Search Results (11)

With the increasing water scarcity and the demand for sustainable agriculture, precise estimation of crop evapotranspiration (ET) is crucial for effective irrigation management, crop yield assessment, and equitable water distribution, particularly in semi-arid regions. In this study, a large aperture scintillometer (LAS) was used to validate the remote sensing-based ET model SETMI (Spatial Evapotranspiration Modeling Interface) in an irrigated maize-wheat cropping system in a semi-arid region at the ICAR-Indian Agricultural Research Institute, New Delhi. Results obtained by the SETMI model depicted modeled surface energy fluxes compared well with LAS field data, showing a very high R² (0.83–0.95) and NRMSE (8–29%). The SETMI model performed better in the case of the maize crop than the wheat crop in field experiments. Further, the SETMI model was employed at the regional level using high-resolution Sentinel-2 to estimate the regional water productivity of wheat crops over a semi-arid region in India. The estimated regional, seasonal wheat actual ET mainly ranged between 101 mm and 325 mm. The regional wheat water productivity varied from 0.9 kg m⁻³ to 2.20 kg m⁻³. Our research reveals that the SETMI model can give reliable estimates of regional wheat water productivity by examining its spatial and temporal fluctuations and facilitating the creation of regional benchmark values. Full article

Water resources are severely scarce in desert steppes, and precipitation rarely collects in rivers or is transformed into groundwater. Evapotranspiration (ET) is the primary “export” of precipitation conversion and is the main mechanism for water vapor exchange between the underlying surface and atmosphere. ET changes have certain scale effects. This study focused on the natural grasslands in the Xilamuren Desert Steppe and analyzed and estimated the ET patterns at different scales, including micro-, point-, and surface scales, using observational data from instruments such as a photosynthetic meter, Eddy-covariance system (EC), and large-aperture scintillometer (LAS) from the Ecological Hydrology National Field Science Observation Station in the northern foothills of the Yin Mountains, Inner Mongolia. The spatial scale was extended based on this analysis. The results showed that at the microscale, the diurnal variation in the photosynthetic and transpiration rates of Leymus chinensis followed a bimodal curve. In July and August (high-temperature months), photosynthetic and transpiration rates were almost synchronous. In May and October, when the temperature was moderate, the transpiration rate was delayed compared to the photosynthetic rate at the first peak, and the second peak was significantly smaller than the first peak. At the point-scale, the daily average ET during the growing season was 1.37 mm·d⁻¹ and the total cumulative ET was 251 mm. Transpiration levels exhibited significant seasonal variation in the following order: July > August > June > September > May > October. At the surface-scale, the daily average ET during the growing season was 1.60 mm·d⁻¹ and the total cumulative ET was 294 mm, which was 17% higher than that of the point-scale. The surface-scale ET was estimated using the observed values of the EC and the scale relationship formula and was optimized using different spatial scales of crop coefficients. This well reflected the ET patterns at the surface-scale. Therefore, this study proposes a spatial scale expansion method for a homogeneous underlying surface, verifies its value, and provides methodological support for estimating ET in cases of data scarcity. Full article

The refractive index structure constant ($C_n^2$) is a key parameter used in describing the influence of turbulence on laser transmissions in the atmosphere. Three different methods for estimating $C_n^2$ were analyzed in detail. A new method that uses a combination of these methods for continuous $C_n^2$ profiling with both high temporal and spatial resolution is proposed and demonstrated. Under the assumption of the Kolmogorov “2/3 law”, the $C_n^2$ profile can be calculated by using the wind field and turbulent kinetic energy dissipation rate (TKEDR) measured by coherent Doppler wind lidar (CDWL) and other meteorological parameters derived from a microwave radiometer (MWR). In a horizontal experiment, a comparison between the results from our new method and measurements made by a large aperture scintillometer (LAS) is conducted. The correlation coefficient, mean error, and standard deviation between them in a six-day observation are 0.8073, 8.18 × 10⁻¹⁶ m^−2/3 and 1.27 × 10⁻¹⁵ m^−2/3, respectively. In the vertical direction, the continuous profiling results of $C_n^2$ and other turbulence parameters with high resolution in the atmospheric boundary layer (ABL) are retrieved. In addition, the limitation and uncertainty of this method under different circumstances were analyzed, which shows that the relative error of $C_n^2$ estimation normally does not exceed 30% under the convective boundary layer (CBL). Full article

An accurate assessment of evapotranspiration (ET) is crucially needed at the basin scale for studying the hydrological processes and water balance especially from upstream to downstream. In the mountains, this term is poorly understood because of various challenges, including the vegetation complexity, plant diversity, lack of available data and because the in situ direct measurement of ET is difficult in complex terrain. The main objective of this work was to investigate the potential of a Two-Source-Energy-Balance model (TSEB) driven by the Landsat and MODIS data for estimating ET over a complex mountain region. The complexity is associated with the type of the vegetation canopy as well as the changes in topography. For validating purposes, a large-aperture scintillometer (LAS) was set up over a heterogeneous transect of about 1.4 km to measure sensible (H) and latent heat (LE) fluxes. Additionally, two towers of eddy covariance (EC) systems were installed along the LAS transect. First, the model was tested at the local scale against the EC measurements using multi-scale remote sensing (MODIS and Landsat) inputs at the satellite overpasses. The obtained averaged values of the root mean square error (RMSE) and correlation coefficient (R) were about 72.4 Wm⁻² and 0.79 and 82.0 Wm⁻² and 0.52 for Landsat and MODIS data, respectively. Secondly, the potential of the TSEB model for evaluating the latent heat fluxes at large scale was investigated by aggregating the derived parameters from both satellites based on the LAS footprint. As for the local scale, the comparison of the latent heat fluxes simulated by TSEB driven by Landsat data performed well against those measured by the LAS (R = 0.69, RMSE = 68.0 Wm⁻²), while slightly more scattering was observed when MODIS products were used (R = 0.38, RMSE = 99.8 Wm⁻²). Based on the obtained results, it can be concluded that (1) the TSEB model can be fairly used to estimate the evapotranspiration over the mountain regions; and (2) medium- to high-resolution inputs are a better option than coarse-resolution products for describing this kind of complex terrain. Full article

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 H_LAS and H_EC were higher at β ≤ 0.5 but improved at 1 ≥ β > 0.5 and β > 1.0 with R² of 0.76, 0.78, and 0.82, respectively. Variable vineyard growth affected LAS performance as its footprints saw lower NDVI_LAS compared to that of the EC (NDVI_EC) 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 H_LAS and H_EC, as well as LE_LAS and LE_{EC 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. Full article

Accurate estimation of evaporation (E₀) over open water bodies in arid regions (e.g., lakes in the desert) is of great importance for local water resource management. Due to the ability to accurately determine sensible (H) and latent (LE) heat fluxes over scales of hundreds to thousands of meters, scintillometers are more and more appreciated. In this study, a scintillometer was installed on both sides of the shore over the Sumu Barun Jaran Lake in the Badain Jaran Desert and was applied to estimate the sensible and latent heat fluxes and evaporation to be compared with the data of an evaporation pan and an aerodynamic model. Based on the field data, we further analyzed the seasonal differences in the flux evaluation using water temperature at different depths at half-hour and daily time scales, respectively. The results showed that in cold seasons, values of H were barely affected by the changes of shallow water temperature, whereas in hot seasons, the values were changed by 20%–30% at the half-hour time scale and 6.2%–18.3% at the daily time scale. In different seasons, shallow water temperature at different depths caused changes in the range of 0%–20% of LE (E₀). This study contributes to a better understanding of uncertainties in measurements by large-aperture scintillometers in open-water environments. Full article

Estimates of turbulent fluxes (i.e., sensible and latent heat fluxes H and LE) over heterogeneous surfaces is not an easy task. The heterogeneity caused by the contrast in vegetation, hydric and soil conditions can generate a large spatial variability in terms of surface–atmosphere interactions. This study considered the issue of using a thermal-based two-source energy model (TSEB) driven by MODIS (Moderate resolution Imaging Spectroradiometer) and MSG (Meteosat Second Generation) observations in conjunction with an aggregation scheme to derive area-averaged H and LE over a heterogeneous watershed in Niamey, Niger (Wankama catchment). Data collected in the context of the African Monsoon Multidisciplinary Analysis (AMMA) program, including a scintillometry campaign, were used to test the proposed approach. The model predictions of area-averaged turbulent fluxes were compared to data acquired by a Large Aperture Scintillometer (LAS) set up over a transect about 3.2 km-long and spanning three vegetation types (millet, fallow and degraded shrubs). First, H and LE fluxes were estimated at the MSG-SEVIRI grid scale by neglecting explicitly the subpixel heterogeneity. Moreover, the impact of upscaling the model’s inputs was investigated using in-situ input data and three aggregation schemes of increasing complexity based on MODIS products: a simple averaging of inputs at the MODIS resolution scale, another simple averaging scheme that considers scintillometer footprint extent, and the weighted average of inputs based on the footprint weighting function. The H and LE simulated using the footprint weighted method were more accurate than for the two other aggregation rules despite the heterogeneity of the landscape. The statistical values are: correlation coefficient (R) = 0.71, root mean square error (RMSE) = 63 W/m² and mean bias error (MBE) = −23 W/m² for H and an R = 0.82, RMSE = 88 W/m² and MBE = 45 W/m² for LE. This study opens perspectives for the monitoring of convective and evaporative fluxes over heterogeneous landscape based on medium resolution satellite products. Full article

The sensible heat is an important component in surface energy partitioning over the land surface. This paper compared the sensible heat fluxes measured by a large aperture scintillometer system (LAS) and an eddy covariance system (EC) over a rice paddy with a patch of mulberry seedlings in the east China coastal region during the period from 13 September–11 October 2015. During the observation period, easterlies and northerlies prevailed, and 96% easterlies and northerlies had a speed of 0–6 m s⁻¹. The sensible heat fluxes measured by the two systems reflected that the value of H_LAS generally was inclined to be larger than H_EC with the average difference of 20.30 W m⁻², and the uncertainty for two instruments was less than 17 W m⁻². Analysis of the average footprint resulted that the mulberry seedling field always had a higher contribution to LAS than that to EC, which could be the reason that H_LAS was always larger than H_EC. During the days when the contributions of the mulberry seedling field to the two systems were close to each other, the sensible heat flux measurements of the two instruments were similar. The case analysis on typical sunny days showed that there would be larger sensible heat fluxes over the mulberry seedling field than in the rice paddy field especially under larger net radiation conditions. Full article

Knowledge of evapotranspiration (ET) is essential for enhancing our understanding of the hydrological cycle, as well as for managing water resources, particularly in semi-arid regions. Remote sensing offers a comprehensive means of monitoring this phenomenon at different spatial and temporal intervals. Currently, several satellite methods exist and are used to assess ET at various spatial and temporal resolutions with various degrees of accuracy and precision. This research investigated the performance of three satellite-based ET algorithms and two global products, namely land surface temperature/vegetation index (TsVI), Penman–Monteith (PM), and the Meteosat Second Generation ET (MET) and the Global Land-surface Evaporation: the Amsterdam Methodology (GLEAM) global products, in two eco-regions of South Africa. Daily ET derived from the eddy covariance system from Skukuza, a sub-tropical, savanna biome, and large aperture boundary layer scintillometer system in Elandsberg, a Mediterranean, fynbos biome, during the dry and wet seasons, were used to evaluate the models. Low coefficients of determination (R²) of between 0 and 0.45 were recorded on both sites, during both seasons. Although PM performed best during periods of high ET at both sites, results show it was outperformed by other models during low ET times. TsVI and MET were similarly accurate in the dry season in Skukuza, as GLEAM was the most accurate in Elandsberg during the wet season. The conclusion is that none of the models performed well, as shown by low R² and high errors in all the models. In essence, our results conclude that further investigation of the PM model is possible to improve its estimation of low ET measurements. Full article

Sensible heat flux (H) plays an important role in characterizations of land surface water and heat balance. There are various types of H measurement methods that depend on observation scale, from local-area-scale eddy covariance (EC) to regional-scale large aperture scintillometer (LAS) and remote sensing (RS) products. However, methods of converting one H scale to another to validate RS products are still open for question. A previous area-to-area regression kriging-based scaling method performed well in converting EC-scale H to LAS-scale H. However, the method does not consider the path-weighting function in the EC- to LAS-scale kriging with the regression residue, which inevitably brought about a bias estimation. In this study, a weighted area-to-area regression kriging (WATA RK) model is proposed to convert EC-scale H to LAS-scale H. It involves path-weighting functions of EC and LAS source areas in both regression and area kriging stages. Results show that WATA RK outperforms traditional methods in most cases, improving estimation accuracy. The method is considered to provide an efficient validation of RS H flux products. Full article

The accuracy in determining sensible heat flux (H) of three Kipp and Zonen large aperture scintillometers (LAS) was evaluated with reference to an eddy covariance (EC) system over relatively flat and uniform grassland near Timpas (CO, USA). Other tests have revealed inherent variability between Kipp and Zonen LAS units and bias to overestimate H. Average H fluxes were compared between LAS units and between LAS and EC. Despite good correlation, inter-LAS biases in H were found between 6% and 13% in terms of the linear regression slope. Physical misalignment was observed to result in increased scatter and bias between H solutions of a well-aligned and poorly-aligned LAS unit. Comparison of LAS and EC H showed little bias for one LAS unit, while the other two units overestimated EC H by more than 10%. A detector alignment issue may have caused the inter-LAS variability, supported by the observation in this study of differing power requirements between LAS units. It is possible that the LAS physical misalignment may have caused edge-of-beam signal noise as well as vulnerability to signal noise from wind-induced vibrations, both having an impact on the solution of H. In addition, there were some uncertainties in the solutions of H from the LAS and EC instruments, including lack of energy balance closure with the EC unit. However, the results obtained do not show clear evidence of inherent bias for the Kipp and Zonen LAS to overestimate H as found in other studies. Full article