Exploring the Factors Controlling the Error Characteristics of the Surface Water and Ocean Topography Mission Discharge Estimates

The Surface Water and Ocean Topography (SWOT) satellite mission will measure river width, water surface elevation, and slope for rivers wider than 50–100 m. SWOT observations will enable estimation of river discharge by using simple flow laws such as the Manning-Strickler equation, complementing in situ streamgages. Several discharge inversion algorithms designed to compute unobserved flow law parameters (e.g., friction coefficient and bathymetry) have been proposed, but to date, a systematic assessment of factors controlling algorithm performance has not been conducted. Here, we assess the performance of the five algorithms that are expected to be used in the construction of the SWOT product. To perform this assessment, we used synthetic SWOT observations created with hydraulic model output corrupted with SWOT-like error. Prior information provided to the algorithms was purposefully limited to an estimate of mean annual flow (MAF), designed to produce a “worst case” benchmark. Prior MAF error was an important control on algorithm performance, but discharge estimates produced by the algorithms are less biased than the MAF; thus, the discharge algorithms improve on the prior. We show for the first time that accuracy and frequency of remote sensing observations are less important than prior bias, hydraulic variability among reaches, and flow law accuracy in governing discharge algorithm performance. The discharge errors and error sensitivities reported herein are a bounding benchmark, representing worst possible expected errors and error sensitivities. This study lays the groundwork to develop predictive power of algorithm performance, and thus map the global distribution of worst-case SWOT discharge accuracy

Engaging the user community for advancing societal applications of the surface water ocean topography mission

Scheduled for launch in 2021, the Surface Water and Ocean Topography (SWOT) mission will be a truly unique mission that will provide high-temporal-frequency maps of surface water extents and elevation variations of global water bodies (lakes/reservoirs, rivers, estuaries, oceans, and sea ice) at higher spatial resolution than is available with current technologies (Biancamaria et al. 2016; Alsdorf et al. 2007). The primary instrument on SWOT is based on a Ka-band radar interferometer (KaRIN), which uses radar interferometery technology. The satellite will fly two radar antennas at either end of a 10-m (33 ft) mast, allowing it to measure the elevation of the surface along a 120-km (75 mi)-wide swath below. The availability of high-frequency and high-resolution maps of elevations and extents for surface water bodies and oceans will present unique opportunities to address numerous societally relevant challenges around the globe (Srinivasan et al. 2015). These opportunities may include such diverse and far-ranging applications as fisheries management, flood inundation mapping/risk mitigation/forecasting, wildlife conservation, global data assimilation for improving forecast of ocean tides and weather, reservoir management, climate change impacts and adaptation, and river discharge estimation, among others

Evaluating the potential for measuring river discharge from space

Numerous studies have demonstrated the potential usefulness of river hydraulic data obtained from satellites in developing general approaches to tracking floods and changes in river discharge from space. Few studies, however, have attempted to estimate the magnitude of discharge in rivers entirely from remotely obtained information. The present study uses multiple-regression analyses of hydraulic data from more than 1000 discharge measurements, ranging in magnitude from over 200,000 to less than 1 m3/s, to develop multi-variate river discharge estimating equations that use various combinations of potentially observable variables to estimate river discharge. Uncertainty analysis indicates that existing satellite-based sensors can measure water-surface width (or surface area), water-surface elevation, and potentially the surface velocity of rivers with accuracies sufficient to provide estimates of discharge with average uncertainty of less than 20%. Development and validation of multi-variate rating equations that are applicable to the full range of rivers that can be observed from satellite sensors, development of techniques to accurately estimate the average depth in rivers from stage measurements, and development of techniques to accurately estimate the average velocity in rivers from surface-velocity measurements will be key to successful prediction of discharge from satellite observations

Sleep is Just a Bad Habit = Dormir es un mal hábito

Modern architecture is dead. The spirit of modern architecture has evaporated. These two ideas, raised by critics such as Charles Jencks were at one point generally believed to be true. This thesis, in part, explores the ambiguity that exists around these issues and its relationship to my own work. The modern spirit refuses to disappear completely and modern architecture survives in many parts of the world. My work as an artist is not intended as a nostalgic review of these alleged losses; through images borrowed from modernity, through fictional stories, texts and cultural hybrids, my work considers the possible meanings of this hybridized, polluted, yet still desirable modernity. Using these topics, I will discuss the specific research carried out during the development of four installations exhibited over the course of the last two years at Stony Brook University galleries and other venues abroad: the project Sleep Is Just A Bad Habit has strong ties to two projects by Buckminster Fuller and his obsession with progress, time and the future; Closer Than We Think connects futuristic architecture and design from the 50s, 60s and 70s with a circular idea of time and with imagery of the future imagined in those years; the death of modern architecture and the iconic housing project Pruit Igoe by Minoru Yamasaki are the basis for the piece Superbloques in its different versions; Circa 1954 allows me to explore the relationship between text and art after Magritte's Ceci n'est pas une pipe and the idea of authorship and the author's signature. Referecia: Jencks, Charles. What is Post – Modernism? Academy Editions, London, 1986. P. 1

Extreme rainfall, vulnerability and risk: a continental-scale assessment for South America

Extreme weather continues to preoccupy society as a formidable public safety concern bearing huge economic costs. While attention has focused on global climate change and how it could intensify key elements of the water cycle such as precipitation and river discharge, it is the conjunction of geophysical and socioeconomic forces that shapes human sensitivity and risks to weather extremes. We demonstrate here the use of high-resolution geophysical and population datasets together with documentary reports of rainfall-induced damage across South America over a multi-decadal, retrospective time domain (1960–2000). We define and map extreme precipitation hazard, exposure, affectedpopulations, vulnerability and risk, and use these variables to analyse the impact of floods as a water security issue. Geospatial experiments uncover major sources of risk from natural climate variability and population growth, with change in climate extremes bearing a minor role. While rural populations display greatest relative sensitivity to extreme rainfall, urban settings show the highest rates of increasing risk. In the coming decades, rapid urbanization will make South American cities the focal point of future climate threats but also an opportunity for reducing vulnerability, protecting lives and sustaining economic development through both traditional and ecosystem-based disaster risk management systems

QCam: sUAS-Based Doppler Radar for Measuring River Discharge

The U.S. Geological Survey is actively investigating remote sensing of surface velocity and river discharge (discharge) from satellite-, high altitude-, small, unmanned aircraft systems- (sUAS or drone), and permanent (fixed) deployments. This initiative is important in ungaged basins and river reaches that lack the infrastructure to deploy conventional streamgaging equipment. By coupling alternative discharge algorithms with sensors capable of measuring surface velocity, streamgage networks can be established in regions where data collection was previously impractical or impossible. To differentiate from satellite or high-altitude platforms, near-field remote sensing is conducted from sUAS or fixed platforms. QCam is a Doppler (velocity) radar mounted and integrated on a 3DR© Solo sUAS. It measures the along-track surface velocity by spot dwelling in a river cross section at a vertical where the maximum surface velocity is recorded. The surface velocity is translated to a mean-channel (mean) velocity using the probability concept (PC), and discharge is computed using the PC-derived mean velocity and cross-sectional area. Factors including surface-scatterer quality, flight altitude, propwash, wind drift, and sample duration may affect the radar-returns and the subsequent computation of mean velocity and river discharge. To evaluate the extensibility of the method, five science flights were conducted on four rivers of varying size and dynamics and included the Arkansas River, Colorado (CO), USA (two events); Salcha River near Salchaket, Alaska (AK), USA; South Platte River, CO, USA; and the Tanana River, AK, USA. QCam surface velocities and river discharges were compared to conventional streamgaging methods, which represented truth. QCam surface velocities for the Arkansas River, Salcha River, South Platte River, and Tanana River were 1.02 meters per second (m/s) and 1.43 m/s; 1.58 m/s; 0.90 m/s; and 2.17 m/s, respectively. QCam discharges (and percent differences) were 9.48 (0.3%) and 20.3 cubic meters per second (m3/s) (2.5%); 62.1 m3/s (−10.4%); 3.42 m3/s (7.3%), and 1579 m3/s (−18.8%). QCam results compare favorably with conventional streamgaging and are a viable near-field remote sensing technology that can be operationalized to deliver real-time surface velocity, mean velocity, and river discharge, if cross-sectional area is available