USGS ScienceSearch

Geology topics

Ping Wang

Publications and source records attributed to Ping Wang.

2 recordsLinked to original sources

Dunes in the world's big rivers are characterized by low-angle lee-side slopes and a complex shape

Dunes form critical agents of bedload transport in all of the world’s big rivers, and constitute appreciable sources of bed roughness and flow resistance. Dunes also generate stratification that is the most common depositional feature of ancient riverine sediments. However, current models of dune dynamics and stratification are conditioned by bedform geometries observed in small rivers and laboratory experiments. For these dunes, the downstream lee-side is often assumed to be simple in shape and sloping at the angle of repose. Here we show, using a unique compilation of high-resolution bathymetry from a range of large rivers, that dunes are instead characterized predominantly by low-angle lee-side slopes (<10°), complex lee-side shapes with the steepest portion near the base of the lee-side slope and a height that is often only 10% of the local flow depth. This radically different shape of river dunes demands that such geometries are incorporated into predictions of flow resistance, water levels and flood risk and calls for rethinking of dune scaling relationships when reconstructing palaeoflow depths and a fundamental reappraisal of the character, and origin, of low-angle cross-stratification within interpretations of ancient alluvial sediments.

Nature Geoscience

SemantEco: a semantically powered modular architecture for integrating distributed environmental and ecological data

We aim to inform the development of decision support tools for resource managers who need to examine large complex ecosystems and make recommendations in the face of many tradeoffs and conflicting drivers. We take a semantic technology approach, leveraging background ontologies and the growing body of linked open data. In previous work, we designed and implemented a semantically enabled environmental monitoring framework called SemantEco and used it to build a water quality portal named SemantAqua. Our previous system included foundational ontologies to support environmental regulation violations and relevant human health effects. In this work, we discuss SemantEco’s new architecture that supports modular extensions and makes it easier to support additional domains. Our enhanced framework includes foundational ontologies to support modeling of wildlife observation and wildlife health impacts, thereby enabling deeper and broader support for more holistically examining the effects of environmental pollution on ecosystems. We conclude with a discussion of how, through the application of semantic technologies, modular designs will make it easier for resource managers to bring in new sources of data to support more complex use cases.

Future Generation Computer Systems