Evaporation from Lake Mead and Lake Mohave, Lower Colorado River Basin, Nevada and Arizona

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The Bureau of Reclamation currently utilizes a model (24-Month Study) that projects future Colorado River reservoir volumes and potential dam operations based on current and forecasted hydrologic conditions and operational policies and guidelines. Each month, a water budget is developed, and Colorado River reservoir volumes and releases are projected for the next 24-month period. Reservoir evaporation is one of the water-budget terms in the model. The evaporation coefficients currently used in the model are based on poorly documented modifications to original USGS estimates from the 1940s and 1950s. The USGS Nevada Water Science Center and Reclamation cooperated on a multi-phase study to improve 24-Month Study model projections by improving monthly estimates of evaporation from Lake Mead and Lake Mohave.

Eddy covariance equipment at Lake Mead, Nev.

Eddy covariance equipment at Lake Mead, Nevada and Arizona (Public domain.)

Evaporation measurements began in March 2010 at Lake Mead and May 2013 at Lake Mohave. Data collection/analysis methods and monthly evaporation results for Lake Mead through February 2012 were documented in Scientific Investigations Report 2013-5229. Monthly evaporation and associated datasets for both reservoirs through April 2015 were published in a USGS Data Release. A final report featuring 9 years of data from Lake Mead from 2010 through 2019 and 6 years of data from Lake Mohave from 2013 through 2019 was published in USGS Open-File Report 2021-1022. All continuous data collected at Lake Mead and Lake Mohave is publicly available for download.

Close up view of Eddy covariance equipment at Lake Mohave, Nev.

Close up view of Eddy covariance equipment at Lake Mohave, Nevada and Arizona (Public domain.)

The continuous data needed to compute monthly evaporation are being collected from a floating platform and a land-based eddy covariance station located at each reservoir. Water-temperature profiles and net radiation are measured from the floating platforms. Eddy covariance relies on high-frequency measurements of water-vapor density and wind-velocity vectors by fast-response sensors. Eddies are turbulent airflow caused by wind, surface roughness, and convective heat flow in the atmospheric surface layer. Eddies transfer energy and mass between land and water surfaces and the atmosphere through a process referred to as turbulent exchange. Eddy covariance provides the most direct measure of turbulent exchange currently available. Fluxes of water vapor and heat can be measured directly without the application of empirical constants by finding the covariance between these scalars and vertical wind speed. Evaporation (positive latent-heat flux) occurs when water vapor in upward moving eddies is greater than in downward moving eddies. Likewise, sensible-heat flux is positive (from the surface to the atmosphere) when upward moving eddies are warmer than downward moving eddies. Unlike most other methods, eddy covariance is particularly well-suited to measuring evaporation from Lakes Mead and Mohave because there is no reliance on difficult-to-measure energy- and water-budget components. Methods used to compute evaporation and estimate uncertainty will follow those described by Moreo and Swancar.

 

RESERVOIR EVAPORATION RESEARCH

Mean monthly evaporation measured for the current study and estimated for Lake Mead, May 2013 through April 2019

Figure 1: Mean monthly evaporation measured for the current study and estimated for the 24-Month Study, Lake Mead, May 2013 through April 2019.

Average annual evaporation at Lake Mead was 1,896 millimeters
(mm; 6.22 feet, ft), a 10 percent difference from the average annual evaporation at Lake Mohave of 1,718 mm (5.64 ft).

Less evaporation at Lake Mohave compared to Lake Mead primarily is due to the difference between inflowing water temperature from Hoover Dam (cooler) and outflowing water temperature from Davis Dam (warmer). This temperature difference results in a persistent loss of energy (negative net advection) meaning that less energy is available to drive evaporation at Mohave than at Mead. The mean annual evaporation rate measured at Mead (6.22 ft, n=9) is less than the summed monthly coefficients used by the 24-Month Study model (6.50 ft), and at Mohave the mean annual evaporation rate (5.64 ft, n=6) is considerably less than the summed monthly coefficients (7.31 ft).

The annual evaporation volume computed for 2014 was 27,000 acre-feet less than estimated for the 24MS model at Lake Mead and 53,000 acre-feet less at Lake Mohave..

Mean monthly evaporation measured for the current study and estimated for Lake Mohave, May 2013 through April 2019

Figure 2: Mean monthly evaporation measured for the current study and estimated for the 24-Month Study, Lake Mohave, May 2013 through April 2019.

Differences between current study monthly evaporation and 24-Month Study coefficients range from minor to substantial with the largest differences occurring during summer and fall at Lake Mead and winter through summer at Lake Mohave (figs. 1 and 2). A lag in current study evaporation relative to the seasonal solar pattern is evident at both reservoirs. Heat storage during spring and early summer (increasing water temperatures) result in a decrease in available energy and less evaporation than estimated for the 24-Month Study coefficients. The subsequent release of that stored energy during fall and winter (decreasing water temperatures) increases the available energy which results in greater evaporation than estimated for the 24-Month Study coefficients. This seasonal lag explains most of the differences observed between current study monthly evaporation and 24-Month Study coefficients at Lake Mead. This seasonal trend also is evident at Lake Mohave, but the large monthly differences there are influenced by the lack of historical evaporation measurements.

 

CURRENT PHASE OF STUDY

The current phase of the study includes the collection of additional years of evaporation measurements at Lake Mead. The longer-term dataset will be used to better quantify the influence of seasonal or annual changes in climate on mean-monthly evaporation rates so that modeling projections are more representative of mean-annual climatic conditions.