Abstract
Evapotranspiration (ET) is a key component of the hydrologic cycle, accounting for ~70% of precipitation in the conterminous U.S. (CONUS), but it has been a challenge to predict accurately across different spatio-temporal scales. The increasing availability of remotely sensed data has led to significant advances in the frequency and spatial resolution of ET estimates, derived from energy balance principles with variables such as temperature used to estimate surface latent heat flux. Although remote sensing methods excel at depicting spatial and temporal variability, estimation of ET independently of other water budget components can lead to inconsistency with other budget terms. Methods that rely on ground-based data better constrain long-term ET, but are unable to provide the same temporal resolution. Here we combine long-term ET estimates from a water-balance approach with the SSEBop (operational Simplified Surface Energy Balance) remote sensing-based ET product for 2000–2015. We test the new combined method, the original SSEBop product, and another remote sensing ET product (MOD16) against monthly measurements from 119 flux towers. The new product showed advantages especially in non-irrigated areas where the new method showed a coefficient of determination R2 of 0.44, compared to 0.41 for SSEBop or 0.35 for MOD16. The resulting monthly data set will be a useful, unique contribution to ET estimation, due to its combination of remote sensing-based variability and ground-based long-term water balance constraints.
Highlights
Background and RationaleEvapotranspiration (ET) is the quantity of water that includes net water evaporation and plant transpiration
The uncertainty of ET estimation is demonstrated by the non-unique partitioning of total ET to multiple landscape sources. One study comparing this variability of ET source partitioning in three remote sensing ET algorithms showed that for the global average ET, different algorithms attributed a range of 14–52% of the ET to soil evaporation, 10–24% to evaporation of water intercepted by canopies, and 24–76% to plant transpiration [12]
The combination aims to combine the advantages of long-term magnitude accuracy and constraint within water budgets of the water-balance-based estimates with the remote sensing benefits of enabling shorter-timescale measuring of ET and improved accuracy in irrigated areas
Summary
Evapotranspiration (ET) is the quantity of water that includes net water evaporation and plant transpiration It plays a significant role in the hydrologic cycle, returning about 70% of precipitation across the conterminous United States (CONUS) to the atmosphere [1,2]. The uncertainty of ET estimation is demonstrated by the non-unique partitioning of total ET to multiple landscape sources One study comparing this variability of ET source partitioning in three remote sensing ET algorithms showed that for the global average ET, different algorithms attributed a range of 14–52% of the ET to soil evaporation, 10–24% to evaporation of water intercepted by canopies, and 24–76% to plant transpiration [12]. Though there are substantial uncertainties among remote sensing ET estimates, the usefulness of the high frequency of measurements and the broad spatial coverage in capturing spatial and temporal variability mark a significant step forward in our ability to measure and monitor ET
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