Xiao Yang

Bio: Xiao Yang is an academic researcher from University of North Carolina at Chapel Hill. The author has contributed to research in topics: Remote sensing (archaeology) & Climate change. The author has an hindex of 9, co-authored 33 publications receiving 293 citations.

Global Relationships Between River Width, Slope, Catchment Area, Meander Wavelength, Sinuosity, and Discharge

Abstract: Using river centerlines created with Landsat images and the Shuttle Radar Topography Mission digital elevation model, we created spatially continuous maps of mean annual flow river width, slope, meander wavelength, sinuosity, and catchment area for all rivers wider than 90 m located between 60°N and 56°S. We analyzed the distributions of these properties, identified their typical ranges, and explored relationships between river planform and slope. We found width to be directly associated with the magnitude of meander wavelength and catchment area. Moreover, we found that narrower rivers show a larger range of slope and sinuosity values than wider rivers. Finally, by comparing simulated discharge from awater balancemodel withmeasured widths, we show that power laws betweenmean annual discharge and width can predict width typically to −35% to +81%, even when a single relationship is applied across all rivers with discharge ranging from 100 to 50,000 m/s. Plain Language Summary For years, scientists and engineers have been using aerial photography to study the shapes of rivers, how they change over time, and how they relate to other river characteristics, such as river width, the slope of the water surface, and flow. These studies served as basis for the development of theories describing erosion, sediment transport, the speed at which flood waves travel through a basin, and serving as guidance for the measurement of river flow. However, such studies were often conducted in person, or done by combining results from other authors, leading to a very limited coverage of world rivers, most of which were in North America. As images of world rivers obtained by satellites became available and adequate computational power became affordable, we were able to describe the shape of worldwide rivers and how other properties, such as slope, width, and flow relate to meander characteristics. We showed that although classical geomorphic studies had limited geographical coverage, their results could generally be applied to typical rivers over the world. Additionally, with our results, rivers with atypical meander characteristics can be better identified, allowing the advancement of our understanding of how rivers work.

The past and future of global river ice

Abstract: More than one-third of Earth’s landmass is drained by rivers that seasonally freeze over. Ice transforms the hydrologic1,2, ecologic3,4, climatic5 and socio-economic6–8 functions of river corridors. Although river ice extent has been shown to be declining in many regions of the world1, the seasonality, historical change and predicted future changes in river ice extent and duration have not yet been quantified globally. Previous studies of river ice, which suggested that declines in extent and duration could be attributed to warming temperatures9,10, were based on data from sparse locations. Furthermore, existing projections of future ice extent are based solely on the location of the 0-°C isotherm11. Here, using satellite observations, we show that the global extent of river ice is declining, and we project a mean decrease in seasonal ice duration of 6.10 ± 0.08 days per 1-°C increase in global mean surface air temperature. We tracked the extent of river ice using over 400,000 clear-sky Landsat images spanning 1984–2018 and observed a mean decline of 2.5 percentage points globally in the past three decades. To project future changes in river ice extent, we developed an observationally calibrated and validated model, based on temperature and season, which reduced the mean bias by 87 per cent compared with the 0-degree-Celsius isotherm approach. We applied this model to future climate projections for 2080–2100: compared with 2009–2029, the average river ice duration declines by 16.7 days under Representative Concentration Pathway (RCP) 8.5, whereas under RCP 4.5 it declines on average by 7.3 days. Our results show that, globally, river ice is measurably declining and will continue to decline linearly with projected increases in surface air temperature towards the end of this century. An analysis based on Landsat imagery shows that the extent of river ice has declined extensively over past decades and that this trend will continue under future global warming.

RivWidthCloud: An Automated Google Earth Engine Algorithm for River Width Extraction From Remotely Sensed Imagery

Abstract: The wetted width of a river is one of the most important hydraulic parameters that can be readily measured using remote sensing. Remotely sensed river widths are used to estimate key attributes of river systems, including changes in their surface area, channel storage, and discharge. Although several published algorithms automate river network and width extraction from remote sensing images, they are limited by only being able to run on local computers and do not automatically manage cloudy images as input. Here we present RivWidthCloud, a river width software package developed on the Google Earth Engine cloud computing platform. RivWidthCloud automatically extracts river centerline and widths from optical satellite images with the ability to flag observations that are obstructed by features like clouds, cloud shadows, and snow based on existing quality band classification. Because RivWidthCloud is built on a popular cloud computing platform, it allows users to easily apply the algorithm to the platform’s vast archive of remote sensing images, thereby reducing the users’ overhead for computing hardware and data storage. By comparing RivWidthCloud-derived widths from Landsat images to in situ widths from the U.S. and Canada, we show that RivWidthCloud can estimate widths with high accuracy (root mean square error: 99 m; mean absolute error: 43 m; mean bias: −21 m). By making RivWidthCloud publicly available, we anticipate that it will be used to address both river science questions and operational applications of water resource management.

Integrating Perspectives to Understand Lake Ice Dynamics in a Changing World

Abstract: Ice cover plays a critical role in physical, biogeochemical, and ecological processes in lakes. Despite its importance, winter limnology remains relatively understudied. Here, we provide a primer on the predominant drivers of freshwater lake ice cover and the current methodologies used to study lake ice, including in situ and remote sensing observations, physical based models, and experiments. We highlight opportunities for future research by integrating these four disciplines to address key knowledge gaps in our understanding of lake ice dynamics in changing winters. Advances in technology, data integration, and interdisciplinary collaboration will allow the field to move toward developing global forecasts of lake ice cover for small to large lakes across broad spatial and temporal scales, quantifying ice quality and ice thickness, moving from binary to continuous ice records, and determining how winter ice conditions and quality impact ecosystem processes in lakes over winter. Ultimately, integrating disciplines will improve our ability to understand the impacts of changing winters on lake ice. Plain Language Summary Lakes are experiencing accelerated rates of warming, including shorter seasonal duration of ice cover, later ice‐on, earlier ice‐off, and in some years no ice cover at all. Lake ice has been historically studied independently by four subdisciplines: observations by in situ and remote sensing scientists, controlled mesocosm experiments by limnologists, and process‐based models by physical modelers. Here, we highlight opportunities for collaboration between disciplines and provide guidelines to successfully integrate the disciplines to tackle the most urgent questions surrounding lake ice loss in warming climates.

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.

Research Trends in the Use of Remote Sensing for Inland Water Quality Science: Moving Towards Multidisciplinary Applications

Abstract: Remote sensing approaches to measuring inland water quality date back nearly 50 years to the beginning of the satellite era. Over this time span, hundreds of peer-reviewed publications have demonstrated promising remote sensing models to estimate biological, chemical, and physical properties of inland waterbodies. Until recently, most of these publications focused largely on algorithm development as opposed to implementation of those algorithms to address specific science questions. This slow evolution contrasts with terrestrial and oceanic remote sensing, where methods development in the 1970s led to publications focused on understanding spatially expansive, complex processes as early as the mid-1980s. This review explores the progression of inland water quality remote sensing from methodological development to scientific applications. We use bibliometric analysis to assess overall patterns in the field and subsequently examine 236 key papers to identify trends in research focus and scale. The results highlight an initial 30 year period where the majority of publications focused on model development and validation followed by a spike in publications, beginning in the early-2000s, applying remote sensing models to analyze spatiotemporal trends, drivers, and impacts of changing water quality on ecosystems and human populations. Recent and emerging resources, including improved data availability and enhanced processing platforms, are enabling researchers to address challenging science questions and model spatiotemporally explicit patterns in water quality. Examination of the literature shows that the past 10–15 years has brought about a focal shift within the field, where researchers are using improved computing resources, datasets, and operational remote sensing algorithms to better understand complex inland water systems. Future satellite missions promise to continue these improvements by providing observational continuity with spatial/spectral resolutions ideal for inland waters.

Global suspended sediment and water discharge dynamics between 1960 and 2010: Continental trends and intra-basin sensitivity

Abstract: Establishing a quantitative description of global riverine fluxes is one of the main goals of contemporary hydrology and geomorphology. Here we study changes in global riverine water discharge and suspended sediment flux over a 50-year period, 1960–2010, applying a new version of the WBMsed (WBMsed v.2.0) global hydrological water balance model. A new floodplain component is introduced to better represent water and sediment dynamics during periods of overbank discharge. Validated against data from 16 globally distributed stations, WBMsed v.2.0 simulation results show considerable improvement over the original model. Normalized departure from an annual mean is used to quantify spatial and temporal dynamics in both water discharge and sediment flux. Considerable intra-basin variability in both water and sediment discharge is observed for the first time in different regions of the world. Continental-scale analysis shows considerable variability in water and sediment discharge fluctuations both in time and between continents. A correlation analysis between predicted continental suspended sediment and water discharge shows strong correspondence in Australia and Africa (R2 of 0.93 and 0.87 respectively), moderate correlation in North and South America (R2 of 0.64 and 0.73 respectively) and weak correlation in Asia and Europe (R2 of 0.35 and 0.24 respectively). We propose that yearly changes in intra-basin precipitation dynamics explain most of these differences in continental water discharge and suspended sediment correlation. The mechanism proposed and demonstrated here (for the Ganges, Danube and Amazon Rivers) is that regions with high relief and soft lithology will amplify the effect of higher than average precipitation by producing an increase in sediment yield that greatly exceeds increase in water discharge.