Colin J. Gleason

Toward global mapping of river discharge using satellite images and at-many-stations hydraulic geometry

Significance Political and practical realities limit our knowledge of water resources in many parts of the world. Here, we present a radically different approach for quantitative remote sensing of river discharge (flow rate) that is enabled by advancing a classic theory of river hydraulics and adapting it for use with satellite or aerial images. Because no ground-based information is required, the approach holds promise for addressing pressing societal, ecological, and scientific problems through global mapping of river flow. Rivers provide critical water supply for many human societies and ecosystems, yet global knowledge of their flow rates is poor. We show that useful estimates of absolute river discharge (in cubic meters per second) may be derived solely from satellite images, with no ground-based or a priori information whatsoever. The approach works owing to discovery of a characteristic scaling law uniquely fundamental to natural rivers, here termed a river’s at-many-stations hydraulic geometry. A first demonstration using Landsat Thematic Mapper images over three rivers in the United States, Canada, and China yields absolute discharges agreeing to within 20–30% of traditional in situ gauging station measurements and good tracking of flow changes over time. Within such accuracies, the door appears open for quantifying river resources globally with repeat imaging, both retroactively and henceforth into the future, with strong implications for water resource management, food security, ecosystem studies, flood forecasting, and geopolitics.

Efficient meltwater drainage through supraglacial streams and rivers on the southwest Greenland ice sheet

Significance Meltwater runoff from the Greenland ice sheet is a key contributor to global sea level rise and is expected to increase in the future, but it has received little observational study. We used satellite and in situ technologies to assess surface drainage conditions on the southwestern ablation surface after an extreme 2012 melting event. We conclude that the ice sheet surface is efficiently drained under optimal conditions, that digital elevation models alone cannot fully describe supraglacial drainage and its connection to subglacial systems, and that predicting outflow from climate models alone, without recognition of subglacial processes, may overestimate true meltwater release from the ice sheet. Thermally incised meltwater channels that flow each summer across melt-prone surfaces of the Greenland ice sheet have received little direct study. We use high-resolution WorldView-1/2 satellite mapping and in situ measurements to characterize supraglacial water storage, drainage pattern, and discharge across 6,812 km2 of southwest Greenland in July 2012, after a record melt event. Efficient surface drainage was routed through 523 high-order stream/river channel networks, all of which terminated in moulins before reaching the ice edge. Low surface water storage (3.6 ± 0.9 cm), negligible impoundment by supraglacial lakes or topographic depressions, and high discharge to moulins (2.54–2.81 cm⋅d−1) indicate that the surface drainage system conveyed its own storage volume every <2 d to the bed. Moulin discharges mapped inside ∼52% of the source ice watershed for Isortoq, a major proglacial river, totaled ∼41–98% of observed proglacial discharge, highlighting the importance of supraglacial river drainage to true outflow from the ice edge. However, Isortoq discharges tended lower than runoff simulations from the Modèle Atmosphérique Régional (MAR) regional climate model (0.056–0.112 km3⋅d−1 vs. ∼0.103 km3⋅d−1), and when integrated over the melt season, totaled just 37–75% of MAR, suggesting nontrivial subglacial water storage even in this melt-prone region of the ice sheet. We conclude that (i) the interior surface of the ice sheet can be efficiently drained under optimal conditions, (ii) that digital elevation models alone cannot fully describe supraglacial drainage and its connection to subglacial systems, and (iii) that predicting outflow from climate models alone, without recognition of subglacial processes, may overestimate true meltwater export from the ice sheet to the ocean.

A review of remote sensing of forest biomass and biofuel: options for small-area applications.

Forests have served as a primary reservoir of terrestrial carbon and have long been investigated in the global climate change context. In addition, increased exposure in the public domain of climate change issues has caused greater interest in the role of forests in the global energy balance. Researchers have been investigating the use of forests as carbon sequestration systems, as well as using forest products for conversion into biofuels. Remote sensing has been widely utilized as a cost-effective tool to provide forest baseline data (e.g., biomass) for effective and efficient forest management. Forest biomass is one of the forest parameters that is widely investigated using remote sensing because biomass is directly related to the productivity of forests and provides valuable information that is necessary for understanding ecosystem functions and carbon cycling. In this paper, we review remote sensing of forest biomass, focusing on recent advances and applications (published after 2000). We also explore the challenges of using forest biomass as biofuel, a topic that is often neglected in remote sensing papers.

Downstream Yangtze River levels impacted by Three Gorges Dam

Changes in the Yangtze River level induced by large-scale human water regulation have profound implications on the inundation dynamics of surrounding lakes/wetlands and the integrity of related ecosystems. Using in situ measurements and hydrological simulation, this study reveals an altered Yangtze level regime downstream from the Three Gorges Dam (TGD) to the Yangtze estuary in the East China Sea as a combined result of (i) TGDs flow regulation and (ii) Yangtze channel erosion due to reduced sediment load. During the average annual cycle of TGDs regular flow control in 2009–2012, downstream Yangtze level variations were estimated to have been reduced by 3.9–13.5% at 15 studied gauging stations, manifested as evident level decrease in fall and increase in winter and spring. The impacts on Yangtze levels generally diminished in a longitudinal direction from the TGD to the estuary, with a total time lag of ~9–12 days. Chronic Yangtze channel erosion since the TGD closure has lowered water levels in relation to flows at most downstream stations, which in turn counteracts the anticipated level increase by nearly or over 50% in winter and spring while reinforcing the anticipated level decrease by over 20% in fall. Continuous downstream channel erosion in the near future may further counteract the benefit of increased Yangtze levels during TGDs water supplement in winter and accelerate the receding of inundation areas/levels of downstream lakes in fall.

Retrieval of river discharge solely from satellite imagery and at‐many‐stations hydraulic geometry: Sensitivity to river form and optimization parameters

Knowledge of river discharge is critically important for water resource management, climate modeling, and improved understanding of the global water cycle, yet discharge is poorly known in much of the world. Remote sensing holds promise to mitigate this gap, yet current approaches for quantitative retrievals of river discharge require in situ calibration or a priori knowledge of river hydraulics, limiting their utility in unmonitored regions. Recently, Gleason and Smith (2014) demonstrated discharge retrievals within 20–30% of in situ observations solely from Landsat TM satellite images through discovery of a river-specific geomorphic scaling phenomenon termed at-many-stations hydraulic geometry (AMHG). This paper advances the AMHG discharge retrieval approach via additional parameter optimizations and validation on 34 gauged rivers spanning a diverse range of geomorphic and climatic settings. Sensitivity experiments reveal that discharge retrieval accuracy varies with river morphology, reach averaging procedure, and optimization parameters. Quality of remotely sensed river flow widths is also important. Recommended best practices include a proposed global parameter set for use when a priori information is unavailable. Using this global parameterization, AMHG discharge retrievals are successful for most investigated river morphologies (median RRMSE 33% of in situ gauge observations), except braided rivers (median RRMSE 74%), rivers having low at-a-station hydraulic geometry b exponents (reach-averaged b   1000%). Excluding such environments, 26–41% RRMSE agreement between AMHG discharge retrievals and in situ gauge observations suggests AMHG can meaningfully address global discharge knowledge gaps solely from repeat satellite imagery.

An intercomparison of remote sensing river discharge estimation algorithms from measurements of river height, width, and slope

The Surface Water and Ocean Topography (SWOT) satellite mission planned for launch in 2020 will map river elevations and inundated area globally for rivers >100 m wide. In advance of this launch, we here evaluated the possibility of estimating discharge in ungauged rivers using synthetic, daily ‘‘remote sensing’’ measurements derived from hydraulic models corrupted with minimal observational errors. Five discharge algorithms were evaluated, as well as the median of the five, for 19 rivers spanning a range of hydraulic and geomorphic conditions. Reliance upon a priori information, and thus applicability to truly ungauged reaches, varied among algorithms: one algorithm employed only global limits on velocity and depth, while the other algorithms relied on globally available prior estimates of discharge. We found at least one algorithm able to estimate instantaneous discharge to within 35% relative root-mean-squared error (RRMSE) on 14/16 nonbraided rivers despite out-of-bank flows, multichannel planforms, and backwater effects. Moreover, we found RRMSE was often dominated by bias; the median standard deviation of relative residuals across the 16 nonbraided rivers was only 12.5%. SWOT discharge algorithm progress is therefore encouraging, yet future efforts should consider incorporating ancillary data or multialgorithm synergy to improve results.

Hydraulic geometry of natural rivers A review and future directions

The geomorphic relationships known as hydraulic geometry (HG) were first introduced by Leopold and Maddock in 1953, and their application remains critically important for assessing water resources the world over. The practical utility of HG for discharge monitoring, habitat studies, and understanding geomorphic change over time is unquestioned, but its elevation beyond empirically observed relationship to physical principle is not complete, despite universal acceptance of its existence. This review summarizes six decades of HG research while surveying rational, extremal, and empirical attempts to derive HG’s underlying physical principles. In addition, so called non-Leopoldian forms of HG are discussed, expanding HG beyond its original construction to examine a range of research that invokes HG in novel ways. The recent discovery of at-many-stations hydraulic geometry (AMHG) is also discussed in the context of previous HG literature. Finally, some common themes linking disparate HG research communities are described in conjunction with suggestions for possible new directions for HG research in the future.

A Caution on the Use of Surface Digital Elevation Models to Simulate Supraglacial Hydrology of the Greenland Ice Sheet

Digital elevation models (DEMs) of ice surface topography are often used for hydrologic analysis of the Greenland ice sheet (GrIS), but their suitability for this purpose has received little quantitative assessment. We compare remotely sensed maps of supraglacial lakes, rivers, and moulins with their DEM-modeled counterparts, using two moderate-resolution DEMs (SPIRIT DEM and ASTER GDEM) for a ~24 000 km2 area of the southwestern GrIS. We find that modeled hydrological features are critically sensitive to selection of a depression area threshold (a user-specified parameter used to fill noise and/or true topographic depressions in the ice surface DEM), with small depression area thresholds over-predicting observed supraglacial lake abundance and large thresholds under-predicting lake abundance. Few remotely sensed moulins are identified in either DEM, even if a small depression area threshold is used. A standard practice of filling all DEM depressions yields modeled surface flow paths that broadly match remotely sensed supraglacial river networks, but are far less fragmented than reality (owing to moulin capture), raising into question the realism of this standard practice. In sum, moderate-resolution DEMs do hold value for simulating broad-scale hydrography of the GrIS surface, but are critically sensitive to choice of the filling threshold, and insensitive to moulins which also influence supraglacial drainage pattern. Our preliminary analysis suggests using a depression area threshold of 0.1-0.2 km2 for lakes, advises against using DEMs to predict moulin locations, and urges caution when using 100% DEM filling to model flow paths of supraglacial rivers.

Theoretical basis for at-many-stations hydraulic geometry

Citation: Gleason, C. J., & Wang, J.(2015). Theoretical basis for at-many-stations hydraulic geometry. Geophysical Research Letters, 42(17), 7107-7114. doi:10.1002/2015gl064935

A Fusion Approach for Tree Crown Delineation from Lidar Data

This study proposes a multi-step method (the COTH method) to delineate individual tree crowns in dense forest conditions using lidar data, with the intent for the final delineation results to be used in a biomass estimation study. The study was conducted for an even-aged Norway Spruce (Picea abies) plantation containing 188 trees located in Tully, New York, and owned by the State University of New York College of Environmental Science and Forestry (SUNY ESF). Lidar data with a point density of 12.7 points/m 2 was collected in August 2010, and field data were collected to measure tree height and species in August 2010 as well. Field data containing tree height and crown width, an important component of treetop detection, were collected in summer 2006. By combining heuristically (genetic algorithm) optimized object recognition to detect tree crown objects, local maxima filtering with variable window size to detect treetops, and a modified hill climbing algorithm to segment crown objects; treetops were identified with 86.2 percent accuracy and 23.9 percent commission error. The overall areal accuracy of the delineation was 72.5 percent. The automated COTH method represents an improvement in crown delineation accuracy for lidar data.