Search Results (8)

The cultivation of Moringa oleifera Lam. (M. oleifera) has steadily increased over the past few decades, and interest in the crop continues to rise due to its unique multi-purpose properties. However, knowledge pertaining to its water use to guide decision-making in relation to the growth and management of this crop remains fairly limited. Since acquiring such information can be challenging using traditional in situ or remote sensing-based methods, particularly in resource-poor regions, this study aims to explore the potential of using the cloud-based Earth Engine Evapotranspiration Flux (EEFlux) model to quantify the water use of M. oleifera in a semi-arid region of South Africa. For this purpose, EEFlux estimates were acquired and compared with eddy covariance measurements between November 2022 and May 2023. The results of these comparisons demonstrated that EEFlux unsatisfactorily estimated ET, producing root mean square error, mean absolute error, and R² values of 2.03 mm d⁻¹, 1.63 mm d⁻¹, and 0.24, respectively. The poor performance of this model can be attributed to several factors such as the quantity and quality of the in situ data as well as inherent model limitations. While these results are less than satisfactory, EEFlux affords users a quick and convenient approach to extracting crucial ET and ancillary data. Subsequently, with further refinement and testing, EEFlux can potentially serve to provide a wide variety of users with an invaluable tool to guide and inform decision-making with regards to agricultural water use management, particularly those in resource-constrained environments. Full article

This study aims to assess the performance of the Global Change Observation Mission—Climate (GCOM-C) ET_index estimation algorithm to estimate the actual evapotranspiration (ETa) in southeastern Afghanistan. Here, the GCOM-C ET_index algorithm was adopted to estimate the monthly ETa for the period from November 2016 to October 2017 using a series of Landsat 8, Thermal Infrared Sensor (TIRS) Band 10 satellite imagery. The estimation accuracy was evaluated by comparing the results with other estimates of ETa, namely the mapping evapotranspiration with the internalized calibration (METRIC) model, the MODIS Global Evapotranspiration Project (MOD16), the surface energy balance system (SEBS) tools, and with the crop evapotranspiration under standard conditions (ETc) as estimated by the FAO-56 procedure. The evaluation was made for irrigated wheat, maize, rice, and orchards and for non-irrigated bare soil land. The comparison of ETa values showed good correlation among the GCOM-C, METRIC, and FAO-56, while the MOD16 and SEBS showed significantly lower values of ETa. The agreement with the METRIC ETa implies that the simple GCOM-C algorithm successfully estimated the ETa in the region and that the precision was similar to that of the METRIC. This study provides the first high-quality evapotranspiration data with the spatial resolution of Landsat Band 10 data for the southeastern part of Afghanistan. The estimation procedure is straightforward, and its results are anticipated to enhance the understanding of regional hydrology. Full article

The global demand for food is growing with the population and urbanization, which puts pressure on water resources, which need assessing and quantifying water requirements. Adopting efficient irrigation methods to optimize water use is essential in this situation. In this study, crop water productivity (CWP) of major crops in the Rohri canal command area was estimated by the ratio of yield and actual evapotranspiration (ET_a). Analyzing the CWP of major crops, water scarcity challenges can be tackled by selecting the most feasible irrigation methods. However, ET_a was calculated and aggregated for all four stages of the crop growth period: initial, crop development, flowering stage, and maturity seasons. The crop yield data were obtained from the districts’ agricultural statistics. For this purpose, evapotranspiration products of Landsat 5 and 8 were downloaded from Earth Engine Evapotranspiration Flux (EEFlux). Landsat images were processed in a GIS environment to calculate ET_a. The approach suggests developing a CWP database for major crops like wheat, cotton, and rice to improve irrigation water management. The objectives of this study are to estimate and analyze the difference in the CWP and evapotranspiration of major crops for the Rabi and Kharif seasons with high and moderate flows during 1998–2019. It comprises nine districts of Sindh that come under the Rohri Canal command area. To analyze the difference in CWP between the Rabi and Kharif seasons for all study crops of the seasons of Rabi (2014–2015 and 2016–2017) and Kharif (1998 and 2017). The growing periods for wheat, cotton, and rice in the Rohri Canal command area are 160, 195, and 180 days, respectively. The estimated ET_a of the Rohri canal command area and CWP were in good agreement with the literature-reported values. Hence, enhanced agricultural productivity can be achieved by making considerable investments to improve agricultural research and extension systems. Full article

This study evaluated evapotranspiration (ET) estimated using the Earth Engine Evapotranspiration Flux (EEFlux), an automated version of the widely used Mapping Evapotranspiration at High Spatial Resolution with Internalized Calibration (METRIC) model, via comparison with ET measured using eddy covariance flux towers at two U.S. sites (St. John, WA, USA and Genesee, ID, USA) and for two years (2018 and 2019). Crops included spring wheat, winter pea, and winter wheat, all grown under rainfed conditions. The performance indices for daily EEFlux ET estimations combined for all sites and years dramatically improved when the cold pixel alfalfa reference ET fraction (ETrF) in METRIC was reduced from 1.05 (typically used for irrigated crops) to 0.85, with further improvement when the periods of early growth and canopy senescence were excluded. Large EEFlux ET overestimation during crop senescence was consistent in all sites and years. The seasonal absolute departure error was 51% (cold pixel ETrF = 1.05) and 23% (cold pixel ETrF = 0.85), the latter reduced to 12% when the early growth and canopy senescence periods were excluded. Departures of 10% are a reasonable expectation for methods of ET estimation, which EEFlux could achieve with more frequent satellite images, better daily weather data sources, automated adjustment of daily ETrF values during crop senescence, and a better understanding of the selection of adequate cold pixel ETrF values for rainfed crops. Full article

Southern California’s Imperial Valley (IV) faces serious water management concerns due to its semi-arid environment, water-intensive crops and limited water supply. Accurate and reliable irrigation system performance and water productivity information is required in order to assess and improve the current water management strategies. This study evaluates the spatially distributed irrigation equity, adequacy and crop water productivity (CWP) for two water-intensive crops, alfalfa and sugar beet, using remotely sensed data and a geographical information system for the 2018/2019 crop growing season. The actual crop evapotranspiration (ETa) was mapped in Google Earth Engine Evapotranspiration Flux, using the linear interpolation method in R version 4.0.2. The approx() function in the base R was used to produce daily ETa maps, and then totaled to compute the ETa for the whole season. The equity and adequacy were determined according to the ETa’s coefficient of variation (CV) and relative evapotranspiration (RET), respectively. The crop classification was performed using a machine learning approach (a random forest algorithm). The CWP was computed as a ratio of the crop yield to the crop water use, employing yield disaggregation to map the crop yield, using county-level production statistics data and normalized difference vegetation index (NDVI) images. The relative errors (RE) of the ETa compared to the reported literature values were 7–27% for alfalfa and 0–3% for sugar beet. The average ETa variation was low; however, the spatial variation within the fields showed that 35% had a variability greater than 10%. The RET was high, indicating adequate irrigation; 31.5% of the alfalfa and 12% of the sugar beet fields clustered in the Valley’s central corner were consuming more water than their potential visibly. The CWP showed wide variation, with CVs of 32.92% for alfalfa and 25.4% for sugar beet, signifying a substantial scope for CWP enhancement. The correlation between the CWP, ETa and yield showed that reducing the ETa to approximately 1500 mm for alfalfa and 1200 mm for sugar beet would help boost the CWP without decreasing the yield, which is nearly equivalent to 44.52M cu. m (36,000 acre-ft) of water. The study’s results could help water managers to identify poorly performing fields where water conservation and management could be focused. Full article

Remote sensing-based evapotranspiration (ET) models with various levels of sophistication have emerged recently with the possibilities of user-defined model calibrations. Their application for water resources management and climate studies from regional to global scale has been rapidly increasing, which makes it important to validate field scale ET in a complex crop assemblage before operational use. Based on in situ flux-tower measurements by the eddy-covariance (EC) system, this study tested three single-source energy balance models for estimating daily ET from fennel/maize/ryegrass-clover cropland rotations in a Mediterranean context in southern Italy. The sensitivity of three user-friendly ET models (SEBS, QWaterModel, and METRIC-EEFlux) with reference to the EC system over a center pivot irrigated cropland is discussed in detail. Results in terms of statistical indicators revealed that SEBS and METRIC-EEFlux showed reasonable agreements with measured ET (r² = 0.59_SEBS, RMSE = 0.71 mm day⁻¹; r² = 0.65_METRIC, RMSE = 1.13 mm day⁻¹) in terms of trends and magnitudes. At 30 m spatial resolution, both models were able to capture the in-field variations only during the maize development stage. The presence of spurious scan lines due to sensor defects in Landsat L7 ETM+ can contribute to the qualities of the METRIC-Efflux’s ET product. In our observation, the QWaterModel did not perform well and showed the weakest congruency (r² = 0.08_QWaterModel) with ground-based ET estimates. In a nutshell, the study evaluated these automated remote sensing-based ET estimations and suggested improvements in the context of a generic approach used in their underlying algorithm for robust ET retrievals in rotational cropland ecosystems. Full article

Accurately quantifying actual evapotranspiration (ETa) over wetlands is important for the improved management of these ecosystems, since 65% of them are threatened by clearing or drainage in South Africa. This study evaluated a range of available estimates of ETa over six palmiet wetlands, which are key ecological structures in terms of water regulation and sediment trapping. The research compared three remote sensing based products (a local product, FruitLook, and two global data products, MOD16 ET and EEFlux) across different rainfall years (2008 to 2019). Their outputs were validated, where possible, with limited ground-based scintillometer data on the Krom palmiet wetland, which indicated that MOD16 and EEFlux were most representative of ground-based measurements. We also compared the small pixel size EEFlux data over three wetlands with ETa over increasing buffers of land cover (100, 500, 1000 m) in order to validate the perception of these wetlands being high water users. While larger wetlands had slightly higher evaporative demands than adjacent areas, ETa over a small wetland was similar to neighboring land cover. The results indicate that palmiet wetland ETa is highly variable and dependent on external factors such as climate, wetland size and seasonality. Full article

Monitoring of crop water consumption, also known as actual evapotranspiration (ETa), is crucial for the prudent use of limited freshwater resources. Remote-sensing-based algorithms have become a popular approach for providing spatio-temporal information on ETa. Satellite-based ETa products are widely available. However, identifying an adequate product remains a challenge due to validation data scarcity. This study developed an assessment process to identify superior ETa products in agricultural areas in Egypt. The land cover product (MCD12Q1) from Moderate Resolution Imaging Spectroradiometer (MODIS) was evaluated and used to detect agricultural areas. The performances of three ETa products, namely: Earth Engine Evapotranspiration Flux (EEFlux), USGS-FEWS NET SSEBop ETa monthly product, and MODIS ETa monthly product (MOD16A2), were evaluated. The ETa values of these products were compared to previous ETa observations and evaluated using the integrated Normalized Difference Vegetation Index (iNDVI) on a seasonal and annual basis. Finally, the irrigation efficiency throughout Egypt was calculated based on the annual Relative Water Supply (RWS) index. Results reveal that the SSEBop monthly product has the best performance in Egypt, followed by the MOD16A2. The EEFlux overestimated ETa values by 36%. RWS had a range of 0.96–1.47, indicating high irrigation efficiency. The findings reported herein can assist in improving irrigation water management in Egypt and the Nile Basin. Full article