEX\u2019s flood modeling has been applied in multiple case studies in both surveyed and ungauged river basins. The development and the implementation of the whole modeling chain have enabled a rapid estimation of flood extent over multiple basins at different scales. When possible, flood modeling results are compared with reference flood hazard maps or with detailed flood simulations. Despite the limitations of the method due to the employed simplified hydraulic modeling approach, obtained results are promising in terms of flood extent and water depth. Given the geomorphological nature of the method, it does not require initial and boundary conditions as it is in traditional 1D/2D hydraulic modeling. Therefore, its usage fits better in data-poor environments or large-scale flood modeling. An extensive employment of this slim method has been adopted by CIMA Research Foundation researchers for flood hazard mapping purposes over multiple African countries. As collateral research, multiple types of Earth observation (EO) data have been employed in the REFLEX modeling chain. Remotely sensed data from the satellites, in fact, are not only a source to obtain input digital terrain models but also to map flooded areas. Thus, in this work, different EO data exploitation methods are used for estimating water extent and surface height. Preliminary results by using Copernicus\u2019s Sentinel-1 SAR and Sentinel-3 radar altimetry data highlighted their potential mainly for model calibration and validation. In conclusion, REFLEX combines the advantages of geomorphological models with the ones of traditional hydraulic modeling to ensure a simplified steady flow computation of flooding in open channels. This work highlights the pros and cons of the method and indicates the way forward for future research in the hydro-geomorphological domain