Tracking Earth's Rivers with Satellites
Rivers serve as a chief source of water to humans and freshwater ecosystems. They also organize landscapes, are integral to global biogeochemical cycles, and are responsible for some of the largest natural disasters in history. Despite their importance, observational assessments of river systems, based largely on river gauge data, are fragmented and often limited to country-level statistics, severely impeding our understanding of this important link in the water cycle. In contrast, satellite remote sensing data provide a globally consistent and spatially continuous tool for studying rivers.
We use historical satellite data and cloud-based analytical platforms to quantify how the global river system is evolving in response to climate and land use change. We also quantify other important aspects of rivers including seasonal changes in inundation extent, floods and water quality, and predict how these properties are likely to change into the future.
Remote Sensing of Plastic Debris in Freshwater Systems
Only recently have rivers been recognized as a major global source of microplastic and macroplastic pollution to the ocean. Despite increasing evidence of widespread plastic contamination in rivers, its detection has been limited to time-intensive manual techniques. Our goal is to develop a method to rapidly identify and quantify plastic debris in river environments. To accomplish this goal, we employ field-based remote sensing using visible-infrared spectroscopy, a technique used in recycling centers to automate sorting of plastics. Rapid detection of plastic pollution in freshwater systems enables denser sampling strategies, thus enhancing our ability to identify the dominant sources of plastic pollution in rivers and to understand the underlying processes of plastic transport in river systems.
Preparing for SWOT: Data Assimilation of Virtual Gauge Data into a Hydrological Model
The upcoming Surface Water and Ocean Topography (SWOT) satellite mission will provide surface water elevation and inundation measurements of rivers at an unprecedented resolution. However, because the satellite is on a 21-day repeat orbit, these measurements will only be made sporadically, often with long gaps between observations.
We assimilate existing satellite observations of river altimetry into the RAPID hydrologic model so that we can develop a system for SWOT to provide continuous discharge estimates across the world's river network.
Headwater Stream Hydromorphology
Headwater streams comprise an estimated 89% of the global fluvial network length and are the source of water, sediment, nutrients, and organic matter for downstream systems. They exhibit highly variable physical, chemical, and biotic attributes; as a result, they contribute to significant biodiversity within watersheds. They are also more hydraulically coupled to hillslope and groundwater processes compared to larger streams and thus are hotspots for biogeochemical activity. The morphology and abundance of streams control the rates of hydraulic and biogeochemical exchange between streams, groundwater, and the atmosphere.
We use field methods, drones, and satellite data to quantify emergent behavior of headwater stream hydromorphology and understand how these important constituents of the landscape are changing.
Multi-Sensor Data Fusion in Hydrology
The field of hydrology stands benefit from novel fusion of many existing observational and model datasets. Disparate observations can often be combined to measure complementary components of the same system. Many low-resolution orbiting sensors provide frequent measurements of Earth's surface but at low resolution, while others measure at high spatial resolution but do not have a fast repeat orbit. Aerial techniques can be very high resolution, but are temporally sporadic with limited coverage. In situ measurements produce continuous, high quality observations but are limited in spatial coverage.
We use geospatial analysis and remote sensing science to assess the potential synergism between multiple sensors, and utilize these relationships to provide a more accurate, and often a more wholistic understanding of Earth's water resources.
Global Flood Wave Travel Time
Satellites can provide upstream conditions for early flood warning systems, reservoir operations, and other river management applications. This information is most useful for time‐sensitive applications if it is made available before an observed upstream flood reaches a downstream point of interest, like a basin outlet, city, or dam.
We use core hydrological principles to quantify satellite data latency requirements for real-time river water applications (e.g. flood mitigation strategies and reservoir operations management).