Surface Energy Balance System Algorithm Research Articles

Assessment of irrigation water distribution using remotely sensed indicators: A case study of Doho Rice Irrigation Scheme, Uganda

The rising competition for scarce land and water resources and the need to satisfy the global food demand from an ever-growing population necessitates novel methods to monitor irrigation scheme performance for improved water use efficiency. The traditional methods employed in sub-Saharan Africa to assess irrigation performance are point-based, expensive, and time-consuming, making monitoring and evaluation of these capital-intensive projects difficult. This study aimed at employing satellite data with high spatial and temporal resolution in assessing the performance of Doho Rice Irrigation Scheme through estimations of actual evapotranspiration. Actual evapotranspiration (ETa) was modelled from Landsat 7 imagery using the surface energy balance system algorithm on five clear days between January and April 2020. Using equity and adequacy metrics, the derived ETa was used to assess the irrigation performance of the scheme. Results showed that the equity indicator was generally fair, with the coefficient of variation between 0.11 and 0.08, close to the 0.10 threshold implying irrigation water is fairly distributed within the scheme. The average adequacy was 0.87, above the 0.65 threshold, indicating adequate water supply throughout the scheme. The study's findings can be used in future research and benchmarking with other irrigation schemes to address the country's water resource management challenges.

Evaluating the role of remote sensing-based energy balance models in improving site-specific irrigation management for young walnut orchards

California’s weather is characterized by extreme droughts and floods. This has resulted in overdraft of groundwater aquifers as growers turn to this source of water for irrigation during droughts. California produces 99% of all walnuts in the US, walnut growers are under extreme pressure to optimize crop water use. Water use estimates at the field scale are crucial for growers to refine irrigation scheduling decisions. In this study, two single source remote sensing-based energy balance models (pySEBAL [python-based Surface Energy Balance Algorithm for Land] and SEBS [Surface Energy Balance System algorithm]) for estimating evapotranspiration (ETa) were evaluated against in-situ ETa measurements from surface renewal in two young walnut orchards in California’s Sacramento Valley. Strong correlations were obtained between the RS-based estimates and in-situ measurements for both pySEBAL and SEBS from 2017 to 2020, with R2 above 0.87, RMSE ranging from 0.79 to 1.05 mm, and NSE ranging from 0.79 to 0.88. SEBS out-performed pySEBAL on estimating time-series daily ETa for walnut at the field scale. During the mid-season characterized by high wind speed and high temperatures, pySEBAL and SEBS both underestimated ETa while the two models slightly overestimated ETa during the early growing season and post-harvest period. These results indicate the need for future research to focus on improving the performance of pySEBAL and SEBS when simulating time-series ETa under advection and sparse vegetation conditions, to provide more accurate ETa for both in-season and off-season irrigation water management. Comparisons of historical Kc and RS-based Kc were evaluated, and RS-based Kc matched better with the actual water use requirements of developing 2nd to 4th leaf young walnuts orchards. We observed substantial spatiotemporal variability of RS-based Kc in wo young walnut orchards at the CAPEX and Kauffman sites. For instance, Kc values for the north and south halves of the CAPEX orchard were above 1.2 and 0.9–1.1 respectively. Kc values for the north and south halves at the Kauffman site were in a range of 0.6–0.71 and 0.82–0.94 respectively. In other words, conventional irrigation management based on multiplying historical Kc and reference evapotranspiration is inadequate for site-specific walnut irrigation management due to spatial and temporal variability in Kc. ETa and Kc mapping from two single source models were similar in the spatial patterns and provided an overall visual characterization of the spatial variability in crop water use. Overall, RS-based ETa models using freely accessible satellite images and open-source algorithms could be used as an alternative to expensive in-situ measurements for enhancing site-specific young walnut irrigation management.

Estimates of Daily Evapotranspiration in the Source Region of the Yellow River Combining Visible/Near-Infrared and Microwave Remote Sensing

The spatial variation of surface net radiation, soil heat flux, sensible heat flux, and latent heat flux at different times of the day over the northern Tibetan Plateau were estimated using the Surface Energy Balance System algorithm, data from the FY-2G geostationary meteorological satellite, and microwave data from the FY-3C polar-orbiting meteorological satellite. In addition, the evaporative fraction was analyzed, and the total evapotranspiration (ET) was obtained by the effective evaporative fraction to avoid the error from accumulation. The hourly change of latent heat flux presented a sound unimodal diurnal variation. The results showed the regional ET ranged between 2.0 and 4.0 mm over the Source Region of the Yellow River. The conditional expectations of surface energy components during the experimental period of the study area were statistically analyzed, and the correspondence between different surface temperatures and the effective energy distribution was examined. The effective energy distribution of the surface changed significantly with the increase in temperature; in particular, when the surface temperature exceeded 290 K, the effective energy was mainly used for surface ET. The aim of this study was to avoid the use of surface meteorological observations that are not readily available over large areas, and the findings lay a foundation for the commercialization of land surface evapotranspiration.

The spatio-temporal soil moisture variation along the major tributaries of Zambezi River in the Mbire District, Zimbabwe

This study uses the Surface Energy Balance System (SEBS) and the TOPographic driven MODEL (TOPMODEL) in estimating soil moisture for Mbire district in Zimbabwe and validates these estimates with ground based gravimetric measurements baseded on fifty-four soil moisture sampling sites. Five atmospherically corrected MODIS images for the period 2013were processed and used to estimate evapotransiration. The result of the relative evaporation from the SEBS algorithm was multiplied by the average of the porosity and the field capacity to get the spatial and temporal soil moisture estimates. The TOPMODEL rainfall-runoff model whose land surface inputs were obtained from remote sensing was calibrated with runoff data for the period ranging 2008−2013. After successful calibration the model was used to to simulate spatial and temporal soil moisture estimates and compare with insitu-measured soil moisture from the fifty-two sampling sites. An upscaling procedure to improve the comparison between soil moisture retrieval point measurements, remote sensing and TOPMODEL outputs was accomplished by the use of geostatistical tools. Land suitability analysis for flood recession farming was performed using soil moisture maps, distance from stream network, vertical channel distance, and land use/cover datasets. The model performance indicators for TOPMODEL simulations show an acceptable match with measured discharge, (NSE = 0.765 and 0.812 and PBIAS= -6.04 % and -10.5 % for Manyame and Angwa sub catchments respectively). Results show that the SEBS approach show spatial and temporal soil moisture variability across the Mbire district simulated. There is a strong relationship (R2 = 0.796) between upscaled insitu-based soil moisture measurements and SEBS based techniques for the period of March to July 2013. The study further revealed that there is a fair relationship (R2 = 0.60) between upscaled ground soil moisture measurements and hydrological modelling (TOPMODEL) for the same period. TOPMODEL soil moisture increases towards the Angwa and Manyame river tributaries. Results also show that approximately 22800 ha of Mbire district has suitable to moderately suitable flood recession farming area. The study concludes that the use of geostatistical approaches, remote sensing and hydrologic models is promising in planning and management of soil moisture and water resources in data scarce and water limited environments.

Evaluation of remote sensing-based evapotranspiration models against surface renewal in almonds, tomatoes and maize

Evapotranspiration (ET) is a major hydrologic flux in water resources planning and irrigation management. While recent advances in remote sensing (RS) have enabled availability of high spatial and temporal resolution ET data, a lack of information related to error in the estimations has made it challenging to use this data for on-farm irrigation management decision making. In this study, three commonly used single-source RS based ET models (pySEBAL — a new version of the Surface Energy Balance Algorithm for Land; SEBS — Surface Energy Balance System algorithm; and METRIC — Mapping Evapotranspiration at High Resolution with Internalized Calibration) were used to estimate daily actual evapotranspiration (ETa) for almonds, processing tomatoes, and maize in the Central Valley of California. Model evaluation was conducted by comparing the predicted ETa from RS with in-situ measured ETa using surface renewal. Results indicated that the RS-based ETa estimations for all three models were within acceptable levels of uncertainty and agreed well with surface renewal estimates except for the underestimation by pySEBAL and METRIC during early season growth stages of processing tomatoes. This underestimation was attributed to the lack of accuracy when using single source ET models under lower vegetation cover condition (when ET is dominated by soil evaporation). Better estimates of ETa with pySEBAL and METRIC were detected at full cover, which explains the applicability of these two models to irrigation management during peak crop water demand. SEBS performed the best among the three RS-based models for daily ETa estimation for all crops. This suggests that SEBS-based ETa estimates can be adopted in operational irrigation management programs for farms that have not installed in field ETa sensors such as Tule Sensors (Tule Technologies Inc.). In addition, RS based ET is spatially distributed which can help to identity spatial variability between different irrigation zones.

Incorporating an iterative energy restraint for the Surface Energy Balance System (SEBS)

The Surface Energy Balance System (SEBS) has proven itself as an effective remotely sensed estimator of actual evapotranspiration (ETa). However, it has several vulnerabilities associated with the partitioning of the available energy (AE) at the land surface. We introduce a two stage energy restraint process into the SEBS algorithm (SEBS-ER) to overcome these vulnerabilities. The first offsets the remotely sensed surface temperature to ensure the surface to air temperature difference reflects AE, while the second stage uses a domain based image search process to identify and adjust the proportions of sensible (H) and latent (λE) heat flux with respect to AE. We effectively implemented SEBS-ER over 61 acquisitions over two Landsat tiles (path 90 row 84 and path 91 row 85) in south-eastern Australia that feature heterogeneous land covers. Across the two areas we showed that the SEBS-ER algorithm has: greater resilience to perturbed errors in surface energy balance algorithm inputs; significantly improved accuracy (p<0.05) at two eddy covariance flux towers in heavily forested (RMSE 62.3Wm−2, R2 0.879) and sub-alpine grassland (RMSE 33.2Wm−2, R2 0.939) land covers; and greater temporal stability across 52 daily actual evapotranspiration (ETa) estimates compared to a temporally stable and independent ETa dataset. The energy restraint within SEBS-ER has reduced exposure to the complex errors and uncertainties within remotely sensed, meteorological, and land type SEBS inputs, providing more reliable and accurate spatially distributed ETa products.

Estimation of Growing Season Daily ET in the Middle Stream and Downstream Areas of the Heihe River Basin Using HJ-1 Data

Spatial mapping of evapotranspiration (ET) is specifically critical for the semi-arid inland river basin with great heterogeneity in land-cover types. This letter estimates the spatial distribution of daily ET over the middle stream and downstream areas of the Heihe River Basin during the growing season of 2012 by using the Surface Energy Balance System algorithm with land surface temperature at high spatial resolution (300 m) derived from observations by the Chinese satellite HJ-1. The results demonstrate that ET estimates are consistent with ground-based measurements collected during the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) with acceptable accuracy. The magnitude of daily ET in the downstream area is obviously lower than that in the middle stream area. Further analysis based on classification maps shows that there is significant temporal–spatial heterogeneity of daily ET over different land-cover surfaces and also within the same vegetation type. The temporal variation of ET in the middle stream area has clear seasonality with an obvious peak in July, whereas it is flat in the downstream area due to the dominating arid-region vegetation species and low soil water content in growing season. In addition, because of the abundant irrigation in the maize and irrigated orchard fields, the daily ET values of them are higher than that of wetland and even comparable with that of water surface in the middle stream area of the Heihe River Basin.