Coastal Flood Modeling Challenges in Defended Urban Backshores

Coastal flooding is a significant and increasing hazard. There are multiple drivers including rising coastal water levels, more intense hydrologic inputs, shoaling groundwater and urbanization. Accurate coastal flood event prediction poses numerous challenges: representing boundary conditions, depicting terrain and hydraulic infrastructure, integrating spatially and temporally variable overtopping flows, routing overland flows and incorporating hydrologic signals. Tremendous advances in geospatial data quality, numerical modeling and overtopping estimation have significantly improved flood prediction; however, risk assessments do not typically consider the co-occurrence of multiple flooding pathways. Compound flooding refers to the combined effects of marine and hydrologic processes. Alternatively, multiple flooding source–receptor pathways (e.g., groundwater–surface water, overtopping–overflow, surface–sewer flow) may simultaneously amplify coastal hazard and vulnerability. Currently, there is no integrated framework considering compound and multi-pathway flooding processes in a unified approach. State-of-the-art urban coastal flood modeling methods and research directions critical to developing an integrated framework for explicitly resolving multiple flooding pathways are presented.

Daily streamflow forecasting for Paraíba do Sul river using machine learning methods with hydrologic inputs

The Paraíba do Sul river flows through the most important industrial region of Brazil and its basin is characterized by conflicts of multiple uses of its water resources. The prediction of its natural flow has strategic value for water management in this basin. This research investigates the applicability of the two machine learning methods (Random Forest and Artificial Neural Networks) for daily streamflow forecasting of the Paraíba do Sul River at lead times of 1-7 days. The impact of fluviometric and pluviometric data from other basin sites on the quality of the forecast is also evaluated.

PERSiST: a flexible rainfall-runoff modelling toolkit for use with the INCA family of models

Runoff generation processes and pathways vary widely between catchments. Credible simulations of solute and pollutant transport in surface waters are dependent on models which facilitate appropriate, catchment-specific representations of perceptual models of the runoff generation process. Here, we present a flexible, semi-distributed landscape-scale rainfall-runoff modelling toolkit suitable for simulating a broad range of user-specified perceptual models of runoff generation and stream flow occurring in different climatic regions and landscape types. PERSiST (the Precipitation, Evapotranspiration and Runoff Simulator for Solute Transport) is designed for simulating present-day hydrology; projecting possible future effects of climate or land use change on runoff and catchment water storage; and generating hydrologic inputs for the Integrated Catchments (INCA) family of models. PERSiST has limited data requirements and is calibrated using observed time series of precipitation, air temperature and runoff at one or more points in a river network. Here, we apply PERSiST to the river Thames in the UK and describe a Monte Carlo tool for model calibration, sensitivity and uncertainty analysis.

Upper Pleistocene to Holocene peatland evolution in Southern Brazilian highlands as depicted by radar stratigraphy, sedimentology and palynology

Paleoenvironmental interpretation of proxy data derived from peatlands is largely based upon an evolutionary model for ombrotrophic bogs, in which peat accumulates in still environments. Reports on proxies obtained from minerotrophic fens, where hydrologic inputs are variable, are less common. In this study, a highland peatland in southern Brazil is presented through ground penetrating radar (GPR) and sedimentological, palynological and geochronologic data. The radar stratigraphic interpretation suggests a relatively complex history of erosion and deposition at the site since the beginning of Marine Isotope Stage 3 (MIS 3) interstadial period. In spite of this, radar stratigraphic and palynologic interpretations converge. Electromagnetic reflections tend to group in clusters that show lateral coherence and correlate with different sediment types, while pollen grains abound and are well preserved. As a result, the study of minerotrophic fens provides a source of proxies, suggesting that ombrotrophic bogs are not the only reliable source of data in wetlands for palynological analysis.

Hydrologic dynamics and ecosystem structure

Ecohydrology is the science that studies the mutual interaction between the hydrological cycle and ecosystems. Such an interaction is especially intense in water-controlled ecosystems, where water may be a limiting factor, not only because of its scarcity, but also because of its intermittent and unpredictable appearance. Hydrologic dynamics is shown to be a crucial factor for ecological patterns and processes. The probabilistic structure of soil moisture in time and space is presented as the key linkage between soil, climate and vegetation dynamics. Nutrient cycles, vegetation coexistence and plant response to environmental conditions are all intimately linked to the stochastic fluctuation of the hydrologic inputs driving an ecosystem.