Abstract
Evapotranspiration (ET) accounts for water movements from land to air and plays a vital role in the terrestrial water, energy, and carbon cycles. Reliable estimates of ET for agricultural landscapes can facilitate water resources management and food security analysis. The widely used Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model has the most potential to operationally simulate ET over large areas, but its inability to fully track soil evaporation dynamics using atmospheric humidity limits its application in agroecosystems. In this study, we isolated the uncertainties resulting from soil evaporation and assessed three Earth observation-based alternatives - apparent thermal inertia (ATI), microwave soil moisture (SM), and optical spectral indices based on shortwave infrared (SWIR) to formulate soil evaporation. Our results illustrate that the incorporation of the SWIR-based soil moisture divergence index (SMDI) and microwave-based SM into monthly soil evaporation led to 6% and 5% increase in explained ET variances and reduced RMSE by 23.2% and 13.1% for cropland and grassland, respectively, as compared to PT-JPL using atmospheric reanalysis data only. Further analyses demonstrated that PT-SMDI explained more observed ET variances than PT-JPL using in-situ measurements of atmospheric humidity during the crop growing season, particularly for irrigated cropland (R2=0.65 for PT-SMDI; R2=0.62 for PT-JPL). On the other hand, the use of microwave SM outperformed other indices for ET assessment in grasslands but had lower performance in croplands. Our results suggest that a combination of optical SWIR and microwave SM has good potential to improve the PT-JPL model accuracy for agricultural landscapes.
Highlights
Evapotranspiration (ET) is the process by which water is transferred from the Earth’s surface to the atmosphere and reflects mass and energy exchange between the hydrosphere, biosphere, and atmosphere (Fisher et al, 2017)
The widely used Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model was proven to be effective across a variety of ecosystems, but have a relatively lower performance in waterlimited agroecosystems, where soil evaporation makes a more signifi cant contribution to ET
Given that these areas are generally prone to issues concerning water scarcity and food insecurity, we investigated if the incorporation of apparent thermal inertia (ATI), microwave soil moisture (SM) and optical shortwave infrared (SWIR)-based spec tral indices into the parametrization of ETs can effectively simulate the exchange of moisture between land surface and atmosphere and further improve the accuracy of ET estimation in agroecosystems
Summary
Evapotranspiration (ET) is the process by which water is transferred from the Earth’s surface to the atmosphere and reflects mass and energy exchange between the hydrosphere, biosphere, and atmosphere (Fisher et al, 2017). In the context of global climate change, agricultural land use, including cropland and grassland, accounts for the majority of fresh water consumption and is especially vulnerable to increasing water scarcity, in dry irrigated regions (Rounsevell et al, 2005; Hoekstra and Mekonnen, 2012). Accurate and timely estimates of ET are important to support agricul tural practices and water resources management, including irrigation scheduling, regional water allocation, drought monitoring, crop growth and production estimates, and projecting long-term effects of global climate change. Ershadi et al (2014) compared the PT-JPL, Penman–Monteith algorithm as realized by MOD16 (Mu et al, 2011), and the Surface Energy Balance System (SEBS) (Su, 2002) over twenty FLUXNET towers. The results for daily ET estimation illustrated that PT-JPL performed best overall (R2=0.70, RMSE=2.31 mm day− 1) for the majority of examined towers, followed by SEBS (R2=0.66, RMSE=2.94 mm day− 1)
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