Mark A. Trigg

Estimating River Depth From Remote Sensing Swath Interferometry Measurements of River Height, Slope, and Width

The Surface Water and Ocean Topography (SWOT) mission is a swath mapping radar interferometer that would provide new measurements of inland water surface elevation (WSE) for rivers, lakes, wetlands, and reservoirs. SWOT WSE estimates would provide a source of information for characterizing streamflow globally and would complement existing in situ gage networks. In this paper, we evaluate the accuracy of river discharge estimates that would be obtained from SWOT measurements over the Ohio river and eleven of its major tributaries within the context of a virtual mission (VM). SWOT VM measurements are obtained by using an instrument measurement model coupled to simulated WSE from the hydrodynamic model LISFLOOD-FP, using USGS streamflow gages as boundary conditions and validation data. Most model pixels were estimated two or three times per 22-day orbit period. These measurements are then input into an algorithm to obtain estimates of river depth and discharge. The algorithm is based on Mannings equation, in which river width and slope are obtained from SWOT, and roughness is estimated a priori. SWOT discharge estimates are compared to the discharge simulated by LISFLOOD-FP. Instantaneous discharge estimates over the one-year evaluation period had median normalized root mean square error of 10.9%, and 86% of all instantaneous errors are less than 25%.

Development of the Global Width Database for Large Rivers

River width is a fundamental parameter of river hydrodynamic simulations, but no global-scale river width database based on observed water bodies has yet been developed. Here we present a new algorithm that automatically calculates river width from satellite-based water masks and flow direction maps. The Global Width Database for Large Rivers (GWD-LR) is developed by applying the algorithm to the SRTM Water Body Database and the HydroSHEDS flow direction map. Both bank-to-bank river width and effective river width excluding islands are calculated for river channels between 60S and 60N. The effective river width of GWD-LR is compared with existing river width databases for the Congo and Mississippi Rivers. The effective river width of the GWD-LR is slightly narrower compared to the existing databases, but the relative difference is within ±20% for most river channels. As the river width of the GWD-LR is calculated along the river channels of the HydroSHEDS flow direction map, it is relatively straightforward to apply the GWD-LR to global and continental-scale river modeling.

Automatic Genetic Optimization Approach to Two-Dimensional Blade Profile Design for Steam Turbines

In this paper a systematic approach to the optimization of two-dimensional blade profiles is presented. A genetic optimizer has been developed that modifies the blade profile and calculates its profile loss. This process is automatic, producing profile designs significantly faster and with significantly lower loss than has previously been possible. The optimizer developed uses a genetic algorithm to optimize a two-dimensional profile, defined using 17 parameters, for minimum loss with a given flow condition. The optimizer works with a population of two-dimensional profiles with varied parameters. A CFD mesh is generated for each profile, and the result is analyzed using a two-dimensional blade-to-blade solver, written for steady viscous compressible flow, to determine profile loss. The loss is used as the measure of a profile`s fitness. The optimizer uses this information to select the members of the next population, applying crossovers, mutations, and elitism in the process. Using this method, the optimizer tends toward the best values for the parameters defining the profile with minimum loss.

The credibility challenge for global fluvial flood risk analysis

Quantifying flood hazard is an essential component of resilience planning, emergency response, and mitigation, including insurance. Traditionally undertaken at catchment and national scales, recently, efforts have intensified to estimate flood risk globally to better allow consistent and equitable decision making. Global flood hazard models are now a practical reality, thanks to improvements in numerical algorithms, global datasets, computing power, and coupled modelling frameworks. Outputs of these models are vital for consistent quantification of global flood risk and in projecting the impacts of climate change. However, the urgency of these tasks means that outputs are being used as soon as they are made available and before such methods have been adequately tested. To address this, we compare multi-probability flood hazard maps for Africa from six global models and show wide variation in their flood hazard, economic loss and exposed population estimates, which has serious implications for model credibility. While there is around 30%–40% agreement in flood extent, our results show that even at continental scales, there are significant differences in hazard magnitude and spatial pattern between models, notably in deltas, arid/semi-arid zones and wetlands. This study is an important step towards a better understanding of modelling global flood hazard, which is urgently required for both current risk and climate change projections.

Validation of River Flows in HadGEM1 and HadCM3 with the TRIP River Flow Model

AbstractThe Total Runoff Integrating Pathways (TRIP) global river-routing scheme in the third climate configuration of the Met Office Unified Model (HadCM3) and the newer Hadley Centre Global Environmental Model version 1 (HadGEM1) general circulation models (GCMs) have been validated against long-term average measured river discharge data from 40 stations on 24 major river basins from the Global Runoff Data Centre (GRDC). TRIP was driven by runoff produced directly by the two GCMs in order to assess both the skill of river flows produced within GCMs in general and to test this as a method for validating large-scale hydrology in GCMs. TRIP predictions of long-term-averaged annual discharge were improved at 28 out of 40 gauging stations on 24 of the world’s major rivers in HadGEM1 compared to HadCM3, particularly for low- and high-latitude basins, with predictions ranging from “good” (within 20% of observed values) to “poor” (biases exceeding 50%). For most regions, the modeled annual average river flows t...

Perspectives on open access high resolution digital elevation models to produce global flood hazard layers

Global flood hazard models have recently become a reality thanks to the release of open access global digital elevation models, the development of simplified and highly efficient flow algorithms, and the steady increase in computational power. In this commentary we argue that although the availability of open access global terrain data has been critical in enabling the development of such models, the relatively poor resolution and precision of these data now limit significantly our ability to estimate flood inundation and risk for the majority of the planet’s surface. The difficulty of deriving an accurate ‘bare-earth’ terrain model due to the interaction of vegetation and urban structures with the satellite-based remote sensors means that global terrain data are often poorest in the areas where people, property (and thus vulnerability) are most concentrated. Furthermore, the current generation of open access global terrain models are over a decade old and many large floodplains, particularly those in developing countries, have undergone significant change in this time. There is therefore a pressing need for a new generation of high resolution and high vertical precision open access global digital elevation models to allow significantly improved global flood hazard models to be developed.

Hydrology: The dynamics of Earth's surface water

High-resolution satellite mapping of Earths surface water during the past 32 years reveals changes in the planets water systems, including the influence of natural cycles and human activities. See Letter p.418 The distribution of surface water has been mapped globally, and local-to-regional studies have tracked changes over time. But to date, there has been no global and methodologically consistent quantification of changes in surface water over time. Jean-Francois Pekel and colleagues have analysed more than three million Landsat images to quantify month-to-month changes in surface water at a resolution of 30 metres and over a 32-year period. They find that surface waters have declined by almost 90,000 square kilometres—largely in the Middle East and Central Asia—but that surface waters equivalent to about twice that area have been created elsewhere. Drought, reservoir creation and water extraction appear to have driven most of the changes in surface water over the past decades.

Estimating seepage flux from ephemeral stream channels using surface water and groundwater level data

Seepage flux from ephemeral streams can be an important component of the water balance in arid and semiarid regions. An emerging technique for quantifying this flux involves the measurement and simulation of a flood wave as it moves along an initially dry channel. This study investigates the usefulness of including surface water and groundwater data to improve model calibration when using this technique. We trialed this approach using a controlled flow event along a 1387 m reach of artificial stream channel. Observations were then simulated using a numerical model that combines the diffusion-wave approximation of the Saint-Venant equations for streamflow routing, with Philips infiltration equation and the groundwater flow equation. Model estimates of seepage flux for the upstream segments of the study reach, where streambed hydraulic conductivities were approximately 101 m d−1, were on the order of 10−4 m3 d−1 m−2. In the downstream segments, streambed hydraulic conductivities were generally much lower but highly variable (∼10−3 to 10−7 m d−1). A Latin Hypercube Monte Carlo sensitivity analysis showed that the flood front timing, surface water stage, groundwater heads, and the predicted streamflow seepage were most influenced by specific yield. Furthermore, inclusion of groundwater data resulted in a higher estimate of total seepage estimates than if the flood front timing were used alone.

Progress Toward Hyperresolution Models of Global Flood Hazard

Abstract Flood modeling at global scales represents a revolution in hydraulic science and has the potential to transform decision-making and risk management in a wide variety of fields. Such modeling draws on a rich heritage of algorithm and data set development in hydraulic modeling over the last 20 years, but conceptually the challenges of global flood modeling are the same as those faced at local and reach scales. This chapter therefore examines recent progress in the field of global flood hazard modeling and, in particular, looks at the development of so-called ‘hyperresolution’ models, defined here as those with a spatial resolution of 1 km or less. This chapter begins by examining how over the last 10 years the field of two-dimensional hydraulic modeling has moved rapidly from the study of single river reaches perhaps 10–60 km in length or restricted local areas of a few kilometers squared, to regional, continental, or even global scale models. This rapid advance has been enabled by three parallel developments: the discovery of new computationally efficient algorithms for solving 2D flow fields, advances in computing power and architectures, and the development of bespoke versions of global terrain data sets optimized for global flood modeling. To illustrate what is now possible this chapter uses the example of a recently developed hyperresolution model: SSBNflow. This is a 1/1200 arc second spatial resolution (∼90 m at the equator) global flood inundation model that solves the local inertial (i.e., a true hydrodynamic) form of the shallow water equations. The hydraulic engine is a clone of the well-known LISFLOOD-FP model. We describe the background to this model and its structure and report the results of a number of extensive validation tests. These show the model to perform well, within the best cases the performance, approaching that of a bespoke model built with local (rather than global) data. We describe how the hazard data can be used to produce global flood risk estimates, and, finally, we provide an extensive discussion of model limitations. Although this is still a young field, the progress, to date, has been rapid. Such models are already making a huge contribution to such fields as disaster risk reduction, disaster forecasting, risk finance, and humanitarian relief efforts, and the prospects for further improvements in model skill are very good.

Domestic water consumption in rural Guatemala

Water-supply projects make assumptions about how much water people need and, therefore, how much they consume- quantities rarely checked out in the field. One group in Guatemala preferred to rely on hard facts- and managed to find them the easy way.