Earth Observations-Based Evapotranspiration in Northeastern Thailand

Estimating daily potential evapotranspiration using GNSS-based precipitable water vapor

Potential evapotranspiration (PET) is a crucial component of the hydrological cycle and energy balance. Although the Penman-Monteith (PM) model is the most widely used method to estimate daily PET, it requires temperature, relative humidity, solar radiation, and wind speed. In Thailand, the number of potential weather stations to provide the required data is limited, which resulted in the absence of some input variables in many locations. The objective of this study is to develop the revised potential evapotranspiration (RPET) model to estimate daily PET using Global Navigation Satellite System-derived Precipitable Water Vapor (GNSS-PWV) and temperature data. The multiple linear regression analysis was used to develop and validate the RPET model. The performance of the RPET model along with the Global Land Evaporation Amsterdam Model (GLEAM v3.2 b) and the European Centre for Medium-Range Weather Forecasts Reanalysis-5 (ERA5-Land) products was investigated using the PM model. The results revealed that the RPET model showed a strong correlation with the PM model (r = 0.85, RMSE = 0.97 mm day^-1, RSR = 0.53, NSE = 0.72) under limited meteorological inputs. The RPET model performance was superior when compared to GLEAM and ERA5-Land (r = 0.80, RMSE = 1.06 mm day^-1). Therefore, the proposed model is greatly suitable for daily PET estimation with only required GNSS-PWV and temperature data, and this can be implemented for drought assessment and water resources management.

Estimation of Global Cropland Gross Primary Production from Satellite Observations by Integrating Water Availability Variable in Light-Use-Efficiency Model

Satellite-based models have been widely used to estimate gross primary production (GPP) of terrestrial ecosystems. Although they have many advantages for mapping spatiotemporal variations of regional or global GPP, the performance in agroecosystems is relatively poor. In this study, a light-use-efficiency model for cropland GPP estimation, named EF-LUE, driven by remote sensing data, was developed by integrating evaporative fraction (EF) as limiting factor accounting for soil water availability. Model parameters were optimized first using CO2 flux measurements by eddy covariance system from flux tower sites, and the optimized parameters were further spatially extrapolated according to climate zones for global cropland GPP estimation in 2001–2019. The major forcing datasets include the fraction of absorbed photosynthetically active radiation (FAPAR) data from the Copernicus Global Land Service System (CGLS) GEOV2 dataset, EF from the ETMonitor model, and meteorological forcing variables from ERA5 data. The EF-LUE model was first evaluated at flux tower site-level, and the results suggested that the proposed EF-LUE model and the LUE model without using water availability limiting factor, both driven by flux tower meteorology data, explained 82% and 74% of the temporal variations of GPP across crop sites, respectively. The overall KGE increased from 0.73 to 0.83, NSE increased from 0.73 to 0.81, and RMSE decreased from 2.87 to 2.39 g C m−2 d−1 in the estimated GPP after integrating EF in the LUE model. These improvements may be largely attributed to parameters optimized for different climatic zones and incorporating water availability limiting factor expressed by EF into the light-use-efficiency model. At global scale, the verification by GPP measurements from cropland flux tower sites showed that GPP estimated by the EF-LUE model driven by ERA5 reanalysis meteorological data and EF from ETMonitor had overall the highest R2, KGE, and NSE and the smallest RMSE over the four existing GPP datasets (MOD17 GPP, revised EC-LUE GPP, GOSIF GPP and PML-V2 GPP). The global GPP from the EF-LUE model could capture the significant negative GPP anomalies during drought or heat-wave events, indicating its ability to express the impacts of the water stress on cropland GPP.

Assessment and Inter-Comparison of Multi-Source High Spatial Resolution Evapotranspiration Products over Lancang–Mekong River Basin, Southeast Asia

Evapotranspiration (ET) plays a crucial role in water balance within the global hydrological cycle. Timely assessment of ET products can provide the scientific basis for quantitative analysis of hydrological cycle processes and water resources assessment. In this paper, four high spatial resolution remote sensing ET products—the Moderate-resolution Imaging Spectroradiometer global terrestrial evapotranspiration product (MOD16), the ET product based on Penman–Monteith–Leuning equation version 2 (PML-V2), the ET product based on the Breathing Earth System Simulator (BESS) and the ET product of the Global LAnd Surface Satellite (GLASS)—were firstly assessed using the eddy covariance (EC) of different vegetation types in the Lancang–Mekong River Basin (LMRB). To fully assess the performances of these four products, spatiotemporal inter-comparisons and literature comparisons were also conducted across different climatic zones. The results are summarized as follows: (1) MOD16 does not perform well as compared to the other three products, with its Root Mean Square Error (RMSE) being higher than GLASS, PML-V2 and BESS, which are approximately 0.47 mm/8-day, 0.66 mm/8-day, and 0.90 mm/8-day, respectively; (2) the performance of each product varies across different vegetation types, and even within the same climate zone. PML-V2 performs best in evergreen broadleaf forests, BESS performs best in deciduous broadleaf forests and croplands, and GLASS performs best in shrubs, grasslands and mixed vegetation; (3) each product can well reflect the spatial difference brought by topography, climate and vegetation over the entire basin but all four ET products do not show either a consistent temporal trend or a uniform spatial distribution; (4) ET ranges of these four products over LMRB are consistent with previous literature in evergreen broadleaf forests, deciduous broadleaf forests, needleleaf forests and mixed forests in other regions with the same climate zones, but they show great differences in croplands, grasslands and shrubs. This study will contribute to improving our understanding of these four ET products in the different climatic zones and vegetation types over LMRB.

Different responses of soil respiration to environmental factors across forest stages in a Southeast Asian forest

Soil respiration (SR) in forests contributes significant carbon dioxide emissions from terrestrial ecosystems and is highly sensitive to environmental changes, including soil temperature, soil moisture, microbial community, surface litter, and vegetation type. Indeed, a small change in SR may have large impacts on the global carbon balance, further influencing feedbacks to climate change. Thus, detailed characterization of SR responses to changes in environmental conditions is needed to accurately estimate carbon dioxide emissions from forest ecosystems. However, data for such analyses are still limited, especially in tropical forests of Southeast Asia where various stages of forest succession exist due to previous land-use changes. In this study, we measured SR and some environmental factors including soil temperature (ST), soil moisture (SM), and organic matter content (OM) in three successional tropical forests in both wet and dry periods. We also analyzed the relationships between SR and these environmental variables. Results showed that SR was higher in the wet period and in older forests. Although no response of SR to ST was found in younger forest stages, SR of the old-growth forest significantly responded to ST, plausibly due to the nonuniform forest structure, including gaps, that resulted in a wide range of ST. Across forest stages, SM was the limiting factor for SR in the wet period, whereas SR significantly varied with OM in the dry period. Overall, our results indicated that the responses of SR to environmental factors varied temporally and across forest succession. Nevertheless, these findings are still preliminary and call for detailed investigations on SR and its variations with environmental factors in Southeast Asian tropical forests where patches of successional stages dominate.

Estimation of Seasonal Evapotranspiration for Crops in Arid Regions Using Multisource Remote Sensing Images

An accurate estimation of evapotranspiration (ET) from crops is crucial in irrigation management, crop yield assessment, and optimal allocation of water resources, particularly in arid regions. This study explores the estimation of seasonal evapotranspiration for crops using multisource remote sensing images. The proposed estimation framework starts with estimating daily evapotranspiration (ETd) values, which are then used to calculate ET estimates during the crop growing season (ETs). We incorporated Landsat images into the surface energy balance algorithm over land (SEBAL) model, and we used the trapezoidal and sinusoidal methods to estimate the seasonal ET. The trapezoidal method used multitemporal ETd images, while the sinusoidal method employs time-series Moderate Resolution Imaging Spectroradiometer (MODIS) images and multitemporal ETd images. Experiments were implemented in the agricultural lands of the Kai-Kong River Basin, Xinjiang, China. The experimental results show that the obtained ETd estimates using the SEBAL model are comparable with those from the Penman–Monteith method. The ETs obtained using the trapezoidal and sinusoidal methods both have a relatively high spatial resolution of 30 m. The sinusoidal method performs better than the trapezoidal method when using low temporal resolution Landsat images. We observed that the omission of Landsat images during the middle stage of crop growth has the greatest impact on the estimation results of ETs using the sinusoidal method. Based on the results of the study, we conclude that the proposed sinusoidal method, with integrated multisource remote sensing images, offers a useful tool in estimating seasonal evapotranspiration for crops in arid regions.

Editorial for the Special Issue “Remote Sensing of Evapotranspiration (ET)”

Evapotranspiration (ET) is a critical component of the water and energy balances, and the number of remote sensing-based ET products and estimation methods has increased in recent years. Various aspects of remote sensing of ET are reported in 11 papers published in this special issue. The major research topics covered by this special issue include inter-comparison and performance evaluation of widely used one- and two-source energy balance models, a new dual-source model (Soil Plant Atmosphere and Remote Sensing Evapotranspiration, SPARSE), and a process-based model (ETMonitor); assessment of multi-source (e.g., remote sensing, reanalysis, and land surface model) ET products; development or improvement of data fusion frameworks to provide continuous daily ET at a high spatial resolution (field-scale or 30 m) by fusing the advanced space-borne thermal emission reflectance radiometer (ASTER), the moderate resolution imaging spectroradiometer (MODIS), and Landsat data; and investigating uncertainties in ET estimates using an ET ensemble composed of 36 land surface models and four diagnostic datasets. The effects of the differences among ET products on water resources and ecosystem management were also investigated. More accurate ET estimates and improved understanding of remotely sensed ET products can help maximize crop productivity while minimizing water loses and management costs.