Quantifying Groundwater Evapotranspiration with Remote Sensing for the Humboldt River Basin, NV

Monday, December 3, 2018: 2:00 p.m.
N109 (Las Vegas Convention Center)
Matt Bromley, M.S. , Division of Hydrologic Sciences, Desert Research Institute, Reno, NV
Justin Huntington, Ph.D. , Division of Hydrologic Sciences, Desert Research Institute, Reno, NV
Charles Morton, M.S. , Division of Hydrologic Sciences, Desert Research Institute, Reno, NV

The Desert Research Institute in cooperation with the USGS and the Nevada Division of Water Resources is currently evaluating groundwater discharge via evapotranspiration from phreatophyte shrubs in the Humboldt River Basin, NV. The overarching goal of this work is to improve the modeling of groundwater for the purposes of evaluating the interplay between groundwater and surface water.

Accurate estimates of groundwater ET (ETg) are essential to developing groundwater budgets, modeling boundary conditions, and ultimately constraining model calibration of aquifer properties (i.e. non-uniqueness between recharge, transmissivity, and discharge). Methods used to estimate ETg are often based on intensive field based micrometeorological measurements, assumed or fixed rates, or a combination of remote sensing and empirical relationships based on past measurement studies.

The approach used in this study uses a regression based on enhanced vegetation index (EVI) calculated from remotely sensed optical data acquired by the Landsat series of satellites, along with precipitation and evaporative demand in the area of interest. This regression was developed through the evaluation of 40 site years of micrometeorological data collected at 26 unique sites, primarily located within phreatophyte areas of Nevada. Google Earth Engine (GEE), a massively parallel, cloud-computing platform, was used to apply this method to 30 years of Landsat images and climate archives, in order to produce annual estimates of rates and volumes of ETg over the entire Humboldt River Basin. Because volume calculations of ETg are sensitive to estimates of phreatophyte area, an evaluation was conducted to determine the accuracy of previously defined phreatophyte boundaries. This review was performed through a combination of field evaluations and an examination of aerial imagery and optical and thermal Landsat data.

This presentation will describe methods used to quantify ETg in the Humboldt River Basin, preliminary results, and the relevance of the data to ongoing groundwater modeling efforts.

Matt Bromley, M.S., Division of Hydrologic Sciences, Desert Research Institute, Reno, NV
Matt is an assistant research scientist at the Desert Research Institute, where his work has primarily focused on the application of GIS and remote sensing tools to produce estimates of evapotranspiration. This work has been conducted in cooperation with several state and federal agencies, as well as private industry. These efforts have primarily focused on the Great Basin, but have also been applied to water management issues in areas outside of Nevada.


Justin Huntington, Ph.D., Division of Hydrologic Sciences, Desert Research Institute, Reno, NV
Justin Huntington is an associate research professor of Hydrology at the Desert Research Institute, Reno, Nevada. His research interests are focused on remote sensing, land surface energy balance measurement and modeling, drought monitoring, and hydrologic modeling. His projects are primarily being funded by the U.S. Bureau of Reclamation, U.S. Geological Survey, U.S. Bureau of Land Management, NASA, and Google. He is one of 25 members of the Landsat Science Team.


Charles Morton, M.S., Division of Hydrologic Sciences, Desert Research Institute, Reno, NV
Charles co-leads METRIC and OpenET software engineering, supports algorithm teams with Google Earth Engine API programming and technology transfer, co-develop back-end/front-end linkages, and participate in training and front-end design. Charles is lead developer of the automated METRIC ET model, co-developer of ClimateEngine.org, and expert in programming within the Google Earth Engine API