Evapotranspiration estimation using Landsat-8 data with a two-layer framework

This work was partially supported by the National Natural Science Foundation of China (41401042), National Key Basic Research Program of China (973 Program) (Grant No. 2015CB452701) and National Natural Science Foundation of China (Grant Nos. 41571019 and 41371043).Peer reviewedproo

Scintillometry in urban and complex environments: a review

Knowledge of turbulent exchange in complex environments is relevant to a wide range of hydro-meteorological applications. Observations are required to improve understanding and inform model parameterisations but the very nature of complex environments presents challenges for measurements. Scintillometry offers several advantages as a technique for providing spatially-integrated turbulence data (structure parameters and fluxes), particularly in areas that would be impracticable to monitor using eddy covariance, such as across a valley, above a city or over heterogeneous landscapes. Despite much of scintillometry theory assuming flat, homogeneous surfaces and ideal conditions, over the last 20 years scintillometers have been deployed in increasingly complex locations, including urban and mountainous areas. This review draws together fundamental and applied research in complex environments, to assess what has been learnt, summarise the state-of-the-art and identify key areas for future research. Particular attention is given to evidence, or relative lack thereof, of the impact of complex environments on scintillometer data. Practical and theoretical considerations to account for the effects of complexity are discussed, with the aim of developing measurement capability towards more reliable and accurate observations in future. The usefulness of structure parameter measurements (in addition to fluxes, which must be derived using similarity theory) should not be overlooked, particularly when comparing or combining scintillometry with other measurement techniques and model simulations

Effects of Surface Heterogeneity Due to Drip Irrigation on Scintillometer Estimates of Sensible, Latent Heat Fluxes and Evapotranspiration over Vineyards

Accurate estimates of sensible (H) and latent (LE) heat fluxes and actual evapotranspiration (ET) are required for monitoring vegetation growth and improved agricultural water management. A large aperture scintillometer (LAS) was used to provide these estimates with the objective of quantifying the effects of surface heterogeneity due to soil moisture and vegetation growth variability. The study was conducted over drip-irrigated vineyards located in a semi-arid region in Albacete, Spain during summer 2007. Surface heterogeneity was characterized by integrating eddy covariance (EC) observations of H, LE and ET; land surface temperature (LST) and normalized difference vegetation index (NDVI) data from Landsat and MODIS sensors; LST from an infrared thermometer (IRT); a data fusion model; and a two-source surface energy balance model. The EC observations showed 16% lack of closure during unstable atmospheric conditions and was corrected using the residual method. The comparison between the LAS and EC measurements of H, LE, and ET showed root mean square difference (RMSD) of 25 W m−2, 19 W m−2, and 0.41 mm day−1, respectively. LAS overestimated H and underestimated both LE and ET by 24 W m−2, 34 W m−2, and 0.36 mm day−1, respectively. The effects of soil moisture on LAS measurement of H was evaluated using the Bowen ratio, β. Discrepancies between HLAS and HEC were higher at β ≤ 0.5 but improved at 1 ≥ β \u3e 0.5 and β \u3e 1.0 with R2 of 0.76, 0.78, and 0.82, respectively. Variable vineyard growth affected LAS performance as its footprints saw lower NDVILAS compared to that of the EC (NDVIEC) by ~0.022. Surface heterogeneity increased during wetter periods, as characterized by the LST–NDVI space and temperature vegetation dryness index (TVDI). As TVDI increased (decreased) during drier (wetter) conditions, the discrepancies between HLAS and HEC, as well as LELAS and LEEC Re decreased (increased). Thresholds of TVDI of 0.3, 0.25, and 0.5 were identified, above which better agreements between LAS and EC estimates of H, LE, and ET, respectively, were obtained. These findings highlight the effectiveness and ability of LAS in monitoring vegetation growth over heterogonous areas with variable soil moisture, its potential use in supporting irrigation scheduling and agricultural water management over large regions

Modeling Spatial Surface Energy Fluxes of Agricultural and Riparian Vegetation Using Remote Sensing

Modeling of surface energy fluxes and evapotranspiration (ET) requires the understanding of the interaction between land and atmosphere as well as the appropriate representation of the associated spatial and temporal variability and heterogeneity. This dissertation provides new methodology showing how to rationally and properly incorporate surface features characteristics/properties, including the leaf area index, fraction of cover, vegetation height, and temperature, using different representations as well as identify the related effects on energy balance flux estimates including ET. The main research objectives were addressed in Chapters 2 through 4 with each presented in a separate paper format with Chapter 1 presenting an introduction and Chapter 5 providing summary and recommendations. Chapter 2 discusses a new approach of incorporating temporal and spatial variability of surface features. We coupled a remote sensing-based energy balance model with a traditional water balance method to provide improved estimates of ET. This approach was tested over rainfed agricultural fields ~ 10 km by 30 km in Ames, Iowa. Before coupling, we modified the water balance method by incorporating a remote sensing-based estimate for one of its parameters to ameliorate its performance on a spatial basis. Promising results were obtained with indications of improved estimates of ET and soil moisture in the root zone. The effects of surface features heterogeneity on measurements of turbulence were investigated in Chapter 3. Scintillometer-based measurements/estimates of sensible heat flux (H) were obtained over the riparian zone of the Cibola National Wildlife Refuge (CNWR), California. Surface roughness including canopy height (hc), roughness length, and zero-plane displacement height were incorporated in different ways, to improve estimates of H. High resolution, 1-m maps of ground surface digital elevation model and canopy height, hc, were derived from airborne LiDAR sensor data to support the analysis. The effects of using different pixel resolutions to account for surface feature variability on modeling energy fluxes, e.g., net radiation, soil, sensible, and latent heat, were studied in Chapter 4. Two different modeling approaches were applied to estimate energy fluxes and ET using high and low pixel resolution datasets obtained from airborne and Landsat sensors, respectively, provided over the riparian zone of the CNWR, California. Enhanced LiDAR-based hc maps were also used to support the modeling process. The related effects were described relative to leaf area index, fraction of cover, hc, soil moisture status at root zone, groundwater table level, and vegetation stress conditions

An analysis of turbulent sensible heat fluxes within a heterogeneous black spruce boreal forest in Alaska

Thesis (Ph.D.) University of Alaska Fairbanks, 2015Turbulent sensible heat fluxes within the heterogeneous canopy of a black spruce boreal forest in Interior Alaska are evaluated at three different scales in order to assess their spatial variability, and to determine the feasibility of upscaling locally measured flux values to the landscape scale for modeling applications and climate studies. The first evaluation is performed locally at a single micrometeorological tower in an area of the boreal forest with a mean canopy height of 4.7 m. The data were taken across winter, spring and summer of 2012 from two sonic anemometers, one below the canopy at 3 m above ground, and one above the canopy at 12 m above ground. A multiresolution analysis is used to isolate coherent structures from the turbulent temperature time series at both instruments. When mean global statistics of coherent structures are analyzed at the two levels independently, results show an average of 8 structures per period, a mean duration of 85 s, and a mean sensible heat flux contribution of 48%. A spectral version of the Stokes parameters is applied to the turbulent horizontal wind components to show that 31% of the coherent turbulent structures detected at 12 m, and 13% at 3 m, may be complicated by canopy waves due to the prevalence of stable flows at this high latitude location. A most remarkable finding is that less than 25% of the coherent structures detected at these two heights occur synchronously, which speaks robustly to the lack of flow interaction within only 9 vertical meters of the forest, and to the complexity of the vertical aggregation of sensible heat therein. The second evaluation quantifies differences in turbulent sensible heat fluxes horizontally between two micrometeorological towers 600 m apart, one in a denser canopy (DC) and the other in a sparser canopy (SC), but under approximately similar atmospheric boundary layer conditions. Results show that SC is ~ 3°C cooler and more stably stratified than DC during nighttime. This suggests that changes in the height and density of the canopy impact local temperature and stability regimes. Most importantly, the sensible heat flux at DC is greater during midday periods, with that difference exceeding 30% of the measured flux and over 30 W m⁻² in magnitude more than 60% of the time. This difference is the result of higher mechanical mixing due to the increased density of roughness elements at DC. Furthermore, the vertical distribution of turbulent heat fluxes verifies a maximum above the canopy crown when compared with the levels below and well above the canopy. These spatial variations of sensible heat flux result from the complex scale aggregation of energy fluxes over a heterogeneous canopy, and suggest that locally measured fluxes will likely differ from large-scale area averaged values. The third evaluation compares locally measured sensible heat fluxes from a sonic anemometer atop a 24 m micrometeorological tower to those derived from a large aperture scintillometer (LAS) whose beam is centered near the tower at an average height of 36 m above ground, and over a path length of 1423 m. This analysis focuses on unstable daytime periods from June, July and August of 2013. The daytime is defined as 0700-2000 Alaska Standard Time, since local sensible heat flux values derived from the sonic anemometer (HEC) are robust (above 50 W m⁻²) during this time, and since this time also agrees with the minima in the mean diurnal pattern of Cn² from the LAS. For daytime periods with robust sensible heat flux values, HEC and the large-scale flux from the LAS (HLAS) correlate with R² = 0.68, while HEC captures about 82% of HLAS on average. The magnitude of HEC and HLAS are both strongly sensitive to incoming solar radiation, with HLAS having a better correlation and regression slope, suggesting that the local measurements are adjusting also to surface and/or flow conditions above the heterogeneous canopy. Evaluation of the magnitude of the ratio of HEC/HLAS for days with varying amounts of solar radiation suggests that while radiation affects the magnitude of HEC and HLAS independently, it does not affect their ratio. For daytime periods with lower fluxes (HEC between 10 and 50 W m⁻²), HEC captures about 69% of HLAS on average. However, local and large-scale fluxes during this low flux regime correlate poorly with incoming solar radiation (R² = 0.42 for HLAS and R² = 0.15 for HEC), and with one another (R² = 0.27), suggesting that local heterogeneities are not well-integrated into the large-scale flux. Therefore, low flux periods should be considered separately for the purposes of upscaling local to landscape scale flux values in the boreal forest. For the high flux regime, a finer resolution of upscaling can be provided based on the mean diurnal pattern of HEC/HLAS and the Obukhov length (L). Namely, as the boundary layer becomes less unstable in late afternoon, HEC/HLAS increases, supporting that the eddy covariance technique can capture more of the large-scale flux when the boundary layer is more shear-driven (less buoyancy driven)

Measuring water-vapour and carbon-dioxide fluxes at field scales with scintillometry

Scintillometry is a measurement technique that has proven itself to be of great value for measuring spatial-averaged fluxes of sensible heat, momentum, and evapotranspiration. Furthermore, for crop fields (field scales), scintillometry has been shown to accurately determine the sensible-heat and momentum flux over time intervals as short as 6 seconds. As a consequence, interests in scintillometry are growing and scintillometers that determine sensible-heat fluxes and momentum fluxes have become commercially available. This thesis deals with two aspects of scintillometry. First, after a general introduction of scintillometry, measurement errors that have been observed in the large-aperture scintillometer from Kipp&Zonen and in the SLS field-scale scintillometer from Scintec are evaluated. For both scintillometer types, we discuss the variability in the measurement errors among different instruments and, where possible, we give solutions to remove these errors. Furthermore, we present the results of a prototype scintillometer that was developed as part of the research project. With our proposed design, we aim to overcome the measurement errors in the Scintec scintillometer and extend the applicability of the field-scale scintillometer to paths that are longer than 200 m. Second, we extend the application of field-scale scintillometry to the flux measurements of latent-heat, carbon-dioxide, and other passive scalars. Until now, scintillometers could not be used for measuring passive-scalar fluxes over crop fields and we show that with our extended methodology these fluxes can be accurately determined over time intervals as short as 1 minute. The methodology is based on a combination of scintillometer measurements and additional high-frequency scalar measurements and works under conditions of homogeneous turbulence, i.e. single crop fields. We introduce four methods, notably the energy-balance method, the Bowen-variance method, the flux-variance method, and the structure-parameter method. Using several validation methods, we show that the energy-balance method is unsuitable for estimating scalar fluxes over 1-min averaging intervals. The Bowen-variance and flux-variance method perform better and the structure-parameter method accurately resolves 1-minute fluxes. Thus, with this methodology fluxes can be resolved with a high temporal resolution, making it possible to study vegetation in a natural environment under non-stationary conditions. This allows us to show that the wheat vegetation affects fluxes upon changes in solar radiation in time periods clearly shorter than 30 minutes and that the canopy resistance can change significantly within several minutes. </p

A Review of Current Methodologies for Regional Evapotranspiration Estimation from Remotely Sensed Data

An overview of the commonly applied evapotranspiration (ET) models using remotely sensed data is given to provide insight into the estimation of ET on a regional scale from satellite data. Generally, these models vary greatly in inputs, main assumptions and accuracy of results, etc. Besides the generally used remotely sensed multi-spectral data from visible to thermal infrared bands, most remotely sensed ET models, from simplified equations models to the more complex physically based two-source energy balance models, must rely to a certain degree on ground-based auxiliary measurements in order to derive the turbulent heat fluxes on a regional scale. We discuss the main inputs, assumptions, theories, advantages and drawbacks of each model. Moreover, approaches to the extrapolation of instantaneous ET to the daily values are also briefly presented. In the final part, both associated problems and future trends regarding these remotely sensed ET models were analyzed to objectively show the limitations and promising aspects of the estimation of regional ET based on remotely sensed data and ground-based measurements

Measuring and modelling evapotranspiration in a South African grassland : comparison of two improved Penman-Monteith formulations

CITATION: Gwate, O., et al. 2018. Measuring and modelling evapotranspiration in a South African grassland : comparison of two improved Penman-Monteith formulations. Water SA, 44(3):482-492, doi:10.4314/wsa.v44i3.16.The original publication is available at http://www.wrc.org.zaAccurately measuring evapotranspiration (ET) is important in the context of global atmospheric changes and for use with climate models. Direct ET measurement is costly to apply widely and local calibration and validation of ET models developed elsewhere improves confidence in ET derived from such models. This study sought to compare the performance of the Penman-Monteith-Leuning (PML) and Penman-Monteith-Palmer (PMP) ET models, over mesic grasslands in two study sites in South Africa. The study used routine meteorological data from a scientific-grade automatic weather station (AWS) to apply the PML and PMP models. The PML model was calibrated at one site and validated in both sites. On the other hand, the PMP model does not require calibration and hence it was validated in both sites. The models were validated using ET derived from a large aperture scintillometer (LAS). The PML model performed well at both sites with root mean square error (RMSE) within 20% of the mean daily observed ET (R2 of 0.83 to 0.91). Routine meteorological data were able to reproduce fluxes calculated using micrometeorological techniques and this increased the confidence in the use of data from sparsely distributed AWSs to derive reasonable ET values. The PML model was better able to simulate observed ET compared to the PMP model, since the former models both transpiration and soil evaporation (ES), while the latter only models transpiration. Hence, the PMP model systematically underestimated ET in a context where the leaf area index (LAI) was < 2.5. Model predictions in the grasslands could be improved by incorporating the ES component in the PMP model while the PML model could be improved by careful choice of the number of days to be used in the determination of the fraction of ES.https://www.watersa.net/article/view/6640Publisher's versio

Remote sensing of energy and water fluxes over Volta Savannah catchments in West Africa

The deterioration of the West African savannah in the last three decades is believed to be closely linked with about 0.5 C rise in temperature leading to evaporation losses and declining levels of the Volta Lake in Ghana. Although hydrological models can be used to predict climate change impacts on the regional hydrology, spatially-observed ground data needed for this purpose are largely unavailable. This thesis seeks to address this problem by developing improved methods for estimating energy and water fluxes (e.g. latent heat [ET]) from remotely sensed data and to demonstrate how these may be used to parameterize hydrological models. The first part of the thesis examines the potential of the Penman-Monteith method to estimate local-scale ET using groundbased hydrometeorological observations, vegetation coefficients and environmental data. The model results were compared with pan observations, scintillometer (eddy correlation) measurements and the Thomthwaite empirical method. The Penman- Monteith model produced better evaporation estimates (~3.90 mm day(^-1) for the Tamale district) than its counterpart methods. The Thomthwaite, for example, overestimated predictions by 5.0-11.0 mm day(^-1). Up-scaling on a monthly time scale and parameterization of the Grindley soil moisture balance model with the Thomthwaite and Penman-Monteith data, however, produced similar estimates of actual evaporation and soil moisture, which correlated strongly (R(^2) = 0.95) with water balance estimates. To improve ET estimation at the regional-scale, the second part of the thesis develops spatial models through energy balance modelling and data up-scaling methods, driven by radiometric measurements from recent satellite sensors such as the Landsat ETM+, MODIS and ENVISAT-AATSR. The results were validated using estimates from the Penman-Monteith method, field observations, detailed satellite measurements and published data. It was realised that the MODIS sensor is a more useful source of energy and water balance parameters than AA TSR. For example, stronger correlations were found between MODIS estimates of ET and other energy balance variables such as NDVI, surface temperature and net radiation (R(^2) = 0.67-0.73) compared with AATSR estimates (R(^2) = 0.31-0.40). There was also a good spatial correlation between MODIS and Landsat ETM+ results (R(^2) = 0.71), but poor correlations were found between AATSR and Landsat data (R(^2) = 0.0-0.13), which may be explained by differences in instrument calibration. The results further showed that ET may be underestimated with deviations of ~2.0 mm day 1 when MODIS/AATSR measurements are validated against point observations because of spatial mismatch. The final part of the thesis demonstrates the application of the ET model for predicting runoff (Q) using a simplified version of the regional water balance equation. This is followed byanalysis of flow sensitivity to declining scenarios of biomass volume. The results showed the absence of Q for >90% of the study area during the dry season due largely to crude model approximation and lack of rainfall data, which makes model testing during the wet season important. Runoff prediction may be improved if spatial estimates of rainfall, ET and geographical data (e.g. land-use/cover maps, soil & geology maps and DEM) could be routinely derived from satellite imagery

The application of the surface energy balance system model to estimate evapotranspiration in South Africa

Includes abstract.Includes bibliographical references.In a water scarce country like South Africa with a number of large consumers of water, it is important to estimate evapotranspiration (ET) with a high degree of accuracy. This is especially important in the semi-arid regions where there is an increasing demand for water and a scarce supply thereof. ET varies regionally and seasonally, so knowledge about ET is fundamental to save and secure water for different uses, and to guarantee that water is distributed to water consumers in a sustainable manner. Models to estimate ET have been developed using a combination of meteorological and remote sensing data inputs. In this study, the pre-packaged Surface Energy Balance System (SEBS) model was used for the first time in the South African environment alongside MODerate Resolution Imaging Spectroradiometer (MODIS) satellite data and validated with eddy covariance data measured in a large apple orchard (11 ha), in the Piketberg area of the Western Cape. Due to the relative infancy of research in this field in South Africa, SEBS is an attractive model choice as it is available as open-source freeware. The model was found to underestimate the sensible heat flux through setting it at the wet limit. Daily ET measured by the eddy covariance system represented 55 to 96% of the SEBS estimate, an overestimation of daily ET. The consistent underestimation of the sensible heat flux was ascribed to sensitivities to the land surface air temperature gradient, the choice of fractional vegetation cover formula as well as the height of the vegetation canopy (3.2 m) relative to weather station reference height (2 m). The methodology was adapted based on the above findings and was applied to a second study area (quaternary catchment P10A, near Grahamstown, Eastern Cape) where two different approaches for deriving surface roughness are applied. It was again demonstrated that the sensible heat flux is sensitive to surface roughness in combination with land surface air temperature gradient and again, the overestimation of daily ET persisted (actual ET being greater than reference ET). It was concluded that in complex environments, at coarse resolution, it is not possible to adequately describe the remote sensing derived input parameters at the correct level of accuracy and at the spatial resolution required for the accurate estimation of the sensible heat flux