Matthew is currently pursuing his MS in civil engineering, with a focus in Hydrology, Water Resources, and Environmental Fluid Mechanics. His research currently focuses on how drought propagates through meteorological, hydrological, and agricultural systems. Previously, Matthew graduated from Colby College in 2021, with a BA in Biology. Before starting his MS, he worked for an EPA contractor on water quality and watershed health projects, performing data analysis and developing web applications.

Jeremy Barroll is currently pursuing an MS in civil engineering. Jeremy’s research presently focuses on small-scale variability in the prediction of snowpack in mountainous regions using remotely-sensed sea surface temperature data. The goal of this is to increase the predictive accuracy of large lead time water supply forecasting for small watersheds in the Western United States. Jeremy previously received a BS in civil and environmental engineering from UC Berkeley in 2016.

Gillian is a Ph.D. student at the University of Colorado Boulder. Her current research is focused on the influence of seasonal snowpack on thresholds related to species' habitat in the western United States. Gillian completed her M.S. in Civil Engineering at Purdue University in 2023, and earned a graduate certificate in GIS. Her previous research involved evaluating methods to improve the simulation of urban flooding using hydrologic models. She also graduated with a B.S. in Civil Engineering from the University of Vermont in 2020.

Melanie received her Ph.D. and M.S. in Civil Engineering from the University of Colorado Boulder. In her graduate studies, Melanie developed and validated monitoring technologies to improve water management and support local policy compliance in California and Colorado. Using a combination of land-surface modeling, in situ groundwater extraction monitoring, and remote sensed data, Melanie’s research focused on developing a groundwater abstraction forecast model to aid agencies in complying with groundwater regulations in the drought-prone western United States.

Justin is a CIRES affiliate and an Assistant Research Scientist with the University of Maryland and NASA Goddard. Prior to this, Justin was a CIRES Visiting Postdoctoral Fellow in the Water and Climate Research Group, where his research focused on investigating the sensitivity of wildlife habitat estimates to snow modeling decisions.

Fangfang is a postdoctoral fellow in Cooperative Institute for Research in Environmental Sciences (CIRES). He holds a Ph.D. in Physical Geography from Kansas State University and an M.S. in Geographic Information Systems (GIS) from the University of the Chinese Academy of Sciences.  His research explores the interaction among lakes, climate change and human activities with a primary focus on the terrestrial water cycle, climate and human impacts on natural and manmade lakes, and the environmental impact of dams.

Parth Modi completed his M.S. in Biological Systems Engineering from Virginia Tech in 2020 and is currently a Doctoral Research Assistant in the Civil, Environmental, and Architectural Engineering department at the University of Colorado Boulder. He has several experiences in land surface modeling (VIC, Noah-MP, National Water Model) and has worked on projects understanding the impacts of climate change on mesoscale hydrological processes and risk assessment of natural hazards including droughts and floods.

Kaitlyn is pursuing her PhD in Civil Engineering at the University of Colorado Boulder with a focus in Hydrology, Water Resources, and Environmental Fluid Mechanics. In 2021, she graduated summa cum laude with a BS in Environmental Engineering from The University of Alabama. Her previous experience spans many disciplines, including civil engineering site design, natural hazards research, and the application of engineering principles to public policy development.

We present a new REmotely Sensed ENsemble of the water cycle (REESEN). The REESEN approach generates a large number of realizations of the remotely sensed water budget and enforces closure for each realization. The REESEN approach is applied to 24 large river basins from Oct. 2002- Dec. 2014. Three water balance closure algorithms are evaluated, ranging from simple redistribution of residuals to more complex Kalman-filtering and multiple-collocation approaches, to understand the impact of algorithm choice on the resulting water budget partitioning.

This is an observationally-based dataset of soil evaporation for the conterminous U.S. (CONUS), gridded to a 9 km resolution for the time-period of April 2015-March 2019. This product (Evaporation-Soil Moisture Active Passive; E-SMAP) represents soil evaporation from the surface layer, defined by the SMAP sensing depth of 50 mm, during SMAP overpass intervals that are screened using precipitation and SMAP quality control flags. Soil evaporation is calculated through an estimated water balance of the surface soil, which we show is largely dominated by SMAP-observed soil drying.