Colin J. Gleason

Bio: Colin J. Gleason is an academic researcher from University of Massachusetts Amherst. The author has contributed to research in topics: Greenland ice sheet & Meltwater. The author has an hindex of 22, co-authored 55 publications receiving 1744 citations. Previous affiliations of Colin J. Gleason include State University of New York at Purchase & University of California, Los Angeles.

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

Abstract: 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.

Abstract: 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 km(2) 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 Modele Atmospherique Regional (MAR) regional climate model (0.056-0.112 km(3)⋅d(-1) vs. ∼0.103 km(3)⋅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.

Global Reconstruction of Naturalized River Flows at 2.94 Million Reaches

Abstract: Spatiotemporally continuous global river discharge estimates across the full spectrum of stream orders are vital to a range of hydrologic applications, yet they remain poorly constrained. Here we present a carefully designed modeling effort (Variable Infiltration Capacity land surface model and Routing Application for Parallel computatIon of Discharge river routing model) to estimate global river discharge at very high resolutions. The precipitation forcing is from a recently published 0.1° global product that optimally merged gauge-, reanalysis-, and satellite-based data. To constrain runoff simulations, we use a set of machine learning-derived, global runoff characteristics maps (i.e., runoff at various exceedance probability percentiles) for grid-by-grid model calibration and bias correction. To support spaceborne discharge studies, the river flowlines are defined at their true geometry and location as much as possible-approximately 2.94 million vector flowlines (median length 6.8 km) and unit catchments are derived from a high-accuracy global digital elevation model at 3-arcsec resolution (~90 m), which serves as the underlying hydrography for river routing. Our 35-year daily and monthly model simulations are evaluated against over 14,000 gauges globally. Among them, 35% (64%) have a percentage bias within ±20% (±50%), and 29% (62%) have a monthly Kling-Gupta Efficiency ≥0.6 (0.2), showing data robustness at the scale the model is assessed. This reconstructed discharge record can be used as a priori information for the Surface Water and Ocean Topography satellite mission's discharge product, thus named "Global Reach-level A priori Discharge Estimates for Surface Water and Ocean Topography". It can also be used in other hydrologic applications requiring spatially explicit estimates of global river flows.

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

Abstract: 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 125% SWOT discharge algorithm progress is therefore encouraging, yet future efforts should consider incorporating ancillary data or multialgorithm synergy to improve results

The Ensemble Kalman Filter: Theoretical formulation and practical implementation

Abstract: The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.

The Water Balance

Abstract: The ultimate source of water for plants is precipitation; rain falling upon soil penetrates it at a rate depending upon the physical properties of that particular soil; snow and hail do the same after melting. If the rate of rainfall or the rate of production of water by melting exceeds the infiltration rate, then surface runoff occurs and the excess water drains into streams and eventually reaches the sea. That water which penetrates the soil replenishes the soil reservoir and when this is filled to capacity (see chapter 3) the surplus drains through into the aquifers. These are strata such as sand or chalk which can hold substantial quantities of recoverable water. Water held in the soil reservoir is drawn into plant roots and up their stems to be evaporated from the leaves back into the atmosphere, where it rejoins water evaporated from the sea, lakes and rivers and from the surface of wet soil. This so-called hydrological cycle (figure 1.2) depends for its continuance upon energy derived from the sun’s radiation and as will be shown in later chapters its rate is governed largely by meteorological factors.

Anthropogenic stresses on the world’s big rivers

Abstract: The world’s big rivers and their floodplains were central to development of civilization and are now home to c. 2.7 billion people. They are economically vital whilst also constituting some of the most diverse habitats on Earth. However, a number of anthropogenic stressors, including large-scale damming, hydrological change, pollution, introduction of non-native species and sediment mining, challenge their integrity and future, as never before. The rapidity and extent of such change is so great that large-scale, and potentially irreparable, transformations may ensue in periods of years to decades, with ecosystem collapse being possible in some big rivers. Prioritizing the fate of the world’s great river corridors on an international political stage is imperative. Future sustainable management, and establishment of environmental flow requirements for the world’s big rivers, must be supported through co-ordinated international funding, and trans-continental political agreement to monitor these rivers, finance their continual upkeep and help ameliorate increasing anthropogenic pressures. To have any effect, all of these must be set within an inclusive governance framework across scales, organizations and local populace. Stressors such as large-scale damming, hydrological change, pollution, the introduction of non-native species and sediment mining are challenging the integrity and future of large rivers, according to a synthesis of the literature on the 32 biggest rivers.

Trading-off Fish Biodiversity, Food Security and Hydropower in the Mekong River Basin

Abstract: The Mekong River Basin, site of the biggest inland fishery in the world, is undergoing massive hydropower development. Planned dams will block critical fish migration routes between the river's downstream floodplains and upstream tributaries. Here we estimate fish biomass and biodiversity losses in numerous damming scenarios using a simple ecological model of fish migration. Our framework allows detailing trade-offs between dam locations, power production, and impacts on fish resources. We find that the completion of 78 dams on tributaries, which have not previously been subject to strategic analysis, would have catastrophic impacts on fish productivity and biodiversity. Our results argue for reassessment of several dams planned, and call for a new regional agreement on tributary development of the Mekong River Basin.

A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems

Abstract: Remote sensing-based methods of aboveground biomass (AGB) estimation in forest ecosystems have gained increased attention, and substantial research has been conducted in the past three decades. This paper provides a survey of current biomass estimation methods using remote sensing data and discusses four critical issues – collection of field-based biomass reference data, extraction and selection of suitable variables from remote sensing data, identification of proper algorithms to develop biomass estimation models, and uncertainty analysis to refine the estimation procedure. Additionally, we discuss the impacts of scales on biomass estimation performance and describe a general biomass estimation procedure. Although optical sensor and radar data have been primary sources for AGB estimation, data saturation is an important factor resulting in estimation uncertainty. LIght Detection and Ranging (lidar) can remove data saturation, but limited availability of lidar data prevents its extensive application. This...