Location: Hydrology and Remote Sensing LaboratoryTitle: Characterizing the spatial heterogeneity in a river corridor to evaluate its impact on evapotranspiration estimates using the TSEB Model and sUAS information
|NASSAR, A. - Utah State University|
|TORRES-RUA, A. - Utah State University|
|HIPPS, L. - Utah State University|
|Kustas, William - Bill|
|MCKEE, M - Utah State University|
|STEVENS, D. - Utah State University|
|NIETO, H. - University Of Alcala|
|KELLER, D. - Utah Division Of Natural Resources|
|GOWING, I. - Utah State University|
|COOPMANS, C. - Utah State University|
Submitted to: Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/8/2022
Publication Date: 1/13/2022
Citation: Nassar, A., Torres-Rua, A., Hipps, L.E., Kustas, W.P., McKee, M., Stevens, D., Nieto, H., Keller, D., Gowing, I., Coopmans, C. 2022. Characterizing the spatial heterogeneity in a river corridor to evaluate its impact on evapotranspiration estimates using the TSEB Model and sUAS information. Remote Sensing. https://doi.org/10.3390/rs14020372.
Interpretive Summary: Remote sensing-based surface energy balance models are applied widely and routinely in agricultural settings to obtain crop water use or evpotranspiration (ET) information on an operational basis for use in water resources management. However, the application of these models in natural rangeland environments is challenging due to spatial heterogeneity in vegetation cover and complexity in the number of vegetation species existing within a biome. To evaluate the necessary remote sensing pixel resolution necessary to characterize ET in such environments, multispectral images acquired through multiple campaigns over different seasons using a small unmanned aerial system (sUAS) was conducted in the San Rafael River corridor in Utah, part of the Upper Colorado River Basin. the Two-Source Energy Balance (TSEB) model, a physically based ET model, was applied with the sUAS imagery and results indicate that spatial resolutions between 6 m and 15 m are suitable for representing ET in this environment. This finding will guide applications of remote sensing ET models over natural rangeland environments to utilize imagery at only high spatial resolutions for reliable plant water use monitoring.
Technical Abstract: Understanding the spatial variability in highly heterogeneous natural environments such as savannas and river corridors is an important issue in characterizing and modeling energy fluxes, particularly for evapotranspiration (ET) estimates. The natural environment is characterized by variation in vegetation types, soil strata and properties, and other geomorphological processes. Various land surface and hydrological models can be applied to estimate ET in such environments; however, model performance may be affected due to the lack of robust methods of accounting for the spatial variability in the vegetation and soil. Remote sensing-based surface energy balance (SEB) models are applied widely and routinely in agricultural settings to obtain ET information on an operational basis for use in water resources management. However, the application of these models in natural environments is challenging due to spatial heterogeneity in vegetation cover and complexity in the number of vegetation species existing within a biome. The analysis in this study relies upon multispectral images acquired through multiple campaigns over different seasons (June, July, and October) by the AggieAirTM small unmanned aerial systems (sUAS) program at Utah State University (https://uwrl.usu.edu/aggieair/) specifically in the San Rafael River corridor in Utah, which is part of the Upper Colorado River Basin. The study area is characterized by arid conditions and variations in soil moisture status and the type and height of vegetation (treated tamarisk, cottonwood, willow, grass, and other vegetation species). Optical data in red, green, blue, and near infrared bands were acquired at 2.5-cm spatial resolution, while thermal data were acquired at 15 cm using a microbolometer camera. The micrometeorological data were obtained from a weather station installed in the field during the flight dates. In this research effort, sUAS data were used to study the influence of land surface spatial heterogeneity on the modeling of ET using high-resolution information. First, a spatial variability analysis was performed using a discrete wavelet transform (DWT) to identify a representative spatial resolution / model grid size for adequately solving energy balance components to derive ET. Next, the Two-Source Energy Balance (TSEB) model, a physically based ET model, was implemented over different vegetation/soil conditions and times at two different scales, 6 m and 15 m. Lastly, the instantaneous (hourly) latent heat flux (LE) was extrapolated/upscaled to daily ET values using the incoming solar radiation (Rs) method. Results indicate that spatial resolutions between 6 m and 15 m are suitable for representing fluxes in the study area. The results also indicate small differences in the LE values between 6-m and 15-m resolutions, with a slight decrease in detail at 15 m due to losses in spatial variability. For daily ET estimation, the results indicate that willow and cottonwood have the highest ET rates, followed by grass/shrubs and treated tamarisk.