Improvement of Two Evapotranspiration Estimation Models Using a Linear Spectral Mixture Model over a Small Agricultural Watershed

Abstract

Accurately measuring regional evapotranspiration (ET) is of great significance for studying global climate change, regional hydrological cycles, and surface energy balance. However, estimating regional ET from mixed vegetation types is still challenging. In this study, the Surface Energy Balance Algorithm for Land (SEBAL) and the Surface Energy Balance System (SEBS) models were applied to estimate surface ET in a small agricultural watershed. Landsat8 satellite images were used as input data to the single-source models. The two models were validated at single point and ecosystem scales. The results showed that both models overestimated ET observations in paddy fields and orange groves but underestimated them in dry farmland. The error was mainly caused by the heterogeneity of the mixed pixels. The linear spectral mixture model and a set of equations were introduced to reduce the simulation error. The revised results showed that the relative precision of SEBAL was improved by 9.87% and 10.06%, respectively. This research is expected to provide new ideas for future development of accurate remote-sensing ET estimations on heterogeneous surfaces.

Estimating the spatial distribution of evapotranspiration within the Pra River Basin of Ghana

“…While at the southern part of the basin (where forest patches, logged forest, traces of water bodies and clusters of settlement and bare landscape exist), ET rates ranged between 4.80 mm/day to 7.70 mm/day representing average to high ET rates. The estimated high temperature in settlements and bare landscapes, coupled with widely varying solar radiation and wind speed resulting in low ET are in-line with studies by Li et al (2018); Ayad et al (2016). Thus spatially, areas with high temperature and high solar radiation experiences high ET (especially, when forest and water bodies occur), while low wind speed, low to average temperature and solar radiation areas experience low ET.…”

“…The effect of temperature, wind speed and solar radiation on spatial distribution of ET within the PRB is also presented in Figure 4. According to Li et al (2018) and Ayad et al (2016), high temperature with corresponding high solar radiation is associated with high ET as this was observed at the upper western part of the basin (314-320 K). Average temperature (310-314 K) and averagely high solar radiation (500-550 W/m 2 ) observed around water bodies together with average wind speed also resulted in average to high ET rates (5.50-6.75 mm/day).…”

“…Thus, ET is the most influential component of the water cycle with immense research potential in hydrological studies ( Andam-Akorful et al., 2015 ; Bonemberger et al., 2018 ; Opoku-Duah, 2007 and Sett et al., 2018 ). In view of this, accurate estimation of ET at both local and regional scales remains a fundamental tool for water resources planning and management ( Allen et al., 2007 ; Kundu et al., 2018 ; Li et al., 2018 ). Intriguingly, ET is the most complex hydrologic parameter to estimate ( Bastiaanssen et al., 1998 ; Sett et al., 2018 ) as it depends on factors such land use land cover (LULC) and climate change ( Li et al., 2017 ) whose dominance is influenced by anthropogenic activities ( Awotwi et al., 2019 ).…”

Application of the Simple Biosphere Model 2 (SiB2) with Irrigation Module to a Typical Low-Hilly Red Soil Farmland and the Sensitivity Analysis of Modeled Energy Fluxes in Southern China

“…Modeling land surface processes plays an important role in understanding the interaction between the land surface and the atmosphere [31][32][33][34]. The energy and water balance should always be held at the land surface, and it should impact all-scale models [35][36][37][38]. In this study, we collected and processed the measured data from the low-hilly red soil farmland region of southern China at The Red Soil Ecological Experiment Station in 2015.…”

Spectral Mixture Analysis as a Unified Framework for the Remote Sensing of Evapotranspiration

“…If these metrics could be improved and standardized, ET models could be made more accurate, and cross-model standardization could be more effective. One recent study [37] has recognized the impact of subpixel heterogeneity on ET model accuracy and used a spectral mixture model to estimate subpixel fractions of different agricultural crops with different ET characteristics. These crop fractions were used as inputs to the SEBAL and SEBS models, resulting in improved accuracies of between 7% and 18% for different crop types.…”